h&1qR.s      !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~                                                                                                                                                                                             !!!!!!!!!!!!!""""""""""""""""""""""""################$$$$$$$$$$$$$%%%%%%%%%%%%%%&&&&&&&&&&&&&&&&&''''''''''''''''''''''''((((((((((((((((((((((((((((((((((((((()))))))))))))))))))))))))))************+++++++++++++++++++++++++++++++++++,,,,,,,,,,,,,-------------------------------------.........................///////////////000000000000111111111111111111111111111122222222222222222222222233333333333333344444444 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 7 7 7 7 7 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 : : : : : : : : : : : : : : ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; < < < < < < < < < < < < < < < < < < < < < < < < = = = = = = = = = = = = > > > > > > > > > > > > > > ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ A A A A A A A A A A A A A A A A A A A A A A A A A B B B B B B B B B B B B B B B B C C C C C C C C C C C C C C C C C C C C C C C C D D D D D D D D D D D D D D D E E E E E E E E E E E E E E E F F F F F F F F F F F F F F F F F F F F F F F F G G G G G G G G G G G G G H H H H H H H H H H H H H H H H H H H H H H H H I I I I I I I I I I I I I I I J J J J J J J J J J J J J J J K K K K K K K K K K K K K L L L L L L L L L L L L L L L M M M M M M M M M M M M M M M M M M M M M M M M M M N N N N N N N N N N N N N N N N N N N N N N N N N O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O P P P P P P P P P P P P P P P P P Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R RRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRSSSSSSSSSSSSSSSTTTTTTTTTTTTTTTTTTTTTUUUUUUUUUUUUUUUUUVVVVVVVVVVVVVWWWWWWWWWWWWWWWWWWWWWWWWWXXXXXXXXXXXXXXXXXXXXXXXXYYYYYYYYYYYYYYYZZZZZZZZZZZZZZZZZ[[[[[[[[[[[[[[[\\\\\\\\\\\\\\\\\\\\\\\\\\\\]]]]]]]]]]]]]]]]]]]]]]]]^^^^^^^^^^^^^^^^^^^^^________________________````````````aaaaaaaaaaaaaaaaaaaaaaaabbbbbbbbbbbbbbbbbbbbbbbbcccccccccccccccccddddddddddddddddddddddeeeeeeeeeeeeeeefffffffffffffffffggggggggggggggggggggggghhhhhhhhhhhhhhhhhhhhiiiiiiiiiiiiiiiiijjjjjjjjjjjjjjjjjjjjjjjjkkkkkkkkkkkkkkkkkkkkkkklllllllllllllllllllmmmmmmmmmmmmmmmmnnnnnnnnnnnnnnnnooooooooooooooooooooooooooppppppppppppppppqqqqqqqqqqqqqqrrrrrrrrrrrrrrrrrrrrrrrrrrssssssssssssssssttttttttttttttttttttttttttttuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuvvvvvvvvvvvvvvvvvvwwwwwwwwwwwwwwxxxxxxxxxxxxxxxxxxxxxxxxxyyyyyyyyyyyyyyyyyyyzzzzzzzzzzzzzzzzzzzzzzzz{{{{{{{{{{{{{{{{{{{{{{{{{|||||||||||||||||||||||||||||}}}}}}}}}}}}}}}}}}}}}}}}~~~~~~~~~~~~~~~~~~                                                                                                                                !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""################################################################################################################################$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''(((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((())))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))********************************************************************************************************************************++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,--------------------------------------------------------------------------------------------------------------------------------................................................................................................................................////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////00000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111112222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222233333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444445555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555566666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777778888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888899999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<================================================================================================================================>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^________________________________________________________________________________________________________________________________````````````````````````````````````````````````````````````````````````````````````````````````````````````````````````````````aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffgggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggghhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiijjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzz{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~€ÀĀŀƀǀȀɀʀˀ̀̀΀πЀрҀӀԀՀր׀؀ـڀۀ܀݀ހ߀ÁāŁƁǁȁɁʁˁ́́΁ρЁсҁӁԁՁցׁ؁فځہ܁݁ށ߁‚ÂĂłƂǂȂɂʂ˂̂͂΂ςЂт҂ӂԂՂւׂ؂قڂۂ܂݂ނ߂ƒÃăŃƃǃȃɃʃ˃̃̓΃σЃу҃ӃԃՃփ׃؃كڃۃ܃݃ރ߃„ÄĄńƄDŽȄɄʄ˄̄̈́΄τЄф҄ӄԄՄքׄ؄لڄۄ܄݄ބ߄…ÅąŅƅDžȅɅʅ˅̅ͅ΅υЅх҅ӅԅՅօׅ؅مڅۅ܅݅ޅ߅†ÆĆņƆdžȆɆʆˆ̆͆ΆφІц҆ӆԆՆֆ׆؆نچۆ܆݆ކ߆‡ÇćŇƇLJȇɇʇˇ͇̇·χЇч҇ӇԇՇևׇ؇هڇۇ܇݇އ߇ˆÈĈňƈLjȈɈʈˈ͈̈ΈψЈш҈ӈԈՈֈ׈؈وڈۈ܈݈ވ߈‰ÉĉʼnƉljȉɉʉˉ͉̉ΉωЉщ҉ӉԉՉ։׉؉ىډۉ܉݉މ߉ŠÊĊŊƊNJȊɊʊˊ̊͊ΊϊЊъҊӊԊՊ֊׊؊يڊۊ܊݊ފߊ‹ËċŋƋNjȋɋʋˋ̋͋΋ϋЋыҋӋԋՋ֋׋؋ًڋۋ܋݋ދߋŒÌČŌƌnjȌɌʌˌ̌͌ΌόЌьҌӌԌՌ֌׌،ٌڌی܌݌ތߌÍčōƍǍȍɍʍˍ͍̍΍ύЍэҍӍԍՍ֍׍؍ٍڍۍ܍ݍލߍŽÎĎŎƎǎȎɎʎˎ͎̎ΎώЎюҎӎԎՎ֎׎؎َڎێ܎ݎގߎÏďŏƏǏȏɏʏˏ̏͏ΏϏЏяҏӏԏՏ֏׏؏ُڏۏ܏ݏޏߏÐĐŐƐǐȐɐʐː̐͐ΐϐАѐҐӐԐՐ֐אِؐڐېܐݐސߐ‘ÑđőƑǑȑɑʑˑ̑͑ΑϑБёґӑԑՑ֑בّؑڑۑܑݑޑߑ’ÒĒŒƒǒȒɒʒ˒̒͒ΒϒВђҒӒԒՒ֒גْؒڒےܒݒޒߒ“ÓēœƓǓȓɓʓ˓͓̓ΓϓГѓғӓԓՓ֓דؓٓړۓܓݓޓߓ”ÔĔŔƔǔȔɔʔ˔͔̔ΔϔДєҔӔԔՔ֔הؔٔڔ۔ܔݔޔߔ•ÕĕŕƕǕȕɕʕ˕͕̕ΕϕЕѕҕӕԕՕ֕וٕؕڕەܕݕޕߕ–ÖĖŖƖǖȖɖʖ˖̖͖ΖϖЖіҖӖԖՖ֖זٖؖږۖܖݖޖߖ—×ėŗƗǗȗɗʗ˗̗͗ΗϗЗїҗӗԗ՗֗חؗٗڗۗܗݗޗߗ˜ØĘŘƘǘȘɘʘ˘̘͘ΘϘИјҘӘԘ՘֘טؘ٘ژۘܘݘޘߘ™ÙęřƙǙșəʙ˙̙͙ΙϙЙљҙәԙՙ֙יؙٙڙۙܙݙޙߙšÚĚŚƚǚȚɚʚ˚͚̚ΚϚКњҚӚԚ՚֚ךؚٚښۚܚݚޚߚ›ÛěśƛǛțɛʛ˛̛͛ΛϛЛћқӛԛ՛֛כ؛ٛڛۛܛݛޛߛœÜĜŜƜǜȜɜʜ˜̜͜ΜϜМќҜӜԜ՜֜ל؜ٜڜۜܜݜޜߜÝĝŝƝǝȝɝʝ˝̝͝ΝϝНѝҝӝԝ՝֝ם؝ٝڝ۝ܝݝޝߝžÞĞŞƞǞȞɞʞ˞̞͞ΞϞОўҞӞԞ՞֞מ؞ٞڞ۞ܞݞޞߞŸßğşƟǟȟɟʟ˟̟͟ΟϟПџҟӟԟ՟֟ן؟ٟڟ۟ܟݟޟߟ àĠŠƠǠȠɠʠˠ̠͠ΠϠРѠҠӠԠՠ֠נؠ٠ڠ۠ܠݠޠߠ¡áġšơǡȡɡʡˡ̡͡ΡϡСѡҡӡԡա֡סء١ڡۡܡݡޡߡ¢âĢŢƢǢȢɢʢˢ̢͢΢ϢТѢҢӢԢբ֢עآ٢ڢۢܢݢޢߢ£ãģţƣǣȣɣʣˣ̣ͣΣϣУѣңӣԣգ֣ףأ٣ڣۣܣݣޣߣ¤äĤŤƤǤȤɤʤˤ̤ͤΤϤФѤҤӤԤդ֤פؤ٤ڤۤܤݤޤߤ¥åĥťƥǥȥɥʥ˥̥ͥΥϥХѥҥӥԥե֥ץإ٥ڥۥܥݥޥߥ¦æĦŦƦǦȦɦʦ˦̦ͦΦϦЦѦҦӦԦզ֦צئ٦ڦۦܦݦަߦ§çħŧƧǧȧɧʧ˧̧ͧΧϧЧѧҧӧԧէ֧קا٧ڧۧܧݧާߧ¨èĨŨƨǨȨɨʨ˨̨ͨΨϨШѨҨӨԨը֨רب٨ڨۨܨݨިߨ©éĩũƩǩȩɩʩ˩̩ͩΩϩЩѩҩөԩթ֩שة٩ک۩ܩݩީߩªêĪŪƪǪȪɪʪ˪̪ͪΪϪЪѪҪӪԪժ֪תت٪ڪ۪ܪݪުߪ«ëīūƫǫȫɫʫ˫̫ͫΫϫЫѫҫӫԫի֫׫ث٫ګ۫ܫݫޫ߫¬ìĬŬƬǬȬɬʬˬ̬ͬάϬЬѬҬӬԬլ֬׬ج٬ڬ۬ܬݬެ߬­íĭŭƭǭȭɭʭ˭̭ͭέϭЭѭҭӭԭխ֭׭ح٭ڭۭܭݭޭ߭®îĮŮƮǮȮɮʮˮ̮ͮήϮЮѮҮӮԮծ֮׮خٮڮۮܮݮޮ߮¯ïįůƯǯȯɯʯ˯̯ͯίϯЯѯүӯԯկ֯ׯدٯگۯܯݯޯ߯°ðİŰưǰȰɰʰ˰̰ͰΰϰаѰҰӰ԰հְװذٰڰ۰ܰݰް߰±ñıűƱDZȱɱʱ˱̱ͱαϱбѱұӱԱձֱױرٱڱ۱ܱݱޱ߱²òIJŲƲDzȲɲʲ˲̲ͲβϲвѲҲӲԲղֲײزٲڲ۲ܲݲ޲߲³óijųƳdzȳɳʳ˳̳ͳγϳгѳҳӳԳճֳ׳سٳڳ۳ܳݳ޳߳´ôĴŴƴǴȴɴʴ˴̴ʹδϴдѴҴӴԴմִ״شٴڴ۴ܴݴ޴ߴµõĵŵƵǵȵɵʵ˵̵͵εϵеѵҵӵԵյֵ׵صٵڵ۵ܵݵ޵ߵ¶öĶŶƶǶȶɶʶ˶̶Ͷζ϶жѶҶӶԶնֶ׶ضٶڶ۶ܶݶ޶߶·÷ķŷƷǷȷɷʷ˷̷ͷηϷзѷҷӷԷշַ׷طٷڷ۷ܷݷ޷߷¸øĸŸƸǸȸɸʸ˸̸͸θϸиѸҸӸԸոָ׸ظٸڸ۸ܸݸ޸߸¹ùĹŹƹǹȹɹʹ˹̹͹ιϹйѹҹӹԹչֹ׹عٹڹ۹ܹݹ޹߹ºúĺźƺǺȺɺʺ˺̺ͺκϺкѺҺӺԺպֺ׺غٺںۺܺݺ޺ߺ»ûĻŻƻǻȻɻʻ˻̻ͻλϻлѻһӻԻջֻ׻ػٻڻۻܻݻ޻߻¼üļżƼǼȼɼʼ˼̼ͼμϼмѼҼӼԼռּ׼ؼټڼۼܼݼ޼߼½ýĽŽƽǽȽɽʽ˽̽ͽνϽнѽҽӽԽսֽ׽ؽٽڽ۽ܽݽ޽߽¾þľžƾǾȾɾʾ˾̾;ξϾоѾҾӾԾվ־׾ؾپھ۾ܾݾ޾߾¿ÿĿſƿǿȿɿʿ˿̿ͿοϿпѿҿӿԿտֿ׿ؿٿڿۿܿݿ޿߿(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';amazonka-sagemaker/A structure describing the source of an action.See:  smart constructor.amazonka-sagemakerThe ID of the source.amazonka-sagemakerThe type of the source.amazonka-sagemakerThe URI of the source.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The ID of the source.,  - The type of the source.,  - The URI of the source.amazonka-sagemakerThe ID of the source.amazonka-sagemakerThe type of the source.amazonka-sagemakerThe URI of the source.amazonka-sagemaker  (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?= (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';-amazonka-sagemakerLists the properties of an action. An action represents an action or activity. Some examples are a workflow step and a model deployment. Generally, an action involves at least one input artifact or output artifact.See: 6 smart constructor./amazonka-sagemaker-The Amazon Resource Name (ARN) of the action.0amazonka-sagemakerThe name of the action.1amazonka-sagemakerThe type of the action.2amazonka-sagemakerWhen the action was created.3amazonka-sagemaker"When the action was last modified.4amazonka-sagemakerThe source of the action.5amazonka-sagemakerThe status of the action.6amazonka-sagemakerCreate a value of -" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:/, 70 - The Amazon Resource Name (ARN) of the action.0, 8 - The name of the action.1, 9 - The type of the action.2, : - When the action was created.3, ;% - When the action was last modified.4, < - The source of the action.5, = - The status of the action.7amazonka-sagemaker-The Amazon Resource Name (ARN) of the action.8amazonka-sagemakerThe name of the action.9amazonka-sagemakerThe type of the action.:amazonka-sagemakerWhen the action was created.;amazonka-sagemaker"When the action was last modified.<amazonka-sagemakerThe source of the action.=amazonka-sagemakerThe status of the action.-3210/54.6789:;<=-3210/54.6789:;<=(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';Eamazonka-sagemakerEdge Manager agent version.See: I smart constructor.Gamazonka-sagemakerVersion of the agent.Hamazonka-sagemaker"The number of Edge Manager agents.Iamazonka-sagemakerCreate a value of E" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:G, J - Version of the agent.H, K% - The number of Edge Manager agents.Jamazonka-sagemakerVersion of the agent.Kamazonka-sagemaker"The number of Edge Manager agents.Iamazonka-sagemakerGamazonka-sagemakerHEHGFIJKEHGFIJK(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';NSamazonka-sagemakerAn Amazon CloudWatch alarm configured to monitor metrics on an endpoint.See: V smart constructor.Uamazonka-sagemaker/The name of a CloudWatch alarm in your account.Vamazonka-sagemakerCreate a value of S" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:U, W2 - The name of a CloudWatch alarm in your account.Wamazonka-sagemaker/The name of a CloudWatch alarm in your account.SUTVWSUTVW(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?`dcab`dcabdc(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?x~}|{yz x~}|{yz~}|{(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; amazonka-sagemaker0Provides summary information about an algorithm.See:  smart constructor.amazonka-sagemaker%A brief description of the algorithm.amazonka-sagemaker;The name of the algorithm that is described by the summary.amazonka-sagemaker0The Amazon Resource Name (ARN) of the algorithm.amazonka-sagemaker6A timestamp that shows when the algorithm was created.amazonka-sagemaker$The overall status of the algorithm.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, ( - A brief description of the algorithm., > - The name of the algorithm that is described by the summary., 3 - The Amazon Resource Name (ARN) of the algorithm., 9 - A timestamp that shows when the algorithm was created., ' - The overall status of the algorithm.amazonka-sagemaker%A brief description of the algorithm.amazonka-sagemaker;The name of the algorithm that is described by the summary.amazonka-sagemaker0The Amazon Resource Name (ARN) of the algorithm.amazonka-sagemaker6A timestamp that shows when the algorithm was created.amazonka-sagemaker$The overall status of the algorithm.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker   (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';amazonka-sagemakerConfigures how labels are consolidated across human workers and processes output data.See:  smart constructor.amazonka-sagemakerThe Amazon Resource Name (ARN) of a Lambda function implements the logic for  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-annotation-consolidation.htmlannotation consolidation and to process output data.7This parameter is required for all labeling jobs. For  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-task-types.htmlbuilt-in task types, use one of the following Amazon SageMaker Ground Truth Lambda function ARNs for  AnnotationConsolidationLambdaArn'. For custom labeling workflows, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-custom-templates-step3.html#sms-custom-templates-step3-postlambdaPost-annotation Lambda. Bounding box - Finds the most similar boxes from different workers based on the Jaccard index of the boxes. >arn:aws:lambda:us-east-1:432418664414:function:ACS-BoundingBox >arn:aws:lambda:us-east-2:266458841044:function:ACS-BoundingBox >arn:aws:lambda:us-west-2:081040173940:function:ACS-BoundingBox >arn:aws:lambda:eu-west-1:568282634449:function:ACS-BoundingBox arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-BoundingBox arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-BoundingBox ?arn:aws:lambda:ap-south-1:565803892007:function:ACS-BoundingBox arn:aws:lambda:eu-central-1:203001061592:function:ACS-BoundingBox arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-BoundingBox >arn:aws:lambda:eu-west-2:487402164563:function:ACS-BoundingBox arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-BoundingBox arn:aws:lambda:ca-central-1:918755190332:function:ACS-BoundingBoxImage classification - Uses a variant of the Expectation Maximization approach to estimate the true class of an image based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClass arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClass arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClass arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClass arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClass arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClass arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClass arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClass arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClass arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClass arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClass arn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClass Multi-label image classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of an image based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClassMultiLabelSemantic segmentation - Treats each pixel in an image as a multi-class classification and treats pixel annotations from workers as "votes" for the correct label. arn:aws:lambda:us-east-1:432418664414:function:ACS-SemanticSegmentation arn:aws:lambda:us-east-2:266458841044:function:ACS-SemanticSegmentation arn:aws:lambda:us-west-2:081040173940:function:ACS-SemanticSegmentation arn:aws:lambda:eu-west-1:568282634449:function:ACS-SemanticSegmentation arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-SemanticSegmentation arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-SemanticSegmentation arn:aws:lambda:ap-south-1:565803892007:function:ACS-SemanticSegmentation arn:aws:lambda:eu-central-1:203001061592:function:ACS-SemanticSegmentation arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-SemanticSegmentation arn:aws:lambda:eu-west-2:487402164563:function:ACS-SemanticSegmentation arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-SemanticSegmentation arn:aws:lambda:ca-central-1:918755190332:function:ACS-SemanticSegmentationText classification - Uses a variant of the Expectation Maximization approach to estimate the true class of text based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClass arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClass arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClass arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClass arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClass arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClass arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClass arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClass arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClass arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClass arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClass arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClassMulti-label text classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of text based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClassMultiLabelNamed entity recognition - Groups similar selections and calculates aggregate boundaries, resolving to most-assigned label. arn:aws:lambda:us-east-1:432418664414:function:ACS-NamedEntityRecognition arn:aws:lambda:us-east-2:266458841044:function:ACS-NamedEntityRecognition arn:aws:lambda:us-west-2:081040173940:function:ACS-NamedEntityRecognition arn:aws:lambda:eu-west-1:568282634449:function:ACS-NamedEntityRecognition arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-NamedEntityRecognition arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-NamedEntityRecognition arn:aws:lambda:ap-south-1:565803892007:function:ACS-NamedEntityRecognition arn:aws:lambda:eu-central-1:203001061592:function:ACS-NamedEntityRecognition arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-NamedEntityRecognition arn:aws:lambda:eu-west-2:487402164563:function:ACS-NamedEntityRecognition arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-NamedEntityRecognition arn:aws:lambda:ca-central-1:918755190332:function:ACS-NamedEntityRecognitionVideo Classification - Use this task type when you need workers to classify videos using predefined labels that you specify. Workers are shown videos and are asked to choose one label for each video. arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoMultiClass arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoMultiClass arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoMultiClass arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoMultiClass arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoMultiClass arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoMultiClass arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoMultiClass arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoMultiClass arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoMultiClass arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoMultiClass arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoMultiClass arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoMultiClassVideo Frame Object Detection - Use this task type to have workers identify and locate objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to identify and localize various objects in a series of video frames, such as cars, bikes, and pedestrians. arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectDetection arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectDetection arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectDetection arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectDetection arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectDetection arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectDetection arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectDetection arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectDetection arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectDetection arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectDetection arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectDetection arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectDetectionVideo Frame Object Tracking - Use this task type to have workers track the movement of objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to track the movement of objects, such as cars, bikes, and pedestrians. arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectTracking arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectTracking arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectTracking arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectTracking arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectTracking arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectTracking arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectTracking arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectTracking arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectTracking arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectTracking arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectTracking arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectTracking3D Point Cloud Object Detection - Use this task type when you want workers to classify objects in a 3D point cloud by drawing 3D cuboids around objects. For example, you can use this task type to ask workers to identify different types of objects in a point cloud, such as cars, bikes, and pedestrians. arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectDetection3D Point Cloud Object Tracking - Use this task type when you want workers to draw 3D cuboids around objects that appear in a sequence of 3D point cloud frames. For example, you can use this task type to ask workers to track the movement of vehicles across multiple point cloud frames. arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectTracking$3D Point Cloud Semantic Segmentation - Use this task type when you want workers to create a point-level semantic segmentation masks by painting objects in a 3D point cloud using different colors where each color is assigned to one of the classes you specify. arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudSemanticSegmentationUse the following ARNs for Label Verification and Adjustment JobsUse label verification and adjustment jobs to review and adjust labels. To learn more, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-verification-data.htmlVerify and Adjust Labels . Semantic Segmentation Adjustment - Treats each pixel in an image as a multi-class classification and treats pixel adjusted annotations from workers as "votes" for the correct label. arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentSemanticSegmentation"Semantic Segmentation Verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgment for semantic segmentation labels based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationSemanticSegmentationBounding Box Adjustment - Finds the most similar boxes from different workers based on the Jaccard index of the adjusted annotations. arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentBoundingBox arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentBoundingBox arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentBoundingBox arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentBoundingBox arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentBoundingBox arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentBoundingBox arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentBoundingBox arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentBoundingBox arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentBoundingBox arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentBoundingBox arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentBoundingBox arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentBoundingBoxBounding Box Verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgement for bounding box labels based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationBoundingBox arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationBoundingBox arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationBoundingBox arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationBoundingBox arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationBoundingBox arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationBoundingBox arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationBoundingBox arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationBoundingBox arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationBoundingBox arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationBoundingBox arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationBoundingBox arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationBoundingBox'Video Frame Object Detection Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to classify and localize objects in a sequence of video frames. arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectDetection&Video Frame Object Tracking Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to track object movement across a sequence of video frames. arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectTracking*3D Point Cloud Object Detection Adjustment - Use this task type when you want workers to adjust 3D cuboids around objects in a 3D point cloud. arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectDetection)3D Point Cloud Object Tracking Adjustment - Use this task type when you want workers to adjust 3D cuboids around objects that appear in a sequence of 3D point cloud frames. arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectTracking/3D Point Cloud Semantic Segmentation Adjustment - Use this task type when you want workers to adjust a point-level semantic segmentation masks using a paint tool. arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudSemanticSegmentationamazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The Amazon Resource Name (ARN) of a Lambda function implements the logic for  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-annotation-consolidation.htmlannotation consolidation and to process output data.7This parameter is required for all labeling jobs. For  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-task-types.htmlbuilt-in task types, use one of the following Amazon SageMaker Ground Truth Lambda function ARNs for  AnnotationConsolidationLambdaArn'. For custom labeling workflows, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-custom-templates-step3.html#sms-custom-templates-step3-postlambdaPost-annotation Lambda. Bounding box - Finds the most similar boxes from different workers based on the Jaccard index of the boxes. >arn:aws:lambda:us-east-1:432418664414:function:ACS-BoundingBox >arn:aws:lambda:us-east-2:266458841044:function:ACS-BoundingBox >arn:aws:lambda:us-west-2:081040173940:function:ACS-BoundingBox >arn:aws:lambda:eu-west-1:568282634449:function:ACS-BoundingBox arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-BoundingBox arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-BoundingBox ?arn:aws:lambda:ap-south-1:565803892007:function:ACS-BoundingBox arn:aws:lambda:eu-central-1:203001061592:function:ACS-BoundingBox arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-BoundingBox >arn:aws:lambda:eu-west-2:487402164563:function:ACS-BoundingBox arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-BoundingBox arn:aws:lambda:ca-central-1:918755190332:function:ACS-BoundingBoxImage classification - Uses a variant of the Expectation Maximization approach to estimate the true class of an image based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClass arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClass arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClass arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClass arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClass arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClass arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClass arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClass arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClass arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClass arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClass arn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClass Multi-label image classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of an image based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClassMultiLabelSemantic segmentation - Treats each pixel in an image as a multi-class classification and treats pixel annotations from workers as "votes" for the correct label. arn:aws:lambda:us-east-1:432418664414:function:ACS-SemanticSegmentation arn:aws:lambda:us-east-2:266458841044:function:ACS-SemanticSegmentation arn:aws:lambda:us-west-2:081040173940:function:ACS-SemanticSegmentation arn:aws:lambda:eu-west-1:568282634449:function:ACS-SemanticSegmentation arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-SemanticSegmentation arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-SemanticSegmentation arn:aws:lambda:ap-south-1:565803892007:function:ACS-SemanticSegmentation arn:aws:lambda:eu-central-1:203001061592:function:ACS-SemanticSegmentation arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-SemanticSegmentation arn:aws:lambda:eu-west-2:487402164563:function:ACS-SemanticSegmentation arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-SemanticSegmentation arn:aws:lambda:ca-central-1:918755190332:function:ACS-SemanticSegmentationText classification - Uses a variant of the Expectation Maximization approach to estimate the true class of text based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClass arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClass arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClass arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClass arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClass arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClass arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClass arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClass arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClass arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClass arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClass arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClassMulti-label text classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of text based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClassMultiLabelNamed entity recognition - Groups similar selections and calculates aggregate boundaries, resolving to most-assigned label. arn:aws:lambda:us-east-1:432418664414:function:ACS-NamedEntityRecognition arn:aws:lambda:us-east-2:266458841044:function:ACS-NamedEntityRecognition arn:aws:lambda:us-west-2:081040173940:function:ACS-NamedEntityRecognition arn:aws:lambda:eu-west-1:568282634449:function:ACS-NamedEntityRecognition arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-NamedEntityRecognition arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-NamedEntityRecognition arn:aws:lambda:ap-south-1:565803892007:function:ACS-NamedEntityRecognition arn:aws:lambda:eu-central-1:203001061592:function:ACS-NamedEntityRecognition arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-NamedEntityRecognition arn:aws:lambda:eu-west-2:487402164563:function:ACS-NamedEntityRecognition arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-NamedEntityRecognition arn:aws:lambda:ca-central-1:918755190332:function:ACS-NamedEntityRecognitionVideo Classification - Use this task type when you need workers to classify videos using predefined labels that you specify. Workers are shown videos and are asked to choose one label for each video. arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoMultiClass arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoMultiClass arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoMultiClass arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoMultiClass arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoMultiClass arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoMultiClass arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoMultiClass arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoMultiClass arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoMultiClass arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoMultiClass arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoMultiClass arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoMultiClassVideo Frame Object Detection - Use this task type to have workers identify and locate objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to identify and localize various objects in a series of video frames, such as cars, bikes, and pedestrians. arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectDetection arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectDetection arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectDetection arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectDetection arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectDetection arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectDetection arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectDetection arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectDetection arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectDetection arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectDetection arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectDetection arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectDetectionVideo Frame Object Tracking - Use this task type to have workers track the movement of objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to track the movement of objects, such as cars, bikes, and pedestrians. arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectTracking arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectTracking arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectTracking arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectTracking arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectTracking arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectTracking arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectTracking arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectTracking arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectTracking arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectTracking arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectTracking arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectTracking3D Point Cloud Object Detection - Use this task type when you want workers to classify objects in a 3D point cloud by drawing 3D cuboids around objects. For example, you can use this task type to ask workers to identify different types of objects in a point cloud, such as cars, bikes, and pedestrians. arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectDetection3D Point Cloud Object Tracking - Use this task type when you want workers to draw 3D cuboids around objects that appear in a sequence of 3D point cloud frames. For example, you can use this task type to ask workers to track the movement of vehicles across multiple point cloud frames. arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectTracking$3D Point Cloud Semantic Segmentation - Use this task type when you want workers to create a point-level semantic segmentation masks by painting objects in a 3D point cloud using different colors where each color is assigned to one of the classes you specify. arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudSemanticSegmentationUse the following ARNs for Label Verification and Adjustment JobsUse label verification and adjustment jobs to review and adjust labels. To learn more, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-verification-data.htmlVerify and Adjust Labels . Semantic Segmentation Adjustment - Treats each pixel in an image as a multi-class classification and treats pixel adjusted annotations from workers as "votes" for the correct label. arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentSemanticSegmentation"Semantic Segmentation Verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgment for semantic segmentation labels based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationSemanticSegmentationBounding Box Adjustment - Finds the most similar boxes from different workers based on the Jaccard index of the adjusted annotations. arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentBoundingBox arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentBoundingBox arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentBoundingBox arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentBoundingBox arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentBoundingBox arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentBoundingBox arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentBoundingBox arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentBoundingBox arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentBoundingBox arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentBoundingBox arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentBoundingBox arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentBoundingBoxBounding Box Verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgement for bounding box labels based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationBoundingBox arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationBoundingBox arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationBoundingBox arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationBoundingBox arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationBoundingBox arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationBoundingBox arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationBoundingBox arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationBoundingBox arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationBoundingBox arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationBoundingBox arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationBoundingBox arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationBoundingBox'Video Frame Object Detection Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to classify and localize objects in a sequence of video frames. arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectDetection&Video Frame Object Tracking Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to track object movement across a sequence of video frames. arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectTracking*3D Point Cloud Object Detection Adjustment - Use this task type when you want workers to adjust 3D cuboids around objects in a 3D point cloud. arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectDetection)3D Point Cloud Object Tracking Adjustment - Use this task type when you want workers to adjust 3D cuboids around objects that appear in a sequence of 3D point cloud frames. arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectTracking/3D Point Cloud Semantic Segmentation Adjustment - Use this task type when you want workers to adjust a point-level semantic segmentation masks using a paint tool. arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudSemanticSegmentationamazonka-sagemakerThe Amazon Resource Name (ARN) of a Lambda function implements the logic for  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-annotation-consolidation.htmlannotation consolidation and to process output data.7This parameter is required for all labeling jobs. For  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-task-types.htmlbuilt-in task types, use one of the following Amazon SageMaker Ground Truth Lambda function ARNs for  AnnotationConsolidationLambdaArn'. For custom labeling workflows, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-custom-templates-step3.html#sms-custom-templates-step3-postlambdaPost-annotation Lambda. Bounding box - Finds the most similar boxes from different workers based on the Jaccard index of the boxes. >arn:aws:lambda:us-east-1:432418664414:function:ACS-BoundingBox >arn:aws:lambda:us-east-2:266458841044:function:ACS-BoundingBox >arn:aws:lambda:us-west-2:081040173940:function:ACS-BoundingBox >arn:aws:lambda:eu-west-1:568282634449:function:ACS-BoundingBox arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-BoundingBox arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-BoundingBox ?arn:aws:lambda:ap-south-1:565803892007:function:ACS-BoundingBox arn:aws:lambda:eu-central-1:203001061592:function:ACS-BoundingBox arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-BoundingBox >arn:aws:lambda:eu-west-2:487402164563:function:ACS-BoundingBox arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-BoundingBox arn:aws:lambda:ca-central-1:918755190332:function:ACS-BoundingBoxImage classification - Uses a variant of the Expectation Maximization approach to estimate the true class of an image based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClass arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClass arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClass arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClass arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClass arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClass arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClass arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClass arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClass arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClass arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClass arn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClass Multi-label image classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of an image based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClassMultiLabelSemantic segmentation - Treats each pixel in an image as a multi-class classification and treats pixel annotations from workers as "votes" for the correct label. arn:aws:lambda:us-east-1:432418664414:function:ACS-SemanticSegmentation arn:aws:lambda:us-east-2:266458841044:function:ACS-SemanticSegmentation arn:aws:lambda:us-west-2:081040173940:function:ACS-SemanticSegmentation arn:aws:lambda:eu-west-1:568282634449:function:ACS-SemanticSegmentation arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-SemanticSegmentation arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-SemanticSegmentation arn:aws:lambda:ap-south-1:565803892007:function:ACS-SemanticSegmentation arn:aws:lambda:eu-central-1:203001061592:function:ACS-SemanticSegmentation arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-SemanticSegmentation arn:aws:lambda:eu-west-2:487402164563:function:ACS-SemanticSegmentation arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-SemanticSegmentation arn:aws:lambda:ca-central-1:918755190332:function:ACS-SemanticSegmentationText classification - Uses a variant of the Expectation Maximization approach to estimate the true class of text based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClass arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClass arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClass arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClass arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClass arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClass arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClass arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClass arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClass arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClass arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClass arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClassMulti-label text classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of text based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClassMultiLabelNamed entity recognition - Groups similar selections and calculates aggregate boundaries, resolving to most-assigned label. arn:aws:lambda:us-east-1:432418664414:function:ACS-NamedEntityRecognition arn:aws:lambda:us-east-2:266458841044:function:ACS-NamedEntityRecognition arn:aws:lambda:us-west-2:081040173940:function:ACS-NamedEntityRecognition arn:aws:lambda:eu-west-1:568282634449:function:ACS-NamedEntityRecognition arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-NamedEntityRecognition arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-NamedEntityRecognition arn:aws:lambda:ap-south-1:565803892007:function:ACS-NamedEntityRecognition arn:aws:lambda:eu-central-1:203001061592:function:ACS-NamedEntityRecognition arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-NamedEntityRecognition arn:aws:lambda:eu-west-2:487402164563:function:ACS-NamedEntityRecognition arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-NamedEntityRecognition arn:aws:lambda:ca-central-1:918755190332:function:ACS-NamedEntityRecognitionVideo Classification - Use this task type when you need workers to classify videos using predefined labels that you specify. Workers are shown videos and are asked to choose one label for each video. arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoMultiClass arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoMultiClass arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoMultiClass arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoMultiClass arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoMultiClass arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoMultiClass arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoMultiClass arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoMultiClass arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoMultiClass arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoMultiClass arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoMultiClass arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoMultiClassVideo Frame Object Detection - Use this task type to have workers identify and locate objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to identify and localize various objects in a series of video frames, such as cars, bikes, and pedestrians. arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectDetection arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectDetection arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectDetection arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectDetection arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectDetection arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectDetection arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectDetection arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectDetection arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectDetection arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectDetection arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectDetection arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectDetectionVideo Frame Object Tracking - Use this task type to have workers track the movement of objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to track the movement of objects, such as cars, bikes, and pedestrians. arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectTracking arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectTracking arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectTracking arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectTracking arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectTracking arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectTracking arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectTracking arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectTracking arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectTracking arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectTracking arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectTracking arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectTracking3D Point Cloud Object Detection - Use this task type when you want workers to classify objects in a 3D point cloud by drawing 3D cuboids around objects. For example, you can use this task type to ask workers to identify different types of objects in a point cloud, such as cars, bikes, and pedestrians. arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectDetection3D Point Cloud Object Tracking - Use this task type when you want workers to draw 3D cuboids around objects that appear in a sequence of 3D point cloud frames. For example, you can use this task type to ask workers to track the movement of vehicles across multiple point cloud frames. arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectTracking$3D Point Cloud Semantic Segmentation - Use this task type when you want workers to create a point-level semantic segmentation masks by painting objects in a 3D point cloud using different colors where each color is assigned to one of the classes you specify. arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudSemanticSegmentationUse the following ARNs for Label Verification and Adjustment JobsUse label verification and adjustment jobs to review and adjust labels. To learn more, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-verification-data.htmlVerify and Adjust Labels . Semantic Segmentation Adjustment - Treats each pixel in an image as a multi-class classification and treats pixel adjusted annotations from workers as "votes" for the correct label. arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentSemanticSegmentation"Semantic Segmentation Verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgment for semantic segmentation labels based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationSemanticSegmentationBounding Box Adjustment - Finds the most similar boxes from different workers based on the Jaccard index of the adjusted annotations. arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentBoundingBox arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentBoundingBox arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentBoundingBox arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentBoundingBox arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentBoundingBox arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentBoundingBox arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentBoundingBox arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentBoundingBox arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentBoundingBox arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentBoundingBox arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentBoundingBox arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentBoundingBoxBounding Box Verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgement for bounding box labels based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationBoundingBox arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationBoundingBox arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationBoundingBox arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationBoundingBox arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationBoundingBox arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationBoundingBox arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationBoundingBox arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationBoundingBox arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationBoundingBox arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationBoundingBox arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationBoundingBox arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationBoundingBox'Video Frame Object Detection Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to classify and localize objects in a sequence of video frames. arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectDetection&Video Frame Object Tracking Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to track object movement across a sequence of video frames. arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectTracking*3D Point Cloud Object Detection Adjustment - Use this task type when you want workers to adjust 3D cuboids around objects in a 3D point cloud. arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectDetection)3D Point Cloud Object Tracking Adjustment - Use this task type when you want workers to adjust 3D cuboids around objects that appear in a sequence of 3D point cloud frames. arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectTracking/3D Point Cloud Semantic Segmentation Adjustment - Use this task type when you want workers to adjust a point-level semantic segmentation masks using a paint tool. arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudSemanticSegmentationamazonka-sagemaker (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?  (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?|< (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";??(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';amazonka-sagemakerConfiguration to run a processing job in a specified container image.See:  smart constructor.amazonka-sagemaker;The arguments for a container used to run a processing job.amazonka-sagemaker - The arguments for a container used to run a processing job., ? - The entrypoint for a container used to run a processing job., 7 - The container image to be run by the processing job.amazonka-sagemaker;The arguments for a container used to run a processing job.amazonka-sagemaker,..) should be a subset of the column names in the input data.If both FeatureDataTypes and FeatureAttributeNames are provided, then the column keys should be a subset of the column names provided in FeatureAttributeNames. The key name FeatureAttributeNames! is fixed. The values listed in ["col1", "col2", ...] is case sensitive and should be a list of strings containing unique values that are a subset of the column names in the input data. The list of columns provided must not include the target column.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - A URL to the Amazon S3 data source containing selected features from the input data source to run an Autopilot job. You can input FeatureAttributeNames* (optional) in JSON format as shown below:1{ "FeatureAttributeNames":["col1", "col2", ...] }.You can also specify the data type of the feature (optional) in the format shown below: { "FeatureDataTypes":{"col1":"numeric", "col2":"categorical" ... } }4These column keys may not include the target column.In ensembling mode, Autopilot will only support the following data types: numeric,  categorical, text and datetime&. In HPO mode, Autopilot can support numeric,  categorical, text, datetime and sequence.If only FeatureDataTypes is provided, the column keys (col1, col2>,..) should be a subset of the column names in the input data.If both FeatureDataTypes and FeatureAttributeNames are provided, then the column keys should be a subset of the column names provided in FeatureAttributeNames. The key name FeatureAttributeNames! is fixed. The values listed in ["col1", "col2", ...] is case sensitive and should be a list of strings containing unique values that are a subset of the column names in the input data. The list of columns provided must not include the target column.amazonka-sagemakerA URL to the Amazon S3 data source containing selected features from the input data source to run an Autopilot job. You can input FeatureAttributeNames* (optional) in JSON format as shown below:1{ "FeatureAttributeNames":["col1", "col2", ...] }.You can also specify the data type of the feature (optional) in the format shown below: { "FeatureDataTypes":{"col1":"numeric", "col2":"categorical" ... } }4These column keys may not include the target column.In ensembling mode, Autopilot will only support the following data types: numeric,  categorical, text and datetime&. In HPO mode, Autopilot can support numeric,  categorical, text, datetime and sequence.If only FeatureDataTypes is provided, the column keys (col1, col2>,..) should be a subset of the column names in the input data.If both FeatureDataTypes and FeatureAttributeNames are provided, then the column keys should be a subset of the column names provided in FeatureAttributeNames. The key name FeatureAttributeNames! is fixed. The values listed in ["col1", "col2", ...] is case sensitive and should be a list of strings containing unique values that are a subset of the column names in the input data. The list of columns provided must not include the target column."(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?O#(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';Vamazonka-sagemakerA list of container definitions that describe the different containers that make up an AutoML candidate. For more information, see .See:  smart constructor.amazonka-sagemakerThe environment variables to set in the container. For more information, see .amazonka-sagemakerThe Amazon Elastic Container Registry (Amazon ECR) path of the container. For more information, see .amazonka-sagemakerThe location of the model artifacts. For more information, see .amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The environment variables to set in the container. For more information, see .,  - The Amazon Elastic Container Registry (Amazon ECR) path of the container. For more information, see .,  - The location of the model artifacts. For more information, see .amazonka-sagemakerThe environment variables to set in the container. For more information, see .amazonka-sagemakerThe Amazon Elastic Container Registry (Amazon ECR) path of the container. For more information, see .amazonka-sagemakerThe location of the model artifacts. For more information, see .amazonka-sagemakeramazonka-sagemaker  $(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';\amazonka-sagemakerThis structure specifies how to split the data into train and validation datasets. The validation and training datasets must contain the same headers. The validation dataset must be less than 2 GB in size.See:  smart constructor.amazonka-sagemakerThe validation fraction (optional) is a float that specifies the portion of the training dataset to be used for validation. The default value is 0.2, and values must be greater than 0 and less than 1. We recommend setting this value to be less than 0.5.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The validation fraction (optional) is a float that specifies the portion of the training dataset to be used for validation. The default value is 0.2, and values must be greater than 0 and less than 1. We recommend setting this value to be less than 0.5.amazonka-sagemakerThe validation fraction (optional) is a float that specifies the portion of the training dataset to be used for validation. The default value is 0.2, and values must be greater than 0 and less than 1. We recommend setting this value to be less than 0.5.%(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';`amazonka-sagemaker6The artifacts that are generated during an AutoML job.See:  smart constructor.amazonka-sagemaker!The URL of the notebook location.amazonka-sagemaker!The URL of the notebook location.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, $ - The URL of the notebook location., $ - The URL of the notebook location.amazonka-sagemaker!The URL of the notebook location.amazonka-sagemaker!The URL of the notebook location.&(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';lHamazonka-sagemakerHow long a job is allowed to run, or how many candidates a job is allowed to generate.See:  smart constructor.amazonka-sagemaker?The maximum runtime, in seconds, an AutoML job has to complete.If an AutoML job exceeds the maximum runtime, the job is stopped automatically and its processing is ended gracefully. The AutoML job identifies the best model whose training was completed and marks it as the best-performing model. Any unfinished steps of the job, such as automatic one-click Autopilot model deployment, will not be completed.amazonka-sagemaker=The maximum number of times a training job is allowed to run.amazonka-sagemakerThe maximum time, in seconds, that each training job executed inside hyperparameter tuning is allowed to run as part of a hyperparameter tuning job. For more information, see the used by the action.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The maximum runtime, in seconds, an AutoML job has to complete.If an AutoML job exceeds the maximum runtime, the job is stopped automatically and its processing is ended gracefully. The AutoML job identifies the best model whose training was completed and marks it as the best-performing model. Any unfinished steps of the job, such as automatic one-click Autopilot model deployment, will not be completed.,  - The maximum number of times a training job is allowed to run.,  - The maximum time, in seconds, that each training job executed inside hyperparameter tuning is allowed to run as part of a hyperparameter tuning job. For more information, see the used by the action.amazonka-sagemaker?The maximum runtime, in seconds, an AutoML job has to complete.If an AutoML job exceeds the maximum runtime, the job is stopped automatically and its processing is ended gracefully. The AutoML job identifies the best model whose training was completed and marks it as the best-performing model. Any unfinished steps of the job, such as automatic one-click Autopilot model deployment, will not be completed.amazonka-sagemaker=The maximum number of times a training job is allowed to run.amazonka-sagemakerThe maximum time, in seconds, that each training job executed inside hyperparameter tuning is allowed to run as part of a hyperparameter tuning job. For more information, see the used by the action.  '(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?m((c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?m%)(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?n *(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';rbamazonka-sagemaker Metadata for an AutoML job step.See:  smart constructor.amazonka-sagemaker1The Amazon Resource Name (ARN) of the AutoML job.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 4 - The Amazon Resource Name (ARN) of the AutoML job.amazonka-sagemaker1The Amazon Resource Name (ARN) of the AutoML job.+(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?s,(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';wamazonka-sagemakerSpecifies a metric to minimize or maximize as the objective of a job.See:  smart constructor.amazonka-sagemakerThe name of the objective metric used to measure the predictive quality of a machine learning system. This metric is optimized during training to provide the best estimate for model parameter values from data.Here are the options: AccuracyThe ratio of the number of correctly classified items to the total number of (correctly and incorrectly) classified items. It is used for both binary and multiclass classification. Accuracy measures how close the predicted class values are to the actual values. Values for accuracy metrics vary between zero (0) and one (1). A value of 1 indicates perfect accuracy, and 0 indicates perfect inaccuracy.AUCThe area under the curve (AUC) metric is used to compare and evaluate binary classification by algorithms that return probabilities, such as logistic regression. To map the probabilities into classifications, these are compared against a threshold value.The relevant curve is the receiver operating characteristic curve (ROC curve). The ROC curve plots the true positive rate (TPR) of predictions (or recall) against the false positive rate (FPR) as a function of the threshold value, above which a prediction is considered positive. Increasing the threshold results in fewer false positives, but more false negatives.AUC is the area under this ROC curve. Therefore, AUC provides an aggregated measure of the model performance across all possible classification thresholds. AUC scores vary between 0 and 1. A score of 1 indicates perfect accuracy, and a score of one half (0.5) indicates that the prediction is not better than a random classifier.BalancedAccuracyBalancedAccuracy is a metric that measures the ratio of accurate predictions to all predictions. This ratio is calculated after normalizing true positives (TP) and true negatives (TN) by the total number of positive (P) and negative (N) values. It is used in both binary and multiclass classification and is defined as follows: 0.5*((TP/P)+(TN/N)), with values ranging from 0 to 1. BalancedAccuracy gives a better measure of accuracy when the number of positives or negatives differ greatly from each other in an imbalanced dataset. For example, when only 1% of email is spam.F1The F1 score is the harmonic mean of the precision and recall, defined as follows: F1 = 2 * (precision * recall) / (precision + recall). It is used for binary classification into classes traditionally referred to as positive and negative. Predictions are said to be true when they match their actual (correct) class, and false when they do not.Precision is the ratio of the true positive predictions to all positive predictions, and it includes the false positives in a dataset. Precision measures the quality of the prediction when it predicts the positive class.Recall (or sensitivity) is the ratio of the true positive predictions to all actual positive instances. Recall measures how completely a model predicts the actual class members in a dataset.F1 scores vary between 0 and 1. A score of 1 indicates the best possible performance, and 0 indicates the worst.F1macroThe F1macro score applies F1 scoring to multiclass classification problems. It does this by calculating the precision and recall, and then taking their harmonic mean to calculate the F1 score for each class. Lastly, the F1macro averages the individual scores to obtain the F1macro score. F1macro scores vary between 0 and 1. A score of 1 indicates the best possible performance, and 0 indicates the worst.MAEThe mean absolute error (MAE) is a measure of how different the predicted and actual values are, when they're averaged over all values. MAE is commonly used in regression analysis to understand model prediction error. If there is linear regression, MAE represents the average distance from a predicted line to the actual value. MAE is defined as the sum of absolute errors divided by the number of observations. Values range from 0 to infinity, with smaller numbers indicating a better model fit to the data.MSEThe mean squared error (MSE) is the average of the squared differences between the predicted and actual values. It is used for regression. MSE values are always positive. The better a model is at predicting the actual values, the smaller the MSE value is PrecisionPrecision measures how well an algorithm predicts the true positives (TP) out of all of the positives that it identifies. It is defined as follows: Precision = TP/(TP+FP), with values ranging from zero (0) to one (1), and is used in binary classification. Precision is an important metric when the cost of a false positive is high. For example, the cost of a false positive is very high if an airplane safety system is falsely deemed safe to fly. A false positive (FP) reflects a positive prediction that is actually negative in the data.PrecisionMacroThe precision macro computes precision for multiclass classification problems. It does this by calculating precision for each class and averaging scores to obtain precision for several classes. PrecisionMacro scores range from zero (0) to one (1). Higher scores reflect the model's ability to predict true positives (TP) out of all of the positives that it identifies, averaged across multiple classes.R2R2, also known as the coefficient of determination, is used in regression to quantify how much a model can explain the variance of a dependent variable. Values range from one (1) to negative one (-1). Higher numbers indicate a higher fraction of explained variability. R2 values close to zero (0) indicate that very little of the dependent variable can be explained by the model. Negative values indicate a poor fit and that the model is outperformed by a constant function. For linear regression, this is a horizontal line.RecallRecall measures how well an algorithm correctly predicts all of the true positives (TP) in a dataset. A true positive is a positive prediction that is also an actual positive value in the data. Recall is defined as follows: Recall = TP/(TP+FN), with values ranging from 0 to 1. Higher scores reflect a better ability of the model to predict true positives (TP) in the data, and is used in binary classification.Recall is important when testing for cancer because it's used to find all of the true positives. A false positive (FP) reflects a positive prediction that is actually negative in the data. It is often insufficient to measure only recall, because predicting every output as a true positive will yield a perfect recall score. RecallMacroThe RecallMacro computes recall for multiclass classification problems by calculating recall for each class and averaging scores to obtain recall for several classes. RecallMacro scores range from 0 to 1. Higher scores reflect the model's ability to predict true positives (TP) in a dataset. Whereas, a true positive reflects a positive prediction that is also an actual positive value in the data. It is often insufficient to measure only recall, because predicting every output as a true positive will yield a perfect recall score.RMSERoot mean squared error (RMSE) measures the square root of the squared difference between predicted and actual values, and it's averaged over all values. It is used in regression analysis to understand model prediction error. It's an important metric to indicate the presence of large model errors and outliers. Values range from zero (0) to infinity, with smaller numbers indicating a better model fit to the data. RMSE is dependent on scale, and should not be used to compare datasets of different sizes.If you do not specify a metric explicitly, the default behavior is to automatically use:MSE: for regression.F1: for binary classificationAccuracy : for multiclass classification.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The name of the objective metric used to measure the predictive quality of a machine learning system. This metric is optimized during training to provide the best estimate for model parameter values from data.Here are the options: AccuracyThe ratio of the number of correctly classified items to the total number of (correctly and incorrectly) classified items. It is used for both binary and multiclass classification. Accuracy measures how close the predicted class values are to the actual values. Values for accuracy metrics vary between zero (0) and one (1). A value of 1 indicates perfect accuracy, and 0 indicates perfect inaccuracy.AUCThe area under the curve (AUC) metric is used to compare and evaluate binary classification by algorithms that return probabilities, such as logistic regression. To map the probabilities into classifications, these are compared against a threshold value.The relevant curve is the receiver operating characteristic curve (ROC curve). The ROC curve plots the true positive rate (TPR) of predictions (or recall) against the false positive rate (FPR) as a function of the threshold value, above which a prediction is considered positive. Increasing the threshold results in fewer false positives, but more false negatives.AUC is the area under this ROC curve. Therefore, AUC provides an aggregated measure of the model performance across all possible classification thresholds. AUC scores vary between 0 and 1. A score of 1 indicates perfect accuracy, and a score of one half (0.5) indicates that the prediction is not better than a random classifier.BalancedAccuracyBalancedAccuracy is a metric that measures the ratio of accurate predictions to all predictions. This ratio is calculated after normalizing true positives (TP) and true negatives (TN) by the total number of positive (P) and negative (N) values. It is used in both binary and multiclass classification and is defined as follows: 0.5*((TP/P)+(TN/N)), with values ranging from 0 to 1. BalancedAccuracy gives a better measure of accuracy when the number of positives or negatives differ greatly from each other in an imbalanced dataset. For example, when only 1% of email is spam.F1The F1 score is the harmonic mean of the precision and recall, defined as follows: F1 = 2 * (precision * recall) / (precision + recall). It is used for binary classification into classes traditionally referred to as positive and negative. Predictions are said to be true when they match their actual (correct) class, and false when they do not.Precision is the ratio of the true positive predictions to all positive predictions, and it includes the false positives in a dataset. Precision measures the quality of the prediction when it predicts the positive class.Recall (or sensitivity) is the ratio of the true positive predictions to all actual positive instances. Recall measures how completely a model predicts the actual class members in a dataset.F1 scores vary between 0 and 1. A score of 1 indicates the best possible performance, and 0 indicates the worst.F1macroThe F1macro score applies F1 scoring to multiclass classification problems. It does this by calculating the precision and recall, and then taking their harmonic mean to calculate the F1 score for each class. Lastly, the F1macro averages the individual scores to obtain the F1macro score. F1macro scores vary between 0 and 1. A score of 1 indicates the best possible performance, and 0 indicates the worst.MAEThe mean absolute error (MAE) is a measure of how different the predicted and actual values are, when they're averaged over all values. MAE is commonly used in regression analysis to understand model prediction error. If there is linear regression, MAE represents the average distance from a predicted line to the actual value. MAE is defined as the sum of absolute errors divided by the number of observations. Values range from 0 to infinity, with smaller numbers indicating a better model fit to the data.MSEThe mean squared error (MSE) is the average of the squared differences between the predicted and actual values. It is used for regression. MSE values are always positive. The better a model is at predicting the actual values, the smaller the MSE value is PrecisionPrecision measures how well an algorithm predicts the true positives (TP) out of all of the positives that it identifies. It is defined as follows: Precision = TP/(TP+FP), with values ranging from zero (0) to one (1), and is used in binary classification. Precision is an important metric when the cost of a false positive is high. For example, the cost of a false positive is very high if an airplane safety system is falsely deemed safe to fly. A false positive (FP) reflects a positive prediction that is actually negative in the data.PrecisionMacroThe precision macro computes precision for multiclass classification problems. It does this by calculating precision for each class and averaging scores to obtain precision for several classes. PrecisionMacro scores range from zero (0) to one (1). Higher scores reflect the model's ability to predict true positives (TP) out of all of the positives that it identifies, averaged across multiple classes.R2R2, also known as the coefficient of determination, is used in regression to quantify how much a model can explain the variance of a dependent variable. Values range from one (1) to negative one (-1). Higher numbers indicate a higher fraction of explained variability. R2 values close to zero (0) indicate that very little of the dependent variable can be explained by the model. Negative values indicate a poor fit and that the model is outperformed by a constant function. For linear regression, this is a horizontal line.RecallRecall measures how well an algorithm correctly predicts all of the true positives (TP) in a dataset. A true positive is a positive prediction that is also an actual positive value in the data. Recall is defined as follows: Recall = TP/(TP+FN), with values ranging from 0 to 1. Higher scores reflect a better ability of the model to predict true positives (TP) in the data, and is used in binary classification.Recall is important when testing for cancer because it's used to find all of the true positives. A false positive (FP) reflects a positive prediction that is actually negative in the data. It is often insufficient to measure only recall, because predicting every output as a true positive will yield a perfect recall score. RecallMacroThe RecallMacro computes recall for multiclass classification problems by calculating recall for each class and averaging scores to obtain recall for several classes. RecallMacro scores range from 0 to 1. Higher scores reflect the model's ability to predict true positives (TP) in a dataset. Whereas, a true positive reflects a positive prediction that is also an actual positive value in the data. It is often insufficient to measure only recall, because predicting every output as a true positive will yield a perfect recall score.RMSERoot mean squared error (RMSE) measures the square root of the squared difference between predicted and actual values, and it's averaged over all values. It is used in regression analysis to understand model prediction error. It's an important metric to indicate the presence of large model errors and outliers. Values range from zero (0) to infinity, with smaller numbers indicating a better model fit to the data. RMSE is dependent on scale, and should not be used to compare datasets of different sizes.If you do not specify a metric explicitly, the default behavior is to automatically use:MSE: for regression.F1: for binary classificationAccuracy : for multiclass classification.amazonka-sagemakerThe name of the objective metric used to measure the predictive quality of a machine learning system. This metric is optimized during training to provide the best estimate for model parameter values from data.Here are the options: AccuracyThe ratio of the number of correctly classified items to the total number of (correctly and incorrectly) classified items. It is used for both binary and multiclass classification. Accuracy measures how close the predicted class values are to the actual values. Values for accuracy metrics vary between zero (0) and one (1). A value of 1 indicates perfect accuracy, and 0 indicates perfect inaccuracy.AUCThe area under the curve (AUC) metric is used to compare and evaluate binary classification by algorithms that return probabilities, such as logistic regression. To map the probabilities into classifications, these are compared against a threshold value.The relevant curve is the receiver operating characteristic curve (ROC curve). The ROC curve plots the true positive rate (TPR) of predictions (or recall) against the false positive rate (FPR) as a function of the threshold value, above which a prediction is considered positive. Increasing the threshold results in fewer false positives, but more false negatives.AUC is the area under this ROC curve. Therefore, AUC provides an aggregated measure of the model performance across all possible classification thresholds. AUC scores vary between 0 and 1. A score of 1 indicates perfect accuracy, and a score of one half (0.5) indicates that the prediction is not better than a random classifier.BalancedAccuracyBalancedAccuracy is a metric that measures the ratio of accurate predictions to all predictions. This ratio is calculated after normalizing true positives (TP) and true negatives (TN) by the total number of positive (P) and negative (N) values. It is used in both binary and multiclass classification and is defined as follows: 0.5*((TP/P)+(TN/N)), with values ranging from 0 to 1. BalancedAccuracy gives a better measure of accuracy when the number of positives or negatives differ greatly from each other in an imbalanced dataset. For example, when only 1% of email is spam.F1The F1 score is the harmonic mean of the precision and recall, defined as follows: F1 = 2 * (precision * recall) / (precision + recall). It is used for binary classification into classes traditionally referred to as positive and negative. Predictions are said to be true when they match their actual (correct) class, and false when they do not.Precision is the ratio of the true positive predictions to all positive predictions, and it includes the false positives in a dataset. Precision measures the quality of the prediction when it predicts the positive class.Recall (or sensitivity) is the ratio of the true positive predictions to all actual positive instances. Recall measures how completely a model predicts the actual class members in a dataset.F1 scores vary between 0 and 1. A score of 1 indicates the best possible performance, and 0 indicates the worst.F1macroThe F1macro score applies F1 scoring to multiclass classification problems. It does this by calculating the precision and recall, and then taking their harmonic mean to calculate the F1 score for each class. Lastly, the F1macro averages the individual scores to obtain the F1macro score. F1macro scores vary between 0 and 1. A score of 1 indicates the best possible performance, and 0 indicates the worst.MAEThe mean absolute error (MAE) is a measure of how different the predicted and actual values are, when they're averaged over all values. MAE is commonly used in regression analysis to understand model prediction error. If there is linear regression, MAE represents the average distance from a predicted line to the actual value. MAE is defined as the sum of absolute errors divided by the number of observations. Values range from 0 to infinity, with smaller numbers indicating a better model fit to the data.MSEThe mean squared error (MSE) is the average of the squared differences between the predicted and actual values. It is used for regression. MSE values are always positive. The better a model is at predicting the actual values, the smaller the MSE value is PrecisionPrecision measures how well an algorithm predicts the true positives (TP) out of all of the positives that it identifies. It is defined as follows: Precision = TP/(TP+FP), with values ranging from zero (0) to one (1), and is used in binary classification. Precision is an important metric when the cost of a false positive is high. For example, the cost of a false positive is very high if an airplane safety system is falsely deemed safe to fly. A false positive (FP) reflects a positive prediction that is actually negative in the data.PrecisionMacroThe precision macro computes precision for multiclass classification problems. It does this by calculating precision for each class and averaging scores to obtain precision for several classes. PrecisionMacro scores range from zero (0) to one (1). Higher scores reflect the model's ability to predict true positives (TP) out of all of the positives that it identifies, averaged across multiple classes.R2R2, also known as the coefficient of determination, is used in regression to quantify how much a model can explain the variance of a dependent variable. Values range from one (1) to negative one (-1). Higher numbers indicate a higher fraction of explained variability. R2 values close to zero (0) indicate that very little of the dependent variable can be explained by the model. Negative values indicate a poor fit and that the model is outperformed by a constant function. For linear regression, this is a horizontal line.RecallRecall measures how well an algorithm correctly predicts all of the true positives (TP) in a dataset. A true positive is a positive prediction that is also an actual positive value in the data. Recall is defined as follows: Recall = TP/(TP+FN), with values ranging from 0 to 1. Higher scores reflect a better ability of the model to predict true positives (TP) in the data, and is used in binary classification.Recall is important when testing for cancer because it's used to find all of the true positives. A false positive (FP) reflects a positive prediction that is actually negative in the data. It is often insufficient to measure only recall, because predicting every output as a true positive will yield a perfect recall score. RecallMacroThe RecallMacro computes recall for multiclass classification problems by calculating recall for each class and averaging scores to obtain recall for several classes. RecallMacro scores range from 0 to 1. Higher scores reflect the model's ability to predict true positives (TP) in a dataset. Whereas, a true positive reflects a positive prediction that is also an actual positive value in the data. It is often insufficient to measure only recall, because predicting every output as a true positive will yield a perfect recall score.RMSERoot mean squared error (RMSE) measures the square root of the squared difference between predicted and actual values, and it's averaged over all values. It is used in regression analysis to understand model prediction error. It's an important metric to indicate the presence of large model errors and outliers. Values range from zero (0) to infinity, with smaller numbers indicating a better model fit to the data. RMSE is dependent on scale, and should not be used to compare datasets of different sizes.If you do not specify a metric explicitly, the default behavior is to automatically use:MSE: for regression.F1: for binary classificationAccuracy : for multiclass classification.amazonka-sagemaker-(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?/!.(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?9 /(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';amazonka-sagemakerThe output data configuration.See:  smart constructor.amazonka-sagemaker3The Key Management Service (KMS) encryption key ID.amazonka-sagemaker:The Amazon S3 output path. Must be 128 characters or less.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 6 - The Key Management Service (KMS) encryption key ID., = - The Amazon S3 output path. Must be 128 characters or less.amazonka-sagemaker3The Key Management Service (KMS) encryption key ID.amazonka-sagemaker:The Amazon S3 output path. Must be 128 characters or less.amazonka-sagemaker0(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';amazonka-sagemaker2The reason for a partial failure of an AutoML job.See:  smart constructor.amazonka-sagemakerThe message containing the reason for a partial failure of an AutoML job.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The message containing the reason for a partial failure of an AutoML job.amazonka-sagemakerThe message containing the reason for a partial failure of an AutoML job.1(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';camazonka-sagemaker'Provides a summary about an AutoML job.See:  smart constructor.amazonka-sagemakerThe end time of an AutoML job.amazonka-sagemaker$The failure reason of an AutoML job.amazonka-sagemaker>The list of reasons for partial failures within an AutoML job.amazonka-sagemaker.The name of the AutoML job you are requesting.amazonka-sagemakerThe ARN of the AutoML job.amazonka-sagemakerThe status of the AutoML job.amazonka-sagemaker'The secondary status of the AutoML job.amazonka-sagemaker When the AutoML job was created.amazonka-sagemaker&When the AutoML job was last modified.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, ! - The end time of an AutoML job., ' - The failure reason of an AutoML job.,  - The list of reasons for partial failures within an AutoML job., 1 - The name of the AutoML job you are requesting.,  - The ARN of the AutoML job.,  - The status of the AutoML job., * - The secondary status of the AutoML job., # - When the AutoML job was created., ) - When the AutoML job was last modified.amazonka-sagemakerThe end time of an AutoML job.amazonka-sagemaker$The failure reason of an AutoML job.amazonka-sagemaker>The list of reasons for partial failures within an AutoML job.amazonka-sagemaker.The name of the AutoML job you are requesting.amazonka-sagemakerThe ARN of the AutoML job.amazonka-sagemakerThe status of the AutoML job.amazonka-sagemaker'The secondary status of the AutoML job.amazonka-sagemaker When the AutoML job was created.amazonka-sagemaker&When the AutoML job was last modified.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker2(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?[3(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';8amazonka-sagemakerThe Amazon S3 data source.See:  smart constructor.amazonka-sagemakerThe data type.2A ManifestFile should have the format shown below: [ {"prefix": "s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER/DOC-EXAMPLE-PREFIX/"}, 6"DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-1", 6"DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-2", ;... "DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-N" ]-An S3Prefix should have the following format: 2s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER-OR-FILEamazonka-sagemaker%The URL to the Amazon S3 data source.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The data type.2A ManifestFile should have the format shown below: [ {"prefix": "s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER/DOC-EXAMPLE-PREFIX/"}, 6"DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-1", 6"DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-2", ;... "DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-N" ]-An S3Prefix should have the following format: 2s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER-OR-FILE, ( - The URL to the Amazon S3 data source.amazonka-sagemakerThe data type.2A ManifestFile should have the format shown below: [ {"prefix": "s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER/DOC-EXAMPLE-PREFIX/"}, 6"DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-1", 6"DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-2", ;... "DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-N" ]-An S3Prefix should have the following format: 2s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER-OR-FILEamazonka-sagemaker%The URL to the Amazon S3 data source.amazonka-sagemakeramazonka-sagemaker4(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';amazonka-sagemaker&The data source for the Autopilot job.See:  smart constructor.amazonka-sagemaker)The Amazon S3 location of the input data.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, , - The Amazon S3 location of the input data.amazonka-sagemaker)The Amazon S3 location of the input data.amazonka-sagemaker5(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?n 6(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?0  7(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';j amazonka-sagemakerAutomatic rollback configuration for handling endpoint deployment failures and recovery.See:   smart constructor. amazonka-sagemakerList of CloudWatch alarms in your account that are configured to monitor metrics on an endpoint. If any alarms are tripped during a deployment, SageMaker rolls back the deployment. amazonka-sagemakerCreate a value of  " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility: ,   - List of CloudWatch alarms in your account that are configured to monitor metrics on an endpoint. If any alarms are tripped during a deployment, SageMaker rolls back the deployment. amazonka-sagemakerList of CloudWatch alarms in your account that are configured to monitor metrics on an endpoint. If any alarms are tripped during a deployment, SageMaker rolls back the deployment.  8(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?"  9(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';  amazonka-sagemakerConfiguration to control how SageMaker captures inference data for batch transform jobs.See:   smart constructor. amazonka-sagemakerFlag that indicates whether to append inference id to the output. amazonka-sagemakerThe Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the batch transform job.1The KmsKeyId can be any of the following formats:Key ID: $1234abcd-12ab-34cd-56ef-1234567890abKey ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab Alias name: alias/ExampleAliasAlias name ARN: 5arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias amazonka-sagemaker6The Amazon S3 location being used to capture the data. amazonka-sagemakerCreate a value of  " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility: ,   - Flag that indicates whether to append inference id to the output. ,   - The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the batch transform job.1The KmsKeyId can be any of the following formats:Key ID: $1234abcd-12ab-34cd-56ef-1234567890abKey ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab Alias name: alias/ExampleAliasAlias name ARN: 5arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias ,  9 - The Amazon S3 location being used to capture the data. amazonka-sagemakerFlag that indicates whether to append inference id to the output. amazonka-sagemakerThe Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the batch transform job.1The KmsKeyId can be any of the following formats:Key ID: $1234abcd-12ab-34cd-56ef-1234567890abKey ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab Alias name: alias/ExampleAliasAlias name ARN: 5arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias amazonka-sagemaker6The Amazon S3 location being used to capture the data. amazonka-sagemaker :(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; amazonka-sagemakerThe error code and error description associated with the resource.See:   smart constructor. amazonka-sagemakerCreate a value of  " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility: ,   - ,   - amazonka-sagemaker amazonka-sagemaker   ;(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?  <(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?;  =(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; amazonka-sagemaker6Details on the cache hit of a pipeline execution step.See:   smart constructor. amazonka-sagemaker9The Amazon Resource Name (ARN) of the pipeline execution. amazonka-sagemakerCreate a value of  " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility: ,  < - The Amazon Resource Name (ARN) of the pipeline execution. amazonka-sagemaker9The Amazon Resource Name (ARN) of the pipeline execution.  >(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';E amazonka-sagemaker6The location of artifacts for an AutoML candidate job.See:   smart constructor. amazonka-sagemakerThe Amazon S3 prefix to the model insight artifacts generated for the AutoML candidate. amazonka-sagemakerThe Amazon S3 prefix to the explainability artifacts generated for the AutoML candidate. amazonka-sagemakerCreate a value of  " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility: ,   - The Amazon S3 prefix to the model insight artifacts generated for the AutoML candidate. ,   - The Amazon S3 prefix to the explainability artifacts generated for the AutoML candidate. amazonka-sagemakerThe Amazon S3 prefix to the model insight artifacts generated for the AutoML candidate. amazonka-sagemakerThe Amazon S3 prefix to the explainability artifacts generated for the AutoML candidate. amazonka-sagemaker   ?(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? @(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? A(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? B(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';!/ amazonka-sagemakerInformation about the steps for a candidate and what step it is working on.See:   smart constructor. amazonka-sagemakerWhether the candidate is at the transform, training, or processing step. amazonka-sagemaker!The ARN for the candidate's step. amazonka-sagemaker"The name for the candidate's step. amazonka-sagemakerCreate a value of  " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility: ,   - Whether the candidate is at the transform, training, or processing step. ,  $ - The ARN for the candidate's step. ,  % - The name for the candidate's step. amazonka-sagemakerWhether the candidate is at the transform, training, or processing step. amazonka-sagemaker!The ARN for the candidate's step. amazonka-sagemaker"The name for the candidate's step. amazonka-sagemaker amazonka-sagemaker amazonka-sagemaker C(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?!  D(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';) amazonka-sagemaker;Specifies the endpoint capacity to activate for production.See:   smart constructor. amazonka-sagemaker%Specifies the endpoint capacity type.INSTANCE_COUNT?: The endpoint activates based on the number of instances.CAPACITY_PERCENT: The endpoint activates based on the specified percentage of capacity. amazonka-sagemakerDefines the capacity size, either as a number of instances or a capacity percentage. amazonka-sagemakerCreate a value of  " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility: ,  ( - Specifies the endpoint capacity type.INSTANCE_COUNT?: The endpoint activates based on the number of instances.CAPACITY_PERCENT: The endpoint activates based on the specified percentage of capacity. ,   - Defines the capacity size, either as a number of instances or a capacity percentage. amazonka-sagemaker%Specifies the endpoint capacity type.INSTANCE_COUNT?: The endpoint activates based on the number of instances.CAPACITY_PERCENT: The endpoint activates based on the specified percentage of capacity. amazonka-sagemakerDefines the capacity size, either as a number of instances or a capacity percentage. amazonka-sagemaker amazonka-sagemaker   E(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';. amazonka-sagemakerConfiguration specifying how to treat different headers. If no headers are specified SageMaker will by default base64 encode when capturing the data.See:   smart constructor. amazonka-sagemakerThe list of all content type headers that SageMaker will treat as CSV and capture accordingly. amazonka-sagemakerThe list of all content type headers that SageMaker will treat as JSON and capture accordingly. amazonka-sagemakerCreate a value of  " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility: ,   - The list of all content type headers that SageMaker will treat as CSV and capture accordingly. ,   - The list of all content type headers that SageMaker will treat as JSON and capture accordingly. amazonka-sagemakerThe list of all content type headers that SageMaker will treat as CSV and capture accordingly. amazonka-sagemakerThe list of all content type headers that SageMaker will treat as JSON and capture accordingly.  F(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?/  G(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';31 amazonka-sagemaker*Specifies data Model Monitor will capture.See:   smart constructor. amazonka-sagemaker(Specify the boundary of data to capture. amazonka-sagemakerCreate a value of  " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility: ,  + - Specify the boundary of data to capture. amazonka-sagemaker(Specify the boundary of data to capture. amazonka-sagemaker   H(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?3  I(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';8; amazonka-sagemakerEnvironment parameters you want to benchmark your load test against.See:   smart constructor. amazonka-sagemaker%The Name of the environment variable. amazonka-sagemaker The list of values you can pass. amazonka-sagemakerCreate a value of  " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility: ,  ( - The Name of the environment variable. ,  # - The list of values you can pass. amazonka-sagemaker%The Name of the environment variable. amazonka-sagemaker The list of values you can pass. amazonka-sagemaker amazonka-sagemaker   J(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';< amazonka-sagemaker.A list of categorical hyperparameters to tune.See:   smart constructor. amazonka-sagemaker3The name of the categorical hyperparameter to tune. amazonka-sagemaker0A list of the categories for the hyperparameter. amazonka-sagemakerCreate a value of  " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility: ,  6 - The name of the categorical hyperparameter to tune. ,  3 - A list of the categories for the hyperparameter. amazonka-sagemaker3The name of the categorical hyperparameter to tune. amazonka-sagemaker0A list of the categories for the hyperparameter. amazonka-sagemaker amazonka-sagemaker   K(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';@x amazonka-sagemaker=Defines the possible values for a categorical hyperparameter.See:   smart constructor. amazonka-sagemaker.The allowed categories for the hyperparameter. amazonka-sagemakerCreate a value of  " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility: ,  1 - The allowed categories for the hyperparameter. amazonka-sagemaker.The allowed categories for the hyperparameter. amazonka-sagemaker   L(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';F amazonka-sagemakerContains information about the output location for managed spot training checkpoint data.See:   smart constructor. amazonka-sagemaker(Optional) The local directory where checkpoints are written. The default directory is /opt/ml/checkpoints/. amazonka-sagemakerIdentifies the S3 path where you want SageMaker to store checkpoints. For example,  s3://bucket-name/key-name-prefix. amazonka-sagemakerCreate a value of  " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility: ,   - (Optional) The local directory where checkpoints are written. The default directory is /opt/ml/checkpoints/. ,   - Identifies the S3 path where you want SageMaker to store checkpoints. For example,  s3://bucket-name/key-name-prefix. amazonka-sagemaker(Optional) The local directory where checkpoints are written. The default directory is /opt/ml/checkpoints/. amazonka-sagemakerIdentifies the S3 path where you want SageMaker to store checkpoints. For example,  s3://bucket-name/key-name-prefix. amazonka-sagemaker   M(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';W amazonka-sagemakerThe container for the metadata for the ClarifyCheck step. For more information, see the topic on  https://docs.aws.amazon.com/sagemaker/latest/dg/build-and-manage-steps.html#step-type-clarify-checkClarifyCheck step in the  Amazon SageMaker Developer Guide.See:   smart constructor. amazonka-sagemakerThe Amazon S3 URI of baseline constraints file to be used for the drift check. amazonka-sagemakerThe Amazon S3 URI of the newly calculated baseline constraints file. amazonka-sagemakerThe Amazon Resource Name (ARN) of the check processing job that was run by this step's execution. amazonka-sagemaker"The type of the Clarify Check step amazonka-sagemakerThe model package group name. amazonka-sagemakerThis flag indicates if a newly calculated baseline can be accessed through step properties $BaselineUsedForDriftCheckConstraints and #BaselineUsedForDriftCheckStatistics. If it is set to False, the previous baseline of the configured check type must also be available. These can be accessed through the $BaselineUsedForDriftCheckConstraints property. amazonka-sagemakerThis flag indicates if the drift check against the previous baseline will be skipped or not. If it is set to False, the previous baseline of the configured check type must be available. amazonka-sagemakerThe Amazon S3 URI of the violation report if violations are detected. amazonka-sagemakerCreate a value of  " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility: ,   - The Amazon S3 URI of baseline constraints file to be used for the drift check. ,   - The Amazon S3 URI of the newly calculated baseline constraints file. ,   - The Amazon Resource Name (ARN) of the check processing job that was run by this step's execution. ,  % - The type of the Clarify Check step ,   - The model package group name. ,   - This flag indicates if a newly calculated baseline can be accessed through step properties $BaselineUsedForDriftCheckConstraints and #BaselineUsedForDriftCheckStatistics. If it is set to False, the previous baseline of the configured check type must also be available. These can be accessed through the $BaselineUsedForDriftCheckConstraints property. ,   - This flag indicates if the drift check against the previous baseline will be skipped or not. If it is set to False, the previous baseline of the configured check type must be available. ,   - The Amazon S3 URI of the violation report if violations are detected. amazonka-sagemakerThe Amazon S3 URI of baseline constraints file to be used for the drift check. amazonka-sagemakerThe Amazon S3 URI of the newly calculated baseline constraints file. amazonka-sagemakerThe Amazon Resource Name (ARN) of the check processing job that was run by this step's execution. amazonka-sagemaker"The type of the Clarify Check step amazonka-sagemakerThe model package group name. amazonka-sagemakerThis flag indicates if a newly calculated baseline can be accessed through step properties $BaselineUsedForDriftCheckConstraints and #BaselineUsedForDriftCheckStatistics. If it is set to False, the previous baseline of the configured check type must also be available. These can be accessed through the $BaselineUsedForDriftCheckConstraints property. amazonka-sagemakerThis flag indicates if the drift check against the previous baseline will be skipped or not. If it is set to False, the previous baseline of the configured check type must be available. amazonka-sagemakerThe Amazon S3 URI of the violation report if violations are detected.  N(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?X O(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';M amazonka-sagemaker>The inference configuration parameter for the model container.See:   smart constructor. amazonka-sagemakerA template string used to format a JSON record into an acceptable model container input. For example, a ContentTemplate string '{"myfeatures":$features}'! will format a list of features [1,2,3] into the record string '{"myfeatures":[1,2,3]}'. Required only when the model container input is in JSON Lines format. amazonka-sagemakerThe names of the features. If provided, these are included in the endpoint response payload to help readability of the InvokeEndpoint output. See the  https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-online-explainability-invoke-endpoint.html#clarify-online-explainability-responseResponse section under Invoke the endpoint. in the Developer Guide for more information. amazonka-sagemakerA list of data types of the features (optional). Applicable only to NLP explainability. If provided,  FeatureTypes must have at least one 'text' string (for example, ['text']). If  FeatureTypes is not provided, the explainer infers the feature types based on the baseline data. The feature types are included in the endpoint response payload. For additional information see the  https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-online-explainability-invoke-endpoint.html#clarify-online-explainability-responseresponse section under Invoke the endpoint. in the Developer Guide for more information. amazonka-sagemakerProvides the JMESPath expression to extract the features from a model container input in JSON Lines format. For example, if FeaturesAttribute is the JMESPath expression  'myfeatures'", it extracts a list of features [1,2,3] from request data '{"myfeatures":[1,2,3]}'. amazonka-sagemakerA JMESPath expression used to locate the list of label headers in the model container output.Example7: If the model container output of a batch request is ='{"labels":["cat","dog","fish"],"probability":[0.6,0.3,0.1]}' , then set LabelAttribute to 'labels'' to extract the list of label headers ["cat","dog","fish"] amazonka-sagemakerFor multiclass classification problems, the label headers are the names of the classes. Otherwise, the label header is the name of the predicted label. These are used to help readability for the output of the InvokeEndpoint API. See the  https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-online-explainability-invoke-endpoint.html#clarify-online-explainability-responseresponse section under Invoke the endpoint in the Developer Guide for more information. If there are no label headers in the model container output, provide them manually using this parameter. amazonka-sagemakerA zero-based index used to extract a label header or list of label headers from model container output in CSV format.Example for a multiclass model: If the model container output consists of label headers followed by probabilities: .'"[\'cat\',\'dog\',\'fish\']","[0.1,0.6,0.3]"', set  LabelIndex to 0 to select the label headers ['cat','dog','fish']. amazonka-sagemakerThe maximum payload size (MB) allowed of a request from the explainer to the model container. Defaults to 6 MB. amazonka-sagemakerThe maximum number of records in a request that the model container can process when querying the model container for the predictions of a  https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-online-explainability-create-endpoint.html#clarify-online-explainability-create-endpoint-syntheticsynthetic dataset. A record is a unit of input data that inference can be made on, for example, a single line in CSV data. If MaxRecordCount is 1, the model container expects one record per request. A value of 2 or greater means that the model expects batch requests, which can reduce overhead and speed up the inferencing process. If this parameter is not provided, the explainer will tune the record count per request according to the model container's capacity at runtime. amazonka-sagemakerA JMESPath expression used to extract the probability (or score) from the model container output if the model container is in JSON Lines format.Example8: If the model container output of a single request is )'{"predicted_label":1,"probability":0.6}' , then set ProbabilityAttribute to  'probability'. amazonka-sagemakerA zero-based index used to extract a probability value (score) or list from model container output in CSV format. If this value is not provided, the entire model container output will be treated as a probability value (score) or list.!Example for a single class model: If the model container output consists of a string-formatted prediction label followed by its probability: '1,0.6', set ProbabilityIndex to 1" to select the probability value 0.6.Example for a multiclass model: If the model container output consists of a string-formatted prediction label followed by its probability: .'"[\'cat\',\'dog\',\'fish\']","[0.1,0.6,0.3]"', set ProbabilityIndex to 1# to select the probability values  [0.1,0.6,0.3]. amazonka-sagemakerCreate a value of  " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility: ,   - A template string used to format a JSON record into an acceptable model container input. For example, a ContentTemplate string '{"myfeatures":$features}'! will format a list of features [1,2,3] into the record string '{"myfeatures":[1,2,3]}'. Required only when the model container input is in JSON Lines format. ,   - The names of the features. If provided, these are included in the endpoint response payload to help readability of the InvokeEndpoint output. See the  https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-online-explainability-invoke-endpoint.html#clarify-online-explainability-responseResponse section under Invoke the endpoint. in the Developer Guide for more information. ,   - A list of data types of the features (optional). Applicable only to NLP explainability. If provided,  FeatureTypes must have at least one 'text' string (for example, ['text']). If  FeatureTypes is not provided, the explainer infers the feature types based on the baseline data. The feature types are included in the endpoint response payload. For additional information see the  https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-online-explainability-invoke-endpoint.html#clarify-online-explainability-responseresponse section under Invoke the endpoint. in the Developer Guide for more information. ,   - Provides the JMESPath expression to extract the features from a model container input in JSON Lines format. For example, if FeaturesAttribute is the JMESPath expression  'myfeatures'", it extracts a list of features [1,2,3] from request data '{"myfeatures":[1,2,3]}'. ,   - A JMESPath expression used to locate the list of label headers in the model container output.Example7: If the model container output of a batch request is ='{"labels":["cat","dog","fish"],"probability":[0.6,0.3,0.1]}' , then set LabelAttribute to 'labels'' to extract the list of label headers ["cat","dog","fish"] ,   - For multiclass classification problems, the label headers are the names of the classes. Otherwise, the label header is the name of the predicted label. These are used to help readability for the output of the InvokeEndpoint API. See the  https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-online-explainability-invoke-endpoint.html#clarify-online-explainability-responseresponse section under Invoke the endpoint in the Developer Guide for more information. If there are no label headers in the model container output, provide them manually using this parameter. ,   - A zero-based index used to extract a label header or list of label headers from model container output in CSV format.Example for a multiclass model: If the model container output consists of label headers followed by probabilities: .'"[\'cat\',\'dog\',\'fish\']","[0.1,0.6,0.3]"', set  LabelIndex to 0 to select the label headers ['cat','dog','fish']. ,   - The maximum payload size (MB) allowed of a request from the explainer to the model container. Defaults to 6 MB. ,   - The maximum number of records in a request that the model container can process when querying the model container for the predictions of a  https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-online-explainability-create-endpoint.html#clarify-online-explainability-create-endpoint-syntheticsynthetic dataset. A record is a unit of input data that inference can be made on, for example, a single line in CSV data. If MaxRecordCount is 1, the model container expects one record per request. A value of 2 or greater means that the model expects batch requests, which can reduce overhead and speed up the inferencing process. If this parameter is not provided, the explainer will tune the record count per request according to the model container's capacity at runtime. ,   - A JMESPath expression used to extract the probability (or score) from the model container output if the model container is in JSON Lines format.Example8: If the model container output of a single request is )'{"predicted_label":1,"probability":0.6}' , then set ProbabilityAttribute to  'probability'. ,   - A zero-based index used to extract a probability value (score) or list from model container output in CSV format. If this value is not provided, the entire model container output will be treated as a probability value (score) or list.!Example for a single class model: If the model container output consists of a string-formatted prediction label followed by its probability: '1,0.6', set ProbabilityIndex to 1" to select the probability value 0.6.Example for a multiclass model: If the model container output consists of a string-formatted prediction label followed by its probability: .'"[\'cat\',\'dog\',\'fish\']","[0.1,0.6,0.3]"', set ProbabilityIndex to 1# to select the probability values  [0.1,0.6,0.3]. amazonka-sagemakerA template string used to format a JSON record into an acceptable model container input. For example, a ContentTemplate string '{"myfeatures":$features}'! will format a list of features [1,2,3] into the record string '{"myfeatures":[1,2,3]}'. Required only when the model container input is in JSON Lines format. amazonka-sagemakerThe names of the features. If provided, these are included in the endpoint response payload to help readability of the InvokeEndpoint output. See the  https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-online-explainability-invoke-endpoint.html#clarify-online-explainability-responseResponse section under Invoke the endpoint. in the Developer Guide for more information. amazonka-sagemakerA list of data types of the features (optional). Applicable only to NLP explainability. If provided,  FeatureTypes must have at least one 'text' string (for example, ['text']). If  FeatureTypes is not provided, the explainer infers the feature types based on the baseline data. The feature types are included in the endpoint response payload. For additional information see the  https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-online-explainability-invoke-endpoint.html#clarify-online-explainability-responseresponse section under Invoke the endpoint. in the Developer Guide for more information. amazonka-sagemakerProvides the JMESPath expression to extract the features from a model container input in JSON Lines format. For example, if FeaturesAttribute is the JMESPath expression  'myfeatures'", it extracts a list of features [1,2,3] from request data '{"myfeatures":[1,2,3]}'. amazonka-sagemakerA JMESPath expression used to locate the list of label headers in the model container output.Example7: If the model container output of a batch request is ='{"labels":["cat","dog","fish"],"probability":[0.6,0.3,0.1]}' , then set LabelAttribute to 'labels'' to extract the list of label headers ["cat","dog","fish"] amazonka-sagemakerFor multiclass classification problems, the label headers are the names of the classes. Otherwise, the label header is the name of the predicted label. These are used to help readability for the output of the InvokeEndpoint API. See the  https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-online-explainability-invoke-endpoint.html#clarify-online-explainability-responseresponse section under Invoke the endpoint in the Developer Guide for more information. If there are no label headers in the model container output, provide them manually using this parameter. amazonka-sagemakerA zero-based index used to extract a label header or list of label headers from model container output in CSV format.Example for a multiclass model: If the model container output consists of label headers followed by probabilities: .'"[\'cat\',\'dog\',\'fish\']","[0.1,0.6,0.3]"', set  LabelIndex to 0 to select the label headers ['cat','dog','fish']. amazonka-sagemakerThe maximum payload size (MB) allowed of a request from the explainer to the model container. Defaults to 6 MB. amazonka-sagemakerThe maximum number of records in a request that the model container can process when querying the model container for the predictions of a  https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-online-explainability-create-endpoint.html#clarify-online-explainability-create-endpoint-syntheticsynthetic dataset. A record is a unit of input data that inference can be made on, for example, a single line in CSV data. If MaxRecordCount is 1, the model container expects one record per request. A value of 2 or greater means that the model expects batch requests, which can reduce overhead and speed up the inferencing process. If this parameter is not provided, the explainer will tune the record count per request according to the model container's capacity at runtime. amazonka-sagemakerA JMESPath expression used to extract the probability (or score) from the model container output if the model container is in JSON Lines format.Example8: If the model container output of a single request is )'{"predicted_label":1,"probability":0.6}' , then set ProbabilityAttribute to  'probability'. amazonka-sagemakerA zero-based index used to extract a probability value (score) or list from model container output in CSV format. If this value is not provided, the entire model container output will be treated as a probability value (score) or list.!Example for a single class model: If the model container output consists of a string-formatted prediction label followed by its probability: '1,0.6', set ProbabilityIndex to 1" to select the probability value 0.6.Example for a multiclass model: If the model container output consists of a string-formatted prediction label followed by its probability: .'"[\'cat\',\'dog\',\'fish\']","[0.1,0.6,0.3]"', set ProbabilityIndex to 1# to select the probability values  [0.1,0.6,0.3].  P(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; amazonka-sagemakerThe configuration for the  https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-feature-attribute-shap-baselines.html SHAP baseline (also called the background or reference dataset) of the Kernal SHAP algorithm.The number of records in the baseline data determines the size of the synthetic dataset, which has an impact on latency of explainability requests. For more information, see the __Synthetic data__ of  https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-online-explainability-create-endpoint.html Configure and create an endpoint. ShapBaseline and ShapBaselineUri are mutually exclusive parameters. One or the either is required to configure a SHAP baseline.See:   smart constructor. amazonka-sagemaker0The MIME type of the baseline data. Choose from  'text/csv' or 'application/jsonlines'. Defaults to  'text/csv'. amazonka-sagemaker0The inline SHAP baseline data in string format.  ShapBaseline can have one or multiple records to be used as the baseline dataset. The format of the SHAP baseline file should be the same format as the training dataset. For example, if the training dataset is in CSV format and each record contains four features, and all features are numerical, then the format of the baseline data should also share these characteristics. For natural language processing (NLP) of text columns, the baseline value should be the value used to replace the unit of text specified by the  Granularity of the  TextConfig parameter. The size limit for  ShapBasline is 4 KB. Use the ShapBaselineUri parameter if you want to provide more than 4 KB of baseline data. amazonka-sagemakerThe uniform resource identifier (URI) of the S3 bucket where the SHAP baseline file is stored. The format of the SHAP baseline file should be the same format as the format of the training dataset. For example, if the training dataset is in CSV format, and each record in the training dataset has four features, and all features are numerical, then the baseline file should also have this same format. Each record should contain only the features. If you are using a virtual private cloud (VPC), the ShapBaselineUri should be accessible to the VPC. For more information about setting up endpoints with Amazon Virtual Private Cloud, see  https://docs.aws.amazon.com/sagemaker/latest/dg/infrastructure-give-access.htmlGive SageMaker access to Resources in your Amazon Virtual Private Cloud. amazonka-sagemakerCreate a value of  " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility: ,  3 - The MIME type of the baseline data. Choose from  'text/csv' or 'application/jsonlines'. Defaults to  'text/csv'. ,  3 - The inline SHAP baseline data in string format.  ShapBaseline can have one or multiple records to be used as the baseline dataset. The format of the SHAP baseline file should be the same format as the training dataset. For example, if the training dataset is in CSV format and each record contains four features, and all features are numerical, then the format of the baseline data should also share these characteristics. For natural language processing (NLP) of text columns, the baseline value should be the value used to replace the unit of text specified by the  Granularity of the  TextConfig parameter. The size limit for  ShapBasline is 4 KB. Use the ShapBaselineUri parameter if you want to provide more than 4 KB of baseline data. ,   - The uniform resource identifier (URI) of the S3 bucket where the SHAP baseline file is stored. The format of the SHAP baseline file should be the same format as the format of the training dataset. For example, if the training dataset is in CSV format, and each record in the training dataset has four features, and all features are numerical, then the baseline file should also have this same format. Each record should contain only the features. If you are using a virtual private cloud (VPC), the ShapBaselineUri should be accessible to the VPC. For more information about setting up endpoints with Amazon Virtual Private Cloud, see  https://docs.aws.amazon.com/sagemaker/latest/dg/infrastructure-give-access.htmlGive SageMaker access to Resources in your Amazon Virtual Private Cloud. amazonka-sagemaker0The MIME type of the baseline data. Choose from  'text/csv' or 'application/jsonlines'. Defaults to  'text/csv'. amazonka-sagemaker0The inline SHAP baseline data in string format.  ShapBaseline can have one or multiple records to be used as the baseline dataset. The format of the SHAP baseline file should be the same format as the training dataset. For example, if the training dataset is in CSV format and each record contains four features, and all features are numerical, then the format of the baseline data should also share these characteristics. For natural language processing (NLP) of text columns, the baseline value should be the value used to replace the unit of text specified by the  Granularity of the  TextConfig parameter. The size limit for  ShapBasline is 4 KB. Use the ShapBaselineUri parameter if you want to provide more than 4 KB of baseline data. amazonka-sagemakerThe uniform resource identifier (URI) of the S3 bucket where the SHAP baseline file is stored. The format of the SHAP baseline file should be the same format as the format of the training dataset. For example, if the training dataset is in CSV format, and each record in the training dataset has four features, and all features are numerical, then the baseline file should also have this same format. Each record should contain only the features. If you are using a virtual private cloud (VPC), the ShapBaselineUri should be accessible to the VPC. For more information about setting up endpoints with Amazon Virtual Private Cloud, see  https://docs.aws.amazon.com/sagemaker/latest/dg/infrastructure-give-access.htmlGive SageMaker access to Resources in your Amazon Virtual Private Cloud. Q(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? R(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";??    S(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';amazonka-sagemakerA parameter used to configure the SageMaker Clarify explainer to treat text features as text so that explanations are provided for individual units of text. Required only for natural language processing (NLP) explainability.See:  smart constructor.amazonka-sagemaker0Specifies the language of the text features in  8%20https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes ISO 639-1 or  'https://en.wikipedia.org/wiki/ISO_639-3 ISO 639-3 code of a supported language.*For a mix of multiple languages, use code 'xx'.amazonka-sagemakerThe unit of granularity for the analysis of text features. For example, if the unit is 'token', then each token (like a word in English) of the text is treated as a feature. SHAP values are computed for each unit/feature.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 3 - Specifies the language of the text features in  8%20https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes ISO 639-1 or  'https://en.wikipedia.org/wiki/ISO_639-3 ISO 639-3 code of a supported language.*For a mix of multiple languages, use code 'xx'.,  - The unit of granularity for the analysis of text features. For example, if the unit is 'token', then each token (like a word in English) of the text is treated as a feature. SHAP values are computed for each unit/feature.amazonka-sagemaker0Specifies the language of the text features in  8%20https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes ISO 639-1 or  'https://en.wikipedia.org/wiki/ISO_639-3 ISO 639-3 code of a supported language.*For a mix of multiple languages, use code 'xx'.amazonka-sagemakerThe unit of granularity for the analysis of text features. For example, if the unit is 'token', then each token (like a word in English) of the text is treated as a feature. SHAP values are computed for each unit/feature.amazonka-sagemakeramazonka-sagemakerT(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; amazonka-sagemakerThe configuration for SHAP analysis using SageMaker Clarify Explainer.See:  smart constructor.amazonka-sagemakerThe number of samples to be used for analysis by the Kernal SHAP algorithm.The number of samples determines the size of the synthetic dataset, which has an impact on latency of explainability requests. For more information, see the Synthetic data of  https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-online-explainability-create-endpoint.html Configure and create an endpoint.amazonka-sagemakerThe starting value used to initialize the random number generator in the explainer. Provide a value for this parameter to obtain a deterministic SHAP result.amazonka-sagemakerA parameter that indicates if text features are treated as text and explanations are provided for individual units of text. Required for natural language processing (NLP) explainability only.amazonka-sagemakerA Boolean toggle to indicate if you want to use the logit function (true) or log-odds units (false) for model predictions. Defaults to false.amazonka-sagemakerThe configuration for the SHAP baseline of the Kernal SHAP algorithm.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The number of samples to be used for analysis by the Kernal SHAP algorithm.The number of samples determines the size of the synthetic dataset, which has an impact on latency of explainability requests. For more information, see the Synthetic data of  https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-online-explainability-create-endpoint.html Configure and create an endpoint.,  - The starting value used to initialize the random number generator in the explainer. Provide a value for this parameter to obtain a deterministic SHAP result.,  - A parameter that indicates if text features are treated as text and explanations are provided for individual units of text. Required for natural language processing (NLP) explainability only.,  - A Boolean toggle to indicate if you want to use the logit function (true) or log-odds units (false) for model predictions. Defaults to false.,  - The configuration for the SHAP baseline of the Kernal SHAP algorithm.amazonka-sagemakerThe number of samples to be used for analysis by the Kernal SHAP algorithm.The number of samples determines the size of the synthetic dataset, which has an impact on latency of explainability requests. For more information, see the Synthetic data of  https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-online-explainability-create-endpoint.html Configure and create an endpoint.amazonka-sagemakerThe starting value used to initialize the random number generator in the explainer. Provide a value for this parameter to obtain a deterministic SHAP result.amazonka-sagemakerA parameter that indicates if text features are treated as text and explanations are provided for individual units of text. Required for natural language processing (NLP) explainability only.amazonka-sagemakerA Boolean toggle to indicate if you want to use the logit function (true) or log-odds units (false) for model predictions. Defaults to false.amazonka-sagemakerThe configuration for the SHAP baseline of the Kernal SHAP algorithm.amazonka-sagemaker  U(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';ڏamazonka-sagemakerThe configuration parameters for the SageMaker Clarify explainer.See:  smart constructor.amazonka-sagemakerA JMESPath boolean expression used to filter which records to explain. Explanations are activated by default. See  https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-online-explainability-create-endpoint.html#clarify-online-explainability-create-endpoint-enableEnableExplanations for additional information.amazonka-sagemaker>The inference configuration parameter for the model container.amazonka-sagemaker$The configuration for SHAP analysis.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - A JMESPath boolean expression used to filter which records to explain. Explanations are activated by default. See  https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-online-explainability-create-endpoint.html#clarify-online-explainability-create-endpoint-enableEnableExplanations for additional information.,  - The inference configuration parameter for the model container., ' - The configuration for SHAP analysis.amazonka-sagemakerA JMESPath boolean expression used to filter which records to explain. Explanations are activated by default. See  https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-online-explainability-create-endpoint.html#clarify-online-explainability-create-endpoint-enableEnableExplanations for additional information.amazonka-sagemaker>The inference configuration parameter for the model container.amazonka-sagemaker$The configuration for SHAP analysis.amazonka-sagemaker  V(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';=amazonka-sagemakerA Git repository that SageMaker automatically displays to users for cloning in the JupyterServer application.See:  smart constructor.amazonka-sagemakerThe URL of the Git repository.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, ! - The URL of the Git repository.amazonka-sagemakerThe URL of the Git repository.amazonka-sagemakerW(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? X(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?߷Y(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';amazonka-sagemakerUse this parameter to configure your Amazon Cognito workforce. A single Cognito workforce is created using and corresponds to a single  https://docs.aws.amazon.com/cognito/latest/developerguide/cognito-user-identity-pools.htmlAmazon Cognito user pool.See:  smart constructor.amazonka-sagemakerA  https://docs.aws.amazon.com/cognito/latest/developerguide/cognito-user-identity-pools.html user pool is a user directory in Amazon Cognito. With a user pool, your users can sign in to your web or mobile app through Amazon Cognito. Your users can also sign in through social identity providers like Google, Facebook, Amazon, or Apple, and through SAML identity providers.amazonka-sagemaker0The client ID for your Amazon Cognito user pool.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - A  https://docs.aws.amazon.com/cognito/latest/developerguide/cognito-user-identity-pools.html user pool is a user directory in Amazon Cognito. With a user pool, your users can sign in to your web or mobile app through Amazon Cognito. Your users can also sign in through social identity providers like Google, Facebook, Amazon, or Apple, and through SAML identity providers., 3 - The client ID for your Amazon Cognito user pool.amazonka-sagemakerA  https://docs.aws.amazon.com/cognito/latest/developerguide/cognito-user-identity-pools.html user pool is a user directory in Amazon Cognito. With a user pool, your users can sign in to your web or mobile app through Amazon Cognito. Your users can also sign in through social identity providers like Google, Facebook, Amazon, or Apple, and through SAML identity providers.amazonka-sagemaker0The client ID for your Amazon Cognito user pool.amazonka-sagemakeramazonka-sagemakerZ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';amazonka-sagemakerIdentifies a Amazon Cognito user group. A user group can be used in on or more work teams.See:  smart constructor.amazonka-sagemakerAn identifier for a user pool. The user pool must be in the same region as the service that you are calling.amazonka-sagemakerAn identifier for a user group.amazonka-sagemakerAn identifier for an application client. You must create the app client ID using Amazon Cognito.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - An identifier for a user pool. The user pool must be in the same region as the service that you are calling., " - An identifier for a user group.,  - An identifier for an application client. You must create the app client ID using Amazon Cognito.amazonka-sagemakerAn identifier for a user pool. The user pool must be in the same region as the service that you are calling.amazonka-sagemakerAn identifier for a user group.amazonka-sagemakerAn identifier for an application client. You must create the app client ID using Amazon Cognito.amazonka-sagemakeramazonka-sagemakeramazonka-sagemaker  [(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';amazonka-sagemakerConfiguration information for the Amazon SageMaker Debugger output tensor collections.See:  smart constructor.amazonka-sagemakerThe name of the tensor collection. The name must be unique relative to other rule configuration names.amazonka-sagemakerParameter values for the tensor collection. The allowed parameters are "name", "include_regex", "reduction_config",  "save_config", "tensor_names", and "save_histogram".amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The name of the tensor collection. The name must be unique relative to other rule configuration names.,  - Parameter values for the tensor collection. The allowed parameters are "name", "include_regex", "reduction_config",  "save_config", "tensor_names", and "save_histogram".amazonka-sagemakerThe name of the tensor collection. The name must be unique relative to other rule configuration names.amazonka-sagemakerParameter values for the tensor collection. The allowed parameters are "name", "include_regex", "reduction_config",  "save_config", "tensor_names", and "save_histogram".\(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? ](c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?^(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; amazonka-sagemakerA channel is a named input source that training algorithms can consume. The validation dataset size is limited to less than 2 GB. The training dataset size must be less than 100 GB. For more information, see .A validation dataset must contain the same headers as the training dataset.See:  smart constructor.amazonka-sagemaker"The channel type (optional) is an enum string. The default value is training<. Channels for training and validation must share the same  ContentType and TargetAttributeName. For information on specifying training and validation channel types, see  https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-datasets-problem-types.html#autopilot-data-sources-training-or-validation/How to specify training and validation datasets .amazonka-sagemaker You can use Gzip or None. The default value is None.amazonka-sagemakerThe content type of the data from the input source. You can use text/csv;header=present or  x-application/vnd.amazon+parquet. The default value is text/csv;header=present.amazonka-sagemaker&The data source for an AutoML channel.amazonka-sagemakerThe name of the target variable in supervised learning, usually represented by 'y'.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, % - The channel type (optional) is an enum string. The default value is training<. Channels for training and validation must share the same  ContentType and TargetAttributeName. For information on specifying training and validation channel types, see  https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-datasets-problem-types.html#autopilot-data-sources-training-or-validation/How to specify training and validation datasets .,  - You can use Gzip or None. The default value is None.,  - The content type of the data from the input source. You can use text/csv;header=present or  x-application/vnd.amazon+parquet. The default value is text/csv;header=present., ) - The data source for an AutoML channel.,  - The name of the target variable in supervised learning, usually represented by 'y'.amazonka-sagemaker"The channel type (optional) is an enum string. The default value is training<. Channels for training and validation must share the same  ContentType and TargetAttributeName. For information on specifying training and validation channel types, see  https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-datasets-problem-types.html#autopilot-data-sources-training-or-validation/How to specify training and validation datasets .amazonka-sagemaker You can use Gzip or None. The default value is None.amazonka-sagemakerThe content type of the data from the input source. You can use text/csv;header=present or  x-application/vnd.amazon+parquet. The default value is text/csv;header=present.amazonka-sagemaker&The data source for an AutoML channel.amazonka-sagemakerThe name of the target variable in supervised learning, usually represented by 'y'.amazonka-sagemakeramazonka-sagemaker  _(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?`(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; #amazonka-sagemakerMetadata for a Condition step.See:  smart constructor.amazonka-sagemaker-The outcome of the Condition step evaluation.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 0 - The outcome of the Condition step evaluation.amazonka-sagemaker-The outcome of the Condition step evaluation.a(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? b(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? c(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';amazonka-sagemaker/A structure describing the source of a context.See:  smart constructor.amazonka-sagemakerThe ID of the source.amazonka-sagemakerThe type of the source.amazonka-sagemakerThe URI of the source.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The ID of the source.,  - The type of the source.,  - The URI of the source.amazonka-sagemakerThe ID of the source.amazonka-sagemakerThe type of the source.amazonka-sagemakerThe URI of the source.amazonka-sagemaker  d(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';amazonka-sagemakerLists a summary of the properties of a context. A context provides a logical grouping of other entities.See:  smart constructor.amazonka-sagemaker.The Amazon Resource Name (ARN) of the context.amazonka-sagemakerThe name of the context.amazonka-sagemakerThe type of the context.amazonka-sagemakerWhen the context was created.amazonka-sagemaker#When the context was last modified.amazonka-sagemakerThe source of the context.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 1 - The Amazon Resource Name (ARN) of the context.,  - The name of the context.,  - The type of the context.,  - When the context was created., & - When the context was last modified.,  - The source of the context.amazonka-sagemaker.The Amazon Resource Name (ARN) of the context.amazonka-sagemakerThe name of the context.amazonka-sagemakerThe type of the context.amazonka-sagemakerWhen the context was created.amazonka-sagemaker#When the context was last modified.amazonka-sagemakerThe source of the context.e(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';Xamazonka-sagemaker - The percentage of requests being captured by your Endpoint., 9 - The Amazon S3 location being used to capture the data., ; - The KMS key being used to encrypt the data in Amazon S3.amazonka-sagemaker,Whether data capture is enabled or disabled.amazonka-sagemaker-Whether data capture is currently functional.amazonka-sagemaker;The percentage of requests being captured by your Endpoint.amazonka-sagemaker6The Amazon S3 location being used to capture the data.amazonka-sagemaker8The KMS key being used to encrypt the data in Amazon S3.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker  i(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';@amazonka-sagemakerThe meta data of the Glue table which serves as data catalog for the  OfflineStore.See:  smart constructor.amazonka-sagemakerThe name of the Glue table.amazonka-sagemaker#The name of the Glue table catalog.amazonka-sagemaker$The name of the Glue table database.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The name of the Glue table., & - The name of the Glue table catalog., ' - The name of the Glue table database.amazonka-sagemakerThe name of the Glue table.amazonka-sagemaker#The name of the Glue table catalog.amazonka-sagemaker$The name of the Glue table database.amazonka-sagemakeramazonka-sagemakeramazonka-sagemaker  j(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?Ak(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';Namazonka-sagemakerInformation about the container that a data quality monitoring job runs.See:  smart constructor.amazonka-sagemakerThe arguments to send to the container that the monitoring job runs.amazonka-sagemakerThe container image that the data quality monitoring job runs.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The arguments to send to the container that the monitoring job runs., ? - The entrypoint for a container used to run a monitoring job.,  - Sets the environment variables in the container that the monitoring job runs.,  - An Amazon S3 URI to a script that is called after analysis has been performed. Applicable only for the built-in (first party) containers.,  - An Amazon S3 URI to a script that is called per row prior to running analysis. It can base64 decode the payload and convert it into a flatted json so that the built-in container can use the converted data. Applicable only for the built-in (first party) containers.,  - The container image that the data quality monitoring job runs.amazonka-sagemakerThe arguments to send to the container that the monitoring job runs.amazonka-sagemakerThe container image that the data quality monitoring job runs.amazonka-sagemakerl(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';Z amazonka-sagemakerConfiguration information for the Amazon SageMaker Debugger hook parameters, metric and tensor collections, and storage paths. To learn more about how to configure the DebugHookConfig parameter, see  https://docs.aws.amazon.com/sagemaker/latest/dg/debugger-createtrainingjob-api.htmlUse the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.See:  smart constructor.amazonka-sagemakerConfiguration information for Amazon SageMaker Debugger tensor collections. To learn more about how to configure the CollectionConfiguration parameter, see  https://docs.aws.amazon.com/sagemaker/latest/dg/debugger-createtrainingjob-api.htmlUse the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.amazonka-sagemakerConfiguration information for the Amazon SageMaker Debugger hook parameters.amazonka-sagemakerPath to local storage location for metrics and tensors. Defaults to /opt/ml/output/tensors/.amazonka-sagemaker;Path to Amazon S3 storage location for metrics and tensors.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - Configuration information for Amazon SageMaker Debugger tensor collections. To learn more about how to configure the CollectionConfiguration parameter, see  https://docs.aws.amazon.com/sagemaker/latest/dg/debugger-createtrainingjob-api.htmlUse the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.,  - Configuration information for the Amazon SageMaker Debugger hook parameters.,  - Path to local storage location for metrics and tensors. Defaults to /opt/ml/output/tensors/., > - Path to Amazon S3 storage location for metrics and tensors.amazonka-sagemakerConfiguration information for Amazon SageMaker Debugger tensor collections. To learn more about how to configure the CollectionConfiguration parameter, see  https://docs.aws.amazon.com/sagemaker/latest/dg/debugger-createtrainingjob-api.htmlUse the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.amazonka-sagemakerConfiguration information for the Amazon SageMaker Debugger hook parameters.amazonka-sagemakerPath to local storage location for metrics and tensors. Defaults to /opt/ml/output/tensors/.amazonka-sagemaker;Path to Amazon S3 storage location for metrics and tensors.amazonka-sagemaker  m(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';camazonka-sagemakerGets the Amazon EC2 Container Registry path of the docker image of the model that is hosted in this ProductionVariant.If you used the registry/repository[:tag] form to specify the image path of the primary container when you created the model hosted in this ProductionVariant+, the path resolves to a path of the form registry/repository[@digest]. A digest is a hash value that identifies a specific version of an image. For information about Amazon ECR paths, see  https://docs.aws.amazon.com/AmazonECR/latest/userguide/docker-pull-ecr-image.htmlPulling an Image in the Amazon ECR User Guide.See:  smart constructor.amazonka-sagemakerThe date and time when the image path for the model resolved to the  ResolvedImageamazonka-sagemaker6The specific digest path of the image hosted in this ProductionVariant.amazonka-sagemaker8The image path you specified when you created the model.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The date and time when the image path for the model resolved to the  ResolvedImage, 9 - The specific digest path of the image hosted in this ProductionVariant., ; - The image path you specified when you created the model.amazonka-sagemakerThe date and time when the image path for the model resolved to the  ResolvedImageamazonka-sagemaker6The specific digest path of the image hosted in this ProductionVariant.amazonka-sagemaker8The image path you specified when you created the model.  n(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';gamazonka-sagemaker>Specifies weight and capacity values for a production variant.See:  smart constructor.amazonka-sagemakerThe variant's capacity.amazonka-sagemakerThe variant's weight.amazonka-sagemaker"The name of the variant to update.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The variant's capacity.,  - The variant's weight., % - The name of the variant to update.amazonka-sagemakerThe variant's capacity.amazonka-sagemakerThe variant's weight.amazonka-sagemaker"The name of the variant to update.amazonka-sagemaker  o(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?h p(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';n'amazonka-sagemaker.Represents the overall status of an algorithm.See:  smart constructor.amazonka-sagemakerif the overall status is Failed, the reason for the failure.amazonka-sagemakerThe name of the algorithm for which the overall status is being reported.amazonka-sagemakerThe current status.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - if the overall status is Failed, the reason for the failure.,  - The name of the algorithm for which the overall status is being reported.,  - The current status.amazonka-sagemakerif the overall status is Failed, the reason for the failure.amazonka-sagemakerThe name of the algorithm for which the overall status is being reported.amazonka-sagemakerThe current status.amazonka-sagemakeramazonka-sagemaker  q(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';ramazonka-sagemakerSpecifies the validation and image scan statuses of the algorithm.See:  smart constructor.amazonka-sagemakerThe status of the scan of the algorithm's Docker image container.amazonka-sagemaker#The status of algorithm validation.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The status of the scan of the algorithm's Docker image container., & - The status of algorithm validation.amazonka-sagemakerThe status of the scan of the algorithm's Docker image container.amazonka-sagemaker#The status of algorithm validation.r(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?sj s(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';xDamazonka-sagemaker#Information of a particular device.See:  smart constructor.amazonka-sagemakerDescription of the device.amazonka-sagemaker9Amazon Web Services Internet of Things (IoT) object name.amazonka-sagemakerThe name of the device.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - Description of the device., < - Amazon Web Services Internet of Things (IoT) object name.,  - The name of the device.amazonka-sagemakerDescription of the device.amazonka-sagemaker9Amazon Web Services Internet of Things (IoT) object name.amazonka-sagemakerThe name of the device.amazonka-sagemaker  t(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?y u(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';amazonka-sagemakerContains information summarizing device details and deployment status.See:  smart constructor.amazonka-sagemakerThe name of the deployed stage.amazonka-sagemaker3The time when the deployment on the device started.amazonka-sagemakerThe description of the device.amazonka-sagemaker$The deployment status of the device.amazonka-sagemaker=The detailed error message for the deployoment status result.amazonka-sagemaker5The name of the fleet to which the device belongs to.amazonka-sagemaker$The ARN of the edge deployment plan.amazonka-sagemaker%The name of the edge deployment plan.amazonka-sagemaker2The name of the stage in the edge deployment plan.amazonka-sagemakerThe name of the device.amazonka-sagemakerThe ARN of the device.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, " - The name of the deployed stage., 6 - The time when the deployment on the device started., ! - The description of the device., ' - The deployment status of the device.,  - The detailed error message for the deployoment status result., 8 - The name of the fleet to which the device belongs to., ' - The ARN of the edge deployment plan., ( - The name of the edge deployment plan., 5 - The name of the stage in the edge deployment plan.,  - The name of the device.,  - The ARN of the device.amazonka-sagemakerThe name of the deployed stage.amazonka-sagemaker3The time when the deployment on the device started.amazonka-sagemakerThe description of the device.amazonka-sagemaker$The deployment status of the device.amazonka-sagemaker=The detailed error message for the deployoment status result.amazonka-sagemaker5The name of the fleet to which the device belongs to.amazonka-sagemaker$The ARN of the edge deployment plan.amazonka-sagemaker%The name of the edge deployment plan.amazonka-sagemaker2The name of the stage in the edge deployment plan.amazonka-sagemakerThe name of the device.amazonka-sagemakerThe ARN of the device.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakerv(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; amazonka-sagemakerSummary of the device fleet.See:  smart constructor.amazonka-sagemaker/Timestamp of when the device fleet was created.amazonka-sagemaker4Timestamp of when the device fleet was last updated.amazonka-sagemaker/Amazon Resource Name (ARN) of the device fleet.amazonka-sagemakerName of the device fleet.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 2 - Timestamp of when the device fleet was created., 7 - Timestamp of when the device fleet was last updated., 2 - Amazon Resource Name (ARN) of the device fleet.,  - Name of the device fleet.amazonka-sagemaker/Timestamp of when the device fleet was created.amazonka-sagemaker4Timestamp of when the device fleet was last updated.amazonka-sagemaker/Amazon Resource Name (ARN) of the device fleet.amazonka-sagemakerName of the device fleet.amazonka-sagemakeramazonka-sagemaker  w(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';4amazonka-sagemakerStatus of devices.See:  smart constructor.amazonka-sagemaker1The number of devices connected with a heartbeat.amazonka-sagemaker!The number of registered devices.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 4 - The number of devices connected with a heartbeat., $ - The number of registered devices.amazonka-sagemaker1The number of devices connected with a heartbeat.amazonka-sagemaker!The number of registered devices.amazonka-sagemakeramazonka-sagemakerx(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? y(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';s amazonka-sagemakerContains information about the configurations of selected devices.See:  smart constructor.amazonka-sagemaker;A filter to select devices with names containing this name.amazonka-sagemaker!List of devices chosen to deploy.amazonka-sagemakerPercentage of devices in the fleet to deploy to the current stage.amazonka-sagemaker6Type of device subsets to deploy to the current stage.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, > - A filter to select devices with names containing this name., $ - List of devices chosen to deploy.,  - Percentage of devices in the fleet to deploy to the current stage., 9 - Type of device subsets to deploy to the current stage.amazonka-sagemaker;A filter to select devices with names containing this name.amazonka-sagemaker!List of devices chosen to deploy.amazonka-sagemakerPercentage of devices in the fleet to deploy to the current stage.amazonka-sagemaker6Type of device subsets to deploy to the current stage.amazonka-sagemaker  z(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?C{(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? |(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? }(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; amazonka-sagemakerThe domain's details.See:  smart constructor.amazonka-sagemakerThe creation time.amazonka-sagemaker(The domain's Amazon Resource Name (ARN).amazonka-sagemakerThe domain ID.amazonka-sagemakerThe domain name.amazonka-sagemakerThe last modified time.amazonka-sagemaker The status.amazonka-sagemakerThe domain's URL.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The creation time., + - The domain's Amazon Resource Name (ARN).,  - The domain ID.,  - The domain name.,  - The last modified time.,  - The status.,  - The domain's URL.amazonka-sagemakerThe creation time.amazonka-sagemaker(The domain's Amazon Resource Name (ARN).amazonka-sagemakerThe domain ID.amazonka-sagemakerThe domain name.amazonka-sagemakerThe last modified time.amazonka-sagemaker The status.amazonka-sagemakerThe domain's URL.~(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';I amazonka-sagemakerThe configurations and outcomes of an Amazon EMR step execution.See:  smart constructor.amazonka-sagemaker"The identifier of the EMR cluster.amazonka-sagemakerThe path to the log file where the cluster step's failure root cause is recorded.amazonka-sagemaker'The identifier of the EMR cluster step.amazonka-sagemaker!The name of the EMR cluster step.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, % - The identifier of the EMR cluster.,  - The path to the log file where the cluster step's failure root cause is recorded., * - The identifier of the EMR cluster step., $ - The name of the EMR cluster step.amazonka-sagemaker"The identifier of the EMR cluster.amazonka-sagemakerThe path to the log file where the cluster step's failure root cause is recorded.amazonka-sagemaker'The identifier of the EMR cluster step.amazonka-sagemaker!The name of the EMR cluster step.  (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';amazonka-sagemaker0A directed edge connecting two lineage entities.See:  smart constructor.amazonka-sagemakerThe type of the Association(Edge) between the source and destination. For example  ContributedTo, Produced, or  DerivedFrom.amazonka-sagemakerThe Amazon Resource Name (ARN) of the destination lineage entity of the directed edge.amazonka-sagemakerThe Amazon Resource Name (ARN) of the source lineage entity of the directed edge.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The type of the Association(Edge) between the source and destination. For example  ContributedTo, Produced, or  DerivedFrom.,  - The Amazon Resource Name (ARN) of the destination lineage entity of the directed edge.,  - The Amazon Resource Name (ARN) of the source lineage entity of the directed edge.amazonka-sagemakerThe type of the Association(Edge) between the source and destination. For example  ContributedTo, Produced, or  DerivedFrom.amazonka-sagemakerThe Amazon Resource Name (ARN) of the destination lineage entity of the directed edge.amazonka-sagemakerThe Amazon Resource Name (ARN) of the source lineage entity of the directed edge.  (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';amazonka-sagemakerContains information about the configuration of a model in a deployment.See:  smart constructor.amazonka-sagemaker=The name the device application uses to reference this model.amazonka-sagemaker7The edge packaging job associated with this deployment.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The name the device application uses to reference this model., : - The edge packaging job associated with this deployment.amazonka-sagemaker=The name the device application uses to reference this model.amazonka-sagemaker7The edge packaging job associated with this deployment.amazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';amazonka-sagemaker9Contains information summarizing an edge deployment plan.See:  smart constructor.amazonka-sagemaker3The time when the edge deployment plan was created.amazonka-sagemaker8The time when the edge deployment plan was last updated.amazonka-sagemaker$The ARN of the edge deployment plan.amazonka-sagemaker%The name of the edge deployment plan.amazonka-sagemaker5The name of the device fleet used for the deployment.amazonka-sagemaker:The number of edge devices with the successful deployment.amazonka-sagemakerThe number of edge devices yet to pick up the deployment, or in progress.amazonka-sagemaker6The number of edge devices that failed the deployment.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 6 - The time when the edge deployment plan was created., ; - The time when the edge deployment plan was last updated., ' - The ARN of the edge deployment plan., ( - The name of the edge deployment plan., 8 - The name of the device fleet used for the deployment., = - The number of edge devices with the successful deployment.,  - The number of edge devices yet to pick up the deployment, or in progress., 9 - The number of edge devices that failed the deployment.amazonka-sagemaker3The time when the edge deployment plan was created.amazonka-sagemaker8The time when the edge deployment plan was last updated.amazonka-sagemaker$The ARN of the edge deployment plan.amazonka-sagemaker%The name of the edge deployment plan.amazonka-sagemaker5The name of the device fleet used for the deployment.amazonka-sagemaker:The number of edge devices with the successful deployment.amazonka-sagemakerThe number of edge devices yet to pick up the deployment, or in progress.amazonka-sagemaker6The number of edge devices that failed the deployment.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; amazonka-sagemakerThe model on the edge device.See:  smart constructor.amazonka-sagemaker2The timestamp of the last inference that was made.amazonka-sagemaker,The timestamp of the last data sample taken.amazonka-sagemakerThe name of the model.amazonka-sagemakerThe model version.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 5 - The timestamp of the last inference that was made., / - The timestamp of the last data sample taken.,  - The name of the model.,  - The model version.amazonka-sagemaker2The timestamp of the last inference that was made.amazonka-sagemaker,The timestamp of the last data sample taken.amazonka-sagemakerThe name of the model.amazonka-sagemakerThe model version.amazonka-sagemakeramazonka-sagemaker  (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';(amazonka-sagemaker'Status of edge devices with this model.See:  smart constructor.amazonka-sagemakerThe name of the model.amazonka-sagemakerThe model version.amazonka-sagemakerThe number of devices that have this model version and do not have a heart beat.amazonka-sagemakerThe number of devices that have this model version and have a heart beat.amazonka-sagemakerThe number of devices that have this model version, a heart beat, and are currently running.amazonka-sagemakerThe number of devices with this model version and are producing sample data.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The name of the model.,  - The model version.,  - The number of devices that have this model version and do not have a heart beat.,  - The number of devices that have this model version and have a heart beat.,  - The number of devices that have this model version, a heart beat, and are currently running.,  - The number of devices with this model version and are producing sample data.amazonka-sagemakerThe name of the model.amazonka-sagemakerThe model version.amazonka-sagemakerThe number of devices that have this model version and do not have a heart beat.amazonka-sagemakerThe number of devices that have this model version and have a heart beat.amazonka-sagemakerThe number of devices that have this model version, a heart beat, and are currently running.amazonka-sagemakerThe number of devices with this model version and are producing sample data.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';#amazonka-sagemaker Summary of model on edge device.See:  smart constructor.amazonka-sagemakerThe name of the model.amazonka-sagemakerThe version model.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The name of the model.,  - The version model.amazonka-sagemakerThe name of the model.amazonka-sagemakerThe version model.amazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';,amazonka-sagemakerSummary of the device.See:  smart constructor.amazonka-sagemakerEdge Manager agent version.amazonka-sagemakerA description of the device.amazonka-sagemaker,The name of the fleet the device belongs to.amazonka-sagemakerThe Amazon Web Services Internet of Things (IoT) object thing name associated with the device..amazonka-sagemaker,The last heartbeat received from the device.amazonka-sagemakerModels on the device.amazonka-sagemakerThe timestamp of when the edge packaging job was last updated.amazonka-sagemakerThe name of the model.amazonka-sagemakerThe version of the model.amazonka-sagemaker9The Amazon Resource Name (ARN) of the edge packaging job.amazonka-sagemaker#The name of the edge packaging job.amazonka-sagemaker%The status of the edge packaging job.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 1 - The name of the SageMaker Neo compilation job., - - The timestamp of when the job was created.,  - The timestamp of when the edge packaging job was last updated.,  - The name of the model.,  - The version of the model., < - The Amazon Resource Name (ARN) of the edge packaging job., & - The name of the edge packaging job., ( - The status of the edge packaging job.amazonka-sagemaker.The name of the SageMaker Neo compilation job.amazonka-sagemaker*The timestamp of when the job was created.amazonka-sagemaker>The timestamp of when the edge packaging job was last updated.amazonka-sagemakerThe name of the model.amazonka-sagemakerThe version of the model.amazonka-sagemaker9The Amazon Resource Name (ARN) of the edge packaging job.amazonka-sagemaker#The name of the edge packaging job.amazonka-sagemaker%The status of the edge packaging job.amazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?5(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; amazonka-sagemaker;The output of a SageMaker Edge Manager deployable resource.See:  smart constructor.amazonka-sagemakerThe Amazon Resource Name (ARN) of the generated deployable resource.amazonka-sagemaker&The status of the deployable resource.amazonka-sagemakerReturns a message describing the status of the deployed resource.amazonka-sagemakerThe deployment type created by SageMaker Edge Manager. Currently only supports Amazon Web Services IoT Greengrass Version 2 components.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The Amazon Resource Name (ARN) of the generated deployable resource., ) - The status of the deployable resource.,  - Returns a message describing the status of the deployed resource.,  - The deployment type created by SageMaker Edge Manager. Currently only supports Amazon Web Services IoT Greengrass Version 2 components.amazonka-sagemakerThe Amazon Resource Name (ARN) of the generated deployable resource.amazonka-sagemaker&The status of the deployable resource.amazonka-sagemakerReturns a message describing the status of the deployed resource.amazonka-sagemakerThe deployment type created by SageMaker Edge Manager. Currently only supports Amazon Web Services IoT Greengrass Version 2 components.amazonka-sagemaker  (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; amazonka-sagemakerThe output configuration.See:  smart constructor.amazonka-sagemakerThe Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume after compilation job. If you don't provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role's account.amazonka-sagemakerThe configuration used to create deployment artifacts. Specify configuration options with a JSON string. The available configuration options for each type are: ComponentName (optional) - Name of the GreenGrass V2 component. If not specified, the default name generated consists of "SagemakerEdgeManager" and the name of your SageMaker Edge Manager packaging job.ComponentDescription+ (optional) - Description of the component.ComponentVersion+ (optional) - The version of the component.Amazon Web Services IoT Greengrass uses semantic versions for components. Semantic versions follow a major.minor.patch number system. For example, version 1.0.0 represents the first major release for a component. For more information, see the  https://semver.org/semantic version specification. PlatformOS (optional) - The name of the operating system for the platform. Supported platforms include Windows and Linux.PlatformArchitecture? (optional) - The processor architecture for the platform.Supported architectures Windows include: Windows32_x86, Windows64_x64.Supported architectures for Linux include: Linux x86_64, Linux ARMV8.amazonka-sagemakerThe deployment type SageMaker Edge Manager will create. Currently only supports Amazon Web Services IoT Greengrass Version 2 components.amazonka-sagemaker*The Amazon Simple Storage (S3) bucker URI.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume after compilation job. If you don't provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role's account.,  - The configuration used to create deployment artifacts. Specify configuration options with a JSON string. The available configuration options for each type are: ComponentName (optional) - Name of the GreenGrass V2 component. If not specified, the default name generated consists of "SagemakerEdgeManager" and the name of your SageMaker Edge Manager packaging job.ComponentDescription+ (optional) - Description of the component.ComponentVersion+ (optional) - The version of the component.Amazon Web Services IoT Greengrass uses semantic versions for components. Semantic versions follow a major.minor.patch number system. For example, version 1.0.0 represents the first major release for a component. For more information, see the  https://semver.org/semantic version specification. PlatformOS (optional) - The name of the operating system for the platform. Supported platforms include Windows and Linux.PlatformArchitecture? (optional) - The processor architecture for the platform.Supported architectures Windows include: Windows32_x86, Windows64_x64.Supported architectures for Linux include: Linux x86_64, Linux ARMV8.,  - The deployment type SageMaker Edge Manager will create. Currently only supports Amazon Web Services IoT Greengrass Version 2 components., - - The Amazon Simple Storage (S3) bucker URI.amazonka-sagemakerThe Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume after compilation job. If you don't provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role's account.amazonka-sagemakerThe configuration used to create deployment artifacts. Specify configuration options with a JSON string. The available configuration options for each type are: ComponentName (optional) - Name of the GreenGrass V2 component. If not specified, the default name generated consists of "SagemakerEdgeManager" and the name of your SageMaker Edge Manager packaging job.ComponentDescription+ (optional) - Description of the component.ComponentVersion+ (optional) - The version of the component.Amazon Web Services IoT Greengrass uses semantic versions for components. Semantic versions follow a major.minor.patch number system. For example, version 1.0.0 represents the first major release for a component. For more information, see the  https://semver.org/semantic version specification. PlatformOS (optional) - The name of the operating system for the platform. Supported platforms include Windows and Linux.PlatformArchitecture? (optional) - The processor architecture for the platform.Supported architectures Windows include: Windows32_x86, Windows64_x64.Supported architectures for Linux include: Linux x86_64, Linux ARMV8.amazonka-sagemakerThe deployment type SageMaker Edge Manager will create. Currently only supports Amazon Web Services IoT Greengrass Version 2 components.amazonka-sagemaker*The Amazon Simple Storage (S3) bucker URI.amazonka-sagemaker  (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; amazonka-sagemaker;Provides summary information for an endpoint configuration.See:  smart constructor.amazonka-sagemaker'The name of the endpoint configuration.amazonka-sagemaker=The Amazon Resource Name (ARN) of the endpoint configuration.amazonka-sagemakerA timestamp that shows when the endpoint configuration was created.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, * - The name of the endpoint configuration.,  - The Amazon Resource Name (ARN) of the endpoint configuration.,  - A timestamp that shows when the endpoint configuration was created.amazonka-sagemaker'The name of the endpoint configuration.amazonka-sagemaker=The Amazon Resource Name (ARN) of the endpoint configuration.amazonka-sagemakerA timestamp that shows when the endpoint configuration was created.amazonka-sagemakeramazonka-sagemakeramazonka-sagemaker  (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';^amazonka-sagemakerDetails about a customer endpoint that was compared in an Inference Recommender job.See:  smart constructor.amazonka-sagemaker"The name of a customer's endpoint.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, % - The name of a customer's endpoint.amazonka-sagemaker"The name of a customer's endpoint.amazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; amazonka-sagemakerThe metadata of the endpoint.See:  smart constructor.amazonka-sagemaker'The name of the endpoint configuration.amazonka-sagemakerThe status of the endpoint. For possible values of the status of an endpoint, see EndpointSummary$EndpointStatus.amazonka-sagemaker!If the status of the endpoint is Failed, or the status is  InService but update operation fails, this provides the reason why it failed.amazonka-sagemakerThe name of the endpoint.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, * - The name of the endpoint configuration.,  - The status of the endpoint. For possible values of the status of an endpoint, see EndpointSummary$EndpointStatus., $ - If the status of the endpoint is Failed, or the status is  InService but update operation fails, this provides the reason why it failed.,  - The name of the endpoint.amazonka-sagemaker'The name of the endpoint configuration.amazonka-sagemakerThe status of the endpoint. For possible values of the status of an endpoint, see EndpointSummary$EndpointStatus.amazonka-sagemaker!If the status of the endpoint is Failed, or the status is  InService but update operation fails, this provides the reason why it failed.amazonka-sagemakerThe name of the endpoint.amazonka-sagemaker  (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';0s amazonka-sagemaker-Provides summary information for an endpoint.See:  smart constructor.amazonka-sagemakerThe name of the endpoint.amazonka-sagemaker/The Amazon Resource Name (ARN) of the endpoint.amazonka-sagemaker5A timestamp that shows when the endpoint was created.amazonka-sagemaker;A timestamp that shows when the endpoint was last modified.amazonka-sagemakerThe status of the endpoint. OutOfService6: Endpoint is not available to take incoming requests.Creating: CreateEndpoint is executing.Updating: UpdateEndpoint or UpdateEndpointWeightsAndCapacities is executing.SystemUpdating: Endpoint is undergoing maintenance and cannot be updated or deleted or re-scaled until it has completed. This maintenance operation does not change any customer-specified values such as VPC config, KMS encryption, model, instance type, or instance count. RollingBack: Endpoint fails to scale up or down or change its variant weight and is in the process of rolling back to its previous configuration. Once the rollback completes, endpoint returns to an  InService status. This transitional status only applies to an endpoint that has autoscaling enabled and is undergoing variant weight or capacity changes as part of an UpdateEndpointWeightsAndCapacities call or when the UpdateEndpointWeightsAndCapacities operation is called explicitly. InService5: Endpoint is available to process incoming requests.Deleting: DeleteEndpoint is executing.Failed: Endpoint could not be created, updated, or re-scaled. Use DescribeEndpointOutput$FailureReason for information about the failure. DeleteEndpoint is the only operation that can be performed on a failed endpoint.To get a list of endpoints with a specified status, use the ListEndpointsInput$StatusEquals filter.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The name of the endpoint., 2 - The Amazon Resource Name (ARN) of the endpoint., 8 - A timestamp that shows when the endpoint was created., > - A timestamp that shows when the endpoint was last modified.,  - The status of the endpoint. OutOfService6: Endpoint is not available to take incoming requests.Creating: CreateEndpoint is executing.Updating: UpdateEndpoint or UpdateEndpointWeightsAndCapacities is executing.SystemUpdating: Endpoint is undergoing maintenance and cannot be updated or deleted or re-scaled until it has completed. This maintenance operation does not change any customer-specified values such as VPC config, KMS encryption, model, instance type, or instance count. RollingBack: Endpoint fails to scale up or down or change its variant weight and is in the process of rolling back to its previous configuration. Once the rollback completes, endpoint returns to an  InService status. This transitional status only applies to an endpoint that has autoscaling enabled and is undergoing variant weight or capacity changes as part of an UpdateEndpointWeightsAndCapacities call or when the UpdateEndpointWeightsAndCapacities operation is called explicitly. InService5: Endpoint is available to process incoming requests.Deleting: DeleteEndpoint is executing.Failed: Endpoint could not be created, updated, or re-scaled. Use DescribeEndpointOutput$FailureReason for information about the failure. DeleteEndpoint is the only operation that can be performed on a failed endpoint.To get a list of endpoints with a specified status, use the ListEndpointsInput$StatusEquals filter.amazonka-sagemakerThe name of the endpoint.amazonka-sagemaker/The Amazon Resource Name (ARN) of the endpoint.amazonka-sagemaker5A timestamp that shows when the endpoint was created.amazonka-sagemaker;A timestamp that shows when the endpoint was last modified.amazonka-sagemakerThe status of the endpoint. OutOfService6: Endpoint is not available to take incoming requests.Creating: CreateEndpoint is executing.Updating: UpdateEndpoint or UpdateEndpointWeightsAndCapacities is executing.SystemUpdating: Endpoint is undergoing maintenance and cannot be updated or deleted or re-scaled until it has completed. This maintenance operation does not change any customer-specified values such as VPC config, KMS encryption, model, instance type, or instance count. RollingBack: Endpoint fails to scale up or down or change its variant weight and is in the process of rolling back to its previous configuration. Once the rollback completes, endpoint returns to an  InService status. This transitional status only applies to an endpoint that has autoscaling enabled and is undergoing variant weight or capacity changes as part of an UpdateEndpointWeightsAndCapacities call or when the UpdateEndpointWeightsAndCapacities operation is called explicitly. InService5: Endpoint is available to process incoming requests.Deleting: DeleteEndpoint is executing.Failed: Endpoint could not be created, updated, or re-scaled. Use DescribeEndpointOutput$FailureReason for information about the failure. DeleteEndpoint is the only operation that can be performed on a failed endpoint.To get a list of endpoints with a specified status, use the ListEndpointsInput$StatusEquals filter.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker  (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';7amazonka-sagemakerA list of environment parameters suggested by the Amazon SageMaker Inference Recommender.See:  smart constructor.amazonka-sagemakerThe environment key suggested by the Amazon SageMaker Inference Recommender.amazonka-sagemakerThe value type suggested by the Amazon SageMaker Inference Recommender.amazonka-sagemakerThe value suggested by the Amazon SageMaker Inference Recommender.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The environment key suggested by the Amazon SageMaker Inference Recommender.,  - The value type suggested by the Amazon SageMaker Inference Recommender.,  - The value suggested by the Amazon SageMaker Inference Recommender.amazonka-sagemakerThe environment key suggested by the Amazon SageMaker Inference Recommender.amazonka-sagemakerThe value type suggested by the Amazon SageMaker Inference Recommender.amazonka-sagemakerThe value suggested by the Amazon SageMaker Inference Recommender.amazonka-sagemakeramazonka-sagemakeramazonka-sagemaker  (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';:amazonka-sagemaker-Specifies the range of environment parametersSee:  smart constructor.amazonka-sagemaker1Specified a list of parameters for each category.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 4 - Specified a list of parameters for each category.amazonka-sagemaker1Specified a list of parameters for each category.(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?;Z(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?< (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';D amazonka-sagemakerAssociates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:CreateProcessingJobCreateTrainingJobCreateTransformJobSee:  smart constructor.amazonka-sagemakerThe name of an existing experiment to associate with the trial component.amazonka-sagemakerThe name of the experiment run to associate with the trial component.amazonka-sagemakerThe display name for the trial component. If this key isn't specified, the display name is the trial component name.amazonka-sagemakerThe name of an existing trial to associate the trial component with. If not specified, a new trial is created.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The name of an existing experiment to associate with the trial component.,  - The name of the experiment run to associate with the trial component.,  - The display name for the trial component. If this key isn't specified, the display name is the trial component name.,  - The name of an existing trial to associate the trial component with. If not specified, a new trial is created.amazonka-sagemakerThe name of an existing experiment to associate with the trial component.amazonka-sagemakerThe name of the experiment run to associate with the trial component.amazonka-sagemakerThe display name for the trial component. If this key isn't specified, the display name is the trial component name.amazonka-sagemakerThe name of an existing trial to associate the trial component with. If not specified, a new trial is created.  (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';Hamazonka-sagemakerThe source of the experiment.See:  smart constructor.amazonka-sagemakerThe source type.amazonka-sagemaker-The Amazon Resource Name (ARN) of the source.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The source type., 0 - The Amazon Resource Name (ARN) of the source.amazonka-sagemakerThe source type.amazonka-sagemaker-The Amazon Resource Name (ARN) of the source.amazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';P amazonka-sagemakerA summary of the properties of an experiment. To get the complete set of properties, call the DescribeExperiment API and provide the ExperimentName.See:  smart constructor.amazonka-sagemaker When the experiment was created.amazonka-sagemaker,The name of the experiment as displayed. If  DisplayName isn't specified, ExperimentName is displayed.amazonka-sagemaker1The Amazon Resource Name (ARN) of the experiment.amazonka-sagemakerThe name of the experiment.amazonka-sagemaker&When the experiment was last modified.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - When the experiment was created., / - The name of the experiment as displayed. If  DisplayName isn't specified, ExperimentName is displayed., 4 - The Amazon Resource Name (ARN) of the experiment.,  - The name of the experiment.,  - Undocumented member., ) - When the experiment was last modified.amazonka-sagemaker When the experiment was created.amazonka-sagemaker,The name of the experiment as displayed. If  DisplayName isn't specified, ExperimentName is displayed.amazonka-sagemaker1The Amazon Resource Name (ARN) of the experiment.amazonka-sagemakerThe name of the experiment.amazonka-sagemakerUndocumented member.amazonka-sagemaker&When the experiment was last modified.(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';U@amazonka-sagemaker#A parameter to activate explainers.See:  smart constructor.amazonka-sagemaker A member of ExplainerConfig that contains configuration parameters for the SageMaker Clarify explainer.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - A member of ExplainerConfig that contains configuration parameters for the SageMaker Clarify explainer.amazonka-sagemaker A member of ExplainerConfig that contains configuration parameters for the SageMaker Clarify explainer.(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';YWamazonka-sagemaker-The container for the metadata for Fail step.See:  smart constructor.amazonka-sagemakerA message that you define and then is processed and rendered by the Fail step when the error occurs.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - A message that you define and then is processed and rendered by the Fail step when the error occurs.amazonka-sagemakerA message that you define and then is processed and rendered by the Fail step when the error occurs.(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?Z(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';_amazonka-sagemaker=Contains information about the configuration of a deployment.See:  smart constructor.amazonka-sagemakerToggle that determines whether to rollback to previous configuration if the current deployment fails. By default this is turned on. You may turn this off if you want to investigate the errors yourself.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - Toggle that determines whether to rollback to previous configuration if the current deployment fails. By default this is turned on. You may turn this off if you want to investigate the errors yourself.amazonka-sagemakerToggle that determines whether to rollback to previous configuration if the current deployment fails. By default this is turned on. You may turn this off if you want to investigate the errors yourself.amazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';damazonka-sagemaker>Contains information about a stage in an edge deployment plan.See:  smart constructor.amazonka-sagemaker(Configuration of the deployment details.amazonka-sagemakerThe name of the stage.amazonka-sagemaker*Configuration of the devices in the stage.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, + - Configuration of the deployment details.,  - The name of the stage., - - Configuration of the devices in the stage.amazonka-sagemaker(Configuration of the deployment details.amazonka-sagemakerThe name of the stage.amazonka-sagemaker*Configuration of the devices in the stage.amazonka-sagemakeramazonka-sagemaker  (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?eO (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?f(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?f (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';k/amazonka-sagemaker:A key-value pair that you specify to describe the feature.See:  smart constructor.amazonka-sagemaker8A key that must contain a value to describe the feature.amazonka-sagemaker The value that belongs to a key.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, ; - A key that must contain a value to describe the feature., # - The value that belongs to a key.amazonka-sagemaker8A key that must contain a value to describe the feature.amazonka-sagemaker The value that belongs to a key.(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?k(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?l (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';vamazonka-sagemakerThe metadata for a feature. It can either be metadata that you specify, or metadata that is updated automatically.See:  smart constructor.amazonka-sagemaker4A timestamp indicating when the feature was created.amazonka-sagemakerAn optional description that you specify to better describe the feature.amazonka-sagemaker6The Amazon Resource Number (ARN) of the feature group.amazonka-sagemaker5The name of the feature group containing the feature.amazonka-sagemakerThe name of feature.amazonka-sagemakerThe data type of the feature.amazonka-sagemaker:A timestamp indicating when the feature was last modified.amazonka-sagemakerOptional key-value pairs that you specify to better describe the feature.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 7 - A timestamp indicating when the feature was created.,  - An optional description that you specify to better describe the feature., 9 - The Amazon Resource Number (ARN) of the feature group., 8 - The name of the feature group containing the feature.,  - The name of feature.,  - The data type of the feature., = - A timestamp indicating when the feature was last modified.,  - Optional key-value pairs that you specify to better describe the feature.amazonka-sagemaker4A timestamp indicating when the feature was created.amazonka-sagemakerAn optional description that you specify to better describe the feature.amazonka-sagemaker6The Amazon Resource Number (ARN) of the feature group.amazonka-sagemaker5The name of the feature group containing the feature.amazonka-sagemakerThe name of feature.amazonka-sagemakerThe data type of the feature.amazonka-sagemaker:A timestamp indicating when the feature was last modified.amazonka-sagemakerOptional key-value pairs that you specify to better describe the feature.(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';}amazonka-sagemaker%A list of features. You must include  FeatureName and  FeatureType. Valid feature  FeatureTypes are Integral,  Fractional and String.See:  smart constructor.amazonka-sagemaker2The name of a feature. The type must be a string.  FeatureName" cannot be any of the following:  is_deleted,  write_time, api_invocation_time.amazonka-sagemakerThe value type of a feature. Valid values are Integral, Fractional, or String.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 5 - The name of a feature. The type must be a string.  FeatureName" cannot be any of the following:  is_deleted,  write_time, api_invocation_time.,  - The value type of a feature. Valid values are Integral, Fractional, or String.amazonka-sagemaker2The name of a feature. The type must be a string.  FeatureName" cannot be any of the following:  is_deleted,  write_time, api_invocation_time.amazonka-sagemakerThe value type of a feature. Valid values are Integral, Fractional, or String.(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';amazonka-sagemaker+Contains details regarding the file source.See:  smart constructor.amazonka-sagemakerThe digest of the file source.amazonka-sagemaker.The type of content stored in the file source.amazonka-sagemaker&The Amazon S3 URI for the file source.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, ! - The digest of the file source., 1 - The type of content stored in the file source., ) - The Amazon S3 URI for the file source.amazonka-sagemakerThe digest of the file source.amazonka-sagemaker.The type of content stored in the file source.amazonka-sagemaker&The Amazon S3 URI for the file source.amazonka-sagemaker  (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?M(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';amazonka-sagemakerThe Amazon Elastic File System (EFS) storage configuration for a SageMaker image.See:  smart constructor.amazonka-sagemakerThe default POSIX group ID (GID). If not specified, defaults to 100.amazonka-sagemaker?The default POSIX user ID (UID). If not specified, defaults to 1000.amazonka-sagemakerThe path within the image to mount the user's EFS home directory. The directory should be empty. If not specified, defaults to /home/sagemaker-user.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The default POSIX group ID (GID). If not specified, defaults to 100.,  - The default POSIX user ID (UID). If not specified, defaults to 1000.,  - The path within the image to mount the user's EFS home directory. The directory should be empty. If not specified, defaults to /home/sagemaker-user.amazonka-sagemakerThe default POSIX group ID (GID). If not specified, defaults to 100.amazonka-sagemaker?The default POSIX user ID (UID). If not specified, defaults to 1000.amazonka-sagemakerThe path within the image to mount the user's EFS home directory. The directory should be empty. If not specified, defaults to /home/sagemaker-user.  (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?Y(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; amazonka-sagemaker2Specifies a file system data source for a channel.See:  smart constructor.amazonka-sagemakerThe file system id.amazonka-sagemakerThe access mode of the mount of the directory associated with the channel. A directory can be mounted either in ro (read-only) or rw (read-write) mode.amazonka-sagemakerThe file system type.amazonka-sagemaker=The full path to the directory to associate with the channel.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The file system id.,  - The access mode of the mount of the directory associated with the channel. A directory can be mounted either in ro (read-only) or rw (read-write) mode.,  - The file system type.,  - The full path to the directory to associate with the channel.amazonka-sagemakerThe file system id.amazonka-sagemakerThe access mode of the mount of the directory associated with the channel. A directory can be mounted either in ro (read-only) or rw (read-write) mode.amazonka-sagemakerThe file system type.amazonka-sagemaker=The full path to the directory to associate with the channel.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker  (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; amazonka-sagemaker6The best candidate result from an AutoML training job.See:  smart constructor.amazonka-sagemaker(The type of metric with the best result.amazonka-sagemakerThe name of the metric with the best result. For a description of the possible objective metrics, see AutoMLJobObjective$MetricName.amazonka-sagemaker-The value of the metric with the best result.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, + - The type of metric with the best result.,  - The name of the metric with the best result. For a description of the possible objective metrics, see AutoMLJobObjective$MetricName., 0 - The value of the metric with the best result.amazonka-sagemaker(The type of metric with the best result.amazonka-sagemakerThe name of the metric with the best result. For a description of the possible objective metrics, see AutoMLJobObjective$MetricName.amazonka-sagemaker-The value of the metric with the best result.amazonka-sagemakeramazonka-sagemaker  (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';hamazonka-sagemaker=Contains information about where human output will be stored.See:  smart constructor.amazonka-sagemakerThe Amazon Key Management Service (KMS) key ID for server-side encryption.amazonka-sagemakerThe Amazon S3 path where the object containing human output will be made available.?To learn more about the format of Amazon A2I output data, see  https://docs.aws.amazon.com/sagemaker/latest/dg/a2i-output-data.htmlAmazon A2I Output Data.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The Amazon Key Management Service (KMS) key ID for server-side encryption.,  - The Amazon S3 path where the object containing human output will be made available.?To learn more about the format of Amazon A2I output data, see  https://docs.aws.amazon.com/sagemaker/latest/dg/a2i-output-data.htmlAmazon A2I Output Data.amazonka-sagemakerThe Amazon Key Management Service (KMS) key ID for server-side encryption.amazonka-sagemakerThe Amazon S3 path where the object containing human output will be made available.?To learn more about the format of Amazon A2I output data, see  https://docs.aws.amazon.com/sagemaker/latest/dg/a2i-output-data.htmlAmazon A2I Output Data.amazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?) (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; amazonka-sagemaker7Contains summary information about the flow definition.See:  smart constructor.amazonka-sagemakerThe reason why the flow definition creation failed. A failure reason is returned only when the flow definition status is Failed.amazonka-sagemaker The name of the flow definition.amazonka-sagemaker6The Amazon Resource Name (ARN) of the flow definition.amazonka-sagemaker0The status of the flow definition. Valid values:amazonka-sagemaker9The timestamp when SageMaker created the flow definition.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The reason why the flow definition creation failed. A failure reason is returned only when the flow definition status is Failed., # - The name of the flow definition., 9 - The Amazon Resource Name (ARN) of the flow definition., 3 - The status of the flow definition. Valid values:, < - The timestamp when SageMaker created the flow definition.amazonka-sagemakerThe reason why the flow definition creation failed. A failure reason is returned only when the flow definition status is Failed.amazonka-sagemaker The name of the flow definition.amazonka-sagemaker6The Amazon Resource Name (ARN) of the flow definition.amazonka-sagemaker0The status of the flow definition. Valid values:amazonka-sagemaker9The timestamp when SageMaker created the flow definition.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker  (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?p (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; amazonka-sagemakerSpecifies configuration details for a Git repository in your Amazon Web Services account.See:  smart constructor.amazonka-sagemaker*The default branch for the Git repository.amazonka-sagemakerThe Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the git repository. The secret must have a staging label of  AWSCURRENT& and must be in the following format: {"username": UserName, "password": Password}amazonka-sagemaker,The URL where the Git repository is located.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, - - The default branch for the Git repository.,  - The Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the git repository. The secret must have a staging label of  AWSCURRENT& and must be in the following format: {"username": UserName, "password": Password}, / - The URL where the Git repository is located.amazonka-sagemaker*The default branch for the Git repository.amazonka-sagemakerThe Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the git repository. The secret must have a staging label of  AWSCURRENT& and must be in the following format: {"username": UserName, "password": Password}amazonka-sagemaker,The URL where the Git repository is located.amazonka-sagemaker  (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';c amazonka-sagemaker5Specifies summary information about a Git repository.See:  smart constructor.amazonka-sagemakerConfiguration details for the Git repository, including the URL where it is located and the ARN of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the repository.amazonka-sagemakerThe name of the Git repository.amazonka-sagemaker5The Amazon Resource Name (ARN) of the Git repository.amazonka-sagemaker6The date and time that the Git repository was created.amazonka-sagemakerThe timestamp at which the inference experiment was completed.$amazonka-sagemaker,The description of the inference experiment.$amazonka-sagemakerThe ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.$amazonka-sagemakerThe duration for which the inference experiment ran or will run.The maximum duration that you can set for an inference experiment is 30 days.$amazonka-sagemaker=The error message for the inference experiment status result.$amazonka-sagemaker%The name of the inference experiment.$amazonka-sagemaker%The type of the inference experiment.$amazonka-sagemaker'The status of the inference experiment.$amazonka-sagemakerThe timestamp when you last modified the inference experiment.$amazonka-sagemakerCreate a value of $" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:$, $ - The timestamp at which the inference experiment was completed.$, $/ - The description of the inference experiment.$, $ - The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.$, $ - The duration for which the inference experiment ran or will run.The maximum duration that you can set for an inference experiment is 30 days.$, $ - The error message for the inference experiment status result.$, $( - The name of the inference experiment.$, $( - The type of the inference experiment.$, $* - The status of the inference experiment.$, $? - The timestamp at which the inference experiment was created.$, $ - The timestamp when you last modified the inference experiment.$amazonka-sagemaker>The timestamp at which the inference experiment was completed.$amazonka-sagemaker,The description of the inference experiment.$amazonka-sagemakerThe ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.$amazonka-sagemakerThe duration for which the inference experiment ran or will run.The maximum duration that you can set for an inference experiment is 30 days.$amazonka-sagemaker=The error message for the inference experiment status result.$amazonka-sagemaker%The name of the inference experiment.$amazonka-sagemaker%The type of the inference experiment.$amazonka-sagemaker'The status of the inference experiment.$amazonka-sagemakerThe timestamp when you last modified the inference experiment.$amazonka-sagemaker$amazonka-sagemaker$amazonka-sagemaker$amazonka-sagemaker$amazonka-sagemaker$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';$amazonka-sagemakerThe metrics for an existing endpoint compared in an Inference Recommender job.See: $ smart constructor.$amazonka-sagemakerThe expected maximum number of requests per minute for the instance.$amazonka-sagemakerThe expected model latency at maximum invocations per minute for the instance.$amazonka-sagemakerCreate a value of $" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:$, $ - The expected maximum number of requests per minute for the instance.$, $ - The expected model latency at maximum invocations per minute for the instance.$amazonka-sagemakerThe expected maximum number of requests per minute for the instance.$amazonka-sagemakerThe expected model latency at maximum invocations per minute for the instance.$amazonka-sagemaker$amazonka-sagemaker$$$$$$$$$$$$$$$(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';%amazonka-sagemakerThe performance results from running an Inference Recommender job on an existing endpoint.See: % smart constructor.%amazonka-sagemaker%The metrics for an existing endpoint.%amazonka-sagemakerCreate a value of %" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:%, %( - The metrics for an existing endpoint.%, % - Undocumented member.%amazonka-sagemaker%The metrics for an existing endpoint.%amazonka-sagemakerUndocumented member.%amazonka-sagemaker%amazonka-sagemaker%%%%%%%%%%%%%%%(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; %amazonka-sagemakerContains information about the location of input model artifacts, the name and shape of the expected data inputs, and the framework in which the model was trained.See: % smart constructor.%amazonka-sagemakerSpecifies the framework version to use. This API field is only supported for the MXNet, PyTorch, TensorFlow and TensorFlow Lite frameworks.For information about framework versions supported for cloud targets and edge devices, see  https://docs.aws.amazon.com/sagemaker/latest/dg/neo-supported-cloud.html-Cloud Supported Instance Types and Frameworks and  https://docs.aws.amazon.com/sagemaker/latest/dg/neo-supported-devices-edge-frameworks.htmlEdge Supported Frameworks.%amazonka-sagemakerThe S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).%amazonka-sagemakerSpecifies the name and shape of the expected data inputs for your trained model with a JSON dictionary form. The data inputs are InputConfig$Framework specific. TensorFlow: You must specify the name and shape (NHWC format) of the expected data inputs using a dictionary format for your trained model. The dictionary formats required for the console and CLI are different.Examples for one input:If using the console, {"input":[1,1024,1024,3]}If using the CLI, {\"input\":[1,1024,1024,3]}Examples for two inputs:If using the console, +{"data1": [1,28,28,1], "data2":[1,28,28,1]}If using the CLI, /{\"data1\": [1,28,28,1], \"data2\":[1,28,28,1]}KERAS: You must specify the name and shape (NCHW format) of expected data inputs using a dictionary format for your trained model. Note that while Keras model artifacts should be uploaded in NHWC (channel-last) format, DataInputConfig should be specified in NCHW (channel-first) format. The dictionary formats required for the console and CLI are different.Examples for one input:If using the console, {"input_1":[1,3,224,224]}If using the CLI, {\"input_1\":[1,3,224,224]}Examples for two inputs:If using the console, 4{"input_1": [1,3,224,224], "input_2":[1,3,224,224]} If using the CLI, 7{\"input_1\": [1,3,224,224], \"input_2\":[1,3,224,224]}MXNET/ONNX/DARKNET: You must specify the name and shape (NCHW format) of the expected data inputs in order using a dictionary format for your trained model. The dictionary formats required for the console and CLI are different.Examples for one input:If using the console, {"data":[1,3,1024,1024]}If using the CLI, {\"data\":[1,3,1024,1024]}Examples for two inputs:If using the console, *{"var1": [1,1,28,28], "var2":[1,1,28,28]} If using the CLI, -{\"var1\": [1,1,28,28], \"var2\":[1,1,28,28]}PyTorch: You can either specify the name and shape (NCHW format) of expected data inputs in order using a dictionary format for your trained model or you can specify the shape only using a list format. The dictionary formats required for the console and CLI are different. The list formats for the console and CLI are the same.,Examples for one input in dictionary format:If using the console, {"input0":[1,3,224,224]}If using the CLI, {\"input0\":[1,3,224,224]}&Example for one input in list format: [[1,3,224,224]]-Examples for two inputs in dictionary format:If using the console, 0{"input0":[1,3,224,224], "input1":[1,3,224,224]}If using the CLI, 5{\"input0\":[1,3,224,224], \"input1\":[1,3,224,224]} +Example for two inputs in list format: [[1,3,224,224], [1,3,224,224]]XGBOOST+: input data name and shape are not needed.DataInputConfig' supports the following parameters for CoreML. OutputConfig$TargetDevice (ML Model format):shape : Input shape, for example %{"input_1": {"shape": [1,224,224,3]}}. In addition to static input shapes, CoreML converter supports Flexible input shapes:Range Dimension. You can use the Range Dimension feature if you know the input shape will be within some specific interval in that dimension, for example: .{"input_1": {"shape": ["1..10", 224, 224, 3]}}Enumerated shapes. Sometimes, the models are trained to work only on a select set of inputs. You can enumerate all supported input shapes, for example: <{"input_1": {"shape": [[1, 224, 224, 3], [1, 160, 160, 3]]}} default_shape: Default input shape. You can set a default shape during conversion for both Range Dimension and Enumerated Shapes. For example {"input_1": {"shape": ["1..10", 224, 224, 3], "default_shape": [1, 224, 224, 3]}}type: Input type. Allowed values: Image and Tensor. By default, the converter generates an ML Model with inputs of type Tensor (MultiArray). User can set input type to be Image. Image input type requires additional input parameters such as bias and scale.bias: If the input type is an Image, you need to provide the bias vector.scale: If the input type is an Image, you need to provide a scale factor.CoreML ClassifierConfig parameters can be specified using OutputConfig$CompilerOptions. CoreML converter supports Tensorflow and PyTorch models. CoreML conversion examples:Tensor type input: "DataInputConfig": {"input_1": {"shape": [[1,224,224,3], [1,160,160,3]], "default_shape": [1,224,224,3]}}/Tensor type input without input name (PyTorch): "DataInputConfig": [{"shape": [[1,3,224,224], [1,3,160,160]], "default_shape": [1,3,224,224]}]Image type input: "DataInputConfig": {"input_1": {"shape": [[1,224,224,3], [1,160,160,3]], "default_shape": [1,224,224,3], "type": "Image", "bias": [-1,-1,-1], "scale": 0.007843137255}} ?"CompilerOptions": {"class_labels": "imagenet_labels_1000.txt"}.Image type input without input name (PyTorch): "DataInputConfig": [{"shape": [[1,3,224,224], [1,3,160,160]], "default_shape": [1,3,224,224], "type": "Image", "bias": [-1,-1,-1], "scale": 0.007843137255}] ?"CompilerOptions": {"class_labels": "imagenet_labels_1000.txt"}Depending on the model format, DataInputConfig( requires the following parameters for ml_eia2  https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_OutputConfig.html#sagemaker-Type-OutputConfig-TargetDeviceOutputConfig:TargetDevice.For TensorFlow models saved in the SavedModel format, specify the input names from signature_def_key% and the input model shapes for DataInputConfig. Specify the signature_def_key in  https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_OutputConfig.html#sagemaker-Type-OutputConfig-CompilerOptionsOutputConfig:CompilerOptions if the model does not use TensorFlow's default signature def key. For example: /"DataInputConfig": {"inputs": [1, 224, 224, 3]} :"CompilerOptions": {"signature_def_key": "serving_custom"}For TensorFlow models saved as a frozen graph, specify the input tensor names and shapes in DataInputConfig& and the output tensor names for  output_names in  https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_OutputConfig.html#sagemaker-Type-OutputConfig-CompilerOptionsOutputConfig:CompilerOptions . For example: 7"DataInputConfig": {"input_tensor:0": [1, 224, 224, 3]} 8"CompilerOptions": {"output_names": ["output_tensor:0"]}%amazonka-sagemakerIdentifies the framework in which the model was trained. For example: TENSORFLOW.%amazonka-sagemakerCreate a value of %" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:%, % - Specifies the framework version to use. This API field is only supported for the MXNet, PyTorch, TensorFlow and TensorFlow Lite frameworks.For information about framework versions supported for cloud targets and edge devices, see  https://docs.aws.amazon.com/sagemaker/latest/dg/neo-supported-cloud.html-Cloud Supported Instance Types and Frameworks and  https://docs.aws.amazon.com/sagemaker/latest/dg/neo-supported-devices-edge-frameworks.htmlEdge Supported Frameworks.%, % - The S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).%, % - Specifies the name and shape of the expected data inputs for your trained model with a JSON dictionary form. The data inputs are InputConfig$Framework specific. TensorFlow: You must specify the name and shape (NHWC format) of the expected data inputs using a dictionary format for your trained model. The dictionary formats required for the console and CLI are different.Examples for one input:If using the console, {"input":[1,1024,1024,3]}If using the CLI, {\"input\":[1,1024,1024,3]}Examples for two inputs:If using the console, +{"data1": [1,28,28,1], "data2":[1,28,28,1]}If using the CLI, /{\"data1\": [1,28,28,1], \"data2\":[1,28,28,1]}KERAS: You must specify the name and shape (NCHW format) of expected data inputs using a dictionary format for your trained model. Note that while Keras model artifacts should be uploaded in NHWC (channel-last) format, DataInputConfig should be specified in NCHW (channel-first) format. The dictionary formats required for the console and CLI are different.Examples for one input:If using the console, {"input_1":[1,3,224,224]}If using the CLI, {\"input_1\":[1,3,224,224]}Examples for two inputs:If using the console, 4{"input_1": [1,3,224,224], "input_2":[1,3,224,224]} If using the CLI, 7{\"input_1\": [1,3,224,224], \"input_2\":[1,3,224,224]}MXNET/ONNX/DARKNET: You must specify the name and shape (NCHW format) of the expected data inputs in order using a dictionary format for your trained model. The dictionary formats required for the console and CLI are different.Examples for one input:If using the console, {"data":[1,3,1024,1024]}If using the CLI, {\"data\":[1,3,1024,1024]}Examples for two inputs:If using the console, *{"var1": [1,1,28,28], "var2":[1,1,28,28]} If using the CLI, -{\"var1\": [1,1,28,28], \"var2\":[1,1,28,28]}PyTorch: You can either specify the name and shape (NCHW format) of expected data inputs in order using a dictionary format for your trained model or you can specify the shape only using a list format. The dictionary formats required for the console and CLI are different. The list formats for the console and CLI are the same.,Examples for one input in dictionary format:If using the console, {"input0":[1,3,224,224]}If using the CLI, {\"input0\":[1,3,224,224]}&Example for one input in list format: [[1,3,224,224]]-Examples for two inputs in dictionary format:If using the console, 0{"input0":[1,3,224,224], "input1":[1,3,224,224]}If using the CLI, 5{\"input0\":[1,3,224,224], \"input1\":[1,3,224,224]} +Example for two inputs in list format: [[1,3,224,224], [1,3,224,224]]XGBOOST+: input data name and shape are not needed.DataInputConfig' supports the following parameters for CoreML. OutputConfig$TargetDevice (ML Model format):shape : Input shape, for example %{"input_1": {"shape": [1,224,224,3]}}. In addition to static input shapes, CoreML converter supports Flexible input shapes:Range Dimension. You can use the Range Dimension feature if you know the input shape will be within some specific interval in that dimension, for example: .{"input_1": {"shape": ["1..10", 224, 224, 3]}}Enumerated shapes. Sometimes, the models are trained to work only on a select set of inputs. You can enumerate all supported input shapes, for example: <{"input_1": {"shape": [[1, 224, 224, 3], [1, 160, 160, 3]]}} default_shape: Default input shape. You can set a default shape during conversion for both Range Dimension and Enumerated Shapes. For example {"input_1": {"shape": ["1..10", 224, 224, 3], "default_shape": [1, 224, 224, 3]}}type: Input type. Allowed values: Image and Tensor. By default, the converter generates an ML Model with inputs of type Tensor (MultiArray). User can set input type to be Image. Image input type requires additional input parameters such as bias and scale.bias: If the input type is an Image, you need to provide the bias vector.scale: If the input type is an Image, you need to provide a scale factor.CoreML ClassifierConfig parameters can be specified using OutputConfig$CompilerOptions. CoreML converter supports Tensorflow and PyTorch models. CoreML conversion examples:Tensor type input: "DataInputConfig": {"input_1": {"shape": [[1,224,224,3], [1,160,160,3]], "default_shape": [1,224,224,3]}}/Tensor type input without input name (PyTorch): "DataInputConfig": [{"shape": [[1,3,224,224], [1,3,160,160]], "default_shape": [1,3,224,224]}]Image type input: "DataInputConfig": {"input_1": {"shape": [[1,224,224,3], [1,160,160,3]], "default_shape": [1,224,224,3], "type": "Image", "bias": [-1,-1,-1], "scale": 0.007843137255}} ?"CompilerOptions": {"class_labels": "imagenet_labels_1000.txt"}.Image type input without input name (PyTorch): "DataInputConfig": [{"shape": [[1,3,224,224], [1,3,160,160]], "default_shape": [1,3,224,224], "type": "Image", "bias": [-1,-1,-1], "scale": 0.007843137255}] ?"CompilerOptions": {"class_labels": "imagenet_labels_1000.txt"}Depending on the model format, DataInputConfig( requires the following parameters for ml_eia2  https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_OutputConfig.html#sagemaker-Type-OutputConfig-TargetDeviceOutputConfig:TargetDevice.For TensorFlow models saved in the SavedModel format, specify the input names from signature_def_key% and the input model shapes for DataInputConfig. Specify the signature_def_key in  https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_OutputConfig.html#sagemaker-Type-OutputConfig-CompilerOptionsOutputConfig:CompilerOptions if the model does not use TensorFlow's default signature def key. For example: /"DataInputConfig": {"inputs": [1, 224, 224, 3]} :"CompilerOptions": {"signature_def_key": "serving_custom"}For TensorFlow models saved as a frozen graph, specify the input tensor names and shapes in DataInputConfig& and the output tensor names for  output_names in  https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_OutputConfig.html#sagemaker-Type-OutputConfig-CompilerOptionsOutputConfig:CompilerOptions . For example: 7"DataInputConfig": {"input_tensor:0": [1, 224, 224, 3]} 8"CompilerOptions": {"output_names": ["output_tensor:0"]}%, % - Identifies the framework in which the model was trained. For example: TENSORFLOW.%amazonka-sagemakerSpecifies the framework version to use. This API field is only supported for the MXNet, PyTorch, TensorFlow and TensorFlow Lite frameworks.For information about framework versions supported for cloud targets and edge devices, see  https://docs.aws.amazon.com/sagemaker/latest/dg/neo-supported-cloud.html-Cloud Supported Instance Types and Frameworks and  https://docs.aws.amazon.com/sagemaker/latest/dg/neo-supported-devices-edge-frameworks.htmlEdge Supported Frameworks.%amazonka-sagemakerThe S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).%amazonka-sagemakerSpecifies the name and shape of the expected data inputs for your trained model with a JSON dictionary form. The data inputs are InputConfig$Framework specific. TensorFlow: You must specify the name and shape (NHWC format) of the expected data inputs using a dictionary format for your trained model. The dictionary formats required for the console and CLI are different.Examples for one input:If using the console, {"input":[1,1024,1024,3]}If using the CLI, {\"input\":[1,1024,1024,3]}Examples for two inputs:If using the console, +{"data1": [1,28,28,1], "data2":[1,28,28,1]}If using the CLI, /{\"data1\": [1,28,28,1], \"data2\":[1,28,28,1]}KERAS: You must specify the name and shape (NCHW format) of expected data inputs using a dictionary format for your trained model. Note that while Keras model artifacts should be uploaded in NHWC (channel-last) format, DataInputConfig should be specified in NCHW (channel-first) format. The dictionary formats required for the console and CLI are different.Examples for one input:If using the console, {"input_1":[1,3,224,224]}If using the CLI, {\"input_1\":[1,3,224,224]}Examples for two inputs:If using the console, 4{"input_1": [1,3,224,224], "input_2":[1,3,224,224]} If using the CLI, 7{\"input_1\": [1,3,224,224], \"input_2\":[1,3,224,224]}MXNET/ONNX/DARKNET: You must specify the name and shape (NCHW format) of the expected data inputs in order using a dictionary format for your trained model. The dictionary formats required for the console and CLI are different.Examples for one input:If using the console, {"data":[1,3,1024,1024]}If using the CLI, {\"data\":[1,3,1024,1024]}Examples for two inputs:If using the console, *{"var1": [1,1,28,28], "var2":[1,1,28,28]} If using the CLI, -{\"var1\": [1,1,28,28], \"var2\":[1,1,28,28]}PyTorch: You can either specify the name and shape (NCHW format) of expected data inputs in order using a dictionary format for your trained model or you can specify the shape only using a list format. The dictionary formats required for the console and CLI are different. The list formats for the console and CLI are the same.,Examples for one input in dictionary format:If using the console, {"input0":[1,3,224,224]}If using the CLI, {\"input0\":[1,3,224,224]}&Example for one input in list format: [[1,3,224,224]]-Examples for two inputs in dictionary format:If using the console, 0{"input0":[1,3,224,224], "input1":[1,3,224,224]}If using the CLI, 5{\"input0\":[1,3,224,224], \"input1\":[1,3,224,224]} +Example for two inputs in list format: [[1,3,224,224], [1,3,224,224]]XGBOOST+: input data name and shape are not needed.DataInputConfig' supports the following parameters for CoreML. OutputConfig$TargetDevice (ML Model format):shape : Input shape, for example %{"input_1": {"shape": [1,224,224,3]}}. In addition to static input shapes, CoreML converter supports Flexible input shapes:Range Dimension. You can use the Range Dimension feature if you know the input shape will be within some specific interval in that dimension, for example: .{"input_1": {"shape": ["1..10", 224, 224, 3]}}Enumerated shapes. Sometimes, the models are trained to work only on a select set of inputs. You can enumerate all supported input shapes, for example: <{"input_1": {"shape": [[1, 224, 224, 3], [1, 160, 160, 3]]}} default_shape: Default input shape. You can set a default shape during conversion for both Range Dimension and Enumerated Shapes. For example {"input_1": {"shape": ["1..10", 224, 224, 3], "default_shape": [1, 224, 224, 3]}}type: Input type. Allowed values: Image and Tensor. By default, the converter generates an ML Model with inputs of type Tensor (MultiArray). User can set input type to be Image. Image input type requires additional input parameters such as bias and scale.bias: If the input type is an Image, you need to provide the bias vector.scale: If the input type is an Image, you need to provide a scale factor.CoreML ClassifierConfig parameters can be specified using OutputConfig$CompilerOptions. CoreML converter supports Tensorflow and PyTorch models. CoreML conversion examples:Tensor type input: "DataInputConfig": {"input_1": {"shape": [[1,224,224,3], [1,160,160,3]], "default_shape": [1,224,224,3]}}/Tensor type input without input name (PyTorch): "DataInputConfig": [{"shape": [[1,3,224,224], [1,3,160,160]], "default_shape": [1,3,224,224]}]Image type input: "DataInputConfig": {"input_1": {"shape": [[1,224,224,3], [1,160,160,3]], "default_shape": [1,224,224,3], "type": "Image", "bias": [-1,-1,-1], "scale": 0.007843137255}} ?"CompilerOptions": {"class_labels": "imagenet_labels_1000.txt"}.Image type input without input name (PyTorch): "DataInputConfig": [{"shape": [[1,3,224,224], [1,3,160,160]], "default_shape": [1,3,224,224], "type": "Image", "bias": [-1,-1,-1], "scale": 0.007843137255}] ?"CompilerOptions": {"class_labels": "imagenet_labels_1000.txt"}Depending on the model format, DataInputConfig( requires the following parameters for ml_eia2  https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_OutputConfig.html#sagemaker-Type-OutputConfig-TargetDeviceOutputConfig:TargetDevice.For TensorFlow models saved in the SavedModel format, specify the input names from signature_def_key% and the input model shapes for DataInputConfig. Specify the signature_def_key in  https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_OutputConfig.html#sagemaker-Type-OutputConfig-CompilerOptionsOutputConfig:CompilerOptions if the model does not use TensorFlow's default signature def key. For example: /"DataInputConfig": {"inputs": [1, 224, 224, 3]} :"CompilerOptions": {"signature_def_key": "serving_custom"}For TensorFlow models saved as a frozen graph, specify the input tensor names and shapes in DataInputConfig& and the output tensor names for  output_names in  https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_OutputConfig.html#sagemaker-Type-OutputConfig-CompilerOptionsOutputConfig:CompilerOptions . For example: 7"DataInputConfig": {"input_tensor:0": [1, 224, 224, 3]} 8"CompilerOptions": {"output_names": ["output_tensor:0"]}%amazonka-sagemakerIdentifies the framework in which the model was trained. For example: TENSORFLOW.%amazonka-sagemaker%amazonka-sagemaker%amazonka-sagemaker% %%%%%%%%%%% %%%%%%%%%%%(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?o%%%%%%%%%%%%(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';,%amazonka-sagemaker>Information on the IMDS configuration of the notebook instanceSee: % smart constructor.%amazonka-sagemakerIndicates the minimum IMDS version that the notebook instance supports. When passed as part of CreateNotebookInstance, if no value is selected, then it defaults to IMDSv1. This means that both IMDSv1 and IMDSv2 are supported. If passed as part of UpdateNotebookInstance, there is no default.%amazonka-sagemakerCreate a value of %" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:%, % - Indicates the minimum IMDS version that the notebook instance supports. When passed as part of CreateNotebookInstance, if no value is selected, then it defaults to IMDSv1. This means that both IMDSv1 and IMDSv2 are supported. If passed as part of UpdateNotebookInstance, there is no default.%amazonka-sagemakerIndicates the minimum IMDS version that the notebook instance supports. When passed as part of CreateNotebookInstance, if no value is selected, then it defaults to IMDSv1. This means that both IMDSv1 and IMDSv2 are supported. If passed as part of UpdateNotebookInstance, there is no default.%amazonka-sagemaker%%%%%%%%%%%(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?%&&&&&&&&&&&&&&&&&&&&%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&&&&&&&&&&&&&&&&&&&&%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&&&&&&&&&&&&&&&&&&&&%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; &amazonka-sagemakerFor a hyperparameter of the integer type, specifies the range that a hyperparameter tuning job searches.See: & smart constructor.&amazonka-sagemakerThe scale that hyperparameter tuning uses to search the hyperparameter range. For information about choosing a hyperparameter scale, see  https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-define-ranges.html#scaling-typeHyperparameter Scaling. One of the following values: AutoSageMaker hyperparameter tuning chooses the best scale for the hyperparameter.LinearHyperparameter tuning searches the values in the hyperparameter range by using a linear scale. LogarithmicHyperparameter tuning searches the values in the hyperparameter range by using a logarithmic scale.Logarithmic scaling works only for ranges that have only values greater than 0.&amazonka-sagemaker)The name of the hyperparameter to search.&amazonka-sagemaker2The minimum value of the hyperparameter to search.&amazonka-sagemaker2The maximum value of the hyperparameter to search.&amazonka-sagemakerCreate a value of &" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:&, & - The scale that hyperparameter tuning uses to search the hyperparameter range. For information about choosing a hyperparameter scale, see  https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-define-ranges.html#scaling-typeHyperparameter Scaling. One of the following values: AutoSageMaker hyperparameter tuning chooses the best scale for the hyperparameter.LinearHyperparameter tuning searches the values in the hyperparameter range by using a linear scale. LogarithmicHyperparameter tuning searches the values in the hyperparameter range by using a logarithmic scale.Logarithmic scaling works only for ranges that have only values greater than 0.&, &, - The name of the hyperparameter to search.&, &5 - The minimum value of the hyperparameter to search.&, &5 - The maximum value of the hyperparameter to search.&amazonka-sagemakerThe scale that hyperparameter tuning uses to search the hyperparameter range. For information about choosing a hyperparameter scale, see  https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-define-ranges.html#scaling-typeHyperparameter Scaling. One of the following values: AutoSageMaker hyperparameter tuning chooses the best scale for the hyperparameter.LinearHyperparameter tuning searches the values in the hyperparameter range by using a linear scale. LogarithmicHyperparameter tuning searches the values in the hyperparameter range by using a logarithmic scale.Logarithmic scaling works only for ranges that have only values greater than 0.&amazonka-sagemaker)The name of the hyperparameter to search.&amazonka-sagemaker2The minimum value of the hyperparameter to search.&amazonka-sagemaker2The maximum value of the hyperparameter to search.&amazonka-sagemaker&amazonka-sagemaker&amazonka-sagemaker& &&&&&&&&&&& &&&&&&&&&&&(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';/&amazonka-sagemaker:Defines the possible values for an integer hyperparameter.See: & smart constructor.&amazonka-sagemaker"The minimum integer value allowed.&amazonka-sagemaker"The maximum integer value allowed.&amazonka-sagemakerCreate a value of &" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:&, &% - The minimum integer value allowed.&, &% - The maximum integer value allowed.&amazonka-sagemaker"The minimum integer value allowed.&amazonka-sagemaker"The maximum integer value allowed.&amazonka-sagemaker&amazonka-sagemaker&&&&&&&&&&&&&&&(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?&&&&&& &&&&&&&&&(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?&&&&&&&&&&&&(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; "~&amazonka-sagemakerThe data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.htmlAssociate Prediction Results with their Corresponding Input Records.See: & smart constructor.&amazonka-sagemakerA  https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operatorsJSONPath expression used to select a portion of the input data to pass to the algorithm. Use the  InputFilter parameter to exclude fields, such as an ID column, from the input. If you want SageMaker to pass the entire input dataset to the algorithm, accept the default value $. Examples: "$", "$[1:]",  "$.features"&amazonka-sagemakerSpecifies the source of the data to join with the transformed data. The valid values are None and Input. The default value is None, which specifies not to join the input with the transformed data. If you want the batch transform job to join the original input data with the transformed data, set  JoinSource to Input. You can specify  OutputFilter as an additional filter to select a portion of the joined dataset and store it in the output file.For JSON or JSONLines objects, such as a JSON array, SageMaker adds the transformed data to the input JSON object in an attribute called SageMakerOutput. The joined result for JSON must be a key-value pair object. If the input is not a key-value pair object, SageMaker creates a new JSON file. In the new JSON file, and the input data is stored under the SageMakerInput$ key and the results are stored in SageMakerOutput.For CSV data, SageMaker takes each row as a JSON array and joins the transformed data with the input by appending each transformed row to the end of the input. The joined data has the original input data followed by the transformed data and the output is a CSV file.0For information on how joining in applied, see  https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#batch-transform-data-processing-workflow6Workflow for Associating Inferences with Input Records.&amazonka-sagemakerA  https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operatorsJSONPath expression used to select a portion of the joined dataset to save in the output file for a batch transform job. If you want SageMaker to store the entire input dataset in the output file, leave the default value, $. If you specify indexes that aren't within the dimension size of the joined dataset, you get an error. Examples: "$",  "$[0,5:]", "$['id','SageMakerOutput']"&amazonka-sagemakerCreate a value of &" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:&, ' - A  https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operatorsJSONPath expression used to select a portion of the input data to pass to the algorithm. Use the  InputFilter parameter to exclude fields, such as an ID column, from the input. If you want SageMaker to pass the entire input dataset to the algorithm, accept the default value $. Examples: "$", "$[1:]",  "$.features"&, ' - Specifies the source of the data to join with the transformed data. The valid values are None and Input. The default value is None, which specifies not to join the input with the transformed data. If you want the batch transform job to join the original input data with the transformed data, set  JoinSource to Input. You can specify  OutputFilter as an additional filter to select a portion of the joined dataset and store it in the output file.For JSON or JSONLines objects, such as a JSON array, SageMaker adds the transformed data to the input JSON object in an attribute called SageMakerOutput. The joined result for JSON must be a key-value pair object. If the input is not a key-value pair object, SageMaker creates a new JSON file. In the new JSON file, and the input data is stored under the SageMakerInput$ key and the results are stored in SageMakerOutput.For CSV data, SageMaker takes each row as a JSON array and joins the transformed data with the input by appending each transformed row to the end of the input. The joined data has the original input data followed by the transformed data and the output is a CSV file.0For information on how joining in applied, see  https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#batch-transform-data-processing-workflow6Workflow for Associating Inferences with Input Records.&, ' - A  https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operatorsJSONPath expression used to select a portion of the joined dataset to save in the output file for a batch transform job. If you want SageMaker to store the entire input dataset in the output file, leave the default value, $. If you specify indexes that aren't within the dimension size of the joined dataset, you get an error. Examples: "$",  "$[0,5:]", "$['id','SageMakerOutput']"'amazonka-sagemakerA  https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operatorsJSONPath expression used to select a portion of the input data to pass to the algorithm. Use the  InputFilter parameter to exclude fields, such as an ID column, from the input. If you want SageMaker to pass the entire input dataset to the algorithm, accept the default value $. Examples: "$", "$[1:]",  "$.features"'amazonka-sagemakerSpecifies the source of the data to join with the transformed data. The valid values are None and Input. The default value is None, which specifies not to join the input with the transformed data. If you want the batch transform job to join the original input data with the transformed data, set  JoinSource to Input. You can specify  OutputFilter as an additional filter to select a portion of the joined dataset and store it in the output file.For JSON or JSONLines objects, such as a JSON array, SageMaker adds the transformed data to the input JSON object in an attribute called SageMakerOutput. The joined result for JSON must be a key-value pair object. If the input is not a key-value pair object, SageMaker creates a new JSON file. In the new JSON file, and the input data is stored under the SageMakerInput$ key and the results are stored in SageMakerOutput.For CSV data, SageMaker takes each row as a JSON array and joins the transformed data with the input by appending each transformed row to the end of the input. The joined data has the original input data followed by the transformed data and the output is a CSV file.0For information on how joining in applied, see  https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#batch-transform-data-processing-workflow6Workflow for Associating Inferences with Input Records.'amazonka-sagemakerA  https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operatorsJSONPath expression used to select a portion of the joined dataset to save in the output file for a batch transform job. If you want SageMaker to store the entire input dataset in the output file, leave the default value, $. If you specify indexes that aren't within the dimension size of the joined dataset, you get an error. Examples: "$",  "$[0,5:]", "$['id','SageMakerOutput']" &&&&&&''' &&&&&&'''(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; ''amazonka-sagemaker&The specification of a Jupyter kernel.See: ' smart constructor.'amazonka-sagemakerThe display name of the kernel.'amazonka-sagemakerThe name of the Jupyter kernel in the image. This value is case sensitive.'amazonka-sagemakerCreate a value of '" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:', '" - The display name of the kernel.', ' - The name of the Jupyter kernel in the image. This value is case sensitive.'amazonka-sagemakerThe display name of the kernel.'amazonka-sagemakerThe name of the Jupyter kernel in the image. This value is case sensitive.'amazonka-sagemaker'''''''''''''''(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; ,@'amazonka-sagemakerThe configuration for the file system and kernels in a SageMaker image running as a KernelGateway app.See: ' smart constructor.'amazonka-sagemakerThe Amazon Elastic File System (EFS) storage configuration for a SageMaker image.'amazonka-sagemaker6The specification of the Jupyter kernels in the image.'amazonka-sagemakerCreate a value of '" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:', ' - The Amazon Elastic File System (EFS) storage configuration for a SageMaker image.', '9 - The specification of the Jupyter kernels in the image.'amazonka-sagemakerThe Amazon Elastic File System (EFS) storage configuration for a SageMaker image.'amazonka-sagemaker6The specification of the Jupyter kernels in the image.'amazonka-sagemaker'''''''''''''''(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; 3 'amazonka-sagemakerThe configuration for running a SageMaker image as a KernelGateway app.See: ' smart constructor.'amazonka-sagemaker5The Amazon Resource Name (ARN) of the AppImageConfig.'amazonka-sagemaker?The name of the AppImageConfig. Must be unique to your account.'amazonka-sagemaker$When the AppImageConfig was created.'amazonka-sagemakerThe configuration for the file system and kernels in the SageMaker image.'amazonka-sagemaker*When the AppImageConfig was last modified.'amazonka-sagemakerCreate a value of '" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:', '8 - The Amazon Resource Name (ARN) of the AppImageConfig.', ' - The name of the AppImageConfig. Must be unique to your account.', '' - When the AppImageConfig was created.', ' - The configuration for the file system and kernels in the SageMaker image.', '- - When the AppImageConfig was last modified.'amazonka-sagemaker5The Amazon Resource Name (ARN) of the AppImageConfig.'amazonka-sagemaker?The name of the AppImageConfig. Must be unique to your account.'amazonka-sagemaker$When the AppImageConfig was created.'amazonka-sagemakerThe configuration for the file system and kernels in the SageMaker image.'amazonka-sagemaker*When the AppImageConfig was last modified. ''''''''''''' '''''''''''''(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; : 'amazonka-sagemaker6Provides a breakdown of the number of objects labeled.See: ' smart constructor.'amazonka-sagemakerThe total number of objects that could not be labeled due to an error.'amazonka-sagemaker6The total number of objects labeled by a human worker.'amazonka-sagemaker?The total number of objects labeled by automated data labeling.'amazonka-sagemaker$The total number of objects labeled.'amazonka-sagemaker,The total number of objects not yet labeled.'amazonka-sagemakerCreate a value of '" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:', ' - The total number of objects that could not be labeled due to an error.', '9 - The total number of objects labeled by a human worker.', ' - The total number of objects labeled by automated data labeling.', '' - The total number of objects labeled.', '/ - The total number of objects not yet labeled.'amazonka-sagemakerThe total number of objects that could not be labeled due to an error.'amazonka-sagemaker6The total number of objects labeled by a human worker.'amazonka-sagemaker?The total number of objects labeled by automated data labeling.'amazonka-sagemaker$The total number of objects labeled.'amazonka-sagemaker,The total number of objects not yet labeled. ''''''''''''' '''''''''''''(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; @'amazonka-sagemaker - The total number of data objects labeled by a human worker.', ' - The total number of data objects that need to be labeled by a human worker.', '1 - The total number of tasks in the labeling job.'amazonka-sagemaker;The total number of data objects labeled by a human worker.'amazonka-sagemakerThe total number of data objects that need to be labeled by a human worker.'amazonka-sagemaker.The total number of tasks in the labeling job. ''''''''' '''''''''(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; FJ'amazonka-sagemakerAttributes of the data specified by the customer. Use these to describe the data to be labeled.See: ' smart constructor.'amazonka-sagemakerDeclares that your content is free of personally identifiable information or adult content. SageMaker may restrict the Amazon Mechanical Turk workers that can view your task based on this information.'amazonka-sagemakerCreate a value of '" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:', ' - Declares that your content is free of personally identifiable information or adult content. SageMaker may restrict the Amazon Mechanical Turk workers that can view your task based on this information.'amazonka-sagemakerDeclares that your content is free of personally identifiable information or adult content. SageMaker may restrict the Amazon Mechanical Turk workers that can view your task based on this information.''''''''''(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; O'amazonka-sagemaker-Provides summary information for a work team.See: ' smart constructor.'amazonka-sagemaker:Provides information about the progress of a labeling job.'amazonka-sagemaker?The name of the labeling job that the work team is assigned to.'amazonka-sagemaker1The configured number of workers per data object.'amazonka-sagemakerA unique identifier for a labeling job. You can use this to refer to a specific labeling job.'amazonka-sagemakerThe Amazon Web Services account ID of the account used to start the labeling job.'amazonka-sagemaker4The date and time that the labeling job was created.'amazonka-sagemakerCreate a value of '" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:', '= - Provides information about the progress of a labeling job.', ' - The name of the labeling job that the work team is assigned to.', '4 - The configured number of workers per data object.', ' - A unique identifier for a labeling job. You can use this to refer to a specific labeling job.', ' - The Amazon Web Services account ID of the account used to start the labeling job.', '7 - The date and time that the labeling job was created.'amazonka-sagemaker:Provides information about the progress of a labeling job.'amazonka-sagemaker?The name of the labeling job that the work team is assigned to.'amazonka-sagemaker1The configured number of workers per data object.'amazonka-sagemakerA unique identifier for a labeling job. You can use this to refer to a specific labeling job.'amazonka-sagemakerThe Amazon Web Services account ID of the account used to start the labeling job.'amazonka-sagemaker4The date and time that the labeling job was created.'amazonka-sagemaker'amazonka-sagemaker'amazonka-sagemaker'''''''''''''''''''''''''''''''(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; UP(amazonka-sagemakerSpecifies the location of the output produced by the labeling job.See: ( smart constructor.(amazonka-sagemakerThe Amazon Resource Name (ARN) for the most recent SageMaker model trained as part of automated data labeling.(amazonka-sagemakerThe Amazon S3 bucket location of the manifest file for labeled data.(amazonka-sagemakerCreate a value of (" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:(, ( - The Amazon Resource Name (ARN) for the most recent SageMaker model trained as part of automated data labeling.(, ( - The Amazon S3 bucket location of the manifest file for labeled data.(amazonka-sagemakerThe Amazon Resource Name (ARN) for the most recent SageMaker model trained as part of automated data labeling.(amazonka-sagemakerThe Amazon S3 bucket location of the manifest file for labeled data.(amazonka-sagemaker((((((((((((((((c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; l(amazonka-sagemaker4Output configuration information for a labeling job.See: ( smart constructor.(amazonka-sagemakerThe Amazon Web Services Key Management Service ID of the key used to encrypt the output data, if any.If you provide your own KMS key ID, you must add the required permissions to your KMS key described in  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-security-permission.html#sms-security-kms-permissionsEncrypt Output Data and Storage Volume with Amazon Web Services KMS.If you don't provide a KMS key ID, Amazon SageMaker uses the default Amazon Web Services KMS key for Amazon S3 for your role's account to encrypt your output data.#If you use a bucket policy with an  s3:PutObject permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption to  "aws:kms". For more information, see  https://docs.aws.amazon.com/AmazonS3/latest/dev/UsingKMSEncryption.htmlKMS-Managed Encryption Keys in the .Amazon Simple Storage Service Developer Guide.(amazonka-sagemakerAn Amazon Simple Notification Service (Amazon SNS) output topic ARN. Provide a  SnsTopicArn if you want to do real time chaining to another streaming job and receive an Amazon SNS notifications each time a data object is submitted by a worker.If you provide an  SnsTopicArn in  OutputConfig, when workers complete labeling tasks, Ground Truth will send labeling task output data to the SNS output topic you specify here.To learn more, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-streaming-labeling-job.html#sms-streaming-how-it-works-output-data1Receive Output Data from a Streaming Labeling Job.(amazonka-sagemaker,The Amazon S3 location to write output data.(amazonka-sagemakerCreate a value of (" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:(, ( - The Amazon Web Services Key Management Service ID of the key used to encrypt the output data, if any.If you provide your own KMS key ID, you must add the required permissions to your KMS key described in  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-security-permission.html#sms-security-kms-permissionsEncrypt Output Data and Storage Volume with Amazon Web Services KMS.If you don't provide a KMS key ID, Amazon SageMaker uses the default Amazon Web Services KMS key for Amazon S3 for your role's account to encrypt your output data.#If you use a bucket policy with an  s3:PutObject permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption to  "aws:kms". For more information, see  https://docs.aws.amazon.com/AmazonS3/latest/dev/UsingKMSEncryption.htmlKMS-Managed Encryption Keys in the .Amazon Simple Storage Service Developer Guide.(, ( - An Amazon Simple Notification Service (Amazon SNS) output topic ARN. Provide a  SnsTopicArn if you want to do real time chaining to another streaming job and receive an Amazon SNS notifications each time a data object is submitted by a worker.If you provide an  SnsTopicArn in  OutputConfig, when workers complete labeling tasks, Ground Truth will send labeling task output data to the SNS output topic you specify here.To learn more, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-streaming-labeling-job.html#sms-streaming-how-it-works-output-data1Receive Output Data from a Streaming Labeling Job.(, (/ - The Amazon S3 location to write output data.(amazonka-sagemakerThe Amazon Web Services Key Management Service ID of the key used to encrypt the output data, if any.If you provide your own KMS key ID, you must add the required permissions to your KMS key described in  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-security-permission.html#sms-security-kms-permissionsEncrypt Output Data and Storage Volume with Amazon Web Services KMS.If you don't provide a KMS key ID, Amazon SageMaker uses the default Amazon Web Services KMS key for Amazon S3 for your role's account to encrypt your output data.#If you use a bucket policy with an  s3:PutObject permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption to  "aws:kms". For more information, see  https://docs.aws.amazon.com/AmazonS3/latest/dev/UsingKMSEncryption.htmlKMS-Managed Encryption Keys in the .Amazon Simple Storage Service Developer Guide.(amazonka-sagemakerAn Amazon Simple Notification Service (Amazon SNS) output topic ARN. Provide a  SnsTopicArn if you want to do real time chaining to another streaming job and receive an Amazon SNS notifications each time a data object is submitted by a worker.If you provide an  SnsTopicArn in  OutputConfig, when workers complete labeling tasks, Ground Truth will send labeling task output data to the SNS output topic you specify here.To learn more, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-streaming-labeling-job.html#sms-streaming-how-it-works-output-data1Receive Output Data from a Streaming Labeling Job.(amazonka-sagemaker,The Amazon S3 location to write output data.(amazonka-sagemaker( ((((((((( ((((((((((c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; yn(amazonka-sagemaker1The Amazon S3 location of the input data objects.See: ( smart constructor.(amazonka-sagemakerThe Amazon S3 location of the manifest file that describes the input data objects.&The input manifest file referenced in  ManifestS3Uri* must contain one of the following keys:  source-ref or source4. The value of the keys are interpreted as follows: source-ref: The source of the object is the Amazon S3 object specified in the value. Use this value when the object is a binary object, such as an image.source: The source of the object is the value. Use this value when the object is a text value.If you are a new user of Ground Truth, it is recommended you review  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-input-data-input-manifest.htmlUse an Input Manifest File in the Amazon SageMaker Developer Guide to learn how to create an input manifest file.(amazonka-sagemakerCreate a value of (" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:(, ( - The Amazon S3 location of the manifest file that describes the input data objects.&The input manifest file referenced in  ManifestS3Uri* must contain one of the following keys:  source-ref or source4. The value of the keys are interpreted as follows: source-ref: The source of the object is the Amazon S3 object specified in the value. Use this value when the object is a binary object, such as an image.source: The source of the object is the value. Use this value when the object is a text value.If you are a new user of Ground Truth, it is recommended you review  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-input-data-input-manifest.htmlUse an Input Manifest File in the Amazon SageMaker Developer Guide to learn how to create an input manifest file.(amazonka-sagemakerThe Amazon S3 location of the manifest file that describes the input data objects.&The input manifest file referenced in  ManifestS3Uri* must contain one of the following keys:  source-ref or source4. The value of the keys are interpreted as follows: source-ref: The source of the object is the Amazon S3 object specified in the value. Use this value when the object is a binary object, such as an image.source: The source of the object is the value. Use this value when the object is a text value.If you are a new user of Ground Truth, it is recommended you review  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-input-data-input-manifest.htmlUse an Input Manifest File in the Amazon SageMaker Developer Guide to learn how to create an input manifest file.(amazonka-sagemaker((((((((((((c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; ~\(amazonka-sagemaker;An Amazon SNS data source used for streaming labeling jobs.See: ( smart constructor.(amazonka-sagemakerThe Amazon SNS input topic Amazon Resource Name (ARN). Specify the ARN of the input topic you will use to send new data objects to a streaming labeling job.(amazonka-sagemakerCreate a value of (" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:(, ( - The Amazon SNS input topic Amazon Resource Name (ARN). Specify the ARN of the input topic you will use to send new data objects to a streaming labeling job.(amazonka-sagemakerThe Amazon SNS input topic Amazon Resource Name (ARN). Specify the ARN of the input topic you will use to send new data objects to a streaming labeling job.(amazonka-sagemaker((((((((((((c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; (amazonka-sagemaker6Provides information about the location of input data.0You must specify at least one of the following:  S3DataSource or  SnsDataSource.Use  SnsDataSource to specify an SNS input topic for a streaming labeling job. If you do not specify and SNS input topic ARN, Ground Truth will create a one-time labeling job.Use  S3DataSource to specify an input manifest file for both streaming and one-time labeling jobs. Adding an  S3DataSource is optional if you use  SnsDataSource$ to create a streaming labeling job.See: ( smart constructor.(amazonka-sagemaker1The Amazon S3 location of the input data objects.(amazonka-sagemakerAn Amazon SNS data source used for streaming labeling jobs. To learn more, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-streaming-labeling-job.html#sms-streaming-how-it-works-send-data%Send Data to a Streaming Labeling Job.(amazonka-sagemakerCreate a value of (" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:(, (4 - The Amazon S3 location of the input data objects.(, ( - An Amazon SNS data source used for streaming labeling jobs. To learn more, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-streaming-labeling-job.html#sms-streaming-how-it-works-send-data%Send Data to a Streaming Labeling Job.(amazonka-sagemaker1The Amazon S3 location of the input data objects.(amazonka-sagemakerAn Amazon SNS data source used for streaming labeling jobs. To learn more, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-streaming-labeling-job.html#sms-streaming-how-it-works-send-data%Send Data to a Streaming Labeling Job.(((((((((((((((c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; N(amazonka-sagemaker3Input configuration information for a labeling job.See: ( smart constructor.(amazonka-sagemaker1Attributes of the data specified by the customer.(amazonka-sagemakerThe location of the input data.(amazonka-sagemakerCreate a value of (" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:(, (4 - Attributes of the data specified by the customer.(, (" - The location of the input data.(amazonka-sagemaker1Attributes of the data specified by the customer.(amazonka-sagemakerThe location of the input data.(amazonka-sagemaker((((((((((((((((c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?  (((((((((((((((((((((((((c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; (amazonka-sagemakerA set of conditions for stopping a labeling job. If any of the conditions are met, the job is automatically stopped. You can use these conditions to control the cost of data labeling.Labeling jobs fail after 30 days with an appropriate client error message.See: ( smart constructor.(amazonka-sagemakerThe maximum number of objects that can be labeled by human workers.(amazonka-sagemakerThe maximum number of input data objects that should be labeled.(amazonka-sagemakerCreate a value of (" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:(, ( - The maximum number of objects that can be labeled by human workers.(, ( - The maximum number of input data objects that should be labeled.(amazonka-sagemakerThe maximum number of objects that can be labeled by human workers.(amazonka-sagemakerThe maximum number of input data objects that should be labeled.(((((((((((((((c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; k)amazonka-sagemaker2Provides summary information about a labeling job.See: ) smart constructor.)amazonka-sagemakerThe Amazon Resource Name (ARN) of the Lambda function used to consolidate the annotations from individual workers into a label for a data object. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-annotation-consolidation.htmlAnnotation Consolidation.)amazonka-sagemakerIf the LabelingJobStatus field is Failed2, this field contains a description of the error.)amazonka-sagemaker)Input configuration for the labeling job.)amazonka-sagemaker8The location of the output produced by the labeling job.)amazonka-sagemakerThe name of the labeling job.)amazonka-sagemakerThe Amazon Resource Name (ARN) assigned to the labeling job when it was created.)amazonka-sagemaker7The date and time that the job was created (timestamp).)amazonka-sagemaker=The date and time that the job was last modified (timestamp).)amazonka-sagemaker'The current status of the labeling job.)amazonka-sagemaker0Counts showing the progress of the labeling job.)amazonka-sagemakerThe Amazon Resource Name (ARN) of the work team assigned to the job.)amazonka-sagemakerThe Amazon Resource Name (ARN) of a Lambda function. The function is run before each data object is sent to a worker.)amazonka-sagemakerCreate a value of )" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:), ) - The Amazon Resource Name (ARN) of the Lambda function used to consolidate the annotations from individual workers into a label for a data object. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-annotation-consolidation.htmlAnnotation Consolidation.), ) - If the LabelingJobStatus field is Failed2, this field contains a description of the error.), ), - Input configuration for the labeling job.), ); - The location of the output produced by the labeling job.), ) - The name of the labeling job.), ) - The Amazon Resource Name (ARN) assigned to the labeling job when it was created.), ): - The date and time that the job was created (timestamp).), ) - The date and time that the job was last modified (timestamp).), )* - The current status of the labeling job.), )3 - Counts showing the progress of the labeling job.), ) - The Amazon Resource Name (ARN) of the work team assigned to the job.), ) - The Amazon Resource Name (ARN) of a Lambda function. The function is run before each data object is sent to a worker.)amazonka-sagemakerThe Amazon Resource Name (ARN) of the Lambda function used to consolidate the annotations from individual workers into a label for a data object. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-annotation-consolidation.htmlAnnotation Consolidation.)amazonka-sagemakerIf the LabelingJobStatus field is Failed2, this field contains a description of the error.)amazonka-sagemaker)Input configuration for the labeling job.)amazonka-sagemaker8The location of the output produced by the labeling job.)amazonka-sagemakerThe name of the labeling job.)amazonka-sagemakerThe Amazon Resource Name (ARN) assigned to the labeling job when it was created.)amazonka-sagemaker7The date and time that the job was created (timestamp).)amazonka-sagemaker=The date and time that the job was last modified (timestamp).)amazonka-sagemaker'The current status of the labeling job.)amazonka-sagemaker0Counts showing the progress of the labeling job.)amazonka-sagemakerThe Amazon Resource Name (ARN) of the work team assigned to the job.)amazonka-sagemakerThe Amazon Resource Name (ARN) of a Lambda function. The function is run before each data object is sent to a worker.)amazonka-sagemaker)amazonka-sagemaker)amazonka-sagemaker)amazonka-sagemaker)amazonka-sagemaker)amazonka-sagemaker)amazonka-sagemaker)amazonka-sagemaker)))))))))))))))))))))))))))))))))))))))))))))))))))))))(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? |)))))) )))))))))(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; i)amazonka-sagemaker9A value that indicates whether the update was successful.See: ) smart constructor.)amazonka-sagemakerIf the update wasn't successful, indicates the reason why it failed.)amazonka-sagemaker>A value that indicates whether the update was made successful.)amazonka-sagemakerCreate a value of )" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:), ) - If the update wasn't successful, indicates the reason why it failed.), ) - A value that indicates whether the update was made successful.)amazonka-sagemakerIf the update wasn't successful, indicates the reason why it failed.)amazonka-sagemaker>A value that indicates whether the update was made successful.)amazonka-sagemaker)))))))))))))))(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; )amazonka-sagemakerLists a summary of the properties of a lineage group. A lineage group provides a group of shareable lineage entity resources.See: ) smart constructor.)amazonka-sagemaker/The creation time of the lineage group summary.)amazonka-sagemaker.The display name of the lineage group summary.)amazonka-sagemaker4The last modified time of the lineage group summary.)amazonka-sagemaker=The Amazon Resource Name (ARN) of the lineage group resource.)amazonka-sagemakerThe inference specification name in the model package version.0amazonka-sagemakerCreate a value of 0" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:0, 0 - Defines the environment parameters that includes key, value types, and values.0, 0 - The inference specification name in the model package version.0amazonka-sagemakerDefines the environment parameters that includes key, value types, and values.0amazonka-sagemaker>The inference specification name in the model package version.00000000000000(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; W 0amazonka-sagemakerAn endpoint that hosts a model displayed in the Amazon SageMaker Model Dashboard.See: 0 smart constructor.0amazonka-sagemakerThe endpoint name.0amazonka-sagemaker/The Amazon Resource Name (ARN) of the endpoint.0amazonka-sagemaker9A timestamp that indicates when the endpoint was created.0amazonka-sagemaker(The last time the endpoint was modified.0amazonka-sagemakerThe endpoint status.0amazonka-sagemakerCreate a value of 0" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:0, 0 - The endpoint name.0, 02 - The Amazon Resource Name (ARN) of the endpoint.0, 0< - A timestamp that indicates when the endpoint was created.0, 0+ - The last time the endpoint was modified.0, 0 - The endpoint status.0amazonka-sagemakerThe endpoint name.0amazonka-sagemaker/The Amazon Resource Name (ARN) of the endpoint.0amazonka-sagemaker9A timestamp that indicates when the endpoint was created.0amazonka-sagemaker(The last time the endpoint was modified.0amazonka-sagemakerThe endpoint status.0amazonka-sagemaker0amazonka-sagemaker0amazonka-sagemaker0amazonka-sagemaker0amazonka-sagemaker0 0000000000000 0000000000000(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; [0amazonka-sagemakerAn alert action taken to light up an icon on the Amazon SageMaker Model Dashboard when an alert goes into InAlert status.See: 0 smart constructor.0amazonka-sagemaker0Indicates whether the alert action is turned on.0amazonka-sagemakerCreate a value of 0" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:0, 03 - Indicates whether the alert action is turned on.0amazonka-sagemaker0Indicates whether the alert action is turned on.0000000000(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; _0amazonka-sagemaker4Data quality constraints and statistics for a model.See: 0 smart constructor.0amazonka-sagemaker%Data quality constraints for a model.0amazonka-sagemaker$Data quality statistics for a model.0amazonka-sagemakerCreate a value of 0" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:0, 0( - Data quality constraints for a model.0, 0' - Data quality statistics for a model.0amazonka-sagemaker%Data quality constraints for a model.0amazonka-sagemaker$Data quality statistics for a model.00000000000000(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; j0amazonka-sagemakerSpecifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.See: 0 smart constructor.0amazonka-sagemakerSet to True to automatically generate an endpoint name for a one-click Autopilot model deployment; set to False" otherwise. The default value is False. If you set AutoGenerateEndpointName to True, do not specify the  EndpointName"; otherwise a 400 error is thrown.0amazonka-sagemakerSpecifies the endpoint name to use for a one-click Autopilot model deployment if the endpoint name is not generated automatically. Specify the  EndpointName if and only if you set AutoGenerateEndpointName to False"; otherwise a 400 error is thrown.0amazonka-sagemakerCreate a value of 0" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:0, 0 - Set to True to automatically generate an endpoint name for a one-click Autopilot model deployment; set to False" otherwise. The default value is False. If you set AutoGenerateEndpointName to True, do not specify the  EndpointName"; otherwise a 400 error is thrown.0, 0 - Specifies the endpoint name to use for a one-click Autopilot model deployment if the endpoint name is not generated automatically. Specify the  EndpointName if and only if you set AutoGenerateEndpointName to False"; otherwise a 400 error is thrown.0amazonka-sagemakerSet to True to automatically generate an endpoint name for a one-click Autopilot model deployment; set to False" otherwise. The default value is False. If you set AutoGenerateEndpointName to True, do not specify the  EndpointName"; otherwise a 400 error is thrown.0amazonka-sagemakerSpecifies the endpoint name to use for a one-click Autopilot model deployment if the endpoint name is not generated automatically. Specify the  EndpointName if and only if you set AutoGenerateEndpointName to False"; otherwise a 400 error is thrown.00000000000000(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; n1amazonka-sagemakerProvides information about the endpoint of the model deployment.See: 1 smart constructor.1amazonka-sagemaker>The name of the endpoint to which the model has been deployed.If model deployment fails, this field is omitted from the response.1amazonka-sagemakerCreate a value of 1" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:1, 1 - The name of the endpoint to which the model has been deployed.If model deployment fails, this field is omitted from the response.1amazonka-sagemaker>The name of the endpoint to which the model has been deployed.If model deployment fails, this field is omitted from the response.1111111111(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; r1amazonka-sagemakerProvides information to verify the integrity of stored model artifacts.See: 1 smart constructor.1amazonka-sagemakerProvides a hash value that uniquely identifies the stored model artifacts.1amazonka-sagemakerCreate a value of 1" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:1, 1 - Provides a hash value that uniquely identifies the stored model artifacts.1amazonka-sagemakerProvides a hash value that uniquely identifies the stored model artifacts.1111111111(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; {1amazonka-sagemakerDocker container image configuration object for the model explainability job.See: 1 smart constructor.1amazonka-sagemaker7Sets the environment variables in the Docker container.1amazonka-sagemaker>The container image to be run by the model explainability job.1amazonka-sagemakerJSON formatted S3 file that defines explainability parameters. For more information on this JSON configuration file, see  https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-config-json-monitor-model-explainability-parameters.html)Configure model explainability parameters.1amazonka-sagemakerCreate a value of 1" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:1, 1: - Sets the environment variables in the Docker container.1, 1 - The container image to be run by the model explainability job.1, 1 - JSON formatted S3 file that defines explainability parameters. For more information on this JSON configuration file, see  https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-config-json-monitor-model-explainability-parameters.html)Configure model explainability parameters.1amazonka-sagemaker7Sets the environment variables in the Docker container.1amazonka-sagemaker>The container image to be run by the model explainability job.1amazonka-sagemakerJSON formatted S3 file that defines explainability parameters. For more information on this JSON configuration file, see  https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-config-json-monitor-model-explainability-parameters.html)Configure model explainability parameters.1amazonka-sagemaker1amazonka-sagemaker1 111111111 111111111(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? {111111111(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; [1amazonka-sagemakerInput object for the model.See: 1 smart constructor.1amazonka-sagemaker-The input configuration object for the model.1amazonka-sagemakerCreate a value of 1" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:1, 10 - The input configuration object for the model.1amazonka-sagemaker-The input configuration object for the model.1amazonka-sagemaker11111111111(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; 1amazonka-sagemakerThe model latency threshold.See: 1 smart constructor.1amazonka-sagemaker'The model latency percentile threshold.1amazonka-sagemaker3The model latency percentile value in milliseconds.1amazonka-sagemakerCreate a value of 1" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:1, 1* - The model latency percentile threshold.1, 16 - The model latency percentile value in milliseconds.1amazonka-sagemaker'The model latency percentile threshold.1amazonka-sagemaker3The model latency percentile value in milliseconds.11111111111111(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? H1111111 11111111111(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; 1amazonka-sagemakerPart of the search expression. You can specify the name and value (domain, task, framework, framework version, task, and model).See: 2 smart constructor.1amazonka-sagemaker*The name of the of the model to filter by.2amazonka-sagemaker'The value to filter the model metadata.2amazonka-sagemakerCreate a value of 1" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:1, 2- - The name of the of the model to filter by.2, 2* - The value to filter the model metadata.2amazonka-sagemaker*The name of the of the model to filter by.2amazonka-sagemaker'The value to filter the model metadata.2amazonka-sagemaker1amazonka-sagemaker211212221121222(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; 2amazonka-sagemakerOne or more filters that searches for the specified resource or resources in a search. All resource objects that satisfy the expression's condition are included in the search resultsSee: 2 smart constructor.2amazonka-sagemakerA list of filter objects.2amazonka-sagemakerCreate a value of 2" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:2, 2 - A list of filter objects.2amazonka-sagemakerA list of filter objects.2222222222(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; u 2amazonka-sagemaker A summary of the model metadata.See: 2 smart constructor.2amazonka-sagemaker)The machine learning domain of the model.2amazonka-sagemaker,The machine learning framework of the model.2amazonka-sagemaker'The machine learning task of the model.2amazonka-sagemakerThe name of the model.2amazonka-sagemaker#The framework version of the model.2amazonka-sagemakerCreate a value of 2" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:2, 2, - The machine learning domain of the model.2, 2/ - The machine learning framework of the model.2, 2* - The machine learning task of the model.2, 2 - The name of the model.2, 2& - The framework version of the model.2amazonka-sagemaker)The machine learning domain of the model.2amazonka-sagemaker,The machine learning framework of the model.2amazonka-sagemaker'The machine learning task of the model.2amazonka-sagemakerThe name of the model.2amazonka-sagemaker#The framework version of the model.2amazonka-sagemaker2amazonka-sagemaker2amazonka-sagemaker2amazonka-sagemaker2amazonka-sagemaker2 2222222222222 2222222222222(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; 2amazonka-sagemaker5Describes the Docker container for the model package.See: 2 smart constructor.2amazonka-sagemaker+The DNS host name for the Docker container.2amazonka-sagemakerThe environment variables to set in the Docker container. Each key and value in the  Environment string to string map can have length of up to 1024. We support up to 16 entries in the map.2amazonka-sagemakerThe machine learning framework of the model package container image.2amazonka-sagemaker;The framework version of the Model Package Container Image.2amazonka-sagemakerAn MD5 hash of the training algorithm that identifies the Docker image used for training.2amazonka-sagemakerThe Amazon S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).The model artifacts must be in an S3 bucket that is in the same region as the model package.2amazonka-sagemaker%A structure with Model Input details.2amazonka-sagemakerThe name of a pre-trained machine learning benchmarked by Amazon SageMaker Inference Recommender model that matches your model. You can find a list of benchmarked models by calling ListModelMetadata.2amazonka-sagemakerThe Amazon Web Services Marketplace product ID of the model package.2amazonka-sagemakerThe Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored.If you are using your own custom algorithm instead of an algorithm provided by SageMaker, the inference code must meet SageMaker requirements. SageMaker supports both registry/repository[:tag] and registry/repository[@digest]1 image path formats. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms.html/Using Your Own Algorithms with Amazon SageMaker.2amazonka-sagemakerCreate a value of 2" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:2, 2. - The DNS host name for the Docker container.2, 2 - The environment variables to set in the Docker container. Each key and value in the  Environment string to string map can have length of up to 1024. We support up to 16 entries in the map.2, 2 - The machine learning framework of the model package container image.2, 2> - The framework version of the Model Package Container Image.2, 2 - An MD5 hash of the training algorithm that identifies the Docker image used for training.2, 2 - The Amazon S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).The model artifacts must be in an S3 bucket that is in the same region as the model package.2, 2( - A structure with Model Input details.2, 2 - The name of a pre-trained machine learning benchmarked by Amazon SageMaker Inference Recommender model that matches your model. You can find a list of benchmarked models by calling ListModelMetadata.2, 2 - The Amazon Web Services Marketplace product ID of the model package.2, 2 - The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored.If you are using your own custom algorithm instead of an algorithm provided by SageMaker, the inference code must meet SageMaker requirements. SageMaker supports both registry/repository[:tag] and registry/repository[@digest]1 image path formats. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms.html/Using Your Own Algorithms with Amazon SageMaker.2amazonka-sagemaker+The DNS host name for the Docker container.2amazonka-sagemakerThe environment variables to set in the Docker container. Each key and value in the  Environment string to string map can have length of up to 1024. We support up to 16 entries in the map.2amazonka-sagemakerThe machine learning framework of the model package container image.2amazonka-sagemaker;The framework version of the Model Package Container Image.2amazonka-sagemakerAn MD5 hash of the training algorithm that identifies the Docker image used for training.2amazonka-sagemakerThe Amazon S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).The model artifacts must be in an S3 bucket that is in the same region as the model package.2amazonka-sagemaker%A structure with Model Input details.2amazonka-sagemakerThe name of a pre-trained machine learning benchmarked by Amazon SageMaker Inference Recommender model that matches your model. You can find a list of benchmarked models by calling ListModelMetadata.2amazonka-sagemakerThe Amazon Web Services Marketplace product ID of the model package.2amazonka-sagemakerThe Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored.If you are using your own custom algorithm instead of an algorithm provided by SageMaker, the inference code must meet SageMaker requirements. SageMaker supports both registry/repository[:tag] and registry/repository[@digest]1 image path formats. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms.html/Using Your Own Algorithms with Amazon SageMaker.2amazonka-sagemaker22222222222222222222222222222222222222222222222(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? 222222222222(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? U 222222222222222222222222(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; 2amazonka-sagemaker(Summary information about a model group.See: 3 smart constructor.3amazonka-sagemaker!A description of the model group.3amazonka-sagemakerThe name of the model group.3amazonka-sagemaker2The Amazon Resource Name (ARN) of the model group.3amazonka-sagemaker*The time that the model group was created.3amazonka-sagemakerThe status of the model group.3amazonka-sagemakerCreate a value of 2" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:3, 3$ - A description of the model group.3, 3 - The name of the model group.3, 35 - The Amazon Resource Name (ARN) of the model group.3, 3- - The time that the model group was created.3, 3! - The status of the model group.3amazonka-sagemaker!A description of the model group.3amazonka-sagemakerThe name of the model group.3amazonka-sagemaker2The Amazon Resource Name (ARN) of the model group.3amazonka-sagemaker*The time that the model group was created.3amazonka-sagemakerThe status of the model group.3amazonka-sagemaker3amazonka-sagemaker3amazonka-sagemaker3amazonka-sagemaker3 2333332333333 2333332333333(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? 333333333333(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? 33333333 3333333333333(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; ^3amazonka-sagemaker1Represents the overall status of a model package.See: 3 smart constructor.3amazonka-sagemakerif the overall status is Failed, the reason for the failure.3amazonka-sagemakerThe name of the model package for which the overall status is being reported.3amazonka-sagemakerThe current status.3amazonka-sagemakerCreate a value of 3" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:3, 3 - if the overall status is Failed, the reason for the failure.3, 3 - The name of the model package for which the overall status is being reported.3, 3 - The current status.3amazonka-sagemakerif the overall status is Failed, the reason for the failure.3amazonka-sagemakerThe name of the model package for which the overall status is being reported.3amazonka-sagemakerThe current status.3amazonka-sagemaker3amazonka-sagemaker3 333333333 333333333(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; 3amazonka-sagemakerSpecifies the validation and image scan statuses of the model package.See: 3 smart constructor.3amazonka-sagemakerThe status of the scan of the Docker image container for the model package.3amazonka-sagemaker+The validation status of the model package.3amazonka-sagemakerCreate a value of 3" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:3, 3 - The status of the scan of the Docker image container for the model package.3, 3. - The validation status of the model package.3amazonka-sagemakerThe status of the scan of the Docker image container for the model package.3amazonka-sagemaker+The validation status of the model package.33333333333333(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; 3amazonka-sagemaker3Provides summary information about a model package.See: 3 smart constructor.3amazonka-sagemakerThe approval status of the model. This can be one of the following values.APPROVED - The model is approvedREJECTED - The model is rejected.PENDING_MANUAL_APPROVAL1 - The model is waiting for manual approval.3amazonka-sagemaker)A brief description of the model package.3amazonka-sagemakerIf the model package is a versioned model, the model group that the versioned model belongs to.3amazonka-sagemakerIf the model package is a versioned model, the version of the model.3amazonka-sagemakerThe name of the model package.3amazonka-sagemaker4The Amazon Resource Name (ARN) of the model package.3amazonka-sagemaker:A timestamp that shows when the model package was created.3amazonka-sagemaker(The overall status of the model package.3amazonka-sagemakerCreate a value of 3" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:3, 3 - The approval status of the model. This can be one of the following values.APPROVED - The model is approvedREJECTED - The model is rejected.PENDING_MANUAL_APPROVAL1 - The model is waiting for manual approval.3, 3, - A brief description of the model package.3, 3 - If the model package is a versioned model, the model group that the versioned model belongs to.3, 3 - If the model package is a versioned model, the version of the model.3, 3! - The name of the model package.3, 37 - The Amazon Resource Name (ARN) of the model package.3, 3= - A timestamp that shows when the model package was created.3, 3+ - The overall status of the model package.3amazonka-sagemakerThe approval status of the model. This can be one of the following values.APPROVED - The model is approvedREJECTED - The model is rejected.PENDING_MANUAL_APPROVAL1 - The model is waiting for manual approval.3amazonka-sagemaker)A brief description of the model package.3amazonka-sagemakerIf the model package is a versioned model, the model group that the versioned model belongs to.3amazonka-sagemakerIf the model package is a versioned model, the version of the model.3amazonka-sagemakerThe name of the model package.3amazonka-sagemaker4The Amazon Resource Name (ARN) of the model package.3amazonka-sagemaker:A timestamp that shows when the model package was created.3amazonka-sagemaker(The overall status of the model package.3amazonka-sagemaker3amazonka-sagemaker3amazonka-sagemaker3amazonka-sagemaker333333333333333333333333333333333333333(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? 344433 344433444(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; і4amazonka-sagemaker)Model quality statistics and constraints.See: 4 smart constructor.4amazonka-sagemakerModel quality constraints.4amazonka-sagemakerModel quality statistics.4amazonka-sagemakerCreate a value of 4" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:4, 4 - Model quality constraints.4, 4 - Model quality statistics.4amazonka-sagemakerModel quality constraints.4amazonka-sagemakerModel quality statistics.44444444444444(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; r 4amazonka-sagemaker'Contains metrics captured from a model.See: 4 smart constructor.4amazonka-sagemaker%Metrics that measure bais in a model.4amazonka-sagemaker"Metrics that help explain a model.4amazonka-sagemaker?Metrics that measure the quality of the input data for a model.4amazonka-sagemaker,Metrics that measure the quality of a model.4amazonka-sagemakerCreate a value of 4" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:4, 4( - Metrics that measure bais in a model.4, 4% - Metrics that help explain a model.4, 4 - Metrics that measure the quality of the input data for a model.4, 4/ - Metrics that measure the quality of a model.4amazonka-sagemaker%Metrics that measure bais in a model.4amazonka-sagemaker"Metrics that help explain a model.4amazonka-sagemaker?Metrics that measure the quality of the input data for a model.4amazonka-sagemaker,Metrics that measure the quality of a model. 44444444444 44444444444(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? C444444444444(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; ۴4amazonka-sagemakerMetadata for Model steps.See: 4 smart constructor.4amazonka-sagemaker4The Amazon Resource Name (ARN) of the created model.4amazonka-sagemakerCreate a value of 4" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:4, 47 - The Amazon Resource Name (ARN) of the created model.4amazonka-sagemaker4The Amazon Resource Name (ARN) of the created model.4444444444(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; ;4amazonka-sagemaker+Provides summary information about a model.See: 4 smart constructor.4amazonka-sagemaker2The name of the model that you want a summary for.4amazonka-sagemaker,The Amazon Resource Name (ARN) of the model.4amazonka-sagemaker6A timestamp that indicates when the model was created.4amazonka-sagemakerCreate a value of 4" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:4, 45 - The name of the model that you want a summary for.4, 4/ - The Amazon Resource Name (ARN) of the model.4, 49 - A timestamp that indicates when the model was created.4amazonka-sagemaker2The name of the model that you want a summary for.4amazonka-sagemaker,The Amazon Resource Name (ARN) of the model.4amazonka-sagemaker6A timestamp that indicates when the model was created.4amazonka-sagemaker4amazonka-sagemaker4amazonka-sagemaker4 444444444 444444444(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? 444444 444444444(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? 55555555 5555555555555(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; A5amazonka-sagemakerA list of alert actions taken in response to an alert going into InAlert status.See: 5 smart constructor.5amazonka-sagemakerAn alert action taken to light up an icon on the Model Dashboard when an alert goes into InAlert status.5amazonka-sagemakerCreate a value of 5" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:5, 5 - An alert action taken to light up an icon on the Model Dashboard when an alert goes into InAlert status.5amazonka-sagemakerAn alert action taken to light up an icon on the Model Dashboard when an alert goes into InAlert status.5555555555(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? 555555555555(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? 555555555555(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; q 5amazonka-sagemaker3Provides summary information of an alert's history.See: 5 smart constructor.5amazonka-sagemaker"The name of a monitoring schedule.5amazonka-sagemakerThe name of a monitoring alert.5amazonka-sagemakerA timestamp that indicates when the first alert transition occurred in an alert history. An alert transition can be from status InAlert to OK , or from OK to InAlert.5amazonka-sagemaker%The current alert status of an alert.5amazonka-sagemakerCreate a value of 5" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:5, 5% - The name of a monitoring schedule.5, 5" - The name of a monitoring alert.5, 5 - A timestamp that indicates when the first alert transition occurred in an alert history. An alert transition can be from status InAlert to OK , or from OK to InAlert.5, 5( - The current alert status of an alert.5amazonka-sagemaker"The name of a monitoring schedule.5amazonka-sagemakerThe name of a monitoring alert.5amazonka-sagemakerA timestamp that indicates when the first alert transition occurred in an alert history. An alert transition can be from status InAlert to OK , or from OK to InAlert.5amazonka-sagemaker%The current alert status of an alert.5amazonka-sagemaker5amazonka-sagemaker5amazonka-sagemaker5amazonka-sagemaker5 55555555555 55555555555(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; 35amazonka-sagemaker3Provides summary information about a monitor alert.See: 5 smart constructor.5amazonka-sagemakerThe name of a monitoring alert.5amazonka-sagemakerThe Amazon Resource Name (ARN) of the lifecycle configuration.:amazonka-sagemakerCreate a value of :" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility::, : - A timestamp that tells when the lifecycle configuration was created.:, : - A timestamp that tells when the lifecycle configuration was last modified.:, :+ - The name of the lifecycle configuration.:, : - The Amazon Resource Name (ARN) of the lifecycle configuration.:amazonka-sagemakerA timestamp that tells when the lifecycle configuration was created.:amazonka-sagemakerA timestamp that tells when the lifecycle configuration was last modified.:amazonka-sagemaker(The name of the lifecycle configuration.:amazonka-sagemaker>The Amazon Resource Name (ARN) of the lifecycle configuration.:amazonka-sagemaker:amazonka-sagemaker: ::::::::::: :::::::::::(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; :amazonka-sagemaker>Contains the notebook instance lifecycle configuration script.Each lifecycle configuration script has a limit of 16384 characters.The value of the $PATH< environment variable that is available to both scripts is /sbin:bin:/usr/sbin:/usr/bin.View CloudWatch Logs for notebook instance lifecycle configurations in log group  /aws/sagemaker/NotebookInstances in log stream .[notebook-instance-name]/[LifecycleConfigHook].Lifecycle configuration scripts cannot run for longer than 5 minutes. If a script runs for longer than 5 minutes, it fails and the notebook instance is not created or started.For information about notebook instance lifestyle configurations, see  https://docs.aws.amazon.com/sagemaker/latest/dg/notebook-lifecycle-config.html2Step 2.1: (Optional) Customize a Notebook Instance.See: : smart constructor.:amazonka-sagemakerA base64-encoded string that contains a shell script for a notebook instance lifecycle configuration.:amazonka-sagemakerCreate a value of :" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility::, : - A base64-encoded string that contains a shell script for a notebook instance lifecycle configuration.:amazonka-sagemakerA base64-encoded string that contains a shell script for a notebook instance lifecycle configuration.::::::::::(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? :::::: :::::::::(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? c::::::::::::(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? :::::::::::::::::::::::::::(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; q:amazonka-sagemakerProvides summary information for an SageMaker notebook instance.See: : smart constructor.:amazonka-sagemakerAn array of up to three Git repositories associated with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in  https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.htmlAmazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html>Associating Git Repositories with SageMaker Notebook Instances.:amazonka-sagemaker>A timestamp that shows when the notebook instance was created.:amazonka-sagemakerThe Git repository associated with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in  https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.htmlAmazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html>Associating Git Repositories with SageMaker Notebook Instances.:amazonka-sagemakerThe type of ML compute instance that the notebook instance is running on.:amazonka-sagemakerA timestamp that shows when the notebook instance was last modified.:amazonka-sagemakerThe name of a notebook instance lifecycle configuration associated with this notebook instance.For information about notebook instance lifestyle configurations, see  https://docs.aws.amazon.com/sagemaker/latest/dg/notebook-lifecycle-config.html2Step 2.1: (Optional) Customize a Notebook Instance.:amazonka-sagemaker$The status of the notebook instance.:amazonka-sagemakerThe URL that you use to connect to the Jupyter notebook running in your notebook instance.:amazonka-sagemaker>The name of the notebook instance that you want a summary for.:amazonka-sagemaker8The Amazon Resource Name (ARN) of the notebook instance.:amazonka-sagemakerCreate a value of :" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility::, : - An array of up to three Git repositories associated with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in  https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.htmlAmazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html>Associating Git Repositories with SageMaker Notebook Instances.:, : - A timestamp that shows when the notebook instance was created.:, : - The Git repository associated with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in  https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.htmlAmazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html>Associating Git Repositories with SageMaker Notebook Instances.:, ; - The type of ML compute instance that the notebook instance is running on.:, ; - A timestamp that shows when the notebook instance was last modified.:, ; - The name of a notebook instance lifecycle configuration associated with this notebook instance.For information about notebook instance lifestyle configurations, see  https://docs.aws.amazon.com/sagemaker/latest/dg/notebook-lifecycle-config.html2Step 2.1: (Optional) Customize a Notebook Instance.:, ;' - The status of the notebook instance.:, ; - The URL that you use to connect to the Jupyter notebook running in your notebook instance.:, ; - The name of the notebook instance that you want a summary for.:, ;; - The Amazon Resource Name (ARN) of the notebook instance.:amazonka-sagemakerAn array of up to three Git repositories associated with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in  https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.htmlAmazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html>Associating Git Repositories with SageMaker Notebook Instances.:amazonka-sagemaker>A timestamp that shows when the notebook instance was created.:amazonka-sagemakerThe Git repository associated with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in  https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.htmlAmazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html>Associating Git Repositories with SageMaker Notebook Instances.;amazonka-sagemakerThe type of ML compute instance that the notebook instance is running on.;amazonka-sagemakerA timestamp that shows when the notebook instance was last modified.;amazonka-sagemakerThe name of a notebook instance lifecycle configuration associated with this notebook instance.For information about notebook instance lifestyle configurations, see  https://docs.aws.amazon.com/sagemaker/latest/dg/notebook-lifecycle-config.html2Step 2.1: (Optional) Customize a Notebook Instance.;amazonka-sagemaker$The status of the notebook instance.;amazonka-sagemakerThe URL that you use to connect to the Jupyter notebook running in your notebook instance.;amazonka-sagemaker>The name of the notebook instance that you want a summary for.;amazonka-sagemaker8The Amazon Resource Name (ARN) of the notebook instance.:amazonka-sagemaker:amazonka-sagemaker:::::::::::::::::;;;;;;;::::::::::::::::;;;;;;;(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? r;;;;;;;;;;;;(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; q;amazonka-sagemakerConfigures Amazon SNS notifications of available or expiring work items for work teams.See: ; smart constructor.;amazonka-sagemakerThe ARN for the Amazon SNS topic to which notifications should be published.;amazonka-sagemakerCreate a value of ;" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:;, ; - The ARN for the Amazon SNS topic to which notifications should be published.;amazonka-sagemakerThe ARN for the Amazon SNS topic to which notifications should be published.;;;;;;;;;;(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? *;;;;;; ;;;;;;;;;(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; );amazonka-sagemakerInformation about a candidate produced by an AutoML training job, including its status, steps, and other properties.See: ; smart constructor.;amazonka-sagemaker*The properties of an AutoML candidate job.;amazonka-sagemaker The end time.;amazonka-sagemakerThe failure reason.;amazonka-sagemaker6Information about the inference container definitions.;amazonka-sagemakerThe name of the candidate.;amazonka-sagemakerThe objective's status.;amazonka-sagemaker(Information about the candidate's steps.;amazonka-sagemakerThe candidate's status.;amazonka-sagemakerThe creation time.;amazonka-sagemakerThe last modified time.;amazonka-sagemakerCreate a value of ;" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:;, ;- - The properties of an AutoML candidate job.;, ; - The end time.;, ; - The failure reason.;, ; - Undocumented member.;, ;9 - Information about the inference container definitions.;, ; - The name of the candidate.;, ; - The objective's status.;, ;+ - Information about the candidate's steps.;, ; - The candidate's status.;, ; - The creation time.;, ; - The last modified time.;amazonka-sagemaker*The properties of an AutoML candidate job.;amazonka-sagemaker The end time.;amazonka-sagemakerThe failure reason.;amazonka-sagemakerUndocumented member.;amazonka-sagemaker6Information about the inference container definitions.;amazonka-sagemakerThe name of the candidate.;amazonka-sagemakerThe objective's status.;amazonka-sagemaker(Information about the candidate's steps.;amazonka-sagemakerThe candidate's status.;amazonka-sagemakerThe creation time.;amazonka-sagemakerThe last modified time.;amazonka-sagemaker;amazonka-sagemaker;amazonka-sagemaker;amazonka-sagemaker;amazonka-sagemaker;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; ;amazonka-sagemakerSpecifies the number of training jobs that this hyperparameter tuning job launched, categorized by the status of their objective metric. The objective metric status shows whether the final objective metric for the training job has been evaluated by the tuning job and used in the hyperparameter tuning process.See: ; smart constructor.;amazonka-sagemakerThe number of training jobs whose final objective metric was not evaluated and used in the hyperparameter tuning process. This typically occurs when the training job failed or did not emit an objective metric.;amazonka-sagemakerThe number of training jobs that are in progress and pending evaluation of their final objective metric.;amazonka-sagemakerThe number of training jobs whose final objective metric was evaluated by the hyperparameter tuning job and used in the hyperparameter tuning process.;amazonka-sagemakerCreate a value of ;" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:;, ; - The number of training jobs whose final objective metric was not evaluated and used in the hyperparameter tuning process. This typically occurs when the training job failed or did not emit an objective metric.;, ; - The number of training jobs that are in progress and pending evaluation of their final objective metric.;, ; - The number of training jobs whose final objective metric was evaluated by the hyperparameter tuning job and used in the hyperparameter tuning process.;amazonka-sagemakerThe number of training jobs whose final objective metric was not evaluated and used in the hyperparameter tuning process. This typically occurs when the training job failed or did not emit an objective metric.;amazonka-sagemakerThe number of training jobs that are in progress and pending evaluation of their final objective metric.;amazonka-sagemakerThe number of training jobs whose final objective metric was evaluated by the hyperparameter tuning job and used in the hyperparameter tuning process. ;;;;;;;;; ;;;;;;;;;(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? N;<<;;; ;<<;;;<<;(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; <amazonka-sagemakerThe status of  OfflineStore.See: < smart constructor.<amazonka-sagemakerThe justification for why the OfflineStoreStatus is Blocked (if applicable).<amazonka-sagemakerAn  OfflineStore status.<amazonka-sagemakerCreate a value of <" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:<, < - The justification for why the OfflineStoreStatus is Blocked (if applicable).<, < - An  OfflineStore status.<amazonka-sagemakerThe justification for why the OfflineStoreStatus is Blocked (if applicable).<amazonka-sagemakerAn  OfflineStore status.<amazonka-sagemaker<<<<<<<<<<<<<<<(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; <amazonka-sagemakerThe name, Arn,  CreationTime,  FeatureGroup values, LastUpdatedTime and EnableOnlineStorage status of a  FeatureGroup.See: < smart constructor.<amazonka-sagemakerThe status of a FeatureGroup. The status can be any of the following: Creating, Created,  CreateFail, Deleting or  DetailFail.<amazonka-sagemaker*Notifies you if replicating data into the  OfflineStore has failed. Returns either: Active or Blocked.<amazonka-sagemaker The name of  FeatureGroup.<amazonka-sagemakerUnique identifier for the  FeatureGroup.<amazonka-sagemaker8A timestamp indicating the time of creation time of the  FeatureGroup.<amazonka-sagemakerCreate a value of <" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:<, < - The status of a FeatureGroup. The status can be any of the following: Creating, Created,  CreateFail, Deleting or  DetailFail.<, <- - Notifies you if replicating data into the  OfflineStore has failed. Returns either: Active or Blocked.<, < - The name of  FeatureGroup.<, < - Unique identifier for the  FeatureGroup.<, <; - A timestamp indicating the time of creation time of the  FeatureGroup.<amazonka-sagemakerThe status of a FeatureGroup. The status can be any of the following: Creating, Created,  CreateFail, Deleting or  DetailFail.<amazonka-sagemaker*Notifies you if replicating data into the  OfflineStore has failed. Returns either: Active or Blocked.<amazonka-sagemaker The name of  FeatureGroup.<amazonka-sagemakerUnique identifier for the  FeatureGroup.<amazonka-sagemaker8A timestamp indicating the time of creation time of the  FeatureGroup.<amazonka-sagemaker<amazonka-sagemaker<amazonka-sagemaker< <<<<<<<<<<<<< <<<<<<<<<<<<<(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; ڟ<amazonka-sagemakerUse this parameter to configure your OIDC Identity Provider (IdP).See: < smart constructor.<amazonka-sagemakerThe OIDC IdP client ID used to configure your private workforce.<amazonka-sagemakerThe OIDC IdP client secret used to configure your private workforce.<amazonka-sagemaker=The OIDC IdP issuer used to configure your private workforce.<amazonka-sagemakerThe OIDC IdP authorization endpoint used to configure your private workforce.<amazonka-sagemakerThe OIDC IdP token endpoint used to configure your private workforce.<amazonka-sagemakerThe OIDC IdP user information endpoint used to configure your private workforce.<amazonka-sagemakerThe OIDC IdP logout endpoint used to configure your private workforce.<amazonka-sagemakerThe OIDC IdP JSON Web Key Set (Jwks) URI used to configure your private workforce.<amazonka-sagemakerCreate a value of <" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:<, < - The OIDC IdP client ID used to configure your private workforce.<, < - The OIDC IdP client secret used to configure your private workforce.<, < - The OIDC IdP issuer used to configure your private workforce.<, < - The OIDC IdP authorization endpoint used to configure your private workforce.<, < - The OIDC IdP token endpoint used to configure your private workforce.<, < - The OIDC IdP user information endpoint used to configure your private workforce.<, < - The OIDC IdP logout endpoint used to configure your private workforce.<, < - The OIDC IdP JSON Web Key Set (Jwks) URI used to configure your private workforce.<amazonka-sagemakerThe OIDC IdP client ID used to configure your private workforce.<amazonka-sagemakerThe OIDC IdP client secret used to configure your private workforce.<amazonka-sagemaker=The OIDC IdP issuer used to configure your private workforce.<amazonka-sagemakerThe OIDC IdP authorization endpoint used to configure your private workforce.<amazonka-sagemakerThe OIDC IdP token endpoint used to configure your private workforce.<amazonka-sagemakerThe OIDC IdP user information endpoint used to configure your private workforce.<amazonka-sagemakerThe OIDC IdP logout endpoint used to configure your private workforce.<amazonka-sagemakerThe OIDC IdP JSON Web Key Set (Jwks) URI used to configure your private workforce.<amazonka-sagemaker<amazonka-sagemaker<amazonka-sagemaker<amazonka-sagemaker<amazonka-sagemaker<amazonka-sagemaker<amazonka-sagemaker<amazonka-sagemaker<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; r<amazonka-sagemaker&Your OIDC IdP workforce configuration.See: < smart constructor.<amazonka-sagemakerThe OIDC IdP authorization endpoint used to configure your private workforce.<amazonka-sagemakerThe OIDC IdP client ID used to configure your private workforce.<amazonka-sagemaker=The OIDC IdP issuer used to configure your private workforce.<amazonka-sagemakerThe OIDC IdP JSON Web Key Set (Jwks) URI used to configure your private workforce.<amazonka-sagemakerThe OIDC IdP logout endpoint used to configure your private workforce.<amazonka-sagemakerThe OIDC IdP token endpoint used to configure your private workforce.<amazonka-sagemakerThe OIDC IdP user information endpoint used to configure your private workforce.<amazonka-sagemakerCreate a value of <" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:<, < - The OIDC IdP authorization endpoint used to configure your private workforce.<, < - The OIDC IdP client ID used to configure your private workforce.<, < - The OIDC IdP issuer used to configure your private workforce.<, < - The OIDC IdP JSON Web Key Set (Jwks) URI used to configure your private workforce.<, < - The OIDC IdP logout endpoint used to configure your private workforce.<, < - The OIDC IdP token endpoint used to configure your private workforce.<, < - The OIDC IdP user information endpoint used to configure your private workforce.<amazonka-sagemakerThe OIDC IdP authorization endpoint used to configure your private workforce.<amazonka-sagemakerThe OIDC IdP client ID used to configure your private workforce.<amazonka-sagemaker=The OIDC IdP issuer used to configure your private workforce.<amazonka-sagemakerThe OIDC IdP JSON Web Key Set (Jwks) URI used to configure your private workforce.<amazonka-sagemakerThe OIDC IdP logout endpoint used to configure your private workforce.<amazonka-sagemakerThe OIDC IdP token endpoint used to configure your private workforce.<amazonka-sagemakerThe OIDC IdP user information endpoint used to configure your private workforce.<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; <amazonka-sagemakerA list of user groups that exist in your OIDC Identity Provider (IdP). One to ten groups can be used to create a single private work team. When you add a user group to the list of Groups, you can add that user group to one or more private work teams. If you add a user group to a private work team, all workers in that user group are added to the work team.See: < smart constructor.<amazonka-sagemakerA list of comma seperated strings that identifies user groups in your OIDC IdP. Each user group is made up of a group of private workers.<amazonka-sagemakerCreate a value of <" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:<, < - A list of comma seperated strings that identifies user groups in your OIDC IdP. Each user group is made up of a group of private workers.<amazonka-sagemakerA list of comma seperated strings that identifies user groups in your OIDC IdP. Each user group is made up of a group of private workers.<amazonka-sagemaker<<<<<<<<<<<(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; <amazonka-sagemakerDefines an Amazon Cognito or your own OIDC IdP user group that is part of a work team.See: < smart constructor.<amazonka-sagemaker", where  is a metric name. For example, the following filter searches for training jobs with an  "accuracy" metric greater than "0.9": { "Name": "Metrics.accuracy", "Operator": "GreaterThan", "Value": "0.9" }HyperParametersTo define a hyperparameter filter, enter a value with the form "HyperParameters.". Decimal hyperparameter values are treated as a decimal in a comparison if the specified Value0 is also a decimal value. If the specified Value is an integer, the decimal hyperparameter values are treated as integers. For example, the following filter is satisfied by training jobs with a "learning_rate"" hyperparameter that is less than "0.5":  { ) "Name": "HyperParameters.learning_rate",  "Operator": "LessThan",  "Value": "0.5"  }Tags4To define a tag filter, enter a value with the form  Tags..See: = smart constructor.=amazonka-sagemakerA Boolean binary operator that is used to evaluate the filter. The operator field contains one of the following values: Equals The value of Name equals Value. NotEquals The value of Name doesn't equal Value.ExistsThe Name property exists. NotExistsThe Name property does not exist. GreaterThan The value of Name is greater than Value). Not supported for text properties.GreaterThanOrEqualTo The value of Name is greater than or equal to Value). Not supported for text properties.LessThan The value of Name is less than Value). Not supported for text properties.LessThanOrEqualTo The value of Name is less than or equal to Value). Not supported for text properties.In The value of Name/ is one of the comma delimited strings in Value%. Only supported for text properties.Contains The value of Name contains the string Value*. Only supported for text properties.A SearchExpression can include the Contains+ operator multiple times when the value of Name is one of the following: Experiment.DisplayName Experiment.ExperimentName Experiment.Tags Trial.DisplayName Trial.TrialName  Trial.Tags TrialComponent.DisplayName !TrialComponent.TrialComponentName TrialComponent.Tags TrialComponent.InputArtifacts TrialComponent.OutputArtifactsA SearchExpression can include only one Contains" operator for all other values of Name*. In these cases, if you include multiple Contains operators in the SearchExpression., the result is the following error message: ".'CONTAINS' operator usage limit of 1 exceeded."=amazonka-sagemakerA value used with Name and Operator to determine which resources satisfy the filter's condition. For numerical properties, Value must be an integer or floating-point decimal. For timestamp properties, Value must be an ISO 8601 date-time string of the following format: YYYY-mm-dd'T'HH:MM:SS.=amazonka-sagemaker'A resource property name. For example, TrainingJobName. For valid property names, see SearchRecord. You must specify a valid property for the resource.=amazonka-sagemakerCreate a value of =" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:=, = - A Boolean binary operator that is used to evaluate the filter. The operator field contains one of the following values: Equals The value of Name equals Value. NotEquals The value of Name doesn't equal Value.ExistsThe Name property exists. NotExistsThe Name property does not exist. GreaterThan The value of Name is greater than Value). Not supported for text properties.GreaterThanOrEqualTo The value of Name is greater than or equal to Value). Not supported for text properties.LessThan The value of Name is less than Value). Not supported for text properties.LessThanOrEqualTo The value of Name is less than or equal to Value). Not supported for text properties.In The value of Name/ is one of the comma delimited strings in Value%. Only supported for text properties.Contains The value of Name contains the string Value*. Only supported for text properties.A SearchExpression can include the Contains+ operator multiple times when the value of Name is one of the following: Experiment.DisplayName Experiment.ExperimentName Experiment.Tags Trial.DisplayName Trial.TrialName  Trial.Tags TrialComponent.DisplayName !TrialComponent.TrialComponentName TrialComponent.Tags TrialComponent.InputArtifacts TrialComponent.OutputArtifactsA SearchExpression can include only one Contains" operator for all other values of Name*. In these cases, if you include multiple Contains operators in the SearchExpression., the result is the following error message: ".'CONTAINS' operator usage limit of 1 exceeded."=, = - A value used with Name and Operator to determine which resources satisfy the filter's condition. For numerical properties, Value must be an integer or floating-point decimal. For timestamp properties, Value must be an ISO 8601 date-time string of the following format: YYYY-mm-dd'T'HH:MM:SS.=, =* - A resource property name. For example, TrainingJobName. For valid property names, see SearchRecord. You must specify a valid property for the resource.=amazonka-sagemakerA Boolean binary operator that is used to evaluate the filter. The operator field contains one of the following values: Equals The value of Name equals Value. NotEquals The value of Name doesn't equal Value.ExistsThe Name property exists. NotExistsThe Name property does not exist. GreaterThan The value of Name is greater than Value). Not supported for text properties.GreaterThanOrEqualTo The value of Name is greater than or equal to Value). Not supported for text properties.LessThan The value of Name is less than Value). Not supported for text properties.LessThanOrEqualTo The value of Name is less than or equal to Value). Not supported for text properties.In The value of Name/ is one of the comma delimited strings in Value%. Only supported for text properties.Contains The value of Name contains the string Value*. Only supported for text properties.A SearchExpression can include the Contains+ operator multiple times when the value of Name is one of the following: Experiment.DisplayName Experiment.ExperimentName Experiment.Tags Trial.DisplayName Trial.TrialName  Trial.Tags TrialComponent.DisplayName !TrialComponent.TrialComponentName TrialComponent.Tags TrialComponent.InputArtifacts TrialComponent.OutputArtifactsA SearchExpression can include only one Contains" operator for all other values of Name*. In these cases, if you include multiple Contains operators in the SearchExpression., the result is the following error message: ".'CONTAINS' operator usage limit of 1 exceeded."=amazonka-sagemakerA value used with Name and Operator to determine which resources satisfy the filter's condition. For numerical properties, Value must be an integer or floating-point decimal. For timestamp properties, Value must be an ISO 8601 date-time string of the following format: YYYY-mm-dd'T'HH:MM:SS.=amazonka-sagemaker'A resource property name. For example, TrainingJobName. For valid property names, see SearchRecord. You must specify a valid property for the resource.=amazonka-sagemaker= ========= =========(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; 6=amazonka-sagemakerA list of nested Filter objects. A resource must satisfy the conditions of all filters to be included in the results returned from the Search API.+For example, to filter on a training job's InputDataConfig, property with a specific channel name and S3Uri' prefix, define the following filters: '{Name:"InputDataConfig.ChannelName", "Operator":"Equals", "Value":"train"}', '{Name:"InputDataConfig.DataSource.S3DataSource.S3Uri", "Operator":"Contains", "Value":"mybucket/catdata"}'See: = smart constructor.=amazonka-sagemakerThe name of the property to use in the nested filters. The value must match a listed property name, such as InputDataConfig.=amazonka-sagemakerA list of filters. Each filter acts on a property. Filters must contain at least one Filters value. For example, a  NestedFilters% call might include a filter on the  PropertyName parameter of the InputDataConfig property: -InputDataConfig.DataSource.S3DataSource.S3Uri.=amazonka-sagemakerCreate a value of =" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:=, = - The name of the property to use in the nested filters. The value must match a listed property name, such as InputDataConfig.=, = - A list of filters. Each filter acts on a property. Filters must contain at least one Filters value. For example, a  NestedFilters% call might include a filter on the  PropertyName parameter of the InputDataConfig property: -InputDataConfig.DataSource.S3DataSource.S3Uri.=amazonka-sagemakerThe name of the property to use in the nested filters. The value must match a listed property name, such as InputDataConfig.=amazonka-sagemakerA list of filters. Each filter acts on a property. Filters must contain at least one Filters value. For example, a  NestedFilters% call might include a filter on the  PropertyName parameter of the InputDataConfig property: -InputDataConfig.DataSource.S3DataSource.S3Uri.=amazonka-sagemaker=amazonka-sagemaker===============(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? 7m============(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; P=amazonka-sagemakerProvides information about how to store model training results (model artifacts).See: = smart constructor.=amazonka-sagemakerThe Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption. The KmsKeyId& can be any of the following formats: // KMS Key ID &"1234abcd-12ab-34cd-56ef-1234567890ab"*// Amazon Resource Name (ARN) of a KMS Key "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"// KMS Key Alias "alias/ExampleAlias"0// Amazon Resource Name (ARN) of a KMS Key Alias 7"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"If you use a KMS key ID or an alias of your KMS key, the SageMaker execution role must include permissions to call  kms:Encrypt. If you don't provide a KMS key ID, SageMaker uses the default KMS key for Amazon S3 for your role's account. SageMaker uses server-side encryption with KMS-managed keys for OutputDataConfig&. If you use a bucket policy with an  s3:PutObject permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption to  "aws:kms". For more information, see  https://docs.aws.amazon.com/AmazonS3/latest/userguide/UsingKMSEncryption.htmlKMS-Managed Encryption Keys in the .Amazon Simple Storage Service Developer Guide.The KMS key policy must grant permission to the IAM role that you specify in your CreateTrainingJob, CreateTransformJob, or CreateHyperParameterTuningJob& requests. For more information, see  https://docs.aws.amazon.com/kms/latest/developerguide/key-policies.html-Using Key Policies in Amazon Web Services KMS in the :Amazon Web Services Key Management Service Developer Guide.=amazonka-sagemakerIdentifies the S3 path where you want SageMaker to store the model artifacts. For example,  s3://bucket-name/key-name-prefix.=amazonka-sagemakerCreate a value of =" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:=, = - The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption. The KmsKeyId& can be any of the following formats: // KMS Key ID &"1234abcd-12ab-34cd-56ef-1234567890ab"*// Amazon Resource Name (ARN) of a KMS Key "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"// KMS Key Alias "alias/ExampleAlias"0// Amazon Resource Name (ARN) of a KMS Key Alias 7"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"If you use a KMS key ID or an alias of your KMS key, the SageMaker execution role must include permissions to call  kms:Encrypt. If you don't provide a KMS key ID, SageMaker uses the default KMS key for Amazon S3 for your role's account. SageMaker uses server-side encryption with KMS-managed keys for OutputDataConfig&. If you use a bucket policy with an  s3:PutObject permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption to  "aws:kms". For more information, see  https://docs.aws.amazon.com/AmazonS3/latest/userguide/UsingKMSEncryption.htmlKMS-Managed Encryption Keys in the .Amazon Simple Storage Service Developer Guide.The KMS key policy must grant permission to the IAM role that you specify in your CreateTrainingJob, CreateTransformJob, or CreateHyperParameterTuningJob& requests. For more information, see  https://docs.aws.amazon.com/kms/latest/developerguide/key-policies.html-Using Key Policies in Amazon Web Services KMS in the :Amazon Web Services Key Management Service Developer Guide.=, = - Identifies the S3 path where you want SageMaker to store the model artifacts. For example,  s3://bucket-name/key-name-prefix.=amazonka-sagemakerThe Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption. The KmsKeyId& can be any of the following formats: // KMS Key ID &"1234abcd-12ab-34cd-56ef-1234567890ab"*// Amazon Resource Name (ARN) of a KMS Key "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"// KMS Key Alias "alias/ExampleAlias"0// Amazon Resource Name (ARN) of a KMS Key Alias 7"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"If you use a KMS key ID or an alias of your KMS key, the SageMaker execution role must include permissions to call  kms:Encrypt. If you don't provide a KMS key ID, SageMaker uses the default KMS key for Amazon S3 for your role's account. SageMaker uses server-side encryption with KMS-managed keys for OutputDataConfig&. If you use a bucket policy with an  s3:PutObject permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption to  "aws:kms". For more information, see  https://docs.aws.amazon.com/AmazonS3/latest/userguide/UsingKMSEncryption.htmlKMS-Managed Encryption Keys in the .Amazon Simple Storage Service Developer Guide.The KMS key policy must grant permission to the IAM role that you specify in your CreateTrainingJob, CreateTransformJob, or CreateHyperParameterTuningJob& requests. For more information, see  https://docs.aws.amazon.com/kms/latest/developerguide/key-policies.html-Using Key Policies in Amazon Web Services KMS in the :Amazon Web Services Key Management Service Developer Guide.=amazonka-sagemakerIdentifies the S3 path where you want SageMaker to store the model artifacts. For example,  s3://bucket-name/key-name-prefix.=amazonka-sagemaker===============(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; U(>amazonka-sagemaker'An output parameter of a pipeline step.See: > smart constructor.>amazonka-sagemaker!The name of the output parameter.>amazonka-sagemaker"The value of the output parameter.>amazonka-sagemakerCreate a value of >" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:>, >$ - The name of the output parameter.>, >% - The value of the output parameter.>amazonka-sagemaker!The name of the output parameter.>amazonka-sagemaker"The value of the output parameter.>amazonka-sagemaker>amazonka-sagemaker>>>>>>>>>>>>>>>(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; Y>amazonka-sagemakerMetadata for a Lambda step.See: > smart constructor.>amazonka-sagemakerThe Amazon Resource Name (ARN) of the Lambda function that was run by this step execution.>amazonka-sagemaker3A list of the output parameters of the Lambda step.>amazonka-sagemakerCreate a value of >" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:>, > - The Amazon Resource Name (ARN) of the Lambda function that was run by this step execution.>, >6 - A list of the output parameters of the Lambda step.>amazonka-sagemakerThe Amazon Resource Name (ARN) of the Lambda function that was run by this step execution.>amazonka-sagemaker3A list of the output parameters of the Lambda step.>>>>>>>>>>>>>>(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; _>amazonka-sagemakerMetadata about a callback step.See: > smart constructor.>amazonka-sagemaker7The pipeline generated token from the Amazon SQS queue.>amazonka-sagemaker5A list of the output parameters of the callback step.>amazonka-sagemakerThe URL of the Amazon Simple Queue Service (Amazon SQS) queue used by the callback step.>amazonka-sagemakerCreate a value of >" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:>, >: - The pipeline generated token from the Amazon SQS queue.>, >8 - A list of the output parameters of the callback step.>, > - The URL of the Amazon Simple Queue Service (Amazon SQS) queue used by the callback step.>amazonka-sagemaker7The pipeline generated token from the Amazon SQS queue.>amazonka-sagemaker5A list of the output parameters of the callback step.>amazonka-sagemakerThe URL of the Amazon Simple Queue Service (Amazon SQS) queue used by the callback step. >>>>>>>>> >>>>>>>>>(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; d>amazonka-sagemakerConfiguration that controls the parallelism of the pipeline. By default, the parallelism configuration specified applies to all executions of the pipeline unless overridden.See: > smart constructor.>amazonka-sagemaker9The max number of steps that can be executed in parallel.>amazonka-sagemakerCreate a value of >" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:>, >< - The max number of steps that can be executed in parallel.>amazonka-sagemaker9The max number of steps that can be executed in parallel.>amazonka-sagemaker>>>>>>>>>>>(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; iO>amazonka-sagemaker.Assigns a value to a named Pipeline parameter.See: > smart constructor.>amazonka-sagemakerThe name of the parameter to assign a value to. This parameter name must match a named parameter in the pipeline definition.>amazonka-sagemaker$The literal value for the parameter.>amazonka-sagemakerCreate a value of >" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:>, > - The name of the parameter to assign a value to. This parameter name must match a named parameter in the pipeline definition.>, >' - The literal value for the parameter.>amazonka-sagemakerThe name of the parameter to assign a value to. This parameter name must match a named parameter in the pipeline definition.>amazonka-sagemaker$The literal value for the parameter.>amazonka-sagemaker>amazonka-sagemaker>>>>>>>>>>>>>>>(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; qM>amazonka-sagemakerDefines the possible values for categorical, continuous, and integer hyperparameters to be used by an algorithm.See: > smart constructor.>amazonka-sagemakerA &CategoricalParameterRangeSpecification object that defines the possible values for a categorical hyperparameter.>amazonka-sagemakerA %ContinuousParameterRangeSpecification object that defines the possible values for a continuous hyperparameter.>amazonka-sagemakerA "IntegerParameterRangeSpecification object that defines the possible values for an integer hyperparameter.>amazonka-sagemakerCreate a value of >" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:>, > - A &CategoricalParameterRangeSpecification object that defines the possible values for a categorical hyperparameter.>, > - A %ContinuousParameterRangeSpecification object that defines the possible values for a continuous hyperparameter.>, > - A "IntegerParameterRangeSpecification object that defines the possible values for an integer hyperparameter.>amazonka-sagemakerA &CategoricalParameterRangeSpecification object that defines the possible values for a categorical hyperparameter.>amazonka-sagemakerA %ContinuousParameterRangeSpecification object that defines the possible values for a continuous hyperparameter.>amazonka-sagemakerA "IntegerParameterRangeSpecification object that defines the possible values for an integer hyperparameter. >>>>>>>>> >>>>>>>>>(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; |=>amazonka-sagemakerSpecifies ranges of integer, continuous, and categorical hyperparameters that a hyperparameter tuning job searches. The hyperparameter tuning job launches training jobs with hyperparameter values within these ranges to find the combination of values that result in the training job with the best performance as measured by the objective metric of the hyperparameter tuning job.*The maximum number of items specified for  Array Members refers to the maximum number of hyperparameters for each range and also the maximum for the hyperparameter tuning job itself. That is, the sum of the number of hyperparameters for all the ranges can't exceed the maximum number specified.See: > smart constructor.>amazonka-sagemakerThe array of CategoricalParameterRange objects that specify ranges of categorical hyperparameters that a hyperparameter tuning job searches.>amazonka-sagemakerThe array of ContinuousParameterRange objects that specify ranges of continuous hyperparameters that a hyperparameter tuning job searches.>amazonka-sagemakerThe array of IntegerParameterRange objects that specify ranges of integer hyperparameters that a hyperparameter tuning job searches.>amazonka-sagemakerCreate a value of >" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:>, > - The array of CategoricalParameterRange objects that specify ranges of categorical hyperparameters that a hyperparameter tuning job searches.>, > - The array of ContinuousParameterRange objects that specify ranges of continuous hyperparameters that a hyperparameter tuning job searches.>, > - The array of IntegerParameterRange objects that specify ranges of integer hyperparameters that a hyperparameter tuning job searches.>amazonka-sagemakerThe array of CategoricalParameterRange objects that specify ranges of categorical hyperparameters that a hyperparameter tuning job searches.>amazonka-sagemakerThe array of ContinuousParameterRange objects that specify ranges of continuous hyperparameters that a hyperparameter tuning job searches.>amazonka-sagemakerThe array of IntegerParameterRange objects that specify ranges of integer hyperparameters that a hyperparameter tuning job searches. >>>>>>>>> >>>>>>>>>(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? }>>>>>>> >>>>>>>>>>>(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; ?amazonka-sagemaker4Defines a hyperparameter to be used by an algorithm.See: ? smart constructor.?amazonka-sagemakerThe default value for this hyperparameter. If a default value is specified, a hyperparameter cannot be required.?amazonka-sagemaker*A brief description of the hyperparameter.?amazonka-sagemaker2Indicates whether this hyperparameter is required.?amazonka-sagemakerIndicates whether this hyperparameter is tunable in a hyperparameter tuning job.?amazonka-sagemaker*The allowed range for this hyperparameter.?amazonka-sagemaker9The name of this hyperparameter. The name must be unique.?amazonka-sagemaker5The type of this hyperparameter. The valid types are Integer,  Continuous,  Categorical, and FreeText.?amazonka-sagemakerCreate a value of ?" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:?, ? - The default value for this hyperparameter. If a default value is specified, a hyperparameter cannot be required.?, ?- - A brief description of the hyperparameter.?, ?5 - Indicates whether this hyperparameter is required.?, ? - Indicates whether this hyperparameter is tunable in a hyperparameter tuning job.?, ?- - The allowed range for this hyperparameter.?, ?< - The name of this hyperparameter. The name must be unique.?, ?8 - The type of this hyperparameter. The valid types are Integer,  Continuous,  Categorical, and FreeText.?amazonka-sagemakerThe default value for this hyperparameter. If a default value is specified, a hyperparameter cannot be required.?amazonka-sagemaker*A brief description of the hyperparameter.?amazonka-sagemaker2Indicates whether this hyperparameter is required.?amazonka-sagemakerIndicates whether this hyperparameter is tunable in a hyperparameter tuning job.?amazonka-sagemaker*The allowed range for this hyperparameter.?amazonka-sagemaker9The name of this hyperparameter. The name must be unique.?amazonka-sagemaker5The type of this hyperparameter. The valid types are Integer,  Continuous,  Categorical, and FreeText.?amazonka-sagemaker?amazonka-sagemaker???????????????????????????????????(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; ?amazonka-sagemakerThe trial that a trial component is associated with and the experiment the trial is part of. A component might not be associated with a trial. A component can be associated with multiple trials.See: ? smart constructor.?amazonka-sagemakerThe name of the experiment.?amazonka-sagemakerThe name of the trial.?amazonka-sagemakerCreate a value of ?" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:?, ? - The name of the experiment.?, ? - The name of the trial.?amazonka-sagemakerThe name of the experiment.?amazonka-sagemakerThe name of the trial.??????????????(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; ?amazonka-sagemakerA previously completed or stopped hyperparameter tuning job to be used as a starting point for a new hyperparameter tuning job.See: ? smart constructor.?amazonka-sagemakerThe name of the hyperparameter tuning job to be used as a starting point for a new hyperparameter tuning job.?amazonka-sagemakerCreate a value of ?" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:?, ? - The name of the hyperparameter tuning job to be used as a starting point for a new hyperparameter tuning job.?amazonka-sagemakerThe name of the hyperparameter tuning job to be used as a starting point for a new hyperparameter tuning job.??????????(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; p?amazonka-sagemakerSpecifies the configuration for a hyperparameter tuning job that uses one or more previous hyperparameter tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.All training jobs launched by the new hyperparameter tuning job are evaluated by using the objective metric, and the training job that performs the best is compared to the best training jobs from the parent tuning jobs. From these, the training job that performs the best as measured by the objective metric is returned as the overall best training job.All training jobs launched by parent hyperparameter tuning jobs and the new hyperparameter tuning jobs count against the limit of training jobs for the tuning job.See: ? smart constructor.?amazonka-sagemakerAn array of hyperparameter tuning jobs that are used as the starting point for the new hyperparameter tuning job. For more information about warm starting a hyperparameter tuning job, see  https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-warm-start.html>Using a Previous Hyperparameter Tuning Job as a Starting Point.Hyperparameter tuning jobs created before October 1, 2018 cannot be used as parent jobs for warm start tuning jobs.?amazonka-sagemakerSpecifies one of the following: IDENTICAL_DATA_AND_ALGORITHMThe new hyperparameter tuning job uses the same input data and training image as the parent tuning jobs. You can change the hyperparameter ranges to search and the maximum number of training jobs that the hyperparameter tuning job launches. You cannot use a new version of the training algorithm, unless the changes in the new version do not affect the algorithm itself. For example, changes that improve logging or adding support for a different data format are allowed. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.TRANSFER_LEARNINGThe new hyperparameter tuning job can include input data, hyperparameter ranges, maximum number of concurrent training jobs, and maximum number of training jobs that are different than those of its parent hyperparameter tuning jobs. The training image can also be a different version from the version used in the parent hyperparameter tuning job. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.?amazonka-sagemakerCreate a value of ?" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:?, ? - An array of hyperparameter tuning jobs that are used as the starting point for the new hyperparameter tuning job. For more information about warm starting a hyperparameter tuning job, see  https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-warm-start.html>Using a Previous Hyperparameter Tuning Job as a Starting Point.Hyperparameter tuning jobs created before October 1, 2018 cannot be used as parent jobs for warm start tuning jobs.?, ?" - Specifies one of the following: IDENTICAL_DATA_AND_ALGORITHMThe new hyperparameter tuning job uses the same input data and training image as the parent tuning jobs. You can change the hyperparameter ranges to search and the maximum number of training jobs that the hyperparameter tuning job launches. You cannot use a new version of the training algorithm, unless the changes in the new version do not affect the algorithm itself. For example, changes that improve logging or adding support for a different data format are allowed. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.TRANSFER_LEARNINGThe new hyperparameter tuning job can include input data, hyperparameter ranges, maximum number of concurrent training jobs, and maximum number of training jobs that are different than those of its parent hyperparameter tuning jobs. The training image can also be a different version from the version used in the parent hyperparameter tuning job. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.?amazonka-sagemakerAn array of hyperparameter tuning jobs that are used as the starting point for the new hyperparameter tuning job. For more information about warm starting a hyperparameter tuning job, see  https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-warm-start.html>Using a Previous Hyperparameter Tuning Job as a Starting Point.Hyperparameter tuning jobs created before October 1, 2018 cannot be used as parent jobs for warm start tuning jobs.?amazonka-sagemakerSpecifies one of the following: IDENTICAL_DATA_AND_ALGORITHMThe new hyperparameter tuning job uses the same input data and training image as the parent tuning jobs. You can change the hyperparameter ranges to search and the maximum number of training jobs that the hyperparameter tuning job launches. You cannot use a new version of the training algorithm, unless the changes in the new version do not affect the algorithm itself. For example, changes that improve logging or adding support for a different data format are allowed. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.TRANSFER_LEARNINGThe new hyperparameter tuning job can include input data, hyperparameter ranges, maximum number of concurrent training jobs, and maximum number of training jobs that are different than those of its parent hyperparameter tuning jobs. The training image can also be a different version from the version used in the parent hyperparameter tuning job. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.?amazonka-sagemaker?amazonka-sagemaker???????????????(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; ?amazonka-sagemakerDefines the traffic pattern.See: ? smart constructor.?amazonka-sagemaker+Specifies how long traffic phase should be.?amazonka-sagemaker2Specifies how many concurrent users to start with.?amazonka-sagemaker2Specified how many new users to spawn in a minute.?amazonka-sagemakerCreate a value of ?" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:?, ?. - Specifies how long traffic phase should be.?, ?5 - Specifies how many concurrent users to start with.?, ?5 - Specified how many new users to spawn in a minute.?amazonka-sagemaker+Specifies how long traffic phase should be.?amazonka-sagemaker2Specifies how many concurrent users to start with.?amazonka-sagemaker2Specified how many new users to spawn in a minute. ????????? ?????????(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; ?amazonka-sagemakerCamazonka-sagemakerConfiguration for downloading input data from Amazon S3 into the processing container.See: C smart constructor.Camazonka-sagemakerThe local path in your container where you want Amazon SageMaker to write input data to.  LocalPath< is an absolute path to the input data and must begin with /opt/ml/processing/.  LocalPath is a required parameter when  AppManaged is False (default).Camazonka-sagemakerWhether to GZIP-decompress the data in Amazon S3 as it is streamed into the processing container. Gzip can only be used when Pipe mode is specified as the  S3InputMode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your container without using the EBS volume.Camazonka-sagemakerWhether to distribute the data from Amazon S3 to all processing instances with FullyReplicated, or whether the data from Amazon S3 is shared by Amazon S3 key, downloading one shard of data to each processing instance.Camazonka-sagemakerWhether to use File or Pipe input mode. In File mode, Amazon SageMaker copies the data from the input source onto the local ML storage volume before starting your processing container. This is the most commonly used input mode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your processing container into named pipes without using the ML storage volume.Camazonka-sagemakerThe URI of the Amazon S3 prefix Amazon SageMaker downloads data required to run a processing job.Camazonka-sagemakerWhether you use an S3Prefix or a  ManifestFile# for the data type. If you choose S3Prefix, S3Uri identifies a key name prefix. Amazon SageMaker uses all objects with the specified key name prefix for the processing job. If you choose  ManifestFile, S3Uri identifies an object that is a manifest file containing a list of object keys that you want Amazon SageMaker to use for the processing job.Camazonka-sagemakerCreate a value of C" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:C, C - The local path in your container where you want Amazon SageMaker to write input data to.  LocalPath< is an absolute path to the input data and must begin with /opt/ml/processing/.  LocalPath is a required parameter when  AppManaged is False (default).C, C - Whether to GZIP-decompress the data in Amazon S3 as it is streamed into the processing container. Gzip can only be used when Pipe mode is specified as the  S3InputMode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your container without using the EBS volume.C, C - Whether to distribute the data from Amazon S3 to all processing instances with FullyReplicated, or whether the data from Amazon S3 is shared by Amazon S3 key, downloading one shard of data to each processing instance.C, C - Whether to use File or Pipe input mode. In File mode, Amazon SageMaker copies the data from the input source onto the local ML storage volume before starting your processing container. This is the most commonly used input mode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your processing container into named pipes without using the ML storage volume.C, C - The URI of the Amazon S3 prefix Amazon SageMaker downloads data required to run a processing job.C, C - Whether you use an S3Prefix or a  ManifestFile# for the data type. If you choose S3Prefix, S3Uri identifies a key name prefix. Amazon SageMaker uses all objects with the specified key name prefix for the processing job. If you choose  ManifestFile, S3Uri identifies an object that is a manifest file containing a list of object keys that you want Amazon SageMaker to use for the processing job.Camazonka-sagemakerThe local path in your container where you want Amazon SageMaker to write input data to.  LocalPath< is an absolute path to the input data and must begin with /opt/ml/processing/.  LocalPath is a required parameter when  AppManaged is False (default).Camazonka-sagemakerWhether to GZIP-decompress the data in Amazon S3 as it is streamed into the processing container. Gzip can only be used when Pipe mode is specified as the  S3InputMode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your container without using the EBS volume.Camazonka-sagemakerWhether to distribute the data from Amazon S3 to all processing instances with FullyReplicated, or whether the data from Amazon S3 is shared by Amazon S3 key, downloading one shard of data to each processing instance.Camazonka-sagemakerWhether to use File or Pipe input mode. In File mode, Amazon SageMaker copies the data from the input source onto the local ML storage volume before starting your processing container. This is the most commonly used input mode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your processing container into named pipes without using the ML storage volume.Camazonka-sagemakerThe URI of the Amazon S3 prefix Amazon SageMaker downloads data required to run a processing job.Camazonka-sagemakerWhether you use an S3Prefix or a  ManifestFile# for the data type. If you choose S3Prefix, S3Uri identifies a key name prefix. Amazon SageMaker uses all objects with the specified key name prefix for the processing job. If you choose  ManifestFile, S3Uri identifies an object that is a manifest file containing a list of object keys that you want Amazon SageMaker to use for the processing job.Camazonka-sagemakerCamazonka-sagemakerCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; TCamazonka-sagemakerInput object for the endpointSee: C smart constructor.Camazonka-sagemakerIf specified, monitoring jobs substract this time from the end time. For information about using offsets for scheduling monitoring jobs, see  https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor-model-quality-schedule.html&Schedule Model Quality Monitoring Jobs.Camazonka-sagemaker=The attributes of the input data that are the input features.Camazonka-sagemakerThe attribute of the input data that represents the ground truth label.Camazonka-sagemakerIn a classification problem, the attribute that represents the class probability.Camazonka-sagemakerThe threshold for the class probability to be evaluated as a positive result.Camazonka-sagemakerWhether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defaults to FullyReplicatedCamazonka-sagemaker Whether the Pipe or File is used as the input mode for transferring data for the monitoring job. Pipe* mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.Camazonka-sagemakerIf specified, monitoring jobs substract this time from the start time. For information about using offsets for scheduling monitoring jobs, see  https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor-model-quality-schedule.html&Schedule Model Quality Monitoring Jobs.Camazonka-sagemaker4An endpoint in customer's account which has enabled DataCaptureConfig enabled.Camazonka-sagemakerPath to the filesystem where the endpoint data is available to the container.Camazonka-sagemakerCreate a value of C" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:C, C - If specified, monitoring jobs substract this time from the end time. For information about using offsets for scheduling monitoring jobs, see  https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor-model-quality-schedule.html&Schedule Model Quality Monitoring Jobs.C, C - The attributes of the input data that are the input features.C, C - The attribute of the input data that represents the ground truth label.C, C - In a classification problem, the attribute that represents the class probability.C, C - The threshold for the class probability to be evaluated as a positive result.C, C - Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defaults to FullyReplicatedC, C - Whether the Pipe or File is used as the input mode for transferring data for the monitoring job. Pipe* mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.C, C - If specified, monitoring jobs substract this time from the start time. For information about using offsets for scheduling monitoring jobs, see  https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor-model-quality-schedule.html&Schedule Model Quality Monitoring Jobs.C, C7 - An endpoint in customer's account which has enabled DataCaptureConfig enabled.C, C - Path to the filesystem where the endpoint data is available to the container.Camazonka-sagemakerIf specified, monitoring jobs substract this time from the end time. For information about using offsets for scheduling monitoring jobs, see  https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor-model-quality-schedule.html&Schedule Model Quality Monitoring Jobs.Camazonka-sagemaker=The attributes of the input data that are the input features.Camazonka-sagemakerThe attribute of the input data that represents the ground truth label.Camazonka-sagemakerIn a classification problem, the attribute that represents the class probability.Camazonka-sagemakerThe threshold for the class probability to be evaluated as a positive result.Camazonka-sagemakerWhether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defaults to FullyReplicatedCamazonka-sagemaker Whether the Pipe or File is used as the input mode for transferring data for the monitoring job. Pipe* mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.Camazonka-sagemakerIf specified, monitoring jobs substract this time from the start time. For information about using offsets for scheduling monitoring jobs, see  https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor-model-quality-schedule.html&Schedule Model Quality Monitoring Jobs.Camazonka-sagemaker4An endpoint in customer's account which has enabled DataCaptureConfig enabled.Camazonka-sagemakerPath to the filesystem where the endpoint data is available to the container.Camazonka-sagemakerCamazonka-sagemakerCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; lCamazonka-sagemaker)Input object for the batch transform job.See: D smart constructor.Camazonka-sagemakerIf specified, monitoring jobs substract this time from the end time. For information about using offsets for scheduling monitoring jobs, see  https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor-model-quality-schedule.html&Schedule Model Quality Monitoring Jobs.Camazonka-sagemaker=The attributes of the input data that are the input features.Camazonka-sagemakerThe attribute of the input data that represents the ground truth label.Camazonka-sagemakerIn a classification problem, the attribute that represents the class probability.Camazonka-sagemakerThe threshold for the class probability to be evaluated as a positive result.Camazonka-sagemakerWhether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defaults to FullyReplicatedCamazonka-sagemaker Whether the Pipe or File is used as the input mode for transferring data for the monitoring job. Pipe* mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.Camazonka-sagemakerIf specified, monitoring jobs substract this time from the start time. For information about using offsets for scheduling monitoring jobs, see  https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor-model-quality-schedule.html&Schedule Model Quality Monitoring Jobs.Damazonka-sagemaker6The Amazon S3 location being used to capture the data.Damazonka-sagemaker0The dataset format for your batch transform job.Damazonka-sagemakerPath to the filesystem where the batch transform data is available to the container.Damazonka-sagemakerCreate a value of C" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:C, D - If specified, monitoring jobs substract this time from the end time. For information about using offsets for scheduling monitoring jobs, see  https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor-model-quality-schedule.html&Schedule Model Quality Monitoring Jobs.C, D - The attributes of the input data that are the input features.C, D - The attribute of the input data that represents the ground truth label.C, D - In a classification problem, the attribute that represents the class probability.C, D - The threshold for the class probability to be evaluated as a positive result.C, D - Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defaults to FullyReplicatedC, D - Whether the Pipe or File is used as the input mode for transferring data for the monitoring job. Pipe* mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.C, D - If specified, monitoring jobs substract this time from the start time. For information about using offsets for scheduling monitoring jobs, see  https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor-model-quality-schedule.html&Schedule Model Quality Monitoring Jobs.D, D9 - The Amazon S3 location being used to capture the data.D, D3 - The dataset format for your batch transform job.D, D - Path to the filesystem where the batch transform data is available to the container.Damazonka-sagemakerIf specified, monitoring jobs substract this time from the end time. For information about using offsets for scheduling monitoring jobs, see  https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor-model-quality-schedule.html&Schedule Model Quality Monitoring Jobs.Damazonka-sagemaker=The attributes of the input data that are the input features.Damazonka-sagemakerThe attribute of the input data that represents the ground truth label.Damazonka-sagemakerIn a classification problem, the attribute that represents the class probability.Damazonka-sagemakerThe threshold for the class probability to be evaluated as a positive result.Damazonka-sagemakerWhether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defaults to FullyReplicatedDamazonka-sagemaker Whether the Pipe or File is used as the input mode for transferring data for the monitoring job. Pipe* mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.Damazonka-sagemakerIf specified, monitoring jobs substract this time from the start time. For information about using offsets for scheduling monitoring jobs, see  https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor-model-quality-schedule.html&Schedule Model Quality Monitoring Jobs.Damazonka-sagemaker6The Amazon S3 location being used to capture the data.Damazonka-sagemaker0The dataset format for your batch transform job.Damazonka-sagemakerPath to the filesystem where the batch transform data is available to the container.Damazonka-sagemakerDamazonka-sagemakerDamazonka-sagemakerDCDDCCCCCCCCDCDDDDDDDDDDDDCDDCCCCCCCCDCDDDDDDDDDDDD(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; peDamazonka-sagemaker The inputs for a monitoring job.See: D smart constructor.Damazonka-sagemaker)Input object for the batch transform job.Damazonka-sagemaker"The endpoint for a monitoring job.Damazonka-sagemakerCreate a value of D" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:D, D, - Input object for the batch transform job.D, D% - The endpoint for a monitoring job.Damazonka-sagemaker)Input object for the batch transform job.Damazonka-sagemaker"The endpoint for a monitoring job.DDDDDDDDDDDDDD(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; uiDamazonka-sagemakerThe input for the model quality monitoring job. Currently endponts are supported for input for model quality monitoring jobs.See: D smart constructor.Damazonka-sagemaker)Input object for the batch transform job.Damazonka-sagemaker.The ground truth label provided for the model.Damazonka-sagemakerCreate a value of D" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:D, D, - Input object for the batch transform job.D, D - Undocumented member.D, D1 - The ground truth label provided for the model.Damazonka-sagemaker)Input object for the batch transform job.Damazonka-sagemakerUndocumented member.Damazonka-sagemaker.The ground truth label provided for the model.Damazonka-sagemakerD DDDDDDDDD DDDDDDDDD(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; y,Damazonka-sagemaker(Inputs for the model explainability job.See: D smart constructor.Damazonka-sagemaker)Input object for the batch transform job.Damazonka-sagemakerCreate a value of D" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:D, D, - Input object for the batch transform job.D, D - Undocumented member.Damazonka-sagemaker)Input object for the batch transform job.Damazonka-sagemakerUndocumented member.DDDDDDDDDDDDDD(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; }Damazonka-sagemakerInputs for the model bias job.See: D smart constructor.Damazonka-sagemaker)Input object for the batch transform job.Damazonka-sagemaker9Location of ground truth labels to use in model bias job.Damazonka-sagemakerCreate a value of D" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:D, D, - Input object for the batch transform job.D, D - Undocumented member.D, D< - Location of ground truth labels to use in model bias job.Damazonka-sagemaker)Input object for the batch transform job.Damazonka-sagemakerUndocumented member.Damazonka-sagemaker9Location of ground truth labels to use in model bias job.Damazonka-sagemakerD DDDDDDDDD DDDDDDDDD(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; Damazonka-sagemakerThe input for the data quality monitoring job. Currently endpoints are supported for input.See: D smart constructor.Damazonka-sagemaker)Input object for the batch transform job.Damazonka-sagemakerCreate a value of D" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:D, D, - Input object for the batch transform job.D, D - Undocumented member.Damazonka-sagemaker)Input object for the batch transform job.Damazonka-sagemakerUndocumented member.DDDDDDDDDDDDDD(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? DDDDDDDDDDDD(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; iDamazonka-sagemakerConfiguration for uploading output data to Amazon S3 from the processing container.See: E smart constructor.Eamazonka-sagemakerA URI that identifies the Amazon S3 bucket where you want Amazon SageMaker to save the results of a processing job.Eamazonka-sagemakerThe local path of a directory where you want Amazon SageMaker to upload its contents to Amazon S3.  LocalPath is an absolute path to a directory containing output files. This directory will be created by the platform and exist when your container's entrypoint is invoked.Eamazonka-sagemakerWhether to upload the results of the processing job continuously or after the job completes.Eamazonka-sagemakerCreate a value of D" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:E, E - A URI that identifies the Amazon S3 bucket where you want Amazon SageMaker to save the results of a processing job.E, E - The local path of a directory where you want Amazon SageMaker to upload its contents to Amazon S3.  LocalPath is an absolute path to a directory containing output files. This directory will be created by the platform and exist when your container's entrypoint is invoked.E, E - Whether to upload the results of the processing job continuously or after the job completes.Eamazonka-sagemakerA URI that identifies the Amazon S3 bucket where you want Amazon SageMaker to save the results of a processing job.Eamazonka-sagemakerThe local path of a directory where you want Amazon SageMaker to upload its contents to Amazon S3.  LocalPath is an absolute path to a directory containing output files. This directory will be created by the platform and exist when your container's entrypoint is invoked.Eamazonka-sagemakerWhether to upload the results of the processing job continuously or after the job completes.Eamazonka-sagemakerEamazonka-sagemakerEamazonka-sagemakerE DEEEDEEEE DEEEDEEEE(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';  Eamazonka-sagemakerDescribes the results of a processing job. The processing output must specify exactly one of either S3Output or FeatureStoreOutput types.See: E smart constructor.Eamazonka-sagemakerWhen True, output operations such as data upload are managed natively by the processing job application. When False? (default), output operations are managed by Amazon SageMaker.Eamazonka-sagemakerConfiguration for processing job outputs in Amazon SageMaker Feature Store. This processing output type is only supported when  AppManaged is specified.Eamazonka-sagemaker6Configuration for processing job outputs in Amazon S3.Eamazonka-sagemaker'The name for the processing job output.Eamazonka-sagemakerCreate a value of E" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:E, E - When True, output operations such as data upload are managed natively by the processing job application. When False? (default), output operations are managed by Amazon SageMaker.E, E - Configuration for processing job outputs in Amazon SageMaker Feature Store. This processing output type is only supported when  AppManaged is specified.E, E9 - Configuration for processing job outputs in Amazon S3.E, E* - The name for the processing job output.Eamazonka-sagemakerWhen True, output operations such as data upload are managed natively by the processing job application. When False? (default), output operations are managed by Amazon SageMaker.Eamazonka-sagemakerConfiguration for processing job outputs in Amazon SageMaker Feature Store. This processing output type is only supported when  AppManaged is specified.Eamazonka-sagemaker6Configuration for processing job outputs in Amazon S3.Eamazonka-sagemaker'The name for the processing job output.Eamazonka-sagemakerE EEEEEEEEEEE EEEEEEEEEEE(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; Eamazonka-sagemakerConfiguration for uploading output from the processing container.See: E smart constructor.Eamazonka-sagemakerThe Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt the processing job output. KmsKeyId can be an ID of a KMS key, ARN of a KMS key, alias of a KMS key, or alias of a KMS key. The KmsKeyId is applied to all outputs.Eamazonka-sagemakerAn array of outputs configuring the data to upload from the processing container.Eamazonka-sagemakerCreate a value of E" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:E, E - The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt the processing job output. KmsKeyId can be an ID of a KMS key, ARN of a KMS key, alias of a KMS key, or alias of a KMS key. The KmsKeyId is applied to all outputs.E, E - An array of outputs configuring the data to upload from the processing container.Eamazonka-sagemakerThe Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt the processing job output. KmsKeyId can be an ID of a KMS key, ARN of a KMS key, alias of a KMS key, or alias of a KMS key. The KmsKeyId is applied to all outputs.Eamazonka-sagemakerAn array of outputs configuring the data to upload from the processing container.EEEEEEEEEEEEEE(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; Eamazonka-sagemakerInformation about where and how you want to store the results of a monitoring job.See: E smart constructor.Eamazonka-sagemakerWhether to upload the results of the monitoring job continuously or after the job completes.Eamazonka-sagemakerA URI that identifies the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job.Eamazonka-sagemakerThe local path to the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job. LocalPath is an absolute path for the output data.Eamazonka-sagemakerCreate a value of E" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:E, E - Whether to upload the results of the monitoring job continuously or after the job completes.E, E - A URI that identifies the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job.E, E - The local path to the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job. LocalPath is an absolute path for the output data.Eamazonka-sagemakerWhether to upload the results of the monitoring job continuously or after the job completes.Eamazonka-sagemakerA URI that identifies the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job.Eamazonka-sagemakerThe local path to the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job. LocalPath is an absolute path for the output data.Eamazonka-sagemakerEamazonka-sagemakerE EEEEEEEEE EEEEEEEEE(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; Eamazonka-sagemaker'The output object for a monitoring job.See: E smart constructor.Eamazonka-sagemakerThe Amazon S3 storage location where the results of a monitoring job are saved.Eamazonka-sagemakerCreate a value of E" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:E, E - The Amazon S3 storage location where the results of a monitoring job are saved.Eamazonka-sagemakerThe Amazon S3 storage location where the results of a monitoring job are saved.Eamazonka-sagemakerEEEEEEEEEEE(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; Eamazonka-sagemaker-The output configuration for monitoring jobs.See: E smart constructor.Eamazonka-sagemakerThe Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.Eamazonka-sagemakerMonitoring outputs for monitoring jobs. This is where the output of the periodic monitoring jobs is uploaded.Eamazonka-sagemakerCreate a value of E" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:E, E - The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.E, E - Monitoring outputs for monitoring jobs. This is where the output of the periodic monitoring jobs is uploaded.Eamazonka-sagemakerThe Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.Eamazonka-sagemakerMonitoring outputs for monitoring jobs. This is where the output of the periodic monitoring jobs is uploaded.Eamazonka-sagemakerEEEEEEEEEEEEEEE(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; Eamazonka-sagemakerConfigures conditions under which the processing job should be stopped, such as how long the processing job has been running. After the condition is met, the processing job is stopped.See: E smart constructor.Eamazonka-sagemaker)Specifies the maximum runtime in seconds.Eamazonka-sagemakerCreate a value of E" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:E, E, - Specifies the maximum runtime in seconds.Eamazonka-sagemaker)Specifies the maximum runtime in seconds.Eamazonka-sagemakerEEEEEEEEEEE(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? EEEEEEEEEEEE(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? h FFFFFFFFFFFFFFFFFFFFFFFF(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; pFamazonka-sagemakerSpecifies configuration for a core dump from the model container when the process crashes.See: F smart constructor.Famazonka-sagemakerThe Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the core dump data at rest using Amazon S3 server-side encryption. The KmsKeyId& can be any of the following formats: // KMS Key ID &"1234abcd-12ab-34cd-56ef-1234567890ab"*// Amazon Resource Name (ARN) of a KMS Key "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"// KMS Key Alias "alias/ExampleAlias"0// Amazon Resource Name (ARN) of a KMS Key Alias 7"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"If you use a KMS key ID or an alias of your KMS key, the SageMaker execution role must include permissions to call  kms:Encrypt. If you don't provide a KMS key ID, SageMaker uses the default KMS key for Amazon S3 for your role's account. SageMaker uses server-side encryption with KMS-managed keys for OutputDataConfig&. If you use a bucket policy with an  s3:PutObject permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption to  "aws:kms". For more information, see  https://docs.aws.amazon.com/AmazonS3/latest/dev/UsingKMSEncryption.htmlKMS-Managed Encryption Keys in the .Amazon Simple Storage Service Developer Guide.The KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint and UpdateEndpoint' requests. For more information, see  https://docs.aws.amazon.com/kms/latest/developerguide/key-policies.html-Using Key Policies in Amazon Web Services KMS in the :Amazon Web Services Key Management Service Developer Guide.Famazonka-sagemaker.The Amazon S3 bucket to send the core dump to.Famazonka-sagemakerCreate a value of F" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:F, F - The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the core dump data at rest using Amazon S3 server-side encryption. The KmsKeyId& can be any of the following formats: // KMS Key ID &"1234abcd-12ab-34cd-56ef-1234567890ab"*// Amazon Resource Name (ARN) of a KMS Key "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"// KMS Key Alias "alias/ExampleAlias"0// Amazon Resource Name (ARN) of a KMS Key Alias 7"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"If you use a KMS key ID or an alias of your KMS key, the SageMaker execution role must include permissions to call  kms:Encrypt. If you don't provide a KMS key ID, SageMaker uses the default KMS key for Amazon S3 for your role's account. SageMaker uses server-side encryption with KMS-managed keys for OutputDataConfig&. If you use a bucket policy with an  s3:PutObject permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption to  "aws:kms". For more information, see  https://docs.aws.amazon.com/AmazonS3/latest/dev/UsingKMSEncryption.htmlKMS-Managed Encryption Keys in the .Amazon Simple Storage Service Developer Guide.The KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint and UpdateEndpoint' requests. For more information, see  https://docs.aws.amazon.com/kms/latest/developerguide/key-policies.html-Using Key Policies in Amazon Web Services KMS in the :Amazon Web Services Key Management Service Developer Guide.F, F1 - The Amazon S3 bucket to send the core dump to.Famazonka-sagemakerThe Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the core dump data at rest using Amazon S3 server-side encryption. The KmsKeyId& can be any of the following formats: // KMS Key ID &"1234abcd-12ab-34cd-56ef-1234567890ab"*// Amazon Resource Name (ARN) of a KMS Key "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"// KMS Key Alias "alias/ExampleAlias"0// Amazon Resource Name (ARN) of a KMS Key Alias 7"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"If you use a KMS key ID or an alias of your KMS key, the SageMaker execution role must include permissions to call  kms:Encrypt. If you don't provide a KMS key ID, SageMaker uses the default KMS key for Amazon S3 for your role's account. SageMaker uses server-side encryption with KMS-managed keys for OutputDataConfig&. If you use a bucket policy with an  s3:PutObject permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption to  "aws:kms". For more information, see  https://docs.aws.amazon.com/AmazonS3/latest/dev/UsingKMSEncryption.htmlKMS-Managed Encryption Keys in the .Amazon Simple Storage Service Developer Guide.The KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint and UpdateEndpoint' requests. For more information, see  https://docs.aws.amazon.com/kms/latest/developerguide/key-policies.html-Using Key Policies in Amazon Web Services KMS in the :Amazon Web Services Key Management Service Developer Guide.Famazonka-sagemaker.The Amazon S3 bucket to send the core dump to.Famazonka-sagemakerFFFFFFFFFFFFFFF(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? 1FGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';  Gamazonka-sagemakerThe endpoint configuration made by Inference Recommender during a recommendation job.See: G smart constructor.Gamazonka-sagemaker:The name of the endpoint made during a recommendation job.Gamazonka-sagemakerThe name of the production variant (deployed model) made during a recommendation job.Gamazonka-sagemakerThe instance type recommended by Amazon SageMaker Inference Recommender.Gamazonka-sagemaker8The number of instances recommended to launch initially.Gamazonka-sagemakerCreate a value of G" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:G, G= - The name of the endpoint made during a recommendation job.G, G - The name of the production variant (deployed model) made during a recommendation job.G, G - The instance type recommended by Amazon SageMaker Inference Recommender.G, G; - The number of instances recommended to launch initially.Gamazonka-sagemaker:The name of the endpoint made during a recommendation job.Gamazonka-sagemakerThe name of the production variant (deployed model) made during a recommendation job.Gamazonka-sagemakerThe instance type recommended by Amazon SageMaker Inference Recommender.Gamazonka-sagemaker8The number of instances recommended to launch initially.Gamazonka-sagemakerGamazonka-sagemakerGamazonka-sagemakerGamazonka-sagemakerG GGGGGGGGGGG GGGGGGGGGGG(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; wGamazonka-sagemaker-The endpoint configuration for the load test.See: G smart constructor.Gamazonka-sagemaker,The parameter you want to benchmark against.Gamazonka-sagemaker>The inference specification name in the model package version.Gamazonka-sagemaker,The instance types to use for the load test.Gamazonka-sagemakerCreate a value of G" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:G, G/ - The parameter you want to benchmark against.G, G - The inference specification name in the model package version.G, G/ - The instance types to use for the load test.Gamazonka-sagemaker,The parameter you want to benchmark against.Gamazonka-sagemaker>The inference specification name in the model package version.Gamazonka-sagemaker,The instance types to use for the load test.Gamazonka-sagemakerG GGGGGGGGG GGGGGGGGG(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; Gamazonka-sagemaker?Specifies the serverless configuration for an endpoint variant.See: G smart constructor.Gamazonka-sagemakerThe memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB.Gamazonka-sagemakerThe maximum number of concurrent invocations your serverless endpoint can process.Gamazonka-sagemakerCreate a value of G" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:G, G - The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB.G, G - The maximum number of concurrent invocations your serverless endpoint can process.Gamazonka-sagemakerThe memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB.Gamazonka-sagemakerThe maximum number of concurrent invocations your serverless endpoint can process.Gamazonka-sagemakerGamazonka-sagemakerGGGGGGGGGGGGGGG(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';/Hamazonka-sagemakerIdentifies a model that you want to host and the resources chosen to deploy for hosting it. If you are deploying multiple models, tell SageMaker how to distribute traffic among the models by specifying variant weights.See: H smart constructor.Hamazonka-sagemakerThe size of the Elastic Inference (EI) instance to use for the production variant. EI instances provide on-demand GPU computing for inference. For more information, see  7https://docs.aws.amazon.com/sagemaker/latest/dg/ei.html+Using Elastic Inference in Amazon SageMaker.Hamazonka-sagemakerThe timeout value, in seconds, for your inference container to pass health check by SageMaker Hosting. For more information about health check, see  https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-inference-code.html#your-algorithms-inference-algo-ping-requestsHow Your Container Should Respond to Health Check (Ping) Requests.Hamazonka-sagemakerSpecifies configuration for a core dump from the model container when the process crashes.Hamazonka-sagemaker(Number of instances to launch initially.Hamazonka-sagemakerDetermines initial traffic distribution among all of the models that you specify in the endpoint configuration. The traffic to a production variant is determined by the ratio of the  VariantWeight to the sum of all  VariantWeight values across all ProductionVariants. If unspecified, it defaults to 1.0.Hamazonka-sagemakerThe ML compute instance type.Hamazonka-sagemakerThe timeout value, in seconds, to download and extract the model that you want to host from Amazon S3 to the individual inference instance associated with this production variant.Hamazonka-sagemakerThe serverless configuration for an endpoint. Specifies a serverless endpoint configuration instead of an instance-based endpoint configuration.Hamazonka-sagemakerThe size, in GB, of the ML storage volume attached to individual inference instance associated with the production variant. Currenly only Amazon EBS gp2 storage volumes are supported.Hamazonka-sagemaker#The name of the production variant.Hamazonka-sagemakerThe name of the model that you want to host. This is the name that you specified when creating the model.Hamazonka-sagemakerCreate a value of H" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:H, H - The size of the Elastic Inference (EI) instance to use for the production variant. EI instances provide on-demand GPU computing for inference. For more information, see  7https://docs.aws.amazon.com/sagemaker/latest/dg/ei.html+Using Elastic Inference in Amazon SageMaker.H, H - The timeout value, in seconds, for your inference container to pass health check by SageMaker Hosting. For more information about health check, see  https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-inference-code.html#your-algorithms-inference-algo-ping-requestsHow Your Container Should Respond to Health Check (Ping) Requests.H, H - Specifies configuration for a core dump from the model container when the process crashes.H, H+ - Number of instances to launch initially.H, H - Determines initial traffic distribution among all of the models that you specify in the endpoint configuration. The traffic to a production variant is determined by the ratio of the  VariantWeight to the sum of all  VariantWeight values across all ProductionVariants. If unspecified, it defaults to 1.0.H, H - The ML compute instance type.H, H - The timeout value, in seconds, to download and extract the model that you want to host from Amazon S3 to the individual inference instance associated with this production variant.H, H - The serverless configuration for an endpoint. Specifies a serverless endpoint configuration instead of an instance-based endpoint configuration.H, H - The size, in GB, of the ML storage volume attached to individual inference instance associated with the production variant. Currenly only Amazon EBS gp2 storage volumes are supported.H, H& - The name of the production variant.H, H - The name of the model that you want to host. This is the name that you specified when creating the model.Hamazonka-sagemakerThe size of the Elastic Inference (EI) instance to use for the production variant. EI instances provide on-demand GPU computing for inference. For more information, see  7https://docs.aws.amazon.com/sagemaker/latest/dg/ei.html+Using Elastic Inference in Amazon SageMaker.Hamazonka-sagemakerThe timeout value, in seconds, for your inference container to pass health check by SageMaker Hosting. For more information about health check, see  https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-inference-code.html#your-algorithms-inference-algo-ping-requestsHow Your Container Should Respond to Health Check (Ping) Requests.Hamazonka-sagemakerSpecifies configuration for a core dump from the model container when the process crashes.Hamazonka-sagemaker(Number of instances to launch initially.Hamazonka-sagemakerDetermines initial traffic distribution among all of the models that you specify in the endpoint configuration. The traffic to a production variant is determined by the ratio of the  VariantWeight to the sum of all  VariantWeight values across all ProductionVariants. If unspecified, it defaults to 1.0.Hamazonka-sagemakerThe ML compute instance type.Hamazonka-sagemakerThe timeout value, in seconds, to download and extract the model that you want to host from Amazon S3 to the individual inference instance associated with this production variant.Hamazonka-sagemakerThe serverless configuration for an endpoint. Specifies a serverless endpoint configuration instead of an instance-based endpoint configuration.Hamazonka-sagemakerThe size, in GB, of the ML storage volume attached to individual inference instance associated with the production variant. Currenly only Amazon EBS gp2 storage volumes are supported.Hamazonka-sagemaker#The name of the production variant.Hamazonka-sagemakerThe name of the model that you want to host. This is the name that you specified when creating the model.Hamazonka-sagemakerHamazonka-sagemakerHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';z Hamazonka-sagemakerConfiguration information for Amazon SageMaker Debugger system monitoring, framework profiling, and storage paths.See: H smart constructor.Hamazonka-sagemakerConfiguration to turn off Amazon SageMaker Debugger's system monitoring and profiling functionality. To turn it off, set to True.Hamazonka-sagemakerA time interval for capturing system metrics in milliseconds. Available values are 100, 200, 500, 1000 (1 second), 5000 (5 seconds), and 60000 (1 minute) milliseconds. The default value is 500 milliseconds.Hamazonka-sagemakerConfiguration information for capturing framework metrics. Available key strings for different profiling options are DetailedProfilingConfig, PythonProfilingConfig, and DataLoaderProfilingConfig<. The following codes are configuration structures for the ProfilingParameters7 parameter. To learn more about how to configure the ProfilingParameters parameter, see  https://docs.aws.amazon.com/sagemaker/latest/dg/debugger-createtrainingjob-api.htmlUse the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.Hamazonka-sagemakerPath to Amazon S3 storage location for system and framework metrics.Hamazonka-sagemakerCreate a value of H" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:H, H - Configuration to turn off Amazon SageMaker Debugger's system monitoring and profiling functionality. To turn it off, set to True.H, H - A time interval for capturing system metrics in milliseconds. Available values are 100, 200, 500, 1000 (1 second), 5000 (5 seconds), and 60000 (1 minute) milliseconds. The default value is 500 milliseconds.H, H - Configuration information for capturing framework metrics. Available key strings for different profiling options are DetailedProfilingConfig, PythonProfilingConfig, and DataLoaderProfilingConfig<. The following codes are configuration structures for the ProfilingParameters7 parameter. To learn more about how to configure the ProfilingParameters parameter, see  https://docs.aws.amazon.com/sagemaker/latest/dg/debugger-createtrainingjob-api.htmlUse the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.H, H - Path to Amazon S3 storage location for system and framework metrics.Hamazonka-sagemakerConfiguration to turn off Amazon SageMaker Debugger's system monitoring and profiling functionality. To turn it off, set to True.Hamazonka-sagemakerA time interval for capturing system metrics in milliseconds. Available values are 100, 200, 500, 1000 (1 second), 5000 (5 seconds), and 60000 (1 minute) milliseconds. The default value is 500 milliseconds.Hamazonka-sagemakerConfiguration information for capturing framework metrics. Available key strings for different profiling options are DetailedProfilingConfig, PythonProfilingConfig, and DataLoaderProfilingConfig<. The following codes are configuration structures for the ProfilingParameters7 parameter. To learn more about how to configure the ProfilingParameters parameter, see  https://docs.aws.amazon.com/sagemaker/latest/dg/debugger-createtrainingjob-api.htmlUse the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.Hamazonka-sagemakerPath to Amazon S3 storage location for system and framework metrics. HHHHHHHHHHH HHHHHHHHHHH(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';! Hamazonka-sagemakerConfiguration information for updating the Amazon SageMaker Debugger profile parameters, system and framework metrics configurations, and storage paths.See: H smart constructor.Hamazonka-sagemakerTo turn off Amazon SageMaker Debugger monitoring and profiling while a training job is in progress, set to True.Hamazonka-sagemakerA time interval for capturing system metrics in milliseconds. Available values are 100, 200, 500, 1000 (1 second), 5000 (5 seconds), and 60000 (1 minute) milliseconds. The default value is 500 milliseconds.Hamazonka-sagemakerConfiguration information for capturing framework metrics. Available key strings for different profiling options are DetailedProfilingConfig, PythonProfilingConfig, and DataLoaderProfilingConfig<. The following codes are configuration structures for the ProfilingParameters7 parameter. To learn more about how to configure the ProfilingParameters parameter, see  https://docs.aws.amazon.com/sagemaker/latest/dg/debugger-createtrainingjob-api.htmlUse the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.Hamazonka-sagemakerPath to Amazon S3 storage location for system and framework metrics.Hamazonka-sagemakerCreate a value of H" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:H, H - To turn off Amazon SageMaker Debugger monitoring and profiling while a training job is in progress, set to True.H, H - A time interval for capturing system metrics in milliseconds. Available values are 100, 200, 500, 1000 (1 second), 5000 (5 seconds), and 60000 (1 minute) milliseconds. The default value is 500 milliseconds.H, H - Configuration information for capturing framework metrics. Available key strings for different profiling options are DetailedProfilingConfig, PythonProfilingConfig, and DataLoaderProfilingConfig<. The following codes are configuration structures for the ProfilingParameters7 parameter. To learn more about how to configure the ProfilingParameters parameter, see  https://docs.aws.amazon.com/sagemaker/latest/dg/debugger-createtrainingjob-api.htmlUse the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.H, H - Path to Amazon S3 storage location for system and framework metrics.Hamazonka-sagemakerTo turn off Amazon SageMaker Debugger monitoring and profiling while a training job is in progress, set to True.Hamazonka-sagemakerA time interval for capturing system metrics in milliseconds. Available values are 100, 200, 500, 1000 (1 second), 5000 (5 seconds), and 60000 (1 minute) milliseconds. The default value is 500 milliseconds.Hamazonka-sagemakerConfiguration information for capturing framework metrics. Available key strings for different profiling options are DetailedProfilingConfig, PythonProfilingConfig, and DataLoaderProfilingConfig<. The following codes are configuration structures for the ProfilingParameters7 parameter. To learn more about how to configure the ProfilingParameters parameter, see  https://docs.aws.amazon.com/sagemaker/latest/dg/debugger-createtrainingjob-api.htmlUse the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.Hamazonka-sagemakerPath to Amazon S3 storage location for system and framework metrics. HHHHHHHHHHH HHHHHHHHHHH(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';,Hamazonka-sagemaker.Configuration information for profiling rules.See: H smart constructor.Hamazonka-sagemakerThe instance type to deploy a custom rule for profiling a training job.Hamazonka-sagemakerPath to local storage location for output of rules. Defaults to /opt/ml/processing/output/rule/.Hamazonka-sagemaker)Runtime configuration for rule container.Hamazonka-sagemaker-Path to Amazon S3 storage location for rules.Hamazonka-sagemakerThe size, in GB, of the ML storage volume attached to the processing instance.Hamazonka-sagemakerThe name of the rule configuration. It must be unique relative to other rule configuration names.Hamazonka-sagemakerThe Amazon Elastic Container Registry Image for the managed rule evaluation.Hamazonka-sagemakerCreate a value of H" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:H, H - The instance type to deploy a custom rule for profiling a training job.H, H - Path to local storage location for output of rules. Defaults to /opt/ml/processing/output/rule/.H, H, - Runtime configuration for rule container.H, H0 - Path to Amazon S3 storage location for rules.H, H - The size, in GB, of the ML storage volume attached to the processing instance.H, H - The name of the rule configuration. It must be unique relative to other rule configuration names.H, H - The Amazon Elastic Container Registry Image for the managed rule evaluation.Hamazonka-sagemakerThe instance type to deploy a custom rule for profiling a training job.Hamazonka-sagemakerPath to local storage location for output of rules. Defaults to /opt/ml/processing/output/rule/.Hamazonka-sagemaker)Runtime configuration for rule container.Hamazonka-sagemaker-Path to Amazon S3 storage location for rules.Hamazonka-sagemakerThe size, in GB, of the ML storage volume attached to the processing instance.Hamazonka-sagemakerThe name of the rule configuration. It must be unique relative to other rule configuration names.Hamazonka-sagemakerThe Amazon Elastic Container Registry Image for the managed rule evaluation.Hamazonka-sagemakerHamazonka-sagemakerHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?-uHHHHHHHHHHHH(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?.2HHHHHHHHHHHH(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?.IIIIIIIIIIII(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?/ IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';6Iamazonka-sagemakerInformation about a project.See: I smart constructor.Iamazonka-sagemakerThe description of the project.Iamazonka-sagemakerThe name of the project.Iamazonka-sagemaker.The Amazon Resource Name (ARN) of the project.Iamazonka-sagemakerThe ID of the project.Iamazonka-sagemaker&The time that the project was created.Iamazonka-sagemakerThe status of the project.Iamazonka-sagemakerCreate a value of I" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:I, I" - The description of the project.I, I - The name of the project.I, I1 - The Amazon Resource Name (ARN) of the project.I, I - The ID of the project.I, I) - The time that the project was created.I, I - The status of the project.Iamazonka-sagemakerThe description of the project.Iamazonka-sagemakerThe name of the project.Iamazonka-sagemaker.The Amazon Resource Name (ARN) of the project.Iamazonka-sagemakerThe ID of the project.Iamazonka-sagemaker&The time that the project was created.Iamazonka-sagemakerThe status of the project.Iamazonka-sagemakerIamazonka-sagemakerIamazonka-sagemakerIamazonka-sagemakerIamazonka-sagemakerIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';:Iamazonka-sagemaker Part of the SuggestionQuery type. Specifies a hint for retrieving property names that begin with the specified text.See: I smart constructor.Iamazonka-sagemaker#Text that begins a property's name.Iamazonka-sagemakerCreate a value of I" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:I, I& - Text that begins a property's name.Iamazonka-sagemaker#Text that begins a property's name.Iamazonka-sagemakerIIIIIIIIIII(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';?@Iamazonka-sagemaker A property name returned from a GetSearchSuggestions% call that specifies a value in the PropertyNameQuery field.See: I smart constructor.Iamazonka-sagemakerA suggested property name based on what you entered in the search textbox in the Amazon SageMaker console.Iamazonka-sagemakerCreate a value of I" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:I, I - A suggested property name based on what you entered in the search textbox in the Amazon SageMaker console.Iamazonka-sagemakerA suggested property name based on what you entered in the search textbox in the Amazon SageMaker console.IIIIIIIIII(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';D:Iamazonka-sagemakerA key value pair used when you provision a project as a service catalog product. For information, see  https://docs.aws.amazon.com/servicecatalog/latest/adminguide/introduction.html+What is Amazon Web Services Service Catalog.See: I smart constructor.Iamazonka-sagemaker1The key that identifies a provisioning parameter.Iamazonka-sagemaker(The value of the provisioning parameter.Iamazonka-sagemakerCreate a value of I" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:I, I4 - The key that identifies a provisioning parameter.I, I+ - The value of the provisioning parameter.Iamazonka-sagemaker1The key that identifies a provisioning parameter.Iamazonka-sagemaker(The value of the provisioning parameter.IIIIIIIIIIIIII(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';X+Jamazonka-sagemakerContainer for the metadata for a Quality check step. For more information, see the topic on  https://docs.aws.amazon.com/sagemaker/latest/dg/build-and-manage-steps.html#step-type-quality-checkQualityCheck step in the  Amazon SageMaker Developer Guide.See: J smart constructor.Jamazonka-sagemakerThe Amazon S3 URI of the baseline constraints file used for the drift check.Jamazonka-sagemakerThe Amazon S3 URI of the baseline statistics file used for the drift check.Jamazonka-sagemakerThe Amazon S3 URI of the newly calculated baseline constraints file.Jamazonka-sagemakerThe Amazon S3 URI of the newly calculated baseline statistics file.Jamazonka-sagemakerThe Amazon Resource Name (ARN) of the Quality check processing job that was run by this step execution.Jamazonka-sagemaker#The type of the Quality check step.Jamazonka-sagemakerThe model package group name.Jamazonka-sagemakerThis flag indicates if a newly calculated baseline can be accessed through step properties $BaselineUsedForDriftCheckConstraints and #BaselineUsedForDriftCheckStatistics. If it is set to False, the previous baseline of the configured check type must also be available. These can be accessed through the $BaselineUsedForDriftCheckConstraints and $ BaselineUsedForDriftCheckStatistics properties.Jamazonka-sagemakerThis flag indicates if the drift check against the previous baseline will be skipped or not. If it is set to False, the previous baseline of the configured check type must be available.Jamazonka-sagemakerThe Amazon S3 URI of violation report if violations are detected.Jamazonka-sagemakerCreate a value of J" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:J, J - The Amazon S3 URI of the baseline constraints file used for the drift check.J, J - The Amazon S3 URI of the baseline statistics file used for the drift check.J, J - The Amazon S3 URI of the newly calculated baseline constraints file.J, J - The Amazon S3 URI of the newly calculated baseline statistics file.J, J - The Amazon Resource Name (ARN) of the Quality check processing job that was run by this step execution.J, J& - The type of the Quality check step.J, J - The model package group name.J, J - This flag indicates if a newly calculated baseline can be accessed through step properties $BaselineUsedForDriftCheckConstraints and #BaselineUsedForDriftCheckStatistics. If it is set to False, the previous baseline of the configured check type must also be available. These can be accessed through the $BaselineUsedForDriftCheckConstraints and $ BaselineUsedForDriftCheckStatistics properties.J, J - This flag indicates if the drift check against the previous baseline will be skipped or not. If it is set to False, the previous baseline of the configured check type must be available.J, J - The Amazon S3 URI of violation report if violations are detected.Jamazonka-sagemakerThe Amazon S3 URI of the baseline constraints file used for the drift check.Jamazonka-sagemakerThe Amazon S3 URI of the baseline statistics file used for the drift check.Jamazonka-sagemakerThe Amazon S3 URI of the newly calculated baseline constraints file.Jamazonka-sagemakerThe Amazon S3 URI of the newly calculated baseline statistics file.Jamazonka-sagemakerThe Amazon Resource Name (ARN) of the Quality check processing job that was run by this step execution.Jamazonka-sagemaker#The type of the Quality check step.Jamazonka-sagemakerThe model package group name.Jamazonka-sagemakerThis flag indicates if a newly calculated baseline can be accessed through step properties $BaselineUsedForDriftCheckConstraints and #BaselineUsedForDriftCheckStatistics. If it is set to False, the previous baseline of the configured check type must also be available. These can be accessed through the $BaselineUsedForDriftCheckConstraints and $ BaselineUsedForDriftCheckStatistics properties.Jamazonka-sagemakerThis flag indicates if the drift check against the previous baseline will be skipped or not. If it is set to False, the previous baseline of the configured check type must be available.Jamazonka-sagemakerThe Amazon S3 URI of violation report if violations are detected.JJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';g$Jamazonka-sagemakerA set of filters to narrow the set of lineage entities connected to the StartArn(s) returned by the  QueryLineage API action.See: J smart constructor.Jamazonka-sagemaker-Filter the lineage entities connected to the StartArn(s) after the create date.Jamazonka-sagemaker-Filter the lineage entities connected to the StartArn(s) by created date.Jamazonka-sagemaker-Filter the lineage entities connected to the StartArn'(s) by the type of the lineage entity.Jamazonka-sagemaker-Filter the lineage entities connected to the StartArn"(s) after the last modified date.Jamazonka-sagemaker-Filter the lineage entities connected to the StartArn#(s) before the last modified date.Jamazonka-sagemaker-Filter the lineage entities connected to the StartArn(s) by a set if property key value pairs. If multiple pairs are provided, an entity is included in the results if it matches any of the provided pairs.Jamazonka-sagemaker-Filter the lineage entities connected to the StartArn by type. For example: DataSet, Model, Endpoint, or ModelDeployment.Jamazonka-sagemakerCreate a value of J" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:J, J0 - Filter the lineage entities connected to the StartArn(s) after the create date.J, J0 - Filter the lineage entities connected to the StartArn(s) by created date.J, J0 - Filter the lineage entities connected to the StartArn'(s) by the type of the lineage entity.J, J0 - Filter the lineage entities connected to the StartArn"(s) after the last modified date.J, J0 - Filter the lineage entities connected to the StartArn#(s) before the last modified date.J, J0 - Filter the lineage entities connected to the StartArn(s) by a set if property key value pairs. If multiple pairs are provided, an entity is included in the results if it matches any of the provided pairs.J, J0 - Filter the lineage entities connected to the StartArn by type. For example: DataSet, Model, Endpoint, or ModelDeployment.Jamazonka-sagemaker-Filter the lineage entities connected to the StartArn(s) after the create date.Jamazonka-sagemaker-Filter the lineage entities connected to the StartArn(s) by created date.Jamazonka-sagemaker-Filter the lineage entities connected to the StartArn'(s) by the type of the lineage entity.Jamazonka-sagemaker-Filter the lineage entities connected to the StartArn"(s) after the last modified date.Jamazonka-sagemaker-Filter the lineage entities connected to the StartArn#(s) before the last modified date.Jamazonka-sagemaker-Filter the lineage entities connected to the StartArn(s) by a set if property key value pairs. If multiple pairs are provided, an entity is included in the results if it matches any of the provided pairs.Jamazonka-sagemaker-Filter the lineage entities connected to the StartArn by type. For example: DataSet, Model, Endpoint, or ModelDeployment.JJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?h JJJJJJJJJJJJ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?hJJJJJJJJJJJJ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';p Jamazonka-sagemakerA collection of settings that configure user interaction with the RStudioServerPro app. RStudioServerProAppSettings cannot be updated. The RStudioServerPro app must be deleted and a new one created to make any changes.See: J smart constructor.Jamazonka-sagemaker5Indicates whether the current user has access to the RStudioServerPro app.Jamazonka-sagemaker6The level of permissions that the user has within the RStudioServerPro app. This value defaults to `User`. The `Admin` value allows the user access to the RStudio Administrative Dashboard.Jamazonka-sagemakerCreate a value of J" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:J, J8 - Indicates whether the current user has access to the RStudioServerPro app.J, J9 - The level of permissions that the user has within the RStudioServerPro app. This value defaults to `User`. The `Admin` value allows the user access to the RStudio Administrative Dashboard.Jamazonka-sagemaker5Indicates whether the current user has access to the RStudioServerPro app.Jamazonka-sagemaker6The level of permissions that the user has within the RStudioServerPro app. This value defaults to `User`. The `Admin` value allows the user access to the RStudio Administrative Dashboard.JJJJJJJJJJJJJJ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';tJamazonka-sagemakerThe infrastructure configuration for deploying the model to a real-time inference endpoint.See: J smart constructor.Jamazonka-sagemaker+The instance type the model is deployed to.Jamazonka-sagemaker1The number of instances of the type specified by  InstanceType.Jamazonka-sagemakerCreate a value of J" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:J, K. - The instance type the model is deployed to.J, K4 - The number of instances of the type specified by  InstanceType.Kamazonka-sagemaker+The instance type the model is deployed to.Kamazonka-sagemaker1The number of instances of the type specified by  InstanceType.Jamazonka-sagemakerJamazonka-sagemakerJJJJJJKKJJJJJKK(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';{!Kamazonka-sagemakerThe configuration for the infrastructure that the model will be deployed to.See: K smart constructor.Kamazonka-sagemakerThe inference option to which to deploy your model. Possible values are the following:RealTime : Deploy to real-time inference.Kamazonka-sagemakerThe infrastructure configuration for deploying the model to real-time inference.Kamazonka-sagemakerCreate a value of K" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:K, K - The inference option to which to deploy your model. Possible values are the following:RealTime : Deploy to real-time inference.K, K - The infrastructure configuration for deploying the model to real-time inference.Kamazonka-sagemakerThe inference option to which to deploy your model. Possible values are the following:RealTime : Deploy to real-time inference.Kamazonka-sagemakerThe infrastructure configuration for deploying the model to real-time inference.Kamazonka-sagemakerKamazonka-sagemakerKKKKKKKKKKKKKKK(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; Kamazonka-sagemaker3Summary of the deployment configuration of a model.See: K smart constructor.Kamazonka-sagemaker.The name of the Amazon SageMaker Model entity.Kamazonka-sagemakerThe name of the variant.Kamazonka-sagemakerThe configuration of the infrastructure that the model has been deployed to.Kamazonka-sagemakerThe status of deployment for the model variant on the hosted inference endpoint.Creating - Amazon SageMaker is preparing the model variant on the hosted inference endpoint. InService - The model variant is running on the hosted inference endpoint.Updating - Amazon SageMaker is updating the model variant on the hosted inference endpoint.Deleting - Amazon SageMaker is deleting the model variant on the hosted inference endpoint.Deleted - The model variant has been deleted on the hosted inference endpoint. This can only happen after stopping the experiment.Kamazonka-sagemakerCreate a value of K" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:K, K1 - The name of the Amazon SageMaker Model entity.K, K - The name of the variant.K, K - The configuration of the infrastructure that the model has been deployed to.K, K - The status of deployment for the model variant on the hosted inference endpoint.Creating - Amazon SageMaker is preparing the model variant on the hosted inference endpoint. InService - The model variant is running on the hosted inference endpoint.Updating - Amazon SageMaker is updating the model variant on the hosted inference endpoint.Deleting - Amazon SageMaker is deleting the model variant on the hosted inference endpoint.Deleted - The model variant has been deleted on the hosted inference endpoint. This can only happen after stopping the experiment.Kamazonka-sagemaker.The name of the Amazon SageMaker Model entity.Kamazonka-sagemakerThe name of the variant.Kamazonka-sagemakerThe configuration of the infrastructure that the model has been deployed to.Kamazonka-sagemakerThe status of deployment for the model variant on the hosted inference endpoint.Creating - Amazon SageMaker is preparing the model variant on the hosted inference endpoint. InService - The model variant is running on the hosted inference endpoint.Updating - Amazon SageMaker is updating the model variant on the hosted inference endpoint.Deleting - Amazon SageMaker is deleting the model variant on the hosted inference endpoint.Deleted - The model variant has been deleted on the hosted inference endpoint. This can only happen after stopping the experiment.Kamazonka-sagemakerKamazonka-sagemakerKamazonka-sagemakerKamazonka-sagemakerK KKKKKKKKKKK KKKKKKKKKKK(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';9Kamazonka-sagemaker=Contains information about the deployment options of a model.See: K smart constructor.Kamazonka-sagemaker.The name of the Amazon SageMaker Model entity.Kamazonka-sagemakerThe name of the variant.Kamazonka-sagemakerThe configuration for the infrastructure that the model will be deployed to.Kamazonka-sagemakerCreate a value of K" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:K, K1 - The name of the Amazon SageMaker Model entity.K, K - The name of the variant.K, K - The configuration for the infrastructure that the model will be deployed to.Kamazonka-sagemaker.The name of the Amazon SageMaker Model entity.Kamazonka-sagemakerThe name of the variant.Kamazonka-sagemakerThe configuration for the infrastructure that the model will be deployed to.Kamazonka-sagemakerKamazonka-sagemakerKamazonka-sagemakerK KKKKKKKKK KKKKKKKKK(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';qKamazonka-sagemakerProvides information about the output configuration for the compiled model.See: K smart constructor.Kamazonka-sagemakerIdentifies the Amazon S3 bucket where you want SageMaker to store the compiled model artifacts.Kamazonka-sagemakerCreate a value of K" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:K, K - Identifies the Amazon S3 bucket where you want SageMaker to store the compiled model artifacts.Kamazonka-sagemakerIdentifies the Amazon S3 bucket where you want SageMaker to store the compiled model artifacts.KKKKKKKKKK(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';Kamazonka-sagemakerProvides information about the output configuration for the compiled model.See: K smart constructor.Kamazonka-sagemakerProvides information about the output configuration for the compiled model.Kamazonka-sagemakerThe Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt your output artifacts with Amazon S3 server-side encryption. The SageMaker execution role must have kms:GenerateDataKey permission.The KmsKeyId% can be any of the following formats: // KMS Key ID &"1234abcd-12ab-34cd-56ef-1234567890ab"*// Amazon Resource Name (ARN) of a KMS Key "arn:aws:kms:::key/"// KMS Key Alias "alias/ExampleAlias"0// Amazon Resource Name (ARN) of a KMS Key Alias 5"arn:aws:kms:::alias/"1For more information about key identifiers, see  https://docs.aws.amazon.com/kms/latest/developerguide/concepts.html#key-id-key-idKey identifiers (KeyID) in the Amazon Web Services Key Management Service (Amazon Web Services KMS) documentation.Kamazonka-sagemakerCreate a value of K" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:K, K - Provides information about the output configuration for the compiled model.K, K - The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt your output artifacts with Amazon S3 server-side encryption. The SageMaker execution role must have kms:GenerateDataKey permission.The KmsKeyId% can be any of the following formats: // KMS Key ID &"1234abcd-12ab-34cd-56ef-1234567890ab"*// Amazon Resource Name (ARN) of a KMS Key "arn:aws:kms:::key/"// KMS Key Alias "alias/ExampleAlias"0// Amazon Resource Name (ARN) of a KMS Key Alias 5"arn:aws:kms:::alias/"1For more information about key identifiers, see  https://docs.aws.amazon.com/kms/latest/developerguide/concepts.html#key-id-key-idKey identifiers (KeyID) in the Amazon Web Services Key Management Service (Amazon Web Services KMS) documentation.Kamazonka-sagemakerProvides information about the output configuration for the compiled model.Kamazonka-sagemakerThe Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt your output artifacts with Amazon S3 server-side encryption. The SageMaker execution role must have kms:GenerateDataKey permission.The KmsKeyId% can be any of the following formats: // KMS Key ID &"1234abcd-12ab-34cd-56ef-1234567890ab"*// Amazon Resource Name (ARN) of a KMS Key "arn:aws:kms:::key/"// KMS Key Alias "alias/ExampleAlias"0// Amazon Resource Name (ARN) of a KMS Key Alias 5"arn:aws:kms:::alias/"1For more information about key identifiers, see  https://docs.aws.amazon.com/kms/latest/developerguide/concepts.html#key-id-key-idKey identifiers (KeyID) in the Amazon Web Services Key Management Service (Amazon Web Services KMS) documentation.KKKKKKKKKKKKKK(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';{Kamazonka-sagemaker;The configuration for the payload for a recommendation job.See: K smart constructor.Kamazonka-sagemakerThe Amazon Simple Storage Service (Amazon S3) path where the sample payload is stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).Kamazonka-sagemaker,The supported MIME types for the input data.Kamazonka-sagemakerCreate a value of K" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:K, K - The Amazon Simple Storage Service (Amazon S3) path where the sample payload is stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).K, K/ - The supported MIME types for the input data.Kamazonka-sagemakerThe Amazon Simple Storage Service (Amazon S3) path where the sample payload is stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).Kamazonka-sagemaker,The supported MIME types for the input data.KKKKKKKKKKKKKK(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';Kamazonka-sagemakerSpecifies mandatory fields for running an Inference Recommender job directly in the  https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateInferenceRecommendationsJob.html!CreateInferenceRecommendationsJob API. The fields specified in ContainerConfig> override the corresponding fields in the model package. Use ContainerConfig if you want to specify these fields for the recommendation job but don't want to edit them in your model package.See: K smart constructor.Kamazonka-sagemaker (default), input operations are managed by Amazon SageMaker.Namazonka-sagemaker-Configuration for a Dataset Definition input.Namazonka-sagemakerConfiguration for downloading input data from Amazon S3 into the processing container.Namazonka-sagemaker&The name for the processing job input.Namazonka-sagemakerCreate a value of N" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:N, N - When True, input operations such as data download are managed natively by the processing job application. When False> (default), input operations are managed by Amazon SageMaker.N, N0 - Configuration for a Dataset Definition input.N, N - Configuration for downloading input data from Amazon S3 into the processing container.N, N) - The name for the processing job input.Namazonka-sagemakerWhen True, input operations such as data download are managed natively by the processing job application. When False> (default), input operations are managed by Amazon SageMaker.Namazonka-sagemaker-Configuration for a Dataset Definition input.Namazonka-sagemakerConfiguration for downloading input data from Amazon S3 into the processing container.Namazonka-sagemaker&The name for the processing job input.Namazonka-sagemakerN NNNNNNNNNNN NNNNNNNNNNN(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';Namazonka-sagemaker'Metadata for a register model job step.See: N smart constructor.Namazonka-sagemaker4The Amazon Resource Name (ARN) of the model package.Namazonka-sagemakerCreate a value of N" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:N, N7 - The Amazon Resource Name (ARN) of the model package.Namazonka-sagemaker4The Amazon Resource Name (ARN) of the model package.NNNNNNNNNN(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';"Namazonka-sagemaker!Contains input values for a task.See: N smart constructor.Namazonka-sagemakerA JSON object that contains values for the variables defined in the template. It is made available to the template under the substitution variable  task.input). For example, if you define a variable task.input.text in your template, you can supply the variable in the JSON object as "text": "sample text".Namazonka-sagemakerCreate a value of N" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:N, N - A JSON object that contains values for the variables defined in the template. It is made available to the template under the substitution variable  task.input). For example, if you define a variable task.input.text in your template, you can supply the variable in the JSON object as "text": "sample text".Namazonka-sagemakerA JSON object that contains values for the variables defined in the template. It is made available to the template under the substitution variable  task.input). For example, if you define a variable task.input.text in your template, you can supply the variable in the JSON object as "text": "sample text".Namazonka-sagemakerNNNNNNNNNNN(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';'ZOamazonka-sagemakerA description of an error that occurred while rendering the template.See: O smart constructor.Oamazonka-sagemaker3A unique identifier for a specific class of errors.Oamazonka-sagemaker.A human-readable message describing the error.Oamazonka-sagemakerCreate a value of O" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:O, O6 - A unique identifier for a specific class of errors.O, O1 - A human-readable message describing the error.Oamazonka-sagemaker3A unique identifier for a specific class of errors.Oamazonka-sagemaker.A human-readable message describing the error.Oamazonka-sagemakerOamazonka-sagemakerOOOOOOOOOOOOOOO(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?(OOOOOOOOOOOO(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';1Oamazonka-sagemakerSpecifies an authentication configuration for the private docker registry where your model image is hosted. Specify a value for this property only if you specified Vpc as the value for the RepositoryAccessMode field of the  ImageConfig& object that you passed to a call to  CreateModel and the private Docker registry where the model image is hosted requires authentication.See: O smart constructor.Oamazonka-sagemakerThe Amazon Resource Name (ARN) of an Amazon Web Services Lambda function that provides credentials to authenticate to the private Docker registry where your model image is hosted. For information about how to create an Amazon Web Services Lambda function, see  https://docs.aws.amazon.com/lambda/latest/dg/getting-started-create-function.html)Create a Lambda function with the console in the *Amazon Web Services Lambda Developer Guide.Oamazonka-sagemakerCreate a value of O" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:O, O - The Amazon Resource Name (ARN) of an Amazon Web Services Lambda function that provides credentials to authenticate to the private Docker registry where your model image is hosted. For information about how to create an Amazon Web Services Lambda function, see  https://docs.aws.amazon.com/lambda/latest/dg/getting-started-create-function.html)Create a Lambda function with the console in the *Amazon Web Services Lambda Developer Guide.Oamazonka-sagemakerThe Amazon Resource Name (ARN) of an Amazon Web Services Lambda function that provides credentials to authenticate to the private Docker registry where your model image is hosted. For information about how to create an Amazon Web Services Lambda function, see  https://docs.aws.amazon.com/lambda/latest/dg/getting-started-create-function.html)Create a Lambda function with the console in the *Amazon Web Services Lambda Developer Guide.Oamazonka-sagemakerOOOOOOOOOOO(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';;Oamazonka-sagemakerSpecifies whether the model container is in Amazon ECR or a private Docker registry accessible from your Amazon Virtual Private Cloud (VPC).See: O smart constructor.Oamazonka-sagemaker(Optional) Specifies an authentication configuration for the private docker registry where your model image is hosted. Specify a value for this property only if you specified Vpc as the value for the RepositoryAccessMode field, and the private Docker registry where the model image is hosted requires authentication.Oamazonka-sagemaker(Set this to one of the following values:Platform+ - The model image is hosted in Amazon ECR.Vpc - The model image is hosted in a private Docker registry in your VPC.Oamazonka-sagemakerCreate a value of O" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:O, O - (Optional) Specifies an authentication configuration for the private docker registry where your model image is hosted. Specify a value for this property only if you specified Vpc as the value for the RepositoryAccessMode field, and the private Docker registry where the model image is hosted requires authentication.O, O+ - Set this to one of the following values:Platform+ - The model image is hosted in Amazon ECR.Vpc - The model image is hosted in a private Docker registry in your VPC.Oamazonka-sagemaker(Optional) Specifies an authentication configuration for the private docker registry where your model image is hosted. Specify a value for this property only if you specified Vpc as the value for the RepositoryAccessMode field, and the private Docker registry where the model image is hosted requires authentication.Oamazonka-sagemaker(Set this to one of the following values:Platform+ - The model image is hosted in Amazon ECR.Vpc - The model image is hosted in a private Docker registry in your VPC.Oamazonka-sagemakerOOOOOOOOOOOOOOO(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';mOamazonka-sagemaker5Describes the container, as part of model definition.See: O smart constructor.Oamazonka-sagemaker:This parameter is ignored for models that contain only a PrimaryContainer.When a ContainerDefinition is part of an inference pipeline, the value of the parameter uniquely identifies the container for the purposes of logging and metrics. For information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/inference-pipeline-logs-metrics.html5Use Logs and Metrics to Monitor an Inference Pipeline:. If you don't specify a value for this parameter for a ContainerDefinition that is part of an inference pipeline, a unique name is automatically assigned based on the position of the ContainerDefinition2 in the pipeline. If you specify a value for the ContainerHostName for any ContainerDefinition that is part of an inference pipeline, you must specify a value for the ContainerHostName parameter of every ContainerDefinition in that pipeline.Oamazonka-sagemakerThe environment variables to set in the Docker container. Each key and value in the  Environment string to string map can have length of up to 1024. We support up to 16 entries in the map.Oamazonka-sagemakerThe path where inference code is stored. This can be either in Amazon EC2 Container Registry or in a Docker registry that is accessible from the same VPC that you configure for your endpoint. If you are using your own custom algorithm instead of an algorithm provided by SageMaker, the inference code must meet SageMaker requirements. SageMaker supports both registry/repository[:tag] and registry/repository[@digest]1 image path formats. For more information, see https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms.html/Using Your Own Algorithms with Amazon SageMakerOamazonka-sagemakerSpecifies whether the model container is in Amazon ECR or a private Docker registry accessible from your Amazon Virtual Private Cloud (VPC). For information about storing containers in a private Docker registry, see https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-containers-inference-private.htmlUse a Private Docker Registry for Real-Time Inference ContainersOamazonka-sagemaker>The inference specification name in the model package version.Oamazonka-sagemaker>Whether the container hosts a single model or multiple models.Oamazonka-sagemakerThe S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix). The S3 path is required for SageMaker built-in algorithms, but not if you use your own algorithms. For more information on built-in algorithms, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-algo-docker-registry-paths.htmlCommon Parameters.The model artifacts must be in an S3 bucket that is in the same region as the model or endpoint you are creating.If you provide a value for this parameter, SageMaker uses Amazon Web Services Security Token Service to download model artifacts from the S3 path you provide. Amazon Web Services STS is activated in your IAM user account by default. If you previously deactivated Amazon Web Services STS for a region, you need to reactivate Amazon Web Services STS for that region. For more information, see  https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp_enable-regions.htmlActivating and Deactivating Amazon Web Services STS in an Amazon Web Services Region in the =Amazon Web Services Identity and Access Management User Guide.If you use a built-in algorithm to create a model, SageMaker requires that you provide a S3 path to the model artifacts in  ModelDataUrl.Oamazonka-sagemakerThe name or Amazon Resource Name (ARN) of the model package to use to create the model.Oamazonka-sagemaker=Specifies additional configuration for multi-model endpoints.Oamazonka-sagemakerCreate a value of O" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:O, O= - This parameter is ignored for models that contain only a PrimaryContainer.When a ContainerDefinition is part of an inference pipeline, the value of the parameter uniquely identifies the container for the purposes of logging and metrics. For information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/inference-pipeline-logs-metrics.html5Use Logs and Metrics to Monitor an Inference Pipeline:. If you don't specify a value for this parameter for a ContainerDefinition that is part of an inference pipeline, a unique name is automatically assigned based on the position of the ContainerDefinition2 in the pipeline. If you specify a value for the ContainerHostName for any ContainerDefinition that is part of an inference pipeline, you must specify a value for the ContainerHostName parameter of every ContainerDefinition in that pipeline.O, O - The environment variables to set in the Docker container. Each key and value in the  Environment string to string map can have length of up to 1024. We support up to 16 entries in the map.O, O - The path where inference code is stored. This can be either in Amazon EC2 Container Registry or in a Docker registry that is accessible from the same VPC that you configure for your endpoint. If you are using your own custom algorithm instead of an algorithm provided by SageMaker, the inference code must meet SageMaker requirements. SageMaker supports both registry/repository[:tag] and registry/repository[@digest]1 image path formats. For more information, see https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms.html/Using Your Own Algorithms with Amazon SageMakerO, O - Specifies whether the model container is in Amazon ECR or a private Docker registry accessible from your Amazon Virtual Private Cloud (VPC). For information about storing containers in a private Docker registry, see https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-containers-inference-private.htmlUse a Private Docker Registry for Real-Time Inference ContainersO, O - The inference specification name in the model package version.O, O - Whether the container hosts a single model or multiple models.O, O - The S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix). The S3 path is required for SageMaker built-in algorithms, but not if you use your own algorithms. For more information on built-in algorithms, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-algo-docker-registry-paths.htmlCommon Parameters.The model artifacts must be in an S3 bucket that is in the same region as the model or endpoint you are creating.If you provide a value for this parameter, SageMaker uses Amazon Web Services Security Token Service to download model artifacts from the S3 path you provide. Amazon Web Services STS is activated in your IAM user account by default. If you previously deactivated Amazon Web Services STS for a region, you need to reactivate Amazon Web Services STS for that region. For more information, see  https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp_enable-regions.htmlActivating and Deactivating Amazon Web Services STS in an Amazon Web Services Region in the =Amazon Web Services Identity and Access Management User Guide.If you use a built-in algorithm to create a model, SageMaker requires that you provide a S3 path to the model artifacts in  ModelDataUrl.O, O - The name or Amazon Resource Name (ARN) of the model package to use to create the model.O, O - Specifies additional configuration for multi-model endpoints.Oamazonka-sagemaker:This parameter is ignored for models that contain only a PrimaryContainer.When a ContainerDefinition is part of an inference pipeline, the value of the parameter uniquely identifies the container for the purposes of logging and metrics. For information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/inference-pipeline-logs-metrics.html5Use Logs and Metrics to Monitor an Inference Pipeline:. If you don't specify a value for this parameter for a ContainerDefinition that is part of an inference pipeline, a unique name is automatically assigned based on the position of the ContainerDefinition2 in the pipeline. If you specify a value for the ContainerHostName for any ContainerDefinition that is part of an inference pipeline, you must specify a value for the ContainerHostName parameter of every ContainerDefinition in that pipeline.Oamazonka-sagemakerThe environment variables to set in the Docker container. Each key and value in the  Environment string to string map can have length of up to 1024. We support up to 16 entries in the map.Oamazonka-sagemakerThe path where inference code is stored. This can be either in Amazon EC2 Container Registry or in a Docker registry that is accessible from the same VPC that you configure for your endpoint. If you are using your own custom algorithm instead of an algorithm provided by SageMaker, the inference code must meet SageMaker requirements. SageMaker supports both registry/repository[:tag] and registry/repository[@digest]1 image path formats. For more information, see https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms.html/Using Your Own Algorithms with Amazon SageMakerOamazonka-sagemakerSpecifies whether the model container is in Amazon ECR or a private Docker registry accessible from your Amazon Virtual Private Cloud (VPC). For information about storing containers in a private Docker registry, see https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-containers-inference-private.htmlUse a Private Docker Registry for Real-Time Inference ContainersOamazonka-sagemaker>The inference specification name in the model package version.Oamazonka-sagemaker>Whether the container hosts a single model or multiple models.Oamazonka-sagemakerThe S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix). The S3 path is required for SageMaker built-in algorithms, but not if you use your own algorithms. For more information on built-in algorithms, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-algo-docker-registry-paths.htmlCommon Parameters.The model artifacts must be in an S3 bucket that is in the same region as the model or endpoint you are creating.If you provide a value for this parameter, SageMaker uses Amazon Web Services Security Token Service to download model artifacts from the S3 path you provide. Amazon Web Services STS is activated in your IAM user account by default. If you previously deactivated Amazon Web Services STS for a region, you need to reactivate Amazon Web Services STS for that region. For more information, see  https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp_enable-regions.htmlActivating and Deactivating Amazon Web Services STS in an Amazon Web Services Region in the =Amazon Web Services Identity and Access Management User Guide.If you use a built-in algorithm to create a model, SageMaker requires that you provide a S3 path to the model artifacts in  ModelDataUrl.Oamazonka-sagemakerThe name or Amazon Resource Name (ARN) of the model package to use to create the model.Oamazonka-sagemaker=Specifies additional configuration for multi-model endpoints.OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';pOamazonka-sagemakerThe resolved attributes.See: O smart constructor.Oamazonka-sagemakerThe problem type.Oamazonka-sagemakerCreate a value of O" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:O, O - Undocumented member.O, O - Undocumented member.O, O - The problem type.Oamazonka-sagemakerUndocumented member.Oamazonka-sagemakerUndocumented member.Oamazonka-sagemakerThe problem type. OOOOOOOOO OOOOOOOOO(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';uvOamazonka-sagemakerThe ResourceConfig to update KeepAlivePeriodInSeconds. Other fields in the ResourceConfig cannot be updated.See: O smart constructor.Oamazonka-sagemakerThe KeepAlivePeriodInSeconds value specified in the ResourceConfig to update.Oamazonka-sagemakerCreate a value of O" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:O, O - The KeepAlivePeriodInSeconds value specified in the ResourceConfig to update.Oamazonka-sagemakerThe KeepAlivePeriodInSeconds value specified in the ResourceConfig to update.Oamazonka-sagemakerOOOOOOOOOOO(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';{Oamazonka-sagemakerSpecifies the maximum number of training jobs and parallel training jobs that a hyperparameter tuning job can launch.See: P smart constructor.Oamazonka-sagemakerThe maximum number of training jobs that a hyperparameter tuning job can launch.Oamazonka-sagemakerThe maximum number of concurrent training jobs that a hyperparameter tuning job can launch.Pamazonka-sagemakerCreate a value of O" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:O, P - The maximum number of training jobs that a hyperparameter tuning job can launch.O, P - The maximum number of concurrent training jobs that a hyperparameter tuning job can launch.Pamazonka-sagemakerThe maximum number of training jobs that a hyperparameter tuning job can launch.Pamazonka-sagemakerThe maximum number of concurrent training jobs that a hyperparameter tuning job can launch.Pamazonka-sagemakerOOOOOPPPOOOOPPP(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; Pamazonka-sagemakerSpecifies the ARN's of a SageMaker image and SageMaker image version, and the instance type that the version runs on.See: P smart constructor.Pamazonka-sagemaker1The instance type that the image version runs on.JupyterServer apps only support the system value.For KernelGateway apps, the system value is translated to  ml.t3.medium. KernelGateway apps also support all other values for available instance types.Pamazonka-sagemakerThe Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.Pamazonka-sagemakerThe ARN of the SageMaker image that the image version belongs to.Pamazonka-sagemaker5The ARN of the image version created on the instance.Pamazonka-sagemakerCreate a value of P" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:P, P4 - The instance type that the image version runs on.JupyterServer apps only support the system value.For KernelGateway apps, the system value is translated to  ml.t3.medium. KernelGateway apps also support all other values for available instance types.P, P - The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.P, P - The ARN of the SageMaker image that the image version belongs to.P, P8 - The ARN of the image version created on the instance.Pamazonka-sagemaker1The instance type that the image version runs on.JupyterServer apps only support the system value.For KernelGateway apps, the system value is translated to  ml.t3.medium. KernelGateway apps also support all other values for available instance types.Pamazonka-sagemakerThe Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.Pamazonka-sagemakerThe ARN of the SageMaker image that the image version belongs to.Pamazonka-sagemaker5The ARN of the image version created on the instance. PPPPPPPPPPP PPPPPPPPPPP(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';@ Pamazonka-sagemakerA collection of settings that update the current configuration for the RStudioServerPro Domain-level app.See: P smart constructor.Pamazonka-sagemaker,A URL pointing to an RStudio Connect server.Pamazonka-sagemaker4A URL pointing to an RStudio Package Manager server.Pamazonka-sagemakerThe execution role for the RStudioServerPro Domain-level app.Pamazonka-sagemakerCreate a value of P" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:P, P - Undocumented member.P, P/ - A URL pointing to an RStudio Connect server.P, P7 - A URL pointing to an RStudio Package Manager server.P, P - The execution role for the RStudioServerPro Domain-level app.Pamazonka-sagemakerUndocumented member.Pamazonka-sagemaker,A URL pointing to an RStudio Connect server.Pamazonka-sagemaker4A URL pointing to an RStudio Package Manager server.Pamazonka-sagemakerThe execution role for the RStudioServerPro Domain-level app.Pamazonka-sagemakerP PPPPPPPPPPP PPPPPPPPPPP(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';gPamazonka-sagemakerA collection of Domain" configuration settings to update.See: P smart constructor.Pamazonka-sagemakerThe configuration for attaching a SageMaker user profile name to the execution role as a  https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp_control-access_monitor.htmlsts:SourceIdentity key. This configuration can only be modified if there are no apps in the  InService or Pending state.Pamazonka-sagemakerA collection of RStudioServerPro% Domain-level app settings to update.Pamazonka-sagemakerThe security groups for the Amazon Virtual Private Cloud that the Domain uses for communication between Domain-level apps and user apps.Pamazonka-sagemakerCreate a value of P" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:P, P - The configuration for attaching a SageMaker user profile name to the execution role as a  https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp_control-access_monitor.htmlsts:SourceIdentity key. This configuration can only be modified if there are no apps in the  InService or Pending state.P, P - A collection of RStudioServerPro% Domain-level app settings to update.P, P - The security groups for the Amazon Virtual Private Cloud that the Domain uses for communication between Domain-level apps and user apps.Pamazonka-sagemakerThe configuration for attaching a SageMaker user profile name to the execution role as a  https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp_control-access_monitor.htmlsts:SourceIdentity key. This configuration can only be modified if there are no apps in the  InService or Pending state.Pamazonka-sagemakerA collection of RStudioServerPro% Domain-level app settings to update.Pamazonka-sagemakerThe security groups for the Amazon Virtual Private Cloud that the Domain uses for communication between Domain-level apps and user apps. PPPPPPPPP PPPPPPPPP(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; Pamazonka-sagemaker,A collection of settings that configure the RStudioServerPro Domain-level app.See: P smart constructor.Pamazonka-sagemaker,A URL pointing to an RStudio Connect server.Pamazonka-sagemaker4A URL pointing to an RStudio Package Manager server.Pamazonka-sagemaker&The ARN of the execution role for the RStudioServerPro Domain-level app.Pamazonka-sagemakerCreate a value of P" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:P, P - Undocumented member.P, P/ - A URL pointing to an RStudio Connect server.P, P7 - A URL pointing to an RStudio Package Manager server.P, P) - The ARN of the execution role for the RStudioServerPro Domain-level app.Pamazonka-sagemakerUndocumented member.Pamazonka-sagemaker,A URL pointing to an RStudio Connect server.Pamazonka-sagemaker4A URL pointing to an RStudio Package Manager server.Pamazonka-sagemaker&The ARN of the execution role for the RStudioServerPro Domain-level app.Pamazonka-sagemakerP PPPPPPPPPPP PPPPPPPPPPP(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';Pamazonka-sagemaker+A collection of settings that apply to the SageMaker Domain,. These settings are specified through the  CreateDomain API call.See: P smart constructor.Pamazonka-sagemakerThe configuration for attaching a SageMaker user profile name to the execution role as a  https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp_control-access_monitor.htmlsts:SourceIdentity key.Pamazonka-sagemaker,A collection of settings that configure the RStudioServerPro Domain-level app.Pamazonka-sagemakerThe security groups for the Amazon Virtual Private Cloud that the Domain uses for communication between Domain-level apps and user apps.Pamazonka-sagemakerCreate a value of P" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:P, P - The configuration for attaching a SageMaker user profile name to the execution role as a  https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp_control-access_monitor.htmlsts:SourceIdentity key.P, P/ - A collection of settings that configure the RStudioServerPro Domain-level app.P, P - The security groups for the Amazon Virtual Private Cloud that the Domain uses for communication between Domain-level apps and user apps.Pamazonka-sagemakerThe configuration for attaching a SageMaker user profile name to the execution role as a  https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp_control-access_monitor.htmlsts:SourceIdentity key.Pamazonka-sagemaker,A collection of settings that configure the RStudioServerPro Domain-level app.Pamazonka-sagemakerThe security groups for the Amazon Virtual Private Cloud that the Domain uses for communication between Domain-level apps and user apps. PPPPPPPPP PPPPPPPPP(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';5Pamazonka-sagemaker*A collection of settings that apply to an RSessionGateway app.See: P smart constructor.Pamazonka-sagemakerA list of custom SageMaker images that are configured to run as a RSession app.Pamazonka-sagemakerCreate a value of P" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:P, P - A list of custom SageMaker images that are configured to run as a RSession app.P, P - Undocumented member.Pamazonka-sagemakerA list of custom SageMaker images that are configured to run as a RSession app.Pamazonka-sagemakerUndocumented member.PPPPPPPPPPPPPP(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';Pamazonka-sagemakerThe KernelGateway app settings.See: P smart constructor.Pamazonka-sagemakerA list of custom SageMaker images that are configured to run as a KernelGateway app.Pamazonka-sagemakerThe default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the KernelGateway app.The Amazon SageMaker Studio UI does not use the default instance type value set here. The default instance type set here is used when Apps are created using the Amazon Web Services Command Line Interface or Amazon Web Services CloudFormation and the instance type parameter value is not passed.Pamazonka-sagemakerThe Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the the user profile or domain.+To remove a Lifecycle Config, you must set LifecycleConfigArns to an empty list.Pamazonka-sagemakerCreate a value of P" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:P, P - A list of custom SageMaker images that are configured to run as a KernelGateway app.P, P - The default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the KernelGateway app.The Amazon SageMaker Studio UI does not use the default instance type value set here. The default instance type set here is used when Apps are created using the Amazon Web Services Command Line Interface or Amazon Web Services CloudFormation and the instance type parameter value is not passed.P, P - The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the the user profile or domain.+To remove a Lifecycle Config, you must set LifecycleConfigArns to an empty list.Pamazonka-sagemakerA list of custom SageMaker images that are configured to run as a KernelGateway app.Pamazonka-sagemakerThe default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the KernelGateway app.The Amazon SageMaker Studio UI does not use the default instance type value set here. The default instance type set here is used when Apps are created using the Amazon Web Services Command Line Interface or Amazon Web Services CloudFormation and the instance type parameter value is not passed.Pamazonka-sagemakerThe Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the the user profile or domain.+To remove a Lifecycle Config, you must set LifecycleConfigArns to an empty list. PPPPPPPPP PPPPPPPPP(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';Qamazonka-sagemakerThe JupyterServer app settings.See: Q smart constructor.Qamazonka-sagemakerA list of Git repositories that SageMaker automatically displays to users for cloning in the JupyterServer application.Qamazonka-sagemakerThe default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the JupyterServer app. If you use the LifecycleConfigArns1 parameter, then this parameter is also required.Qamazonka-sagemakerThe Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the JupyterServerApp. If you use this parameter, the DefaultResourceSpec parameter is also required.+To remove a Lifecycle Config, you must set LifecycleConfigArns to an empty list.Qamazonka-sagemakerCreate a value of Q" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:Q, Q - A list of Git repositories that SageMaker automatically displays to users for cloning in the JupyterServer application.Q, Q - The default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the JupyterServer app. If you use the LifecycleConfigArns1 parameter, then this parameter is also required.Q, Q - The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the JupyterServerApp. If you use this parameter, the DefaultResourceSpec parameter is also required.+To remove a Lifecycle Config, you must set LifecycleConfigArns to an empty list.Qamazonka-sagemakerA list of Git repositories that SageMaker automatically displays to users for cloning in the JupyterServer application.Qamazonka-sagemakerThe default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the JupyterServer app. If you use the LifecycleConfigArns1 parameter, then this parameter is also required.Qamazonka-sagemakerThe Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the JupyterServerApp. If you use this parameter, the DefaultResourceSpec parameter is also required.+To remove a Lifecycle Config, you must set LifecycleConfigArns to an empty list. QQQQQQQQQ QQQQQQQQQ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';=Qamazonka-sagemakerA collection of settings that apply to spaces created in the Domain.See: Q smart constructor.Qamazonka-sagemaker!The execution role for the space.Qamazonka-sagemakerThe security groups for the Amazon Virtual Private Cloud that the space uses for communication.Qamazonka-sagemakerCreate a value of Q" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:Q, Q$ - The execution role for the space.Q, Q - Undocumented member.Q, Q - Undocumented member.Q, Q - The security groups for the Amazon Virtual Private Cloud that the space uses for communication.Qamazonka-sagemaker!The execution role for the space.Qamazonka-sagemakerUndocumented member.Qamazonka-sagemakerUndocumented member.Qamazonka-sagemakerThe security groups for the Amazon Virtual Private Cloud that the space uses for communication. QQQQQQQQQQQ QQQQQQQQQQQ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?QQQQQQQQQQQQQQQQQQ!QQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?QQQQQQQQQQQQ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';Qamazonka-sagemakerThe retention policy for data stored on an Amazon Elastic File System (EFS) volume.See: Q smart constructor.Qamazonka-sagemakerThe default is Retain=, which specifies to keep the data stored on the EFS volume.Specify Delete- to delete the data stored on the EFS volume.Qamazonka-sagemakerCreate a value of Q" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:Q, Q - The default is Retain=, which specifies to keep the data stored on the EFS volume.Specify Delete- to delete the data stored on the EFS volume.Qamazonka-sagemakerThe default is Retain=, which specifies to keep the data stored on the EFS volume.Specify Delete- to delete the data stored on the EFS volume.QQQQQQQQQQ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';ќQamazonka-sagemaker?The retry strategy to use when a training job fails due to an InternalServerError.  RetryStrategy is specified as part of the CreateTrainingJob and CreateHyperParameterTuningJob requests. You can add the StoppingCondition parameter to the request to limit the training time for the complete job.See: Q smart constructor.Qamazonka-sagemakerThe number of times to retry the job. When the job is retried, it's SecondaryStatus is changed to STARTING.Qamazonka-sagemakerCreate a value of Q" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:Q, Q - The number of times to retry the job. When the job is retried, it's SecondaryStatus is changed to STARTING.Qamazonka-sagemakerThe number of times to retry the job. When the job is retried, it's SecondaryStatus is changed to STARTING.Qamazonka-sagemakerQQQQQQQQQQQ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?UQRRQRQRRQRRR(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? RRRRRRRRRRRRRRRRRRRRRRRR(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; Ramazonka-sagemaker4Information about the status of the rule evaluation.See: R smart constructor.Ramazonka-sagemakerA list of algorithms that were used to create a model package.See: X smart constructor.Xamazonka-sagemakerA list of the algorithms that were used to create a model package.Xamazonka-sagemakerCreate a value of X" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:X, X - A list of the algorithms that were used to create a model package.Xamazonka-sagemakerA list of the algorithms that were used to create a model package.Xamazonka-sagemakerXXXXXXXXXXX(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';Xamazonka-sagemakerA list of IP address ranges ( https://docs.aws.amazon.com/vpc/latest/userguide/VPC_Subnets.htmlCIDRs). Used to create an allow list of IP addresses for a private workforce. Workers will only be able to login to their worker portal from an IP address within this range. By default, a workforce isn't restricted to specific IP addresses.See: X smart constructor.Xamazonka-sagemakerA list of one to ten  https://docs.aws.amazon.com/vpc/latest/userguide/VPC_Subnets.htmlClassless Inter-Domain Routing (CIDR) values.Maximum: Ten CIDR valuesThe following Length Constraints apply to individual CIDR values in the CIDR value list.Xamazonka-sagemakerCreate a value of X" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:X, X - A list of one to ten  https://docs.aws.amazon.com/vpc/latest/userguide/VPC_Subnets.htmlClassless Inter-Domain Routing (CIDR) values.Maximum: Ten CIDR valuesThe following Length Constraints apply to individual CIDR values in the CIDR value list.Xamazonka-sagemakerA list of one to ten  https://docs.aws.amazon.com/vpc/latest/userguide/VPC_Subnets.htmlClassless Inter-Domain Routing (CIDR) values.Maximum: Ten CIDR valuesThe following Length Constraints apply to individual CIDR values in the CIDR value list.XXXXXXXXXX(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';Xamazonka-sagemakerA collection of space settings.See: X smart constructor.Xamazonka-sagemakerCreate a value of X" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:X, X - Undocumented member.X, X - Undocumented member.Xamazonka-sagemakerUndocumented member.Xamazonka-sagemakerUndocumented member.XXXXXXXXXXXXXX(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?XXXXXXXXXXXX(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?Ȇ XXXXXXXXXXXXXXXXXXXXXXXXXXX(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; Yamazonka-sagemakerThe space's details.See: Y smart constructor.Yamazonka-sagemakerThe creation time.Yamazonka-sagemaker The ID of the associated Domain.Yamazonka-sagemakerThe last modified time.Yamazonka-sagemakerThe name of the space.Yamazonka-sagemaker The status.Yamazonka-sagemakerCreate a value of Y" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:Y, Y - The creation time.Y, Y# - The ID of the associated Domain.Y, Y - The last modified time.Y, Y - The name of the space.Y, Y - The status.Yamazonka-sagemakerThe creation time.Yamazonka-sagemaker The ID of the associated Domain.Yamazonka-sagemakerThe last modified time.Yamazonka-sagemakerThe name of the space.Yamazonka-sagemaker The status. YYYYYYYYYYYYY YYYYYYYYYYYYY(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?γYYYYYYY YYYYYYYYYYY(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?| YYYYYYYYYYYYYYYYYYYYYYYYYYYYYY(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';Yamazonka-sagemaker>Contains information summarizing the deployment stage results.See: Y smart constructor.Yamazonka-sagemaker)The time when the deployment API started.Yamazonka-sagemakerContains information summarizing the deployment stage results.See: Y smart constructor.Yamazonka-sagemakerThe name of the stage.Yamazonka-sagemaker*Configuration of the devices in the stage.Yamazonka-sagemaker(Configuration of the deployment details.Yamazonka-sagemaker$General status of the current state.Yamazonka-sagemakerCreate a value of Y" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:Y, Y - The name of the stage.Y, Y- - Configuration of the devices in the stage.Y, Y+ - Configuration of the deployment details.Y, Y' - General status of the current state.Yamazonka-sagemakerThe name of the stage.Yamazonka-sagemaker*Configuration of the devices in the stage.Yamazonka-sagemaker(Configuration of the deployment details.Yamazonka-sagemaker$General status of the current state.Yamazonka-sagemakerYamazonka-sagemakerYamazonka-sagemakerYamazonka-sagemakerY YYYYYYYYYYY YYYYYYYYYYY(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? ZZZZZZZZZZZZZZZZZZZZZZZZ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';QZamazonka-sagemakerSpecifies a limit to how long a model training job or model compilation job can run. It also specifies how long a managed spot training job has to complete. When the job reaches the time limit, SageMaker ends the training or compilation job. Use this API to cap model training costs.:To stop a training job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.The training algorithms provided by SageMaker automatically save the intermediate results of a model training job when possible. This attempt to save artifacts is only a best effort case as model might not be in a state from which it can be saved. For example, if training has just started, the model might not be ready to save. When saved, this intermediate data is a valid model artifact. You can use it to create a model with  CreateModel.The Neural Topic Model (NTM) currently does not support saving intermediate model artifacts. When training NTMs, make sure that the maximum runtime is sufficient for the training job to complete.See: Z smart constructor.Zamazonka-sagemakerThe maximum length of time, in seconds, that a training or compilation job can run before it is stopped.For compilation jobs, if the job does not complete during this time, a TimeOut error is generated. We recommend starting with 900 seconds and increasing as necessary based on your model.For all other jobs, if the job does not complete during this time, SageMaker ends the job. When  RetryStrategy# is specified in the job request, MaxRuntimeInSeconds specifies the maximum time for all of the attempts in total, not each individual attempt. The default value is 1 day. The maximum value is 28 days.The maximum time that a  TrainingJob can run in total, including any time spent publishing metrics or archiving and uploading models after it has been stopped, is 30 days.Zamazonka-sagemakerThe maximum length of time, in seconds, that a managed Spot training job has to complete. It is the amount of time spent waiting for Spot capacity plus the amount of time the job can run. It must be equal to or greater than MaxRuntimeInSeconds. If the job does not complete during this time, SageMaker ends the job.When  RetryStrategy# is specified in the job request, MaxWaitTimeInSeconds specifies the maximum time for all of the attempts in total, not each individual attempt.Zamazonka-sagemakerCreate a value of Z" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:Z, Z - The maximum length of time, in seconds, that a training or compilation job can run before it is stopped.For compilation jobs, if the job does not complete during this time, a TimeOut error is generated. We recommend starting with 900 seconds and increasing as necessary based on your model.For all other jobs, if the job does not complete during this time, SageMaker ends the job. When  RetryStrategy# is specified in the job request, MaxRuntimeInSeconds specifies the maximum time for all of the attempts in total, not each individual attempt. The default value is 1 day. The maximum value is 28 days.The maximum time that a  TrainingJob can run in total, including any time spent publishing metrics or archiving and uploading models after it has been stopped, is 30 days.Z, Z - The maximum length of time, in seconds, that a managed Spot training job has to complete. It is the amount of time spent waiting for Spot capacity plus the amount of time the job can run. It must be equal to or greater than MaxRuntimeInSeconds. If the job does not complete during this time, SageMaker ends the job.When  RetryStrategy# is specified in the job request, MaxWaitTimeInSeconds specifies the maximum time for all of the attempts in total, not each individual attempt.Zamazonka-sagemakerThe maximum length of time, in seconds, that a training or compilation job can run before it is stopped.For compilation jobs, if the job does not complete during this time, a TimeOut error is generated. We recommend starting with 900 seconds and increasing as necessary based on your model.For all other jobs, if the job does not complete during this time, SageMaker ends the job. When  RetryStrategy# is specified in the job request, MaxRuntimeInSeconds specifies the maximum time for all of the attempts in total, not each individual attempt. The default value is 1 day. The maximum value is 28 days.The maximum time that a  TrainingJob can run in total, including any time spent publishing metrics or archiving and uploading models after it has been stopped, is 30 days.Zamazonka-sagemakerThe maximum length of time, in seconds, that a managed Spot training job has to complete. It is the amount of time spent waiting for Spot capacity plus the amount of time the job can run. It must be equal to or greater than MaxRuntimeInSeconds. If the job does not complete during this time, SageMaker ends the job.When  RetryStrategy# is specified in the job request, MaxWaitTimeInSeconds specifies the maximum time for all of the attempts in total, not each individual attempt.ZZZZZZZZZZZZZZ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?ZZZZZZZZZZZZ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; Zamazonka-sagemaker.Details of the Studio Lifecycle Configuration.See: Z smart constructor.Zamazonka-sagemaker8The creation time of the Studio Lifecycle Configuration.Zamazonka-sagemakerThis value is equivalent to CreationTime because Studio Lifecycle Configurations are immutable.Zamazonka-sagemaker>The App type to which the Lifecycle Configuration is attached.Zamazonka-sagemaker>The Amazon Resource Name (ARN) of the Lifecycle Configuration.Zamazonka-sagemaker/The name of the Studio Lifecycle Configuration.Zamazonka-sagemakerCreate a value of Z" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:Z, Z; - The creation time of the Studio Lifecycle Configuration.Z, Z - This value is equivalent to CreationTime because Studio Lifecycle Configurations are immutable.Z, Z - The App type to which the Lifecycle Configuration is attached.Z, Z - The Amazon Resource Name (ARN) of the Lifecycle Configuration.Z, Z2 - The name of the Studio Lifecycle Configuration.Zamazonka-sagemaker8The creation time of the Studio Lifecycle Configuration.Zamazonka-sagemakerThis value is equivalent to CreationTime because Studio Lifecycle Configurations are immutable.Zamazonka-sagemaker>The App type to which the Lifecycle Configuration is attached.Zamazonka-sagemaker>The Amazon Resource Name (ARN) of the Lifecycle Configuration.Zamazonka-sagemaker/The name of the Studio Lifecycle Configuration. ZZZZZZZZZZZZZ ZZZZZZZZZZZZZ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?ZZZZZZ ZZZZZZZZZ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';k Zamazonka-sagemakerDescribes a work team of a vendor that does the a labelling job.See: Z smart constructor.Zamazonka-sagemakerMarketplace product listing ID.Zamazonka-sagemaker:The description of the vendor from the Amazon Marketplace.Zamazonka-sagemakerThe title of the service provided by the vendor in the Amazon Marketplace.Zamazonka-sagemaker1The name of the vendor in the Amazon Marketplace.Zamazonka-sagemakerThe Amazon Resource Name (ARN) of the vendor that you have subscribed.Zamazonka-sagemakerCreate a value of Z" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:Z, Z" - Marketplace product listing ID.Z, Z= - The description of the vendor from the Amazon Marketplace.Z, Z - The title of the service provided by the vendor in the Amazon Marketplace.Z, Z4 - The name of the vendor in the Amazon Marketplace.Z, Z - The Amazon Resource Name (ARN) of the vendor that you have subscribed.Zamazonka-sagemakerMarketplace product listing ID.Zamazonka-sagemaker:The description of the vendor from the Amazon Marketplace.Zamazonka-sagemakerThe title of the service provided by the vendor in the Amazon Marketplace.Zamazonka-sagemaker1The name of the vendor in the Amazon Marketplace.Zamazonka-sagemakerThe Amazon Resource Name (ARN) of the vendor that you have subscribed.Zamazonka-sagemakerZ ZZZZZZZZZZZZZ ZZZZZZZZZZZZZ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; [amazonka-sagemakerSpecified in the GetSearchSuggestions request. Limits the property names that are included in the response.See: [ smart constructor.[amazonka-sagemakerDefines a property name hint. Only property names that begin with the specified hint are included in the response.[amazonka-sagemakerCreate a value of [" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:[, [ - Defines a property name hint. Only property names that begin with the specified hint are included in the response.[amazonka-sagemakerDefines a property name hint. Only property names that begin with the specified hint are included in the response.[[[[[[[[[[(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";? [[[[[[[[[[[[(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; [amazonka-sagemakerThe configuration of an  OfflineStore. Provide an OfflineStoreConfig in a request to CreateFeatureGroup to create an  OfflineStore.To encrypt an  OfflineStore using at rest data encryption, specify Amazon Web Services Key Management Service (KMS) key ID, or KMSKeyId, in S3StorageConfig.See: [ smart constructor.[amazonka-sagemaker?The meta data of the Glue table that is autogenerated when an  OfflineStore is created.[amazonka-sagemakerSet to True to disable the automatic creation of an Amazon Web Services Glue table when configuring an  OfflineStore.[amazonka-sagemakerFormat for the offline store table. Supported formats are Glue (Default) and  https://iceberg.apache.org/Apache Iceberg.[amazonka-sagemaker2The Amazon Simple Storage (Amazon S3) location of  OfflineStore.[amazonka-sagemakerCreate a value of [" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:[, [ - The meta data of the Glue table that is autogenerated when an  OfflineStore is created.[, [ - Set to True to disable the automatic creation of an Amazon Web Services Glue table when configuring an  OfflineStore.[, [ - Format for the offline store table. Supported formats are Glue (Default) and  https://iceberg.apache.org/Apache Iceberg.[, [5 - The Amazon Simple Storage (Amazon S3) location of  OfflineStore.[amazonka-sagemaker?The meta data of the Glue table that is autogenerated when an  OfflineStore is created.[amazonka-sagemakerSet to True to disable the automatic creation of an Amazon Web Services Glue table when configuring an  OfflineStore.[amazonka-sagemakerFormat for the offline store table. Supported formats are Glue (Default) and  https://iceberg.apache.org/Apache Iceberg.[amazonka-sagemaker2The Amazon Simple Storage (Amazon S3) location of  OfflineStore.[amazonka-sagemaker[ [[[[[[[[[[[ [[[[[[[[[[[(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';J[amazonka-sagemakerA tag object that consists of a key and an optional value, used to manage metadata for SageMaker Amazon Web Services resources.You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints. For more information on adding tags to SageMaker resources, see AddTags.For more information on adding metadata to your Amazon Web Services resources with tagging, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services resources. For advice on best practices for managing Amazon Web Services resources with tagging, see  https://d1.awsstatic.com/whitepapers/aws-tagging-best-practices.pdfTagging Best Practices: Implement an Effective Amazon Web Services Resource Tagging Strategy.See: [ smart constructor.[amazonka-sagemaker2The tag key. Tag keys must be unique per resource.[amazonka-sagemakerThe tag value.[amazonka-sagemakerCreate a value of [" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:[, [5 - The tag key. Tag keys must be unique per resource.[, [ - The tag value.[amazonka-sagemaker2The tag key. Tag keys must be unique per resource.[amazonka-sagemakerThe tag value.[amazonka-sagemaker[amazonka-sagemaker[[[[[[[[[[[[[[[(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';:m[amazonka-sagemakerAmazon SageMaker Feature Store stores features in a collection called Feature Group. A Feature Group can be visualized as a table which has rows, with a unique identifier for each row where each column in the table is a feature. In principle, a Feature Group is composed of features and values per features.See: [ smart constructor.[amazonka-sagemaker The time a  FeatureGroup was created.[amazonka-sagemakerA free form description of a  FeatureGroup.[amazonka-sagemaker(The name of the feature that stores the  EventTime of a Record in a  FeatureGroup.A  EventTime is point in time when a new event occurs that corresponds to the creation or update of a Record in  FeatureGroup. All Records in the  FeatureGroup must have a corresponding  EventTime.[amazonka-sagemakerThe reason that the  FeatureGroup! failed to be replicated in the  OfflineStore7. This is failure may be due to a failure to create a  FeatureGroup in or delete a  FeatureGroup from the  OfflineStore.[amazonka-sagemaker A list of Features. Each Feature must include a  FeatureName and a  FeatureType.Valid  FeatureTypes are Integral,  Fractional and String. FeatureName"s cannot be any of the following:  is_deleted,  write_time, api_invocation_time.You can create up to 2,500 FeatureDefinitions per  FeatureGroup.[amazonka-sagemaker$The Amazon Resource Name (ARN) of a  FeatureGroup.[amazonka-sagemakerThe name of the  FeatureGroup.[amazonka-sagemakerA  FeatureGroup status.[amazonka-sagemakerA timestamp indicating the last time you updated the feature group.[amazonka-sagemakerA value that indicates whether the feature group was updated successfully.[amazonka-sagemakerThe name of the Feature# whose value uniquely identifies a Record defined in the  FeatureGroup FeatureDefinitions.[amazonka-sagemakerThe Amazon Resource Name (ARN) of the IAM execution role used to create the feature group.[amazonka-sagemakerTags used to define a  FeatureGroup.[amazonka-sagemakerCreate a value of [" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:[, [ - The time a  FeatureGroup was created.[, [ - A free form description of a  FeatureGroup.[, [+ - The name of the feature that stores the  EventTime of a Record in a  FeatureGroup.A  EventTime is point in time when a new event occurs that corresponds to the creation or update of a Record in  FeatureGroup. All Records in the  FeatureGroup must have a corresponding  EventTime.[, [ - The reason that the  FeatureGroup! failed to be replicated in the  OfflineStore7. This is failure may be due to a failure to create a  FeatureGroup in or delete a  FeatureGroup from the  OfflineStore.[, [ - A list of Features. Each Feature must include a  FeatureName and a  FeatureType.Valid  FeatureTypes are Integral,  Fractional and String. FeatureName"s cannot be any of the following:  is_deleted,  write_time, api_invocation_time.You can create up to 2,500 FeatureDefinitions per  FeatureGroup.[, [' - The Amazon Resource Name (ARN) of a  FeatureGroup.[, [ - The name of the  FeatureGroup.[, [ - A  FeatureGroup status.[, [ - A timestamp indicating the last time you updated the feature group.[, [ - A value that indicates whether the feature group was updated successfully.[, [ - Undocumented member.[, [ - Undocumented member.[, [ - Undocumented member.[, [ - The name of the Feature# whose value uniquely identifies a Record defined in the  FeatureGroup FeatureDefinitions.[, [ - The Amazon Resource Name (ARN) of the IAM execution role used to create the feature group.[, [ - Tags used to define a  FeatureGroup.[amazonka-sagemaker The time a  FeatureGroup was created.[amazonka-sagemakerA free form description of a  FeatureGroup.[amazonka-sagemaker(The name of the feature that stores the  EventTime of a Record in a  FeatureGroup.A  EventTime is point in time when a new event occurs that corresponds to the creation or update of a Record in  FeatureGroup. All Records in the  FeatureGroup must have a corresponding  EventTime.[amazonka-sagemakerThe reason that the  FeatureGroup! failed to be replicated in the  OfflineStore7. This is failure may be due to a failure to create a  FeatureGroup in or delete a  FeatureGroup from the  OfflineStore.[amazonka-sagemaker A list of Features. Each Feature must include a  FeatureName and a  FeatureType.Valid  FeatureTypes are Integral,  Fractional and String. FeatureName"s cannot be any of the following:  is_deleted,  write_time, api_invocation_time.You can create up to 2,500 FeatureDefinitions per  FeatureGroup.[amazonka-sagemaker$The Amazon Resource Name (ARN) of a  FeatureGroup.[amazonka-sagemakerThe name of the  FeatureGroup.[amazonka-sagemakerA  FeatureGroup status.[amazonka-sagemakerA timestamp indicating the last time you updated the feature group.[amazonka-sagemakerA value that indicates whether the feature group was updated successfully.[amazonka-sagemakerUndocumented member.[amazonka-sagemakerUndocumented member.[amazonka-sagemakerUndocumented member.[amazonka-sagemakerThe name of the Feature# whose value uniquely identifies a Record defined in the  FeatureGroup FeatureDefinitions.[amazonka-sagemakerThe Amazon Resource Name (ARN) of the IAM execution role used to create the feature group.[amazonka-sagemakerTags used to define a  FeatureGroup.#[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[#[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?;#[\\\\\\\\\\\\\\\\\\\\\\\\\\[[[[[[[[[\\\\\\\\\\\\\\\\\\\\\\\\\\[[[[[[[[\\\\\\\\\\\\\\\\\\\\\\\\\\[[[[[[(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?=\\\\\\\ \\\\\\\\\\\(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?=\\\\\\\\ \\\\\\\\\\\\\(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?>\\\\\\\\\\\\(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';M\amazonka-sagemakerContains information about a target platform that you want your model to run on, such as OS, architecture, and accelerators. It is an alternative of  TargetDevice.See: \ smart constructor.\amazonka-sagemaker3Specifies a target platform accelerator (optional).NVIDIA9: Nvidia graphics processing unit. It also requires gpu-code, trt-ver, cuda-ver compiler optionsMALI: ARM Mali graphics processorINTEL_GRAPHICS: Integrated Intel graphics\amazonka-sagemakerSpecifies a target platform OS.LINUX : Linux-based operating systems.ANDROID: Android operating systems. Android API level can be specified using the ANDROID_PLATFORM$ compiler option. For example, +"CompilerOptions": {'ANDROID_PLATFORM': 28}\amazonka-sagemaker)Specifies a target platform architecture.X86_64,: 64-bit version of the x86 instruction set.X86,: 32-bit version of the x86 instruction set.ARM64: ARMv8 64-bit CPU. ARM_EABIHF: ARMv7 32-bit, Hard Float.ARM_EABI: ARMv7 32-bit, Soft Float. Used by Android 32-bit ARM platform.\amazonka-sagemakerCreate a value of \" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:\, ]6 - Specifies a target platform accelerator (optional).NVIDIA9: Nvidia graphics processing unit. It also requires gpu-code, trt-ver, cuda-ver compiler optionsMALI: ARM Mali graphics processorINTEL_GRAPHICS: Integrated Intel graphics\, ]" - Specifies a target platform OS.LINUX : Linux-based operating systems.ANDROID: Android operating systems. Android API level can be specified using the ANDROID_PLATFORM$ compiler option. For example, +"CompilerOptions": {'ANDROID_PLATFORM': 28}\, ], - Specifies a target platform architecture.X86_64,: 64-bit version of the x86 instruction set.X86,: 32-bit version of the x86 instruction set.ARM64: ARMv8 64-bit CPU. ARM_EABIHF: ARMv7 32-bit, Hard Float.ARM_EABI: ARMv7 32-bit, Soft Float. Used by Android 32-bit ARM platform.]amazonka-sagemaker3Specifies a target platform accelerator (optional).NVIDIA9: Nvidia graphics processing unit. It also requires gpu-code, trt-ver, cuda-ver compiler optionsMALI: ARM Mali graphics processorINTEL_GRAPHICS: Integrated Intel graphics]amazonka-sagemakerSpecifies a target platform OS.LINUX : Linux-based operating systems.ANDROID: Android operating systems. Android API level can be specified using the ANDROID_PLATFORM$ compiler option. For example, +"CompilerOptions": {'ANDROID_PLATFORM': 28}]amazonka-sagemaker)Specifies a target platform architecture.X86_64,: 64-bit version of the x86 instruction set.X86,: 32-bit version of the x86 instruction set.ARM64: ARMv8 64-bit CPU. ARM_EABIHF: ARMv7 32-bit, Hard Float.ARM_EABI: ARMv7 32-bit, Soft Float. Used by Android 32-bit ARM platform.\amazonka-sagemaker\amazonka-sagemaker\ \\\\\\]]] \\\\\\]]](c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';A ]amazonka-sagemakerContains information about the output location for the compiled model and the target device that the model runs on.  TargetDevice and TargetPlatform are mutually exclusive, so you need to choose one between the two to specify your target device or platform. If you cannot find your device you want to use from the  TargetDevice list, use TargetPlatform3 to describe the platform of your edge device and CompilerOptions if there are specific settings that are required or recommended to use for particular TargetPlatform.See: ] smart constructor.]amazonka-sagemakerSpecifies additional parameters for compiler options in JSON format. The compiler options are TargetPlatform specific. It is required for NVIDIA accelerators and highly recommended for CPU compilations. For any other cases, it is optional to specify CompilerOptions.DTYPE: Specifies the data type for the input. When compiling for ml_* (except for ml_inf) instances using PyTorch framework, provide the data type (dtype) of the model's input.  "float32" is used if "DTYPE"- is not specified. Options for data type are:float32: Use either "float" or  "float32".int64: Use either "int64" or "long". For example, {"dtype" : "float32"}.CPU>: Compilation for CPU supports the following compiler options.mcpu+: CPU micro-architecture. For example, {'mcpu': 'skylake-avx512'}mattr: CPU flags. For example, {'mattr': ['+neon', '+vfpv4']}ARM": Details of ARM CPU compilations.NEON: NEON is an implementation of the Advanced SIMD extension used in ARMv7 processors.For example, add {'mattr': ['+neon']} to the compiler options if compiling for ARM 32-bit platform with the NEON support.NVIDIA: Compilation for NVIDIA GPU supports the following compiler options.gpu_code&: Specifies the targeted architecture.trt-ver3: Specifies the TensorRT versions in x.y.z. format.cuda-ver+: Specifies the CUDA version in x.y format. For example, ={'gpu-code': 'sm_72', 'trt-ver': '6.0.1', 'cuda-ver': '10.1'}ANDROID: Compilation for the Android OS supports the following compiler options:ANDROID_PLATFORM: Specifies the Android API levels. Available levels range from 21 to 29. For example, {'ANDROID_PLATFORM': 28}.mattr: Add {'mattr': ['+neon']} to compiler options if compiling for ARM 32-bit platform with NEON support. INFERENTIA: Compilation for target ml_inf1 uses compiler options passed in as a JSON string. For example, <"CompilerOptions": "\"--verbose 1 --num-neuroncores 2 -O2\"".6For information about supported compiler options, see  https://github.com/aws/aws-neuron-sdk/blob/master/docs/neuron-cc/command-line-reference.mdNeuron Compiler CLI.CoreML: Compilation for the CoreML OutputConfig$TargetDevice supports the following compiler options: class_labels: Specifies the classification labels file name inside input tar.gz file. For example, ,{"class_labels": "imagenet_labels_1000.txt"}. Labels inside the txt file should be separated by newlines.EIA: Compilation for the Elastic Inference Accelerator supports the following compiler options:precision_mode: Specifies the precision of compiled artifacts. Supported values are "FP16" and "FP32". Default is "FP32".signature_def_key: Specifies the signature to use for models in SavedModel format. Defaults is TensorFlow's default signature def key. output_names: Specifies a list of output tensor names for models in FrozenGraph format. Set at most one API field, either: signature_def_key or  output_names. For example: 8{"precision_mode": "FP32", "output_names": ["output:0"]}]amazonka-sagemakerThe Amazon Web Services Key Management Service key (Amazon Web Services KMS) that Amazon SageMaker uses to encrypt your output models with Amazon S3 server-side encryption after compilation job. If you don't provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role's account. For more information, see  https://docs.aws.amazon.com/AmazonS3/latest/userguide/UsingKMSEncryption.htmlKMS-Managed Encryption Keys in the .Amazon Simple Storage Service Developer Guide.1The KmsKeyId can be any of the following formats:Key ID: $1234abcd-12ab-34cd-56ef-1234567890abKey ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab Alias name: alias/ExampleAliasAlias name ARN: 5arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias]amazonka-sagemakerIdentifies the target device or the machine learning instance that you want to run your model on after the compilation has completed. Alternatively, you can specify OS, architecture, and accelerator using TargetPlatform fields. It can be used instead of TargetPlatform.]amazonka-sagemakerContains information about a target platform that you want your model to run on, such as OS, architecture, and accelerators. It is an alternative of  TargetDevice.1The following examples show how to configure the TargetPlatform and CompilerOptions+ JSON strings for popular target platforms:Raspberry Pi 3 Model B+ 8"TargetPlatform": {"Os": "LINUX", "Arch": "ARM_EABIHF"}, ( "CompilerOptions": {'mattr': ['+neon']} Jetson TX2 "TargetPlatform": {"Os": "LINUX", "Arch": "ARM64", "Accelerator": "NVIDIA"},  "CompilerOptions": {'gpu-code': 'sm_62', 'trt-ver': '6.0.1', 'cuda-ver': '10.0'}EC2 m5.2xlarge instance OS "TargetPlatform": {"Os": "LINUX", "Arch": "X86_64", "Accelerator": "NVIDIA"}, . "CompilerOptions": {'mcpu': 'skylake-avx512'}RK3399 "TargetPlatform": {"Os": "LINUX", "Arch": "ARM64", "Accelerator": "MALI"}ARMv7 phone (CPU) 8"TargetPlatform": {"Os": "ANDROID", "Arch": "ARM_EABI"},  "CompilerOptions": {'ANDROID_PLATFORM': 25, 'mattr': ['+neon']}ARMv8 phone (CPU) 5"TargetPlatform": {"Os": "ANDROID", "Arch": "ARM64"}, , "CompilerOptions": {'ANDROID_PLATFORM': 29}]amazonka-sagemakerIdentifies the S3 bucket where you want Amazon SageMaker to store the model artifacts. For example,  s3://bucket-name/key-name-prefix.]amazonka-sagemakerCreate a value of ]" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:], ] - Specifies additional parameters for compiler options in JSON format. The compiler options are TargetPlatform specific. It is required for NVIDIA accelerators and highly recommended for CPU compilations. For any other cases, it is optional to specify CompilerOptions.DTYPE: Specifies the data type for the input. When compiling for ml_* (except for ml_inf) instances using PyTorch framework, provide the data type (dtype) of the model's input.  "float32" is used if "DTYPE"- is not specified. Options for data type are:float32: Use either "float" or  "float32".int64: Use either "int64" or "long". For example, {"dtype" : "float32"}.CPU>: Compilation for CPU supports the following compiler options.mcpu+: CPU micro-architecture. For example, {'mcpu': 'skylake-avx512'}mattr: CPU flags. For example, {'mattr': ['+neon', '+vfpv4']}ARM": Details of ARM CPU compilations.NEON: NEON is an implementation of the Advanced SIMD extension used in ARMv7 processors.For example, add {'mattr': ['+neon']} to the compiler options if compiling for ARM 32-bit platform with the NEON support.NVIDIA: Compilation for NVIDIA GPU supports the following compiler options.gpu_code&: Specifies the targeted architecture.trt-ver3: Specifies the TensorRT versions in x.y.z. format.cuda-ver+: Specifies the CUDA version in x.y format. For example, ={'gpu-code': 'sm_72', 'trt-ver': '6.0.1', 'cuda-ver': '10.1'}ANDROID: Compilation for the Android OS supports the following compiler options:ANDROID_PLATFORM: Specifies the Android API levels. Available levels range from 21 to 29. For example, {'ANDROID_PLATFORM': 28}.mattr: Add {'mattr': ['+neon']} to compiler options if compiling for ARM 32-bit platform with NEON support. INFERENTIA: Compilation for target ml_inf1 uses compiler options passed in as a JSON string. For example, <"CompilerOptions": "\"--verbose 1 --num-neuroncores 2 -O2\"".6For information about supported compiler options, see  https://github.com/aws/aws-neuron-sdk/blob/master/docs/neuron-cc/command-line-reference.mdNeuron Compiler CLI.CoreML: Compilation for the CoreML OutputConfig$TargetDevice supports the following compiler options: class_labels: Specifies the classification labels file name inside input tar.gz file. For example, ,{"class_labels": "imagenet_labels_1000.txt"}. Labels inside the txt file should be separated by newlines.EIA: Compilation for the Elastic Inference Accelerator supports the following compiler options:precision_mode: Specifies the precision of compiled artifacts. Supported values are "FP16" and "FP32". Default is "FP32".signature_def_key: Specifies the signature to use for models in SavedModel format. Defaults is TensorFlow's default signature def key. output_names: Specifies a list of output tensor names for models in FrozenGraph format. Set at most one API field, either: signature_def_key or  output_names. For example: 8{"precision_mode": "FP32", "output_names": ["output:0"]}], ] - The Amazon Web Services Key Management Service key (Amazon Web Services KMS) that Amazon SageMaker uses to encrypt your output models with Amazon S3 server-side encryption after compilation job. If you don't provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role's account. For more information, see  https://docs.aws.amazon.com/AmazonS3/latest/userguide/UsingKMSEncryption.htmlKMS-Managed Encryption Keys in the .Amazon Simple Storage Service Developer Guide.1The KmsKeyId can be any of the following formats:Key ID: $1234abcd-12ab-34cd-56ef-1234567890abKey ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab Alias name: alias/ExampleAliasAlias name ARN: 5arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias], ] - Identifies the target device or the machine learning instance that you want to run your model on after the compilation has completed. Alternatively, you can specify OS, architecture, and accelerator using TargetPlatform fields. It can be used instead of TargetPlatform.], ] - Contains information about a target platform that you want your model to run on, such as OS, architecture, and accelerators. It is an alternative of  TargetDevice.1The following examples show how to configure the TargetPlatform and CompilerOptions+ JSON strings for popular target platforms:Raspberry Pi 3 Model B+ 8"TargetPlatform": {"Os": "LINUX", "Arch": "ARM_EABIHF"}, ( "CompilerOptions": {'mattr': ['+neon']} Jetson TX2 "TargetPlatform": {"Os": "LINUX", "Arch": "ARM64", "Accelerator": "NVIDIA"},  "CompilerOptions": {'gpu-code': 'sm_62', 'trt-ver': '6.0.1', 'cuda-ver': '10.0'}EC2 m5.2xlarge instance OS "TargetPlatform": {"Os": "LINUX", "Arch": "X86_64", "Accelerator": "NVIDIA"}, . "CompilerOptions": {'mcpu': 'skylake-avx512'}RK3399 "TargetPlatform": {"Os": "LINUX", "Arch": "ARM64", "Accelerator": "MALI"}ARMv7 phone (CPU) 8"TargetPlatform": {"Os": "ANDROID", "Arch": "ARM_EABI"},  "CompilerOptions": {'ANDROID_PLATFORM': 25, 'mattr': ['+neon']}ARMv8 phone (CPU) 5"TargetPlatform": {"Os": "ANDROID", "Arch": "ARM64"}, , "CompilerOptions": {'ANDROID_PLATFORM': 29}], ] - Identifies the S3 bucket where you want Amazon SageMaker to store the model artifacts. For example,  s3://bucket-name/key-name-prefix.]amazonka-sagemakerSpecifies additional parameters for compiler options in JSON format. The compiler options are TargetPlatform specific. It is required for NVIDIA accelerators and highly recommended for CPU compilations. For any other cases, it is optional to specify CompilerOptions.DTYPE: Specifies the data type for the input. When compiling for ml_* (except for ml_inf) instances using PyTorch framework, provide the data type (dtype) of the model's input.  "float32" is used if "DTYPE"- is not specified. Options for data type are:float32: Use either "float" or  "float32".int64: Use either "int64" or "long". For example, {"dtype" : "float32"}.CPU>: Compilation for CPU supports the following compiler options.mcpu+: CPU micro-architecture. For example, {'mcpu': 'skylake-avx512'}mattr: CPU flags. For example, {'mattr': ['+neon', '+vfpv4']}ARM": Details of ARM CPU compilations.NEON: NEON is an implementation of the Advanced SIMD extension used in ARMv7 processors.For example, add {'mattr': ['+neon']} to the compiler options if compiling for ARM 32-bit platform with the NEON support.NVIDIA: Compilation for NVIDIA GPU supports the following compiler options.gpu_code&: Specifies the targeted architecture.trt-ver3: Specifies the TensorRT versions in x.y.z. format.cuda-ver+: Specifies the CUDA version in x.y format. For example, ={'gpu-code': 'sm_72', 'trt-ver': '6.0.1', 'cuda-ver': '10.1'}ANDROID: Compilation for the Android OS supports the following compiler options:ANDROID_PLATFORM: Specifies the Android API levels. Available levels range from 21 to 29. For example, {'ANDROID_PLATFORM': 28}.mattr: Add {'mattr': ['+neon']} to compiler options if compiling for ARM 32-bit platform with NEON support. INFERENTIA: Compilation for target ml_inf1 uses compiler options passed in as a JSON string. For example, <"CompilerOptions": "\"--verbose 1 --num-neuroncores 2 -O2\"".6For information about supported compiler options, see  https://github.com/aws/aws-neuron-sdk/blob/master/docs/neuron-cc/command-line-reference.mdNeuron Compiler CLI.CoreML: Compilation for the CoreML OutputConfig$TargetDevice supports the following compiler options: class_labels: Specifies the classification labels file name inside input tar.gz file. For example, ,{"class_labels": "imagenet_labels_1000.txt"}. Labels inside the txt file should be separated by newlines.EIA: Compilation for the Elastic Inference Accelerator supports the following compiler options:precision_mode: Specifies the precision of compiled artifacts. Supported values are "FP16" and "FP32". Default is "FP32".signature_def_key: Specifies the signature to use for models in SavedModel format. Defaults is TensorFlow's default signature def key. output_names: Specifies a list of output tensor names for models in FrozenGraph format. Set at most one API field, either: signature_def_key or  output_names. For example: 8{"precision_mode": "FP32", "output_names": ["output:0"]}]amazonka-sagemakerThe Amazon Web Services Key Management Service key (Amazon Web Services KMS) that Amazon SageMaker uses to encrypt your output models with Amazon S3 server-side encryption after compilation job. If you don't provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role's account. For more information, see  https://docs.aws.amazon.com/AmazonS3/latest/userguide/UsingKMSEncryption.htmlKMS-Managed Encryption Keys in the .Amazon Simple Storage Service Developer Guide.1The KmsKeyId can be any of the following formats:Key ID: $1234abcd-12ab-34cd-56ef-1234567890abKey ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab Alias name: alias/ExampleAliasAlias name ARN: 5arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias]amazonka-sagemakerIdentifies the target device or the machine learning instance that you want to run your model on after the compilation has completed. Alternatively, you can specify OS, architecture, and accelerator using TargetPlatform fields. It can be used instead of TargetPlatform.]amazonka-sagemakerContains information about a target platform that you want your model to run on, such as OS, architecture, and accelerators. It is an alternative of  TargetDevice.1The following examples show how to configure the TargetPlatform and CompilerOptions+ JSON strings for popular target platforms:Raspberry Pi 3 Model B+ 8"TargetPlatform": {"Os": "LINUX", "Arch": "ARM_EABIHF"}, ( "CompilerOptions": {'mattr': ['+neon']} Jetson TX2 "TargetPlatform": {"Os": "LINUX", "Arch": "ARM64", "Accelerator": "NVIDIA"},  "CompilerOptions": {'gpu-code': 'sm_62', 'trt-ver': '6.0.1', 'cuda-ver': '10.0'}EC2 m5.2xlarge instance OS "TargetPlatform": {"Os": "LINUX", "Arch": "X86_64", "Accelerator": "NVIDIA"}, . "CompilerOptions": {'mcpu': 'skylake-avx512'}RK3399 "TargetPlatform": {"Os": "LINUX", "Arch": "ARM64", "Accelerator": "MALI"}ARMv7 phone (CPU) 8"TargetPlatform": {"Os": "ANDROID", "Arch": "ARM_EABI"},  "CompilerOptions": {'ANDROID_PLATFORM': 25, 'mattr': ['+neon']}ARMv8 phone (CPU) 5"TargetPlatform": {"Os": "ANDROID", "Arch": "ARM64"}, , "CompilerOptions": {'ANDROID_PLATFORM': 29}]amazonka-sagemakerIdentifies the S3 bucket where you want Amazon SageMaker to store the model artifacts. For example,  s3://bucket-name/key-name-prefix.]amazonka-sagemaker] ]]]]]]]]]]]]] ]]]]]]]]]]]]](c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';+]amazonka-sagemaker%A summary of a model compilation job.See: ] smart constructor.]amazonka-sagemaker2The time when the model compilation job completed.]amazonka-sagemaker0The time when the model compilation job started.]amazonka-sagemakerThe type of device that the model will run on after the compilation job has completed.]amazonka-sagemakerThe type of accelerator that the model will run on after the compilation job has completed.]amazonka-sagemakerThe type of architecture that the model will run on after the compilation job has completed.]amazonka-sagemakerThe type of OS that the model will run on after the compilation job has completed.]amazonka-sagemaker:The time when the model compilation job was last modified.]amazonka-sagemakerThe name of the model compilation job that you want a summary for.]amazonka-sagemaker^amazonka-sagemaker&Defines the resource limit of the job.^amazonka-sagemaker)Specifies the traffic pattern of the job.^amazonka-sagemakerThe Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint. This key will be passed to SageMaker Hosting for endpoint creation.'The SageMaker execution role must have kms:CreateGrant permission in order to encrypt data on the storage volume of the endpoints created for inference recommendation. The inference recommendation job will fail asynchronously during endpoint configuration creation if the role passed does not have kms:CreateGrant permission.The KmsKeyId% can be any of the following formats: // KMS Key ID &"1234abcd-12ab-34cd-56ef-1234567890ab"*// Amazon Resource Name (ARN) of a KMS Key "arn:aws:kms:::key/"// KMS Key Alias "alias/ExampleAlias"0// Amazon Resource Name (ARN) of a KMS Key Alias 5"arn:aws:kms:::alias/"1For more information about key identifiers, see  https://docs.aws.amazon.com/kms/latest/developerguide/concepts.html#key-id-key-idKey identifiers (KeyID) in the Amazon Web Services Key Management Service (Amazon Web Services KMS) documentation.^amazonka-sagemakerInference Recommender provisions SageMaker endpoints with access to VPC in the inference recommendation job.^amazonka-sagemaker^, ^) - Defines the resource limit of the job.^, ^, - Specifies the traffic pattern of the job.^, ^ - The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint. This key will be passed to SageMaker Hosting for endpoint creation.'The SageMaker execution role must have kms:CreateGrant permission in order to encrypt data on the storage volume of the endpoints created for inference recommendation. The inference recommendation job will fail asynchronously during endpoint configuration creation if the role passed does not have kms:CreateGrant permission.The KmsKeyId% can be any of the following formats: // KMS Key ID &"1234abcd-12ab-34cd-56ef-1234567890ab"*// Amazon Resource Name (ARN) of a KMS Key "arn:aws:kms:::key/"// KMS Key Alias "alias/ExampleAlias"0// Amazon Resource Name (ARN) of a KMS Key Alias 5"arn:aws:kms:::alias/"1For more information about key identifiers, see  https://docs.aws.amazon.com/kms/latest/developerguide/concepts.html#key-id-key-idKey identifiers (KeyID) in the Amazon Web Services Key Management Service (Amazon Web Services KMS) documentation.^, ^ - Inference Recommender provisions SageMaker endpoints with access to VPC in the inference recommendation job.^, ^? - The Amazon Resource Name (ARN) of a versioned model package.^amazonka-sagemakerSpecifies mandatory fields for running an Inference Recommender job. The fields specified in ContainerConfig9 override the corresponding fields in the model package.^amazonka-sagemaker6Specifies the endpoint configuration to use for a job.^amazonka-sagemakerExisting customer endpoints on which to run an Inference Recommender job.^amazonka-sagemaker7Specifies the maximum duration of the job, in seconds.>^amazonka-sagemaker&Defines the resource limit of the job.^amazonka-sagemaker)Specifies the traffic pattern of the job.^amazonka-sagemakerThe Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint. This key will be passed to SageMaker Hosting for endpoint creation.'The SageMaker execution role must have kms:CreateGrant permission in order to encrypt data on the storage volume of the endpoints created for inference recommendation. The inference recommendation job will fail asynchronously during endpoint configuration creation if the role passed does not have kms:CreateGrant permission.The KmsKeyId% can be any of the following formats: // KMS Key ID &"1234abcd-12ab-34cd-56ef-1234567890ab"*// Amazon Resource Name (ARN) of a KMS Key "arn:aws:kms:::key/"// KMS Key Alias "alias/ExampleAlias"0// Amazon Resource Name (ARN) of a KMS Key Alias 5"arn:aws:kms:::alias/"1For more information about key identifiers, see  https://docs.aws.amazon.com/kms/latest/developerguide/concepts.html#key-id-key-idKey identifiers (KeyID) in the Amazon Web Services Key Management Service (Amazon Web Services KMS) documentation.^amazonka-sagemakerInference Recommender provisions SageMaker endpoints with access to VPC in the inference recommendation job.^amazonka-sagemaker - Indicates whether the channel is required by the algorithm._, _> - The allowed compression types, if data compression is used._, _ - The name of the channel._, _) - The supported MIME types for the data._, _/ - The allowed input mode, either FILE or PIPE.In FILE mode, Amazon SageMaker copies the data from the input source onto the local Amazon Elastic Block Store (Amazon EBS) volumes before starting your training algorithm. This is the most commonly used input mode.In PIPE mode, Amazon SageMaker streams input data from the source directly to your algorithm without using the EBS volume._amazonka-sagemaker#A brief description of the channel._amazonka-sagemaker;Indicates whether the channel is required by the algorithm._amazonka-sagemaker;The allowed compression types, if data compression is used._amazonka-sagemakerThe name of the channel._amazonka-sagemaker&The supported MIME types for the data._amazonka-sagemaker,The allowed input mode, either FILE or PIPE.In FILE mode, Amazon SageMaker copies the data from the input source onto the local Amazon Elastic Block Store (Amazon EBS) volumes before starting your training algorithm. This is the most commonly used input mode.In PIPE mode, Amazon SageMaker streams input data from the source directly to your algorithm without using the EBS volume._amazonka-sagemaker_amazonka-sagemaker_______________________________(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';H|_amazonka-sagemakerA channel is a named input source that training algorithms can consume.See: _ smart constructor._amazonka-sagemakerIf training data is compressed, the compression type. The default value is None. CompressionType is used only in Pipe input mode. In File mode, leave this field unset or set it to None._amazonka-sagemakerThe MIME type of the data._amazonka-sagemaker(Optional) The input mode to use for the data channel in a training job. If you don't set a value for  InputMode$, SageMaker uses the value set for TrainingInputMode&. Use this parameter to override the TrainingInputMode setting in a AlgorithmSpecification request when you have a channel that needs a different input mode from the training job's general setting. To download the data from Amazon Simple Storage Service (Amazon S3) to the provisioned ML storage volume, and mount the directory to a Docker volume, use File input mode. To stream data directly from Amazon S3 to the container, choose Pipe input mode.0To use a model for incremental training, choose File input model._amazonka-sagemakerSpecify RecordIO as the value when input data is in raw format but the training algorithm requires the RecordIO format. In this case, SageMaker wraps each individual S3 object in a RecordIO record. If the input data is already in RecordIO format, you don't need to set this attribute. For more information, see  https://mxnet.apache.org/api/architecture/note_data_loading#data-formatCreate a Dataset Using RecordIO.7In File mode, leave this field unset or set it to None._amazonka-sagemakerA configuration for a shuffle option for input data in a channel. If you use S3Prefix for  S3DataType, this shuffles the results of the S3 key prefix matches. If you use  ManifestFile0, the order of the S3 object references in the  ManifestFile is shuffled. If you use AugmentedManifestFile&, the order of the JSON lines in the AugmentedManifestFile; is shuffled. The shuffling order is determined using the Seed value.For Pipe input mode, shuffling is done at the start of every epoch. With large datasets this ensures that the order of the training data is different for each epoch, it helps reduce bias and possible overfitting. In a multi-node training job when ShuffleConfig is combined with S3DataDistributionType of ShardedByS3Key, the data is shuffled across nodes so that the content sent to a particular node on the first epoch might be sent to a different node on the second epoch._amazonka-sagemakerThe name of the channel._amazonka-sagemaker!The location of the channel data._amazonka-sagemakerCreate a value of _" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:_, _ - If training data is compressed, the compression type. The default value is None. CompressionType is used only in Pipe input mode. In File mode, leave this field unset or set it to None._, _ - The MIME type of the data._, _ - (Optional) The input mode to use for the data channel in a training job. If you don't set a value for  InputMode$, SageMaker uses the value set for TrainingInputMode&. Use this parameter to override the TrainingInputMode setting in a AlgorithmSpecification request when you have a channel that needs a different input mode from the training job's general setting. To download the data from Amazon Simple Storage Service (Amazon S3) to the provisioned ML storage volume, and mount the directory to a Docker volume, use File input mode. To stream data directly from Amazon S3 to the container, choose Pipe input mode.0To use a model for incremental training, choose File input model._, _ - Specify RecordIO as the value when input data is in raw format but the training algorithm requires the RecordIO format. In this case, SageMaker wraps each individual S3 object in a RecordIO record. If the input data is already in RecordIO format, you don't need to set this attribute. For more information, see  https://mxnet.apache.org/api/architecture/note_data_loading#data-formatCreate a Dataset Using RecordIO.7In File mode, leave this field unset or set it to None._, _ - A configuration for a shuffle option for input data in a channel. If you use S3Prefix for  S3DataType, this shuffles the results of the S3 key prefix matches. If you use  ManifestFile0, the order of the S3 object references in the  ManifestFile is shuffled. If you use AugmentedManifestFile&, the order of the JSON lines in the AugmentedManifestFile; is shuffled. The shuffling order is determined using the Seed value.For Pipe input mode, shuffling is done at the start of every epoch. With large datasets this ensures that the order of the training data is different for each epoch, it helps reduce bias and possible overfitting. In a multi-node training job when ShuffleConfig is combined with S3DataDistributionType of ShardedByS3Key, the data is shuffled across nodes so that the content sent to a particular node on the first epoch might be sent to a different node on the second epoch._, _ - The name of the channel._, _$ - The location of the channel data._amazonka-sagemakerIf training data is compressed, the compression type. The default value is None. CompressionType is used only in Pipe input mode. In File mode, leave this field unset or set it to None._amazonka-sagemakerThe MIME type of the data._amazonka-sagemaker(Optional) The input mode to use for the data channel in a training job. If you don't set a value for  InputMode$, SageMaker uses the value set for TrainingInputMode&. Use this parameter to override the TrainingInputMode setting in a AlgorithmSpecification request when you have a channel that needs a different input mode from the training job's general setting. To download the data from Amazon Simple Storage Service (Amazon S3) to the provisioned ML storage volume, and mount the directory to a Docker volume, use File input mode. To stream data directly from Amazon S3 to the container, choose Pipe input mode.0To use a model for incremental training, choose File input model._amazonka-sagemakerSpecify RecordIO as the value when input data is in raw format but the training algorithm requires the RecordIO format. In this case, SageMaker wraps each individual S3 object in a RecordIO record. If the input data is already in RecordIO format, you don't need to set this attribute. For more information, see  https://mxnet.apache.org/api/architecture/note_data_loading#data-formatCreate a Dataset Using RecordIO.7In File mode, leave this field unset or set it to None._amazonka-sagemakerA configuration for a shuffle option for input data in a channel. If you use S3Prefix for  S3DataType, this shuffles the results of the S3 key prefix matches. If you use  ManifestFile0, the order of the S3 object references in the  ManifestFile is shuffled. If you use AugmentedManifestFile&, the order of the JSON lines in the AugmentedManifestFile; is shuffled. The shuffling order is determined using the Seed value.For Pipe input mode, shuffling is done at the start of every epoch. With large datasets this ensures that the order of the training data is different for each epoch, it helps reduce bias and possible overfitting. In a multi-node training job when ShuffleConfig is combined with S3DataDistributionType of ShardedByS3Key, the data is shuffled across nodes so that the content sent to a particular node on the first epoch might be sent to a different node on the second epoch._amazonka-sagemakerThe name of the channel._amazonka-sagemaker!The location of the channel data._amazonka-sagemaker_amazonka-sagemaker___________________________________(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';r_amazonka-sagemakerSpecifies the training algorithm to use in a CreateTrainingJob request.For more information about algorithms provided by SageMaker, see  :https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html Algorithms9. For information about using your own algorithms, see  https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms.html/Using Your Own Algorithms with Amazon SageMaker.See: _ smart constructor._amazonka-sagemakerThe name of the algorithm resource to use for the training job. This must be an algorithm resource that you created or subscribe to on Amazon Web Services Marketplace.2You must specify either the algorithm name to the  AlgorithmName parameter or the image URI of the algorithm container to the  TrainingImage parameter.Note that the  AlgorithmName+ parameter is mutually exclusive with the  TrainingImage, parameter. If you specify a value for the  AlgorithmName+ parameter, you can't specify a value for  TrainingImage, and vice versa.If you specify values for both parameters, the training job might break; if you don't specify any value for both parameters, the training job might raise a null error._amazonka-sagemaker?The arguments for a container used to run a training job. See  https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-training-algo-dockerfile.html-How Amazon SageMaker Runs Your Training Image for additional information._amazonka-sagemakerThe  1https://docs.docker.com/engine/reference/builder/(entrypoint script for a Docker container used to run a training job. This script takes precedence over the default train processing instructions. See  https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-training-algo-dockerfile.html-How Amazon SageMaker Runs Your Training Image for more information._amazonka-sagemakerTo generate and save time-series metrics during training, set to true. The default is false and time-series metrics aren't generated except in the following cases:0You use one of the SageMaker built-in algorithms"You use one of the following  https://docs.aws.amazon.com/sagemaker/latest/dg/pre-built-containers-frameworks-deep-learning.html Prebuilt SageMaker Docker Images:Tensorflow (version >= 1.15)MXNet (version >= 1.6)PyTorch (version >= 1.3))You specify at least one MetricDefinition_amazonka-sagemakerA list of metric definition objects. Each object specifies the metric name and regular expressions used to parse algorithm logs. SageMaker publishes each metric to Amazon CloudWatch._amazonka-sagemakerThe registry path of the Docker image that contains the training algorithm. For information about docker registry paths for SageMaker built-in algorithms, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-algo-docker-registry-paths.html&Docker Registry Paths and Example Code in the  Amazon SageMaker developer guide. SageMaker supports both registry/repository[:tag] and registry/repository[@digest] image path formats. For more information about using your custom training container, see  https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms.html/Using Your Own Algorithms with Amazon SageMaker.2You must specify either the algorithm name to the  AlgorithmName parameter or the image URI of the algorithm container to the  TrainingImage parameter.*For more information, see the note in the  AlgorithmName parameter description._amazonka-sagemakerCreate a value of _" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:_, _ - The name of the algorithm resource to use for the training job. This must be an algorithm resource that you created or subscribe to on Amazon Web Services Marketplace.2You must specify either the algorithm name to the  AlgorithmName parameter or the image URI of the algorithm container to the  TrainingImage parameter.Note that the  AlgorithmName+ parameter is mutually exclusive with the  TrainingImage, parameter. If you specify a value for the  AlgorithmName+ parameter, you can't specify a value for  TrainingImage, and vice versa.If you specify values for both parameters, the training job might break; if you don't specify any value for both parameters, the training job might raise a null error._, _ - The arguments for a container used to run a training job. See  https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-training-algo-dockerfile.html-How Amazon SageMaker Runs Your Training Image for additional information._, _ - The  1https://docs.docker.com/engine/reference/builder/(entrypoint script for a Docker container used to run a training job. This script takes precedence over the default train processing instructions. See  https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-training-algo-dockerfile.html-How Amazon SageMaker Runs Your Training Image for more information._, _ - To generate and save time-series metrics during training, set to true. The default is false and time-series metrics aren't generated except in the following cases:0You use one of the SageMaker built-in algorithms"You use one of the following  https://docs.aws.amazon.com/sagemaker/latest/dg/pre-built-containers-frameworks-deep-learning.html Prebuilt SageMaker Docker Images:Tensorflow (version >= 1.15)MXNet (version >= 1.6)PyTorch (version >= 1.3))You specify at least one MetricDefinition_, _ - A list of metric definition objects. Each object specifies the metric name and regular expressions used to parse algorithm logs. SageMaker publishes each metric to Amazon CloudWatch._, _ - The registry path of the Docker image that contains the training algorithm. For information about docker registry paths for SageMaker built-in algorithms, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-algo-docker-registry-paths.html&Docker Registry Paths and Example Code in the  Amazon SageMaker developer guide. SageMaker supports both registry/repository[:tag] and registry/repository[@digest] image path formats. For more information about using your custom training container, see  https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms.html/Using Your Own Algorithms with Amazon SageMaker.2You must specify either the algorithm name to the  AlgorithmName parameter or the image URI of the algorithm container to the  TrainingImage parameter.*For more information, see the note in the  AlgorithmName parameter description._, _ - Undocumented member._amazonka-sagemakerThe name of the algorithm resource to use for the training job. This must be an algorithm resource that you created or subscribe to on Amazon Web Services Marketplace.2You must specify either the algorithm name to the  AlgorithmName parameter or the image URI of the algorithm container to the  TrainingImage parameter.Note that the  AlgorithmName+ parameter is mutually exclusive with the  TrainingImage, parameter. If you specify a value for the  AlgorithmName+ parameter, you can't specify a value for  TrainingImage, and vice versa.If you specify values for both parameters, the training job might break; if you don't specify any value for both parameters, the training job might raise a null error._amazonka-sagemaker?The arguments for a container used to run a training job. See  https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-training-algo-dockerfile.html-How Amazon SageMaker Runs Your Training Image for additional information._amazonka-sagemakerThe  1https://docs.docker.com/engine/reference/builder/(entrypoint script for a Docker container used to run a training job. This script takes precedence over the default train processing instructions. See  https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-training-algo-dockerfile.html-How Amazon SageMaker Runs Your Training Image for more information._amazonka-sagemakerTo generate and save time-series metrics during training, set to true. The default is false and time-series metrics aren't generated except in the following cases:0You use one of the SageMaker built-in algorithms"You use one of the following  https://docs.aws.amazon.com/sagemaker/latest/dg/pre-built-containers-frameworks-deep-learning.html Prebuilt SageMaker Docker Images:Tensorflow (version >= 1.15)MXNet (version >= 1.6)PyTorch (version >= 1.3))You specify at least one MetricDefinition_amazonka-sagemakerA list of metric definition objects. Each object specifies the metric name and regular expressions used to parse algorithm logs. SageMaker publishes each metric to Amazon CloudWatch._amazonka-sagemakerThe registry path of the Docker image that contains the training algorithm. For information about docker registry paths for SageMaker built-in algorithms, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-algo-docker-registry-paths.html&Docker Registry Paths and Example Code in the  Amazon SageMaker developer guide. SageMaker supports both registry/repository[:tag] and registry/repository[@digest] image path formats. For more information about using your custom training container, see  https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms.html/Using Your Own Algorithms with Amazon SageMaker.2You must specify either the algorithm name to the  AlgorithmName parameter or the image URI of the algorithm container to the  TrainingImage parameter.*For more information, see the note in the  AlgorithmName parameter description._amazonka-sagemakerUndocumented member._amazonka-sagemaker___________________________________(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?s4_````````````````````````````````````````````````____````````````````````````````````````````````````___````````````````````````````````````````````````_(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';{`amazonka-sagemakerDefines an instance group for heterogeneous cluster training. When requesting a training job using the  https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTrainingJob.htmlCreateTrainingJob3 API, you can configure multiple instance groups .See: ` smart constructor.`amazonka-sagemaker2Specifies the instance type of the instance group.`amazonka-sagemaker8Specifies the number of instances of the instance group.`amazonka-sagemaker)Specifies the name of the instance group.`amazonka-sagemakerCreate a value of `" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:`, `5 - Specifies the instance type of the instance group.`, `; - Specifies the number of instances of the instance group.`, `, - Specifies the name of the instance group.`amazonka-sagemaker2Specifies the instance type of the instance group.`amazonka-sagemaker8Specifies the number of instances of the instance group.`amazonka-sagemaker)Specifies the name of the instance group.`amazonka-sagemaker`amazonka-sagemaker`amazonka-sagemaker` ````````` `````````(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';`amazonka-sagemakerDescribes the resources, including machine learning (ML) compute instances and ML storage volumes, to use for model training.See: ` smart constructor.`amazonka-sagemakerThe number of ML compute instances to use. For distributed training, provide a value greater than 1.`amazonka-sagemakerbamazonka-sagemakerA list of the metrics that the algorithm emits that can be used as the objective metric in a hyperparameter tuning job.bamazonka-sagemakerIndicates whether the algorithm supports distributed training. If set to false, buyers can't request more than one instance during training.bamazonka-sagemakerAn MD5 hash of the training algorithm that identifies the Docker image used for training.bamazonka-sagemakerThe Amazon ECR registry path of the Docker image that contains the training algorithm.bamazonka-sagemakerA list of the instance types that this algorithm can use for training.bamazonka-sagemaker A list of ChannelSpecification objects, which specify the input sources to be used by the algorithm.bamazonka-sagemakerCreate a value of b" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:b, b - A list of MetricDefinition objects, which are used for parsing metrics generated by the algorithm.b, b - A list of the HyperParameterSpecification objects, that define the supported hyperparameters. This is required if the algorithm supports automatic model tuning.>b, b - A list of the metrics that the algorithm emits that can be used as the objective metric in a hyperparameter tuning job.b, b - Indicates whether the algorithm supports distributed training. If set to false, buyers can't request more than one instance during training.b, b - An MD5 hash of the training algorithm that identifies the Docker image used for training.b, b - The Amazon ECR registry path of the Docker image that contains the training algorithm.b, b - A list of the instance types that this algorithm can use for training.b, b - A list of ChannelSpecification objects, which specify the input sources to be used by the algorithm.bamazonka-sagemaker A list of MetricDefinition objects, which are used for parsing metrics generated by the algorithm.bamazonka-sagemakerA list of the HyperParameterSpecification objects, that define the supported hyperparameters. This is required if the algorithm supports automatic model tuning.>bamazonka-sagemakerA list of the metrics that the algorithm emits that can be used as the objective metric in a hyperparameter tuning job.bamazonka-sagemakerIndicates whether the algorithm supports distributed training. If set to false, buyers can't request more than one instance during training.bamazonka-sagemakerAn MD5 hash of the training algorithm that identifies the Docker image used for training.bamazonka-sagemakerThe Amazon ECR registry path of the Docker image that contains the training algorithm.bamazonka-sagemakerA list of the instance types that this algorithm can use for training.bamazonka-sagemaker A list of ChannelSpecification objects, which specify the input sources to be used by the algorithm.bamazonka-sagemakerbamazonka-sagemakerbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbb(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?A@#bcccccccccccccccccccccbbbbbbbbbbbbbbcccccccccccccccccccccbbbbbbbbbbbbbcccccccccccccccccccccbbbbbbbbbbb(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';L camazonka-sagemakerDefines how to perform inference generation after a training job is run.See: c smart constructor.camazonka-sagemakerA list of the instance types that are used to generate inferences in real-time.This parameter is required for unversioned models, and optional for versioned models.camazonka-sagemakerA list of the instance types on which a transformation job can be run or on which an endpoint can be deployed.This parameter is required for unversioned models, and optional for versioned models.camazonka-sagemakerThe Amazon ECR registry path of the Docker image that contains the inference code.camazonka-sagemaker,The supported MIME types for the input data.camazonka-sagemaker-The supported MIME types for the output data.camazonka-sagemakerCreate a value of c" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:c, c - A list of the instance types that are used to generate inferences in real-time.This parameter is required for unversioned models, and optional for versioned models.c, c - A list of the instance types on which a transformation job can be run or on which an endpoint can be deployed.This parameter is required for unversioned models, and optional for versioned models.c, c - The Amazon ECR registry path of the Docker image that contains the inference code.c, c/ - The supported MIME types for the input data.c, c0 - The supported MIME types for the output data.camazonka-sagemakerA list of the instance types that are used to generate inferences in real-time.This parameter is required for unversioned models, and optional for versioned models.camazonka-sagemakerA list of the instance types on which a transformation job can be run or on which an endpoint can be deployed.This parameter is required for unversioned models, and optional for versioned models.camazonka-sagemakerThe Amazon ECR registry path of the Docker image that contains the inference code.camazonka-sagemaker,The supported MIME types for the input data.camazonka-sagemaker-The supported MIME types for the output data.camazonka-sagemakerc ccccccccccccc ccccccccccccc(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';Ucamazonka-sagemaker5Provides summary information about the model package.See: c smart constructor.camazonka-sagemaker!The approval status of the model.camazonka-sagemaker%The description of the model package.camazonka-sagemaker(The version number of a versioned model.camazonka-sagemaker$The group name for the model packagecamazonka-sagemaker4The Amazon Resource Name (ARN) of the model package.camazonka-sagemaker2The creation time of the mortgage package summary.camazonka-sagemaker#The status of the mortgage package.camazonka-sagemakerCreate a value of c" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:c, c$ - The approval status of the model.c, c( - The description of the model package.c, c+ - The version number of a versioned model.c, c' - The group name for the model packagec, c7 - The Amazon Resource Name (ARN) of the model package.c, c5 - The creation time of the mortgage package summary.c, c - Undocumented member.c, c& - The status of the mortgage package.camazonka-sagemaker!The approval status of the model.camazonka-sagemaker%The description of the model package.camazonka-sagemaker(The version number of a versioned model.camazonka-sagemaker$The group name for the model packagecamazonka-sagemaker4The Amazon Resource Name (ARN) of the model package.camazonka-sagemaker2The creation time of the mortgage package summary.camazonka-sagemakerUndocumented member.camazonka-sagemaker#The status of the mortgage package.camazonka-sagemakercamazonka-sagemakercamazonka-sagemakercamazonka-sagemakercamazonka-sagemakerccccccccccccccccccccccccccccccccccccccc(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';b[camazonka-sagemakerA structure of additional Inference Specification. Additional Inference Specification specifies details about inference jobs that can be run with models based on this model packageSee: c smart constructor.camazonka-sagemaker7A description of the additional Inference specificationcamazonka-sagemaker,The supported MIME types for the input data.camazonka-sagemakerA list of the instance types that are used to generate inferences in real-time.camazonka-sagemaker-The supported MIME types for the output data.camazonka-sagemakerA list of the instance types on which a transformation job can be run or on which an endpoint can be deployed.camazonka-sagemakerA unique name to identify the additional inference specification. The name must be unique within the list of your additional inference specifications for a particular model package.camazonka-sagemakerThe Amazon ECR registry path of the Docker image that contains the inference code.camazonka-sagemakerCreate a value of c" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:c, c: - A description of the additional Inference specificationc, c/ - The supported MIME types for the input data.c, c - A list of the instance types that are used to generate inferences in real-time.c, c0 - The supported MIME types for the output data.c, c - A list of the instance types on which a transformation job can be run or on which an endpoint can be deployed.c, c - A unique name to identify the additional inference specification. The name must be unique within the list of your additional inference specifications for a particular model package.c, c - The Amazon ECR registry path of the Docker image that contains the inference code.camazonka-sagemaker7A description of the additional Inference specificationcamazonka-sagemaker,The supported MIME types for the input data.camazonka-sagemakerA list of the instance types that are used to generate inferences in real-time.camazonka-sagemaker-The supported MIME types for the output data.camazonka-sagemakerA list of the instance types on which a transformation job can be run or on which an endpoint can be deployed.camazonka-sagemakerA unique name to identify the additional inference specification. The name must be unique within the list of your additional inference specifications for a particular model package.camazonka-sagemakerThe Amazon ECR registry path of the Docker image that contains the inference code.camazonka-sagemakercamazonka-sagemakerccccccccccccccccccccccccccccccccccc(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?cDcccccccc ccccccccccccc(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';gBdamazonka-sagemaker"Metadata for a transform job step.See: d smart constructor.damazonka-sagemakerThe Amazon Resource Name (ARN) of the transform job that was run by this step execution.damazonka-sagemakerCreate a value of d" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:d, d - The Amazon Resource Name (ARN) of the transform job that was run by this step execution.damazonka-sagemakerThe Amazon Resource Name (ARN) of the transform job that was run by this step execution.dddddddddd(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';rdamazonka-sagemaker0Provides a summary of a transform job. Multiple TransformJobSummary objects are returned as a list after in response to a ListTransformJobs call.See: d smart constructor.damazonka-sagemaker2If the transform job failed, the reason it failed.damazonka-sagemaker3Indicates when the transform job was last modified.damazonka-sagemakerIndicates when the transform job ends on compute instances. For successful jobs and stopped jobs, this is the exact time recorded after the results are uploaded. For failed jobs, this is when Amazon SageMaker detected that the job failed.damazonka-sagemakerThe name of the transform job.damazonka-sagemaker4The Amazon Resource Name (ARN) of the transform job.damazonka-sagemaker:A timestamp that shows when the transform Job was created.damazonka-sagemaker The status of the transform job.damazonka-sagemakerCreate a value of d" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:d, d5 - If the transform job failed, the reason it failed.d, d6 - Indicates when the transform job was last modified.d, d - Indicates when the transform job ends on compute instances. For successful jobs and stopped jobs, this is the exact time recorded after the results are uploaded. For failed jobs, this is when Amazon SageMaker detected that the job failed.d, d! - The name of the transform job.d, d7 - The Amazon Resource Name (ARN) of the transform job.d, d= - A timestamp that shows when the transform Job was created.d, d# - The status of the transform job.damazonka-sagemaker2If the transform job failed, the reason it failed.damazonka-sagemaker3Indicates when the transform job was last modified.damazonka-sagemakerIndicates when the transform job ends on compute instances. For successful jobs and stopped jobs, this is the exact time recorded after the results are uploaded. For failed jobs, this is when Amazon SageMaker detected that the job failed.damazonka-sagemakerThe name of the transform job.damazonka-sagemaker4The Amazon Resource Name (ARN) of the transform job.damazonka-sagemaker:A timestamp that shows when the transform Job was created.damazonka-sagemaker The status of the transform job.damazonka-sagemakerdamazonka-sagemakerdamazonka-sagemakerdamazonka-sagemakerddddddddddddddddddddddddddddddddddd(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; damazonka-sagemaker)Describes the results of a transform job.See: d smart constructor.damazonka-sagemakerThe MIME type used to specify the output data. Amazon SageMaker uses the MIME type with each http call to transfer data from the transform job.damazonka-sagemakerDefines how to assemble the results of the transform job as a single S3 object. Choose a format that is most convenient to you. To concatenate the results in binary format, specify None. To add a newline character at the end of every transformed record, specify Line.damazonka-sagemakerThe Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption. The KmsKeyId& can be any of the following formats:Key ID: $1234abcd-12ab-34cd-56ef-1234567890abKey ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab Alias name: alias/ExampleAliasAlias name ARN: 5arn:aws:kms:us-west-2:111122223333:alias/ExampleAliasIf you don't provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role's account. For more information, see  https://docs.aws.amazon.com/AmazonS3/latest/dev/UsingKMSEncryption.htmlKMS-Managed Encryption Keys in the .Amazon Simple Storage Service Developer Guide.The KMS key policy must grant permission to the IAM role that you specify in your  https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateModel.html CreateModel& request. For more information, see  https://docs.aws.amazon.com/kms/latest/developerguide/key-policies.html-Using Key Policies in Amazon Web Services KMS in the :Amazon Web Services Key Management Service Developer Guide.damazonka-sagemakerThe Amazon S3 path where you want Amazon SageMaker to store the results of the transform job. For example,  s3://bucket-name/key-name-prefix.For every S3 object used as input for the transform job, batch transform stores the transformed data with an .out suffix in a corresponding subfolder in the location in the output prefix. For example, for the input data stored at 5s3://bucket-name/input-name-prefix/dataset01/data.csv3, batch transform stores the transformed data at s3://bucket-name/output-name-prefix/input-name-prefix/data.csv.out. Batch transform doesn't upload partially processed objects. For an input S3 object that contains multiple records, it creates an .out file only if the transform job succeeds on the entire file. When the input contains multiple S3 objects, the batch transform job processes the listed S3 objects and uploads only the output for successfully processed objects. If any object fails in the transform job batch transform marks the job as failed to prompt investigation.damazonka-sagemakerCreate a value of d" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:d, d - The MIME type used to specify the output data. Amazon SageMaker uses the MIME type with each http call to transfer data from the transform job.d, d - Defines how to assemble the results of the transform job as a single S3 object. Choose a format that is most convenient to you. To concatenate the results in binary format, specify None. To add a newline character at the end of every transformed record, specify Line.d, d - The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption. The KmsKeyId& can be any of the following formats:Key ID: $1234abcd-12ab-34cd-56ef-1234567890abKey ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab Alias name: alias/ExampleAliasAlias name ARN: 5arn:aws:kms:us-west-2:111122223333:alias/ExampleAliasIf you don't provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role's account. For more information, see  https://docs.aws.amazon.com/AmazonS3/latest/dev/UsingKMSEncryption.htmlKMS-Managed Encryption Keys in the .Amazon Simple Storage Service Developer Guide.The KMS key policy must grant permission to the IAM role that you specify in your  https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateModel.html CreateModel& request. For more information, see  https://docs.aws.amazon.com/kms/latest/developerguide/key-policies.html-Using Key Policies in Amazon Web Services KMS in the :Amazon Web Services Key Management Service Developer Guide.d, d - The Amazon S3 path where you want Amazon SageMaker to store the results of the transform job. For example,  s3://bucket-name/key-name-prefix.For every S3 object used as input for the transform job, batch transform stores the transformed data with an .out suffix in a corresponding subfolder in the location in the output prefix. For example, for the input data stored at 5s3://bucket-name/input-name-prefix/dataset01/data.csv3, batch transform stores the transformed data at s3://bucket-name/output-name-prefix/input-name-prefix/data.csv.out. Batch transform doesn't upload partially processed objects. For an input S3 object that contains multiple records, it creates an .out file only if the transform job succeeds on the entire file. When the input contains multiple S3 objects, the batch transform job processes the listed S3 objects and uploads only the output for successfully processed objects. If any object fails in the transform job batch transform marks the job as failed to prompt investigation.damazonka-sagemakerThe MIME type used to specify the output data. Amazon SageMaker uses the MIME type with each http call to transfer data from the transform job.damazonka-sagemakerDefines how to assemble the results of the transform job as a single S3 object. Choose a format that is most convenient to you. To concatenate the results in binary format, specify None. To add a newline character at the end of every transformed record, specify Line.damazonka-sagemakerThe Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption. The KmsKeyId& can be any of the following formats:Key ID: $1234abcd-12ab-34cd-56ef-1234567890abKey ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab Alias name: alias/ExampleAliasAlias name ARN: 5arn:aws:kms:us-west-2:111122223333:alias/ExampleAliasIf you don't provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role's account. For more information, see  https://docs.aws.amazon.com/AmazonS3/latest/dev/UsingKMSEncryption.htmlKMS-Managed Encryption Keys in the .Amazon Simple Storage Service Developer Guide.The KMS key policy must grant permission to the IAM role that you specify in your  https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateModel.html CreateModel& request. For more information, see  https://docs.aws.amazon.com/kms/latest/developerguide/key-policies.html-Using Key Policies in Amazon Web Services KMS in the :Amazon Web Services Key Management Service Developer Guide.damazonka-sagemakerThe Amazon S3 path where you want Amazon SageMaker to store the results of the transform job. For example,  s3://bucket-name/key-name-prefix.For every S3 object used as input for the transform job, batch transform stores the transformed data with an .out suffix in a corresponding subfolder in the location in the output prefix. For example, for the input data stored at 5s3://bucket-name/input-name-prefix/dataset01/data.csv3, batch transform stores the transformed data at s3://bucket-name/output-name-prefix/input-name-prefix/data.csv.out. Batch transform doesn't upload partially processed objects. For an input S3 object that contains multiple records, it creates an .out file only if the transform job succeeds on the entire file. When the input contains multiple S3 objects, the batch transform job processes the listed S3 objects and uploads only the output for successfully processed objects. If any object fails in the transform job batch transform marks the job as failed to prompt investigation.damazonka-sagemakerd ddddddddddd ddddddddddd(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';damazonka-sagemakerDescribes the resources, including ML instance types and ML instance count, to use for transform job.See: d smart constructor.damazonka-sagemakerThe Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt model data on the storage volume attached to the ML compute instance(s) that run the batch transform job.Certain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can't request a VolumeKmsKeyId1 when using an instance type with local storage.For a list of instance types that support local instance storage, see  https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/InstanceStorage.html#instance-store-volumesInstance Store Volumes.For more information about local instance storage encryption, see  https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ssd-instance-store.htmlSSD Instance Store Volumes.The VolumeKmsKeyId% can be any of the following formats:Key ID: $1234abcd-12ab-34cd-56ef-1234567890abKey ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab Alias name: alias/ExampleAliasAlias name ARN: 5arn:aws:kms:us-west-2:111122223333:alias/ExampleAliasdamazonka-sagemakerThe ML compute instance type for the transform job. If you are using built-in algorithms to transform moderately sized datasets, we recommend using ml.m4.xlarge or  ml.m5.largeinstance types.damazonka-sagemakerThe number of ML compute instances to use in the transform job. The default value is 1, and the maximum is 100. For distributed transform jobs, specify a value greater than 1.damazonka-sagemakerCreate a value of d" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:d, d - The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt model data on the storage volume attached to the ML compute instance(s) that run the batch transform job.Certain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can't request a VolumeKmsKeyId1 when using an instance type with local storage.For a list of instance types that support local instance storage, see  https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/InstanceStorage.html#instance-store-volumesInstance Store Volumes.For more information about local instance storage encryption, see  https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ssd-instance-store.htmlSSD Instance Store Volumes.The VolumeKmsKeyId% can be any of the following formats:Key ID: $1234abcd-12ab-34cd-56ef-1234567890abKey ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab Alias name: alias/ExampleAliasAlias name ARN: 5arn:aws:kms:us-west-2:111122223333:alias/ExampleAliasd, d - The ML compute instance type for the transform job. If you are using built-in algorithms to transform moderately sized datasets, we recommend using ml.m4.xlarge or  ml.m5.largeinstance types.d, d - The number of ML compute instances to use in the transform job. The default value is 1, and the maximum is 100. For distributed transform jobs, specify a value greater than 1.damazonka-sagemakerThe Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt model data on the storage volume attached to the ML compute instance(s) that run the batch transform job.Certain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can't request a VolumeKmsKeyId1 when using an instance type with local storage.For a list of instance types that support local instance storage, see  https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/InstanceStorage.html#instance-store-volumesInstance Store Volumes.For more information about local instance storage encryption, see  https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ssd-instance-store.htmlSSD Instance Store Volumes.The VolumeKmsKeyId% can be any of the following formats:Key ID: $1234abcd-12ab-34cd-56ef-1234567890abKey ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab Alias name: alias/ExampleAliasAlias name ARN: 5arn:aws:kms:us-west-2:111122223333:alias/ExampleAliasdamazonka-sagemakerThe ML compute instance type for the transform job. If you are using built-in algorithms to transform moderately sized datasets, we recommend using ml.m4.xlarge or  ml.m5.largeinstance types.damazonka-sagemakerThe number of ML compute instances to use in the transform job. The default value is 1, and the maximum is 100. For distributed transform jobs, specify a value greater than 1.damazonka-sagemakerdamazonka-sagemakerd ddddddddd ddddddddd(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';`damazonka-sagemakerDescribes the S3 data source.See: d smart constructor.damazonka-sagemakerIf you choose S3Prefix, S3Uri identifies a key name prefix. Amazon SageMaker uses all objects with the specified key name prefix for batch transform.If you choose  ManifestFile, S3Uri identifies an object that is a manifest file containing a list of object keys that you want Amazon SageMaker to use for batch transform.%The following values are compatible:  ManifestFile, S3Prefix'The following value is not compatible: AugmentedManifestFiledamazonka-sagemaker)Depending on the value specified for the  S3DataType, identifies either a key name prefix or a manifest. For example:-A key name prefix might look like this: s3://bucketname/exampleprefix.&A manifest might look like this:  s3://bucketname/example.manifestThe manifest is an S3 object which is a JSON file with the following format: 2[ {"prefix": "s3://customer_bucket/some/prefix/"}, "relative/path/to/custdata-1", "relative/path/custdata-2", ... "relative/path/custdata-N" ])The preceding JSON matches the following S3Uris:  - The IAM roles that SageMaker uses to run the training jobs.e, e - An array of AlgorithmValidationProfile objects, each of which specifies a training job and batch transform job that SageMaker runs to validate your algorithm.eamazonka-sagemaker;The IAM roles that SageMaker uses to run the training jobs.eamazonka-sagemaker An array of AlgorithmValidationProfile objects, each of which specifies a training job and batch transform job that SageMaker runs to validate your algorithm.eamazonka-sagemakereamazonka-sagemakereeeeeeeeeeeeeee(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';:d&eamazonka-sagemakerA batch transform job. For information about SageMaker batch transform, see  https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform.htmlUse Batch Transform.See: e smart constructor.eamazonka-sagemakerThe Amazon Resource Name (ARN) of the AutoML job that created the transform job.eamazonka-sagemakerSpecifies the number of records to include in a mini-batch for an HTTP inference request. A record is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.eamazonka-sagemaker:A timestamp that shows when the transform Job was created.eamazonka-sagemakerThe environment variables to set in the Docker container. We support up to 16 key and values entries in the map.eamazonka-sagemaker2If the transform job failed, the reason it failed.eamazonka-sagemakerThe Amazon Resource Name (ARN) of the labeling job that created the transform job.eamazonka-sagemakerThe maximum number of parallel requests that can be sent to each instance in a transform job. If MaxConcurrentTransforms is set to 0 or left unset, SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm. If the execution-parameters endpoint is not enabled, the default value is 1. For built-in algorithms, you don't need to set a value for MaxConcurrentTransforms.eamazonka-sagemakerThe maximum allowed size of the payload, in MB. A payload is the data portion of a record (without metadata). The value in MaxPayloadInMB must be greater than, or equal to, the size of a single record. To estimate the size of a record in MB, divide the size of your dataset by the number of records. To ensure that the records fit within the maximum payload size, we recommend using a slightly larger value. The default value is 6 MB. For cases where the payload might be arbitrarily large and is transmitted using HTTP chunked encoding, set the value to 0. This feature works only in supported algorithms. Currently, SageMaker built-in algorithms do not support HTTP chunked encoding.eamazonka-sagemaker8The name of the model associated with the transform job.eamazonka-sagemaker1A list of tags associated with the transform job.eamazonka-sagemakerIndicates when the transform job has been completed, or has stopped or failed. You are billed for the time interval between this time and the value of TransformStartTime.eamazonka-sagemaker4The Amazon Resource Name (ARN) of the transform job.eamazonka-sagemakerThe name of the transform job.eamazonka-sagemaker The status of the transform job.Transform job statuses are: InProgress - The job is in progress. Completed - The job has completed.Failed - The transform job has failed. To see the reason for the failure, see the  FailureReason! field in the response to a DescribeTransformJob call.Stopping! - The transform job is stopping.Stopped! - The transform job has stopped.eamazonka-sagemakerIndicates when the transform job starts on ML instances. You are billed for the time interval between this time and the value of TransformEndTime.eamazonka-sagemakerCreate a value of e" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:e, e - The Amazon Resource Name (ARN) of the AutoML job that created the transform job.e, e - Specifies the number of records to include in a mini-batch for an HTTP inference request. A record is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.e, e= - A timestamp that shows when the transform Job was created.e, e - Undocumented member.e, e - The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.e, e - Undocumented member.e, e5 - If the transform job failed, the reason it failed.e, e - The Amazon Resource Name (ARN) of the labeling job that created the transform job.e, e - The maximum number of parallel requests that can be sent to each instance in a transform job. If MaxConcurrentTransforms is set to 0 or left unset, SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm. If the execution-parameters endpoint is not enabled, the default value is 1. For built-in algorithms, you don't need to set a value for MaxConcurrentTransforms.e, e - The maximum allowed size of the payload, in MB. A payload is the data portion of a record (without metadata). The value in MaxPayloadInMB must be greater than, or equal to, the size of a single record. To estimate the size of a record in MB, divide the size of your dataset by the number of records. To ensure that the records fit within the maximum payload size, we recommend using a slightly larger value. The default value is 6 MB. For cases where the payload might be arbitrarily large and is transmitted using HTTP chunked encoding, set the value to 0. This feature works only in supported algorithms. Currently, SageMaker built-in algorithms do not support HTTP chunked encoding.e, e - Undocumented member.e, e; - The name of the model associated with the transform job.e, e4 - A list of tags associated with the transform job.e, e - Indicates when the transform job has been completed, or has stopped or failed. You are billed for the time interval between this time and the value of TransformStartTime.e, e - Undocumented member.e, f7 - The Amazon Resource Name (ARN) of the transform job.e, f! - The name of the transform job.e, f# - The status of the transform job.Transform job statuses are: InProgress - The job is in progress. Completed - The job has completed.Failed - The transform job has failed. To see the reason for the failure, see the  FailureReason! field in the response to a DescribeTransformJob call.Stopping! - The transform job is stopping.Stopped! - The transform job has stopped.e, f - Undocumented member.e, f - Undocumented member.e, f - Indicates when the transform job starts on ML instances. You are billed for the time interval between this time and the value of TransformEndTime.eamazonka-sagemakerThe Amazon Resource Name (ARN) of the AutoML job that created the transform job.eamazonka-sagemakerSpecifies the number of records to include in a mini-batch for an HTTP inference request. A record is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.eamazonka-sagemaker:A timestamp that shows when the transform Job was created.eamazonka-sagemakerUndocumented member.eamazonka-sagemakerThe environment variables to set in the Docker container. We support up to 16 key and values entries in the map.eamazonka-sagemakerUndocumented member.eamazonka-sagemaker2If the transform job failed, the reason it failed.eamazonka-sagemakerThe Amazon Resource Name (ARN) of the labeling job that created the transform job.eamazonka-sagemakerThe maximum number of parallel requests that can be sent to each instance in a transform job. If MaxConcurrentTransforms is set to 0 or left unset, SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm. If the execution-parameters endpoint is not enabled, the default value is 1. For built-in algorithms, you don't need to set a value for MaxConcurrentTransforms.eamazonka-sagemakerThe maximum allowed size of the payload, in MB. A payload is the data portion of a record (without metadata). The value in MaxPayloadInMB must be greater than, or equal to, the size of a single record. To estimate the size of a record in MB, divide the size of your dataset by the number of records. To ensure that the records fit within the maximum payload size, we recommend using a slightly larger value. The default value is 6 MB. For cases where the payload might be arbitrarily large and is transmitted using HTTP chunked encoding, set the value to 0. This feature works only in supported algorithms. Currently, SageMaker built-in algorithms do not support HTTP chunked encoding.eamazonka-sagemakerUndocumented member.eamazonka-sagemaker8The name of the model associated with the transform job.eamazonka-sagemaker1A list of tags associated with the transform job.eamazonka-sagemakerIndicates when the transform job has been completed, or has stopped or failed. You are billed for the time interval between this time and the value of TransformStartTime.eamazonka-sagemakerUndocumented member.famazonka-sagemaker4The Amazon Resource Name (ARN) of the transform job.famazonka-sagemakerThe name of the transform job.famazonka-sagemaker The status of the transform job.Transform job statuses are: InProgress - The job is in progress. Completed - The job has completed.Failed - The transform job has failed. To see the reason for the failure, see the  FailureReason! field in the response to a DescribeTransformJob call.Stopping! - The transform job is stopping.Stopped! - The transform job has stopped.famazonka-sagemakerUndocumented member.famazonka-sagemakerUndocumented member.famazonka-sagemakerIndicates when the transform job starts on ML instances. You are billed for the time interval between this time and the value of TransformEndTime.-eeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeffffff-eeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeffffff(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';Cfamazonka-sagemakerRepresents an input or output artifact of a trial component. You specify TrialComponentArtifact as part of the InputArtifacts and OutputArtifacts0 parameters in the CreateTrialComponent request.Examples of input artifacts are datasets, algorithms, hyperparameters, source code, and instance types. Examples of output artifacts are metrics, snapshots, logs, and images.See: f smart constructor.famazonka-sagemakerThe media type of the artifact, which indicates the type of data in the artifact file. The media type consists of a type and a subtype concatenated with a slash (/) character, for example, text/csv, image/jpeg, and s3/uri. The type specifies the category of the media. The subtype specifies the kind of data.famazonka-sagemakerThe location of the artifact.famazonka-sagemakerCreate a value of f" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:f, f - The media type of the artifact, which indicates the type of data in the artifact file. The media type consists of a type and a subtype concatenated with a slash (/) character, for example, text/csv, image/jpeg, and s3/uri. The type specifies the category of the media. The subtype specifies the kind of data.f, f - The location of the artifact.famazonka-sagemakerThe media type of the artifact, which indicates the type of data in the artifact file. The media type consists of a type and a subtype concatenated with a slash (/) character, for example, text/csv, image/jpeg, and s3/uri. The type specifies the category of the media. The subtype specifies the kind of data.famazonka-sagemakerThe location of the artifact.famazonka-sagemakerfffffffffffffff(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';Lfamazonka-sagemaker.A summary of the metrics of a trial component.See: f smart constructor.famazonka-sagemaker The average value of the metric.famazonka-sagemaker2The number of samples used to generate the metric.famazonka-sagemaker$The most recent value of the metric.famazonka-sagemaker The maximum value of the metric.famazonka-sagemakerThe name of the metric.famazonka-sagemaker The minimum value of the metric.famazonka-sagemaker-The Amazon Resource Name (ARN) of the source.famazonka-sagemaker%The standard deviation of the metric.famazonka-sagemaker!When the metric was last updated.famazonka-sagemakerCreate a value of f" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:f, f# - The average value of the metric.f, f5 - The number of samples used to generate the metric.f, f' - The most recent value of the metric.f, f# - The maximum value of the metric.f, f - The name of the metric.f, f# - The minimum value of the metric.f, f0 - The Amazon Resource Name (ARN) of the source.f, f( - The standard deviation of the metric.f, f$ - When the metric was last updated.famazonka-sagemaker The average value of the metric.famazonka-sagemaker2The number of samples used to generate the metric.famazonka-sagemaker$The most recent value of the metric.famazonka-sagemaker The maximum value of the metric.famazonka-sagemakerThe name of the metric.famazonka-sagemaker The minimum value of the metric.famazonka-sagemaker-The Amazon Resource Name (ARN) of the source.famazonka-sagemaker%The standard deviation of the metric.famazonka-sagemaker!When the metric was last updated.ffffffffffffffffffffffffffffffffffffffffff(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';T+famazonka-sagemaker+The value of a hyperparameter. Only one of  NumberValue or  StringValue can be specified.=This object is specified in the CreateTrialComponent request.See: f smart constructor.famazonka-sagemakerThe numeric value of a numeric hyperparameter. If you specify a value for this parameter, you can't specify the  StringValue parameter.famazonka-sagemakerThe string value of a categorical hyperparameter. If you specify a value for this parameter, you can't specify the  NumberValue parameter.famazonka-sagemakerCreate a value of f" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:f, f - The numeric value of a numeric hyperparameter. If you specify a value for this parameter, you can't specify the  StringValue parameter.f, f - The string value of a categorical hyperparameter. If you specify a value for this parameter, you can't specify the  NumberValue parameter.famazonka-sagemakerThe numeric value of a numeric hyperparameter. If you specify a value for this parameter, you can't specify the  StringValue parameter.famazonka-sagemakerThe string value of a categorical hyperparameter. If you specify a value for this parameter, you can't specify the  NumberValue parameter.ffffffffffffff(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?Tffffffff fffffffffffff(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';Y!famazonka-sagemakerThe Amazon Resource Name (ARN) and job type of the source of a trial component.See: f smart constructor.famazonka-sagemakerThe source job type.famazonka-sagemaker&The source Amazon Resource Name (ARN).famazonka-sagemakerCreate a value of f" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:f, f - The source job type.f, f) - The source Amazon Resource Name (ARN).famazonka-sagemakerThe source job type.famazonka-sagemaker&The source Amazon Resource Name (ARN).famazonka-sagemakerfffffffffffffff(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';]Ifamazonka-sagemaker"The status of the trial component.See: f smart constructor.famazonka-sagemaker2If the component failed, a message describing why.famazonka-sagemaker"The status of the trial component.famazonka-sagemakerCreate a value of f" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:f, f5 - If the component failed, a message describing why.f, f% - The status of the trial component.famazonka-sagemaker2If the component failed, a message describing why.famazonka-sagemaker"The status of the trial component.ffffffffffffff(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';aLfamazonka-sagemakerThe source of the trial.See: g smart constructor.gamazonka-sagemakerThe source job type.gamazonka-sagemaker-The Amazon Resource Name (ARN) of the source.gamazonka-sagemakerCreate a value of f" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:g, g - The source job type.g, g0 - The Amazon Resource Name (ARN) of the source.gamazonka-sagemakerThe source job type.gamazonka-sagemaker-The Amazon Resource Name (ARN) of the source.gamazonka-sagemakergfggggggfgggggg(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';h gamazonka-sagemakerA summary of the properties of a trial. To get the complete set of properties, call the DescribeTrial API and provide the  TrialName.See: g smart constructor.gamazonka-sagemakerWhen the trial was created.gamazonka-sagemaker'The name of the trial as displayed. If  DisplayName isn't specified,  TrialName is displayed.gamazonka-sagemaker!When the trial was last modified.gamazonka-sagemaker,The Amazon Resource Name (ARN) of the trial.gamazonka-sagemakerThe name of the trial.gamazonka-sagemakerCreate a value of g" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:g, g - When the trial was created.g, g* - The name of the trial as displayed. If  DisplayName isn't specified,  TrialName is displayed.g, g$ - When the trial was last modified.g, g/ - The Amazon Resource Name (ARN) of the trial.g, g - The name of the trial.g, g - Undocumented member.gamazonka-sagemakerWhen the trial was created.gamazonka-sagemaker'The name of the trial as displayed. If  DisplayName isn't specified,  TrialName is displayed.gamazonka-sagemaker!When the trial was last modified.gamazonka-sagemaker,The Amazon Resource Name (ARN) of the trial.gamazonka-sagemakerThe name of the trial.gamazonka-sagemakerUndocumented member.gggggggggggggggggggggggggggggg(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';lQgamazonka-sagemakerThe job completion criteria.See: g smart constructor.gamazonka-sagemaker"The value of the objective metric.gamazonka-sagemakerCreate a value of g" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:g, g% - The value of the objective metric.gamazonka-sagemaker"The value of the objective metric.gamazonka-sagemakerggggggggggg(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';2gamazonka-sagemaker'Configures a hyperparameter tuning job.See: g smart constructor.gamazonka-sagemakerThe HyperParameterTuningJobObjective specifies the objective metric used to evaluate the performance of training jobs launched by this tuning job.gamazonka-sagemakerThe ParameterRanges object that specifies the ranges of hyperparameters that this tuning job searches over to find the optimal configuration for the highest model performance against your chosen objective metric.gamazonka-sagemakerA value used to initialize a pseudo-random number generator. Setting a random seed and using the same seed later for the same tuning job will allow hyperparameter optimization to find more a consistent hyperparameter configuration between the two runs.gamazonka-sagemakerThe configuration for the  Hyperband optimization strategy. This parameter should be provided only if  Hyperband" is selected as the strategy for HyperParameterTuningJobConfig.gamazonka-sagemakerSpecifies whether to use early stopping for training jobs launched by the hyperparameter tuning job. Because the  Hyperband strategy has its own advanced internal early stopping mechanism, TrainingJobEarlyStoppingType must be OFF to use  Hyperband. This parameter can take on one of the following values (the default value is OFF): OFFTraining jobs launched by the hyperparameter tuning job do not use early stopping.AUTOSageMaker stops training jobs launched by the hyperparameter tuning job when they are unlikely to perform better than previously completed training jobs. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-early-stopping.htmlStop Training Jobs Early.gamazonka-sagemaker%The tuning job's completion criteria.gamazonka-sagemakerSpecifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training job it launches. For information about search strategies, see  https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-how-it-works.htmlHow Hyperparameter Tuning Works.gamazonka-sagemakerThe ResourceLimits object that specifies the maximum number of training and parallel training jobs that can be used for this hyperparameter tuning job.gamazonka-sagemakerCreate a value of g" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:g, g - The HyperParameterTuningJobObjective specifies the objective metric used to evaluate the performance of training jobs launched by this tuning job.g, g - The ParameterRanges object that specifies the ranges of hyperparameters that this tuning job searches over to find the optimal configuration for the highest model performance against your chosen objective metric.g, g - A value used to initialize a pseudo-random number generator. Setting a random seed and using the same seed later for the same tuning job will allow hyperparameter optimization to find more a consistent hyperparameter configuration between the two runs.g, g - The configuration for the  Hyperband optimization strategy. This parameter should be provided only if  Hyperband" is selected as the strategy for HyperParameterTuningJobConfig.g, g - Specifies whether to use early stopping for training jobs launched by the hyperparameter tuning job. Because the  Hyperband strategy has its own advanced internal early stopping mechanism, TrainingJobEarlyStoppingType must be OFF to use  Hyperband. This parameter can take on one of the following values (the default value is OFF): OFFTraining jobs launched by the hyperparameter tuning job do not use early stopping.AUTOSageMaker stops training jobs launched by the hyperparameter tuning job when they are unlikely to perform better than previously completed training jobs. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-early-stopping.htmlStop Training Jobs Early.g, g( - The tuning job's completion criteria.g, g - Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training job it launches. For information about search strategies, see  https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-how-it-works.htmlHow Hyperparameter Tuning Works.g, g - The ResourceLimits object that specifies the maximum number of training and parallel training jobs that can be used for this hyperparameter tuning job.gamazonka-sagemakerThe HyperParameterTuningJobObjective specifies the objective metric used to evaluate the performance of training jobs launched by this tuning job.gamazonka-sagemakerThe ParameterRanges object that specifies the ranges of hyperparameters that this tuning job searches over to find the optimal configuration for the highest model performance against your chosen objective metric.gamazonka-sagemakerA value used to initialize a pseudo-random number generator. Setting a random seed and using the same seed later for the same tuning job will allow hyperparameter optimization to find more a consistent hyperparameter configuration between the two runs.gamazonka-sagemakerThe configuration for the  Hyperband optimization strategy. This parameter should be provided only if  Hyperband" is selected as the strategy for HyperParameterTuningJobConfig.gamazonka-sagemakerSpecifies whether to use early stopping for training jobs launched by the hyperparameter tuning job. Because the  Hyperband strategy has its own advanced internal early stopping mechanism, TrainingJobEarlyStoppingType must be OFF to use  Hyperband. This parameter can take on one of the following values (the default value is OFF): OFFTraining jobs launched by the hyperparameter tuning job do not use early stopping.AUTOSageMaker stops training jobs launched by the hyperparameter tuning job when they are unlikely to perform better than previously completed training jobs. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-early-stopping.htmlStop Training Jobs Early.gamazonka-sagemaker%The tuning job's completion criteria.gamazonka-sagemakerSpecifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training job it launches. For information about search strategies, see  https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-how-it-works.htmlHow Hyperparameter Tuning Works.gamazonka-sagemakerThe ResourceLimits object that specifies the maximum number of training and parallel training jobs that can be used for this hyperparameter tuning job.gamazonka-sagemakergamazonka-sagemakerggggggggggggggggggggggggggggggggggggggg(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';Bgamazonka-sagemakerMetadata for a tuning step.See: g smart constructor.gamazonka-sagemakerThe Amazon Resource Name (ARN) of the tuning job that was run by this step execution.gamazonka-sagemakerCreate a value of g" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:g, g - The Amazon Resource Name (ARN) of the tuning job that was run by this step execution.gamazonka-sagemakerThe Amazon Resource Name (ARN) of the tuning job that was run by this step execution.gggggggggg(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';gamazonka-sagemakerMetadata for a step execution.See: g smart constructor.gamazonka-sagemakerThe Amazon Resource Name (ARN) of the AutoML job that was run by this step.gamazonka-sagemakerThe URL of the Amazon SQS queue used by this step execution, the pipeline generated token, and a list of output parameters.gamazonka-sagemakerContainer for the metadata for a Clarify check step. The configurations and outcomes of the check step execution. This includes: The type of the check conducted,The Amazon S3 URIs of baseline constraints and statistics files to be used for the drift check.The Amazon S3 URIs of newly calculated baseline constraints and statistics.&The model package group name provided.The Amazon S3 URI of the violation report if violations detected.The Amazon Resource Name (ARN) of check processing job initiated by the step execution.;The boolean flags indicating if the drift check is skipped.If step property BaselineUsedForDriftCheck is set the same as CalculatedBaseline.gamazonka-sagemakerThe outcome of the condition evaluation that was run by this step execution.gamazonka-sagemakerThe configurations and outcomes of an Amazon EMR step execution.gamazonka-sagemaker9The configurations and outcomes of a Fail step execution.gamazonka-sagemakerThe Amazon Resource Name (ARN) of the Lambda function that was run by this step execution and a list of output parameters.gamazonka-sagemakerThe Amazon Resource Name (ARN) of the model that was created by this step execution.gamazonka-sagemakerThe Amazon Resource Name (ARN) of the processing job that was run by this step execution.gamazonka-sagemakerThe configurations and outcomes of the check step execution. This includes: The type of the check conducted.The Amazon S3 URIs of baseline constraints and statistics files to be used for the drift check.The Amazon S3 URIs of newly calculated baseline constraints and statistics.&The model package group name provided.The Amazon S3 URI of the violation report if violations detected.The Amazon Resource Name (ARN) of check processing job initiated by the step execution.;The Boolean flags indicating if the drift check is skipped.If step property BaselineUsedForDriftCheck is set the same as CalculatedBaseline.gamazonka-sagemakerThe Amazon Resource Name (ARN) of the model package that the model was registered to by this step execution.gamazonka-sagemakerThe Amazon Resource Name (ARN) of the training job that was run by this step execution.gamazonka-sagemakerThe Amazon Resource Name (ARN) of the transform job that was run by this step execution.gamazonka-sagemakerThe Amazon Resource Name (ARN) of the tuning job that was run by this step execution.gamazonka-sagemakerCreate a value of g" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:g, g - The Amazon Resource Name (ARN) of the AutoML job that was run by this step.g, g - The URL of the Amazon SQS queue used by this step execution, the pipeline generated token, and a list of output parameters.g, g - Container for the metadata for a Clarify check step. The configurations and outcomes of the check step execution. This includes: The type of the check conducted,The Amazon S3 URIs of baseline constraints and statistics files to be used for the drift check.The Amazon S3 URIs of newly calculated baseline constraints and statistics.&The model package group name provided.The Amazon S3 URI of the violation report if violations detected.The Amazon Resource Name (ARN) of check processing job initiated by the step execution.;The boolean flags indicating if the drift check is skipped.If step property BaselineUsedForDriftCheck is set the same as CalculatedBaseline.g, g - The outcome of the condition evaluation that was run by this step execution.g, g - The configurations and outcomes of an Amazon EMR step execution.g, g< - The configurations and outcomes of a Fail step execution.g, g - The Amazon Resource Name (ARN) of the Lambda function that was run by this step execution and a list of output parameters.g, g - The Amazon Resource Name (ARN) of the model that was created by this step execution.g, g - The Amazon Resource Name (ARN) of the processing job that was run by this step execution.g, g - The configurations and outcomes of the check step execution. This includes: The type of the check conducted.The Amazon S3 URIs of baseline constraints and statistics files to be used for the drift check.The Amazon S3 URIs of newly calculated baseline constraints and statistics.&The model package group name provided.The Amazon S3 URI of the violation report if violations detected.The Amazon Resource Name (ARN) of check processing job initiated by the step execution.;The Boolean flags indicating if the drift check is skipped.If step property BaselineUsedForDriftCheck is set the same as CalculatedBaseline.g, g - The Amazon Resource Name (ARN) of the model package that the model was registered to by this step execution.g, g - The Amazon Resource Name (ARN) of the training job that was run by this step execution.g, g - The Amazon Resource Name (ARN) of the transform job that was run by this step execution.g, g - The Amazon Resource Name (ARN) of the tuning job that was run by this step execution.gamazonka-sagemakerThe Amazon Resource Name (ARN) of the AutoML job that was run by this step.gamazonka-sagemakerThe URL of the Amazon SQS queue used by this step execution, the pipeline generated token, and a list of output parameters.gamazonka-sagemakerContainer for the metadata for a Clarify check step. The configurations and outcomes of the check step execution. This includes: The type of the check conducted,The Amazon S3 URIs of baseline constraints and statistics files to be used for the drift check.The Amazon S3 URIs of newly calculated baseline constraints and statistics.&The model package group name provided.The Amazon S3 URI of the violation report if violations detected.The Amazon Resource Name (ARN) of check processing job initiated by the step execution.;The boolean flags indicating if the drift check is skipped.If step property BaselineUsedForDriftCheck is set the same as CalculatedBaseline.gamazonka-sagemakerThe outcome of the condition evaluation that was run by this step execution.gamazonka-sagemakerThe configurations and outcomes of an Amazon EMR step execution.gamazonka-sagemaker9The configurations and outcomes of a Fail step execution.gamazonka-sagemakerThe Amazon Resource Name (ARN) of the Lambda function that was run by this step execution and a list of output parameters.gamazonka-sagemakerThe Amazon Resource Name (ARN) of the model that was created by this step execution.gamazonka-sagemakerThe Amazon Resource Name (ARN) of the processing job that was run by this step execution.gamazonka-sagemakerThe configurations and outcomes of the check step execution. This includes: The type of the check conducted.The Amazon S3 URIs of baseline constraints and statistics files to be used for the drift check.The Amazon S3 URIs of newly calculated baseline constraints and statistics.&The model package group name provided.The Amazon S3 URI of the violation report if violations detected.The Amazon Resource Name (ARN) of check processing job initiated by the step execution.;The Boolean flags indicating if the drift check is skipped.If step property BaselineUsedForDriftCheck is set the same as CalculatedBaseline.gamazonka-sagemakerThe Amazon Resource Name (ARN) of the model package that the model was registered to by this step execution.gamazonka-sagemakerThe Amazon Resource Name (ARN) of the training job that was run by this step execution.gamazonka-sagemakerThe Amazon Resource Name (ARN) of the transform job that was run by this step execution.gamazonka-sagemakerThe Amazon Resource Name (ARN) of the tuning job that was run by this step execution.gggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggg(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';gamazonka-sagemaker%An execution of a step in a pipeline.See: h smart constructor.gamazonka-sagemakerThe current attempt of the execution step. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/pipelines-retry-policy.html*Retry Policy for SageMaker Pipelines steps.hamazonka-sagemakerIf this pipeline execution step was cached, details on the cache hit.hamazonka-sagemaker)The time that the step stopped executing.hamazonka-sagemakerThe reason why the step failed execution. This is only returned if the step failed its execution.hamazonka-sagemaker"Metadata to run the pipeline step.hamazonka-sagemaker)The time that the step started executing.hamazonka-sagemakerThe description of the step.hamazonka-sagemakerThe display name of the step.hamazonka-sagemaker&The name of the step that is executed.hamazonka-sagemaker!The status of the step execution.hamazonka-sagemakerCreate a value of g" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:g, h - The current attempt of the execution step. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/pipelines-retry-policy.html*Retry Policy for SageMaker Pipelines steps.h, h - If this pipeline execution step was cached, details on the cache hit.h, h, - The time that the step stopped executing.h, h - The reason why the step failed execution. This is only returned if the step failed its execution.h, h% - Metadata to run the pipeline step.h, h, - The time that the step started executing.h, h - The description of the step.h, h - The display name of the step.h, h) - The name of the step that is executed.h, h$ - The status of the step execution.hamazonka-sagemakerThe current attempt of the execution step. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/pipelines-retry-policy.html*Retry Policy for SageMaker Pipelines steps.hamazonka-sagemakerIf this pipeline execution step was cached, details on the cache hit.hamazonka-sagemaker)The time that the step stopped executing.hamazonka-sagemakerThe reason why the step failed execution. This is only returned if the step failed its execution.hamazonka-sagemaker"Metadata to run the pipeline step.hamazonka-sagemaker)The time that the step started executing.hamazonka-sagemakerThe description of the step.hamazonka-sagemakerThe display name of the step.hamazonka-sagemaker&The name of the step that is executed.hamazonka-sagemaker!The status of the step execution.ghhhhhghhhhghhhhhhhhhhhghhhhhghhhhghhhhhhhhhhh(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';+hamazonka-sagemaker7Represents an amount of money in United States dollars.See: h smart constructor.hamazonka-sagemaker0The fractional portion, in cents, of the amount.hamazonka-sagemaker*The whole number of dollars in the amount.hamazonka-sagemakerFractions of a cent, in tenths.hamazonka-sagemakerCreate a value of h" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:h, h3 - The fractional portion, in cents, of the amount.h, h- - The whole number of dollars in the amount.h, h" - Fractions of a cent, in tenths.hamazonka-sagemaker0The fractional portion, in cents, of the amount.hamazonka-sagemaker*The whole number of dollars in the amount.hamazonka-sagemakerFractions of a cent, in tenths. hhhhhhhhh hhhhhhhhh(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';Ρhamazonka-sagemakerDefines the amount of money paid to an Amazon Mechanical Turk worker for each task performed.Use one of the following prices for bounding box tasks. Prices are in US dollars and should be based on the complexity of the task; the longer it takes in your initial testing, the more you should offer.0.0360.0480.0600.0720.1200.2400.3600.4800.6000.7200.8400.9601.0801.200Use one of the following prices for image classification, text classification, and custom tasks. Prices are in US dollars.0.0120.0240.0360.0480.0600.0720.1200.2400.3600.4800.6000.7200.8400.9601.0801.200Use one of the following prices for semantic segmentation tasks. Prices are in US dollars.0.8400.9601.0801.200Use one of the following prices for Textract AnalyzeDocument Important Form Key Amazon Augmented AI review tasks. Prices are in US dollars.2.4002.2802.1602.0401.9201.8001.6801.5601.4401.3201.2001.0800.9600.8400.7200.6000.4800.3600.2400.1200.0720.0600.0480.0360.0240.012Use one of the following prices for Rekognition DetectModerationLabels Amazon Augmented AI review tasks. Prices are in US dollars.1.2001.0800.9600.8400.7200.6000.4800.3600.2400.1200.0720.0600.0480.0360.0240.012Use one of the following prices for Amazon Augmented AI custom human review tasks. Prices are in US dollars.1.2001.0800.9600.8400.7200.6000.4800.3600.2400.1200.0720.0600.0480.0360.0240.012See: h smart constructor.hamazonka-sagemakerDefines the amount of money paid to an Amazon Mechanical Turk worker in United States dollars.hamazonka-sagemakerCreate a value of h" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:h, h - Defines the amount of money paid to an Amazon Mechanical Turk worker in United States dollars.hamazonka-sagemakerDefines the amount of money paid to an Amazon Mechanical Turk worker in United States dollars.hhhhhhhhhh(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';Bhamazonka-sagemaker4Describes the work to be performed by human workers.See: h smart constructor.hamazonka-sagemakerThe length of time that a task remains available for review by human workers.hamazonka-sagemakerKeywords used to describe the task so that workers can discover the task.hamazonka-sagemakerThe amount of time that a worker has to complete a task. The default value is 3,600 seconds (1 hour).hamazonka-sagemakerAmazon Resource Name (ARN) of a team of workers. To learn more about the types of workforces and work teams you can create and use with Amazon A2I, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-workforce-management.htmlCreate and Manage Workforces.hamazonka-sagemakerThe Amazon Resource Name (ARN) of the human task user interface.You can use standard HTML and Crowd HTML Elements to create a custom worker task template. You use this template to create a human task UI.4To learn how to create a custom HTML template, see  https://docs.aws.amazon.com/sagemaker/latest/dg/a2i-custom-templates.html"Create Custom Worker Task Template.To learn how to create a human task UI, which is a worker task template that can be used in a flow definition, see  https://docs.aws.amazon.com/sagemaker/latest/dg/a2i-worker-template-console.html)Create and Delete a Worker Task Templates.hamazonka-sagemaker"A title for the human worker task.hamazonka-sagemaker(A description for the human worker task.hamazonka-sagemakerThe number of distinct workers who will perform the same task on each object. For example, if  TaskCount is set to 3 for an image classification labeling job, three workers will classify each input image. Increasing  TaskCount can improve label accuracy.hamazonka-sagemakerCreate a value of h" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:h, h - Undocumented member.h, h - The length of time that a task remains available for review by human workers.h, h - Keywords used to describe the task so that workers can discover the task.h, h - The amount of time that a worker has to complete a task. The default value is 3,600 seconds (1 hour).h, h - Amazon Resource Name (ARN) of a team of workers. To learn more about the types of workforces and work teams you can create and use with Amazon A2I, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-workforce-management.htmlCreate and Manage Workforces.h, h - The Amazon Resource Name (ARN) of the human task user interface.You can use standard HTML and Crowd HTML Elements to create a custom worker task template. You use this template to create a human task UI.4To learn how to create a custom HTML template, see  https://docs.aws.amazon.com/sagemaker/latest/dg/a2i-custom-templates.html"Create Custom Worker Task Template.To learn how to create a human task UI, which is a worker task template that can be used in a flow definition, see  https://docs.aws.amazon.com/sagemaker/latest/dg/a2i-worker-template-console.html)Create and Delete a Worker Task Templates.h, h% - A title for the human worker task.h, h+ - A description for the human worker task.h, h - The number of distinct workers who will perform the same task on each object. For example, if  TaskCount is set to 3 for an image classification labeling job, three workers will classify each input image. Increasing  TaskCount can improve label accuracy.hamazonka-sagemakerUndocumented member.hamazonka-sagemakerThe length of time that a task remains available for review by human workers.hamazonka-sagemakerKeywords used to describe the task so that workers can discover the task.hamazonka-sagemakerThe amount of time that a worker has to complete a task. The default value is 3,600 seconds (1 hour).hamazonka-sagemakerAmazon Resource Name (ARN) of a team of workers. To learn more about the types of workforces and work teams you can create and use with Amazon A2I, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-workforce-management.htmlCreate and Manage Workforces.hamazonka-sagemakerThe Amazon Resource Name (ARN) of the human task user interface.You can use standard HTML and Crowd HTML Elements to create a custom worker task template. You use this template to create a human task UI.4To learn how to create a custom HTML template, see  https://docs.aws.amazon.com/sagemaker/latest/dg/a2i-custom-templates.html"Create Custom Worker Task Template.To learn how to create a human task UI, which is a worker task template that can be used in a flow definition, see  https://docs.aws.amazon.com/sagemaker/latest/dg/a2i-worker-template-console.html)Create and Delete a Worker Task Templates.hamazonka-sagemaker"A title for the human worker task.hamazonka-sagemaker(A description for the human worker task.hamazonka-sagemakerThe number of distinct workers who will perform the same task on each object. For example, if  TaskCount is set to 3 for an image classification labeling job, three workers will classify each input image. Increasing  TaskCount can improve label accuracy.hamazonka-sagemakerhamazonka-sagemakerhamazonka-sagemakerhamazonka-sagemakerhamazonka-sagemakerhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhh(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';:hamazonka-sagemakerProvided configuration information for the worker UI for a labeling job. Provide either HumanTaskUiArn or UiTemplateS3Uri.For named entity recognition, 3D point cloud and video frame labeling jobs, use HumanTaskUiArn.For all other Ground Truth built-in task types and custom task types, use UiTemplateS3Uri to specify the location of a worker task template in Amazon S3.See: h smart constructor.hamazonka-sagemakerThe ARN of the worker task template used to render the worker UI and tools for labeling job tasks.Use this parameter when you are creating a labeling job for named entity recognition, 3D point cloud and video frame labeling jobs. Use your labeling job task type to select one of the following ARNs and use it with this parameter when you create a labeling job. Replace  aws-region with the Amazon Web Services Region you are creating your labeling job in. For example, replace  aws-region with  us-west-1: if you create a labeling job in US West (N. California).Named Entity RecognitionUse the following HumanTaskUiArn- for named entity recognition labeling jobs: arn:aws:sagemaker:aws-region:394669845002:human-task-ui/NamedEntityRecognition3D Point Cloud HumanTaskUiArns Use this HumanTaskUiArn for 3D point cloud object detection and 3D point cloud object detection adjustment labeling jobs. arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectDetection Use this HumanTaskUiArn for 3D point cloud object tracking and 3D point cloud object tracking adjustment labeling jobs. arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectTracking Use this HumanTaskUiArn for 3D point cloud semantic segmentation and 3D point cloud semantic segmentation adjustment labeling jobs. arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudSemanticSegmentationVideo Frame HumanTaskUiArns Use this HumanTaskUiArn for video frame object detection and video frame object detection adjustment labeling jobs. arn:aws:sagemaker:region:394669845002:human-task-ui/VideoObjectDetection Use this HumanTaskUiArn for video frame object tracking and video frame object tracking adjustment labeling jobs. arn:aws:sagemaker:aws-region:394669845002:human-task-ui/VideoObjectTrackinghamazonka-sagemakerThe Amazon S3 bucket location of the UI template, or worker task template. This is the template used to render the worker UI and tools for labeling job tasks. For more information about the contents of a UI template, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-custom-templates-step2.html+Creating Your Custom Labeling Task Template.hamazonka-sagemakerCreate a value of h" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:h, h - The ARN of the worker task template used to render the worker UI and tools for labeling job tasks.Use this parameter when you are creating a labeling job for named entity recognition, 3D point cloud and video frame labeling jobs. Use your labeling job task type to select one of the following ARNs and use it with this parameter when you create a labeling job. Replace  aws-region with the Amazon Web Services Region you are creating your labeling job in. For example, replace  aws-region with  us-west-1: if you create a labeling job in US West (N. California).Named Entity RecognitionUse the following HumanTaskUiArn- for named entity recognition labeling jobs: arn:aws:sagemaker:aws-region:394669845002:human-task-ui/NamedEntityRecognition3D Point Cloud HumanTaskUiArns Use this HumanTaskUiArn for 3D point cloud object detection and 3D point cloud object detection adjustment labeling jobs. arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectDetection Use this HumanTaskUiArn for 3D point cloud object tracking and 3D point cloud object tracking adjustment labeling jobs. arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectTracking Use this HumanTaskUiArn for 3D point cloud semantic segmentation and 3D point cloud semantic segmentation adjustment labeling jobs. arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudSemanticSegmentationVideo Frame HumanTaskUiArns Use this HumanTaskUiArn for video frame object detection and video frame object detection adjustment labeling jobs. arn:aws:sagemaker:region:394669845002:human-task-ui/VideoObjectDetection Use this HumanTaskUiArn for video frame object tracking and video frame object tracking adjustment labeling jobs. arn:aws:sagemaker:aws-region:394669845002:human-task-ui/VideoObjectTrackingh, h - The Amazon S3 bucket location of the UI template, or worker task template. This is the template used to render the worker UI and tools for labeling job tasks. For more information about the contents of a UI template, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-custom-templates-step2.html+Creating Your Custom Labeling Task Template.hamazonka-sagemakerThe ARN of the worker task template used to render the worker UI and tools for labeling job tasks.Use this parameter when you are creating a labeling job for named entity recognition, 3D point cloud and video frame labeling jobs. Use your labeling job task type to select one of the following ARNs and use it with this parameter when you create a labeling job. Replace  aws-region with the Amazon Web Services Region you are creating your labeling job in. For example, replace  aws-region with  us-west-1: if you create a labeling job in US West (N. California).Named Entity RecognitionUse the following HumanTaskUiArn- for named entity recognition labeling jobs: arn:aws:sagemaker:aws-region:394669845002:human-task-ui/NamedEntityRecognition3D Point Cloud HumanTaskUiArns Use this HumanTaskUiArn for 3D point cloud object detection and 3D point cloud object detection adjustment labeling jobs. arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectDetection Use this HumanTaskUiArn for 3D point cloud object tracking and 3D point cloud object tracking adjustment labeling jobs. arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectTracking Use this HumanTaskUiArn for 3D point cloud semantic segmentation and 3D point cloud semantic segmentation adjustment labeling jobs. arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudSemanticSegmentationVideo Frame HumanTaskUiArns Use this HumanTaskUiArn for video frame object detection and video frame object detection adjustment labeling jobs. arn:aws:sagemaker:region:394669845002:human-task-ui/VideoObjectDetection Use this HumanTaskUiArn for video frame object tracking and video frame object tracking adjustment labeling jobs. arn:aws:sagemaker:aws-region:394669845002:human-task-ui/VideoObjectTrackinghamazonka-sagemakerThe Amazon S3 bucket location of the UI template, or worker task template. This is the template used to render the worker UI and tools for labeling job tasks. For more information about the contents of a UI template, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-custom-templates-step2.html+Creating Your Custom Labeling Task Template.hhhhhhhhhhhhhh(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';hhamazonka-sagemakerInformation required for human workers to complete a labeling task.See: h smart constructor.hamazonka-sagemakerDefines the maximum number of data objects that can be labeled by human workers at the same time. Also referred to as batch size. Each object may have more than one worker at one time. The default value is 1000 objects. To increase the maximum value to 5000 objects, contact Amazon Web Services Support.hamazonka-sagemakerThe price that you pay for each task performed by an Amazon Mechanical Turk worker.hamazonka-sagemakerThe length of time that a task remains available for labeling by human workers. The default and maximum values for this parameter depend on the type of workforce you use.If you choose the Amazon Mechanical Turk workforce, the maximum is 12 hours (43,200 seconds). The default is 6 hours (21,600 seconds).If you choose a private or vendor workforce, the default value is 30 days (2592,000 seconds) for non-AL mode. For most users, the maximum is also 30 days.hamazonka-sagemakerKeywords used to describe the task so that workers on Amazon Mechanical Turk can discover the task.hamazonka-sagemakerThe Amazon Resource Name (ARN) of the work team assigned to complete the tasks.hamazonka-sagemakerInformation about the user interface that workers use to complete the labeling task.hamazonka-sagemakerThe Amazon Resource Name (ARN) of a Lambda function that is run before a data object is sent to a human worker. Use this function to provide input to a custom labeling job.For  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-task-types.htmlbuilt-in task types, use one of the following Amazon SageMaker Ground Truth Lambda function ARNs for PreHumanTaskLambdaArn&. For custom labeling workflows, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-custom-templates-step3.html#sms-custom-templates-step3-prelambdaPre-annotation Lambda. Bounding box - Finds the most similar boxes from different workers based on the Jaccard index of the boxes. >arn:aws:lambda:us-east-1:432418664414:function:PRE-BoundingBox >arn:aws:lambda:us-east-2:266458841044:function:PRE-BoundingBox >arn:aws:lambda:us-west-2:081040173940:function:PRE-BoundingBox arn:aws:lambda:ca-central-1:918755190332:function:PRE-BoundingBox >arn:aws:lambda:eu-west-1:568282634449:function:PRE-BoundingBox >arn:aws:lambda:eu-west-2:487402164563:function:PRE-BoundingBox arn:aws:lambda:eu-central-1:203001061592:function:PRE-BoundingBox arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-BoundingBox arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-BoundingBox ?arn:aws:lambda:ap-south-1:565803892007:function:PRE-BoundingBox arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-BoundingBox arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-BoundingBoxImage classification - Uses a variant of the Expectation Maximization approach to estimate the true class of an image based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClass arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClass arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClass arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClass arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClass arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClass arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClass arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClass arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClass arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClass arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClass arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClass Multi-label image classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of an image based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClassMultiLabel arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClassMultiLabel arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClassMultiLabel arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClassMultiLabel arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClassMultiLabel arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClassMultiLabel arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClassMultiLabel arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClassMultiLabel arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClassMultiLabel arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClassMultiLabel arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClassMultiLabel arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClassMultiLabelSemantic segmentation - Treats each pixel in an image as a multi-class classification and treats pixel annotations from workers as "votes" for the correct label. arn:aws:lambda:us-east-1:432418664414:function:PRE-SemanticSegmentation arn:aws:lambda:us-east-2:266458841044:function:PRE-SemanticSegmentation arn:aws:lambda:us-west-2:081040173940:function:PRE-SemanticSegmentation arn:aws:lambda:ca-central-1:918755190332:function:PRE-SemanticSegmentation arn:aws:lambda:eu-west-1:568282634449:function:PRE-SemanticSegmentation arn:aws:lambda:eu-west-2:487402164563:function:PRE-SemanticSegmentation arn:aws:lambda:eu-central-1:203001061592:function:PRE-SemanticSegmentation arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-SemanticSegmentation arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-SemanticSegmentation arn:aws:lambda:ap-south-1:565803892007:function:PRE-SemanticSegmentation arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-SemanticSegmentation arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-SemanticSegmentationText classification - Uses a variant of the Expectation Maximization approach to estimate the true class of text based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClass arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClass arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClass arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClass arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClass arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClass arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClass arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClass arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClass arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClass arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClass arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClassMulti-label text classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of text based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClassMultiLabel arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClassMultiLabel arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClassMultiLabel arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClassMultiLabel arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClassMultiLabel arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClassMultiLabel arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClassMultiLabel arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClassMultiLabel arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClassMultiLabel arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClassMultiLabel arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClassMultiLabel arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClassMultiLabelNamed entity recognition - Groups similar selections and calculates aggregate boundaries, resolving to most-assigned label. arn:aws:lambda:us-east-1:432418664414:function:PRE-NamedEntityRecognition arn:aws:lambda:us-east-2:266458841044:function:PRE-NamedEntityRecognition arn:aws:lambda:us-west-2:081040173940:function:PRE-NamedEntityRecognition arn:aws:lambda:ca-central-1:918755190332:function:PRE-NamedEntityRecognition arn:aws:lambda:eu-west-1:568282634449:function:PRE-NamedEntityRecognition arn:aws:lambda:eu-west-2:487402164563:function:PRE-NamedEntityRecognition arn:aws:lambda:eu-central-1:203001061592:function:PRE-NamedEntityRecognition arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-NamedEntityRecognition arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-NamedEntityRecognition arn:aws:lambda:ap-south-1:565803892007:function:PRE-NamedEntityRecognition arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-NamedEntityRecognition arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-NamedEntityRecognitionVideo Classification - Use this task type when you need workers to classify videos using predefined labels that you specify. Workers are shown videos and are asked to choose one label for each video. arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoMultiClass arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoMultiClass arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoMultiClass arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoMultiClass arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoMultiClass arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoMultiClass arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoMultiClass arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoMultiClass arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoMultiClass arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoMultiClass arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoMultiClass arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoMultiClassVideo Frame Object Detection - Use this task type to have workers identify and locate objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to identify and localize various objects in a series of video frames, such as cars, bikes, and pedestrians. arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoObjectDetection arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoObjectDetection arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoObjectDetection arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoObjectDetection arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoObjectDetection arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoObjectDetection arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoObjectDetection arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoObjectDetection arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoObjectDetection arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoObjectDetection arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoObjectDetection arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoObjectDetectionVideo Frame Object Tracking - Use this task type to have workers track the movement of objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to track the movement of objects, such as cars, bikes, and pedestrians. arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoObjectTracking arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoObjectTracking arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoObjectTracking arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoObjectTracking arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoObjectTracking arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoObjectTracking arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoObjectTracking arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoObjectTracking arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoObjectTracking arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoObjectTracking arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoObjectTracking arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoObjectTracking3D Point Cloud ModalitiesUse the following pre-annotation lambdas for 3D point cloud labeling modality tasks. See  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-point-cloud-task-types.html3D Point Cloud Task types to learn more.3D Point Cloud Object Detection - Use this task type when you want workers to classify objects in a 3D point cloud by drawing 3D cuboids around objects. For example, you can use this task type to ask workers to identify different types of objects in a point cloud, such as cars, bikes, and pedestrians. arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectDetection arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectDetection arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectDetection arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectDetection arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectDetection arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectDetection arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectDetection arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectDetection arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectDetection arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectDetection arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectDetection arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectDetection3D Point Cloud Object Tracking - Use this task type when you want workers to draw 3D cuboids around objects that appear in a sequence of 3D point cloud frames. For example, you can use this task type to ask workers to track the movement of vehicles across multiple point cloud frames. arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectTracking arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectTracking arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectTracking arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectTracking arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectTracking arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectTracking arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectTracking arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectTracking arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectTracking arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectTracking arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectTracking arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectTracking$3D Point Cloud Semantic Segmentation - Use this task type when you want workers to create a point-level semantic segmentation masks by painting objects in a 3D point cloud using different colors where each color is assigned to one of the classes you specify. arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudSemanticSegmentation arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudSemanticSegmentation arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudSemanticSegmentation arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudSemanticSegmentation arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudSemanticSegmentation arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudSemanticSegmentation arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudSemanticSegmentation arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudSemanticSegmentation arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudSemanticSegmentation arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudSemanticSegmentation arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudSemanticSegmentation arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudSemanticSegmentationUse the following ARNs for Label Verification and Adjustment JobsUse label verification and adjustment jobs to review and adjust labels. To learn more, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-verification-data.htmlVerify and Adjust Labels .Bounding box verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgement for bounding box labels based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:PRE-VerificationBoundingBox arn:aws:lambda:us-east-2:266458841044:function:PRE-VerificationBoundingBox arn:aws:lambda:us-west-2:081040173940:function:PRE-VerificationBoundingBox arn:aws:lambda:eu-west-1:568282634449:function:PRE-VerificationBoundingBox arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VerificationBoundingBox arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VerificationBoundingBox arn:aws:lambda:ap-south-1:565803892007:function:PRE-VerificationBoundingBox arn:aws:lambda:eu-central-1:203001061592:function:PRE-VerificationBoundingBox arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VerificationBoundingBox arn:aws:lambda:eu-west-2:487402164563:function:PRE-VerificationBoundingBox arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VerificationBoundingBox arn:aws:lambda:ca-central-1:918755190332:function:PRE-VerificationBoundingBoxBounding box adjustment - Finds the most similar boxes from different workers based on the Jaccard index of the adjusted annotations. arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentBoundingBox arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentBoundingBox arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentBoundingBox arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentBoundingBox arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentBoundingBox arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentBoundingBox arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentBoundingBox arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentBoundingBox arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentBoundingBox arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentBoundingBox arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentBoundingBox arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentBoundingBox"Semantic segmentation verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgment for semantic segmentation labels based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:PRE-VerificationSemanticSegmentation arn:aws:lambda:us-east-2:266458841044:function:PRE-VerificationSemanticSegmentation arn:aws:lambda:us-west-2:081040173940:function:PRE-VerificationSemanticSegmentation arn:aws:lambda:ca-central-1:918755190332:function:PRE-VerificationSemanticSegmentation arn:aws:lambda:eu-west-1:568282634449:function:PRE-VerificationSemanticSegmentation arn:aws:lambda:eu-west-2:487402164563:function:PRE-VerificationSemanticSegmentation arn:aws:lambda:eu-central-1:203001061592:function:PRE-VerificationSemanticSegmentation arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VerificationSemanticSegmentation arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VerificationSemanticSegmentation arn:aws:lambda:ap-south-1:565803892007:function:PRE-VerificationSemanticSegmentation arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VerificationSemanticSegmentation arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VerificationSemanticSegmentation Semantic segmentation adjustment - Treats each pixel in an image as a multi-class classification and treats pixel adjusted annotations from workers as "votes" for the correct label. arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentSemanticSegmentation arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentSemanticSegmentation arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentSemanticSegmentation arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentSemanticSegmentation arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentSemanticSegmentation arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentSemanticSegmentation arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentSemanticSegmentation arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentSemanticSegmentation arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentSemanticSegmentation arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentSemanticSegmentation arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentSemanticSegmentation arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentSemanticSegmentation'Video Frame Object Detection Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to classify and localize objects in a sequence of video frames. arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentVideoObjectDetection arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentVideoObjectDetection arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentVideoObjectDetection arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentVideoObjectDetection arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentVideoObjectDetection arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentVideoObjectDetection arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentVideoObjectDetection arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentVideoObjectDetection arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentVideoObjectDetection arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentVideoObjectDetection arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentVideoObjectDetection arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentVideoObjectDetection&Video Frame Object Tracking Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to track object movement across a sequence of video frames. arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentVideoObjectTracking arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentVideoObjectTracking arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentVideoObjectTracking arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentVideoObjectTracking arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentVideoObjectTracking arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentVideoObjectTracking arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentVideoObjectTracking arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentVideoObjectTracking arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentVideoObjectTracking arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentVideoObjectTracking arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentVideoObjectTracking arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentVideoObjectTracking*3D point cloud object detection adjustment- - Adjust 3D cuboids in a point cloud frame. arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectDetection arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectDetection arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectDetection arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectDetection arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectDetection arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectDetection)3D point cloud object tracking adjustment> - Adjust 3D cuboids across a sequence of point cloud frames. arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectTracking arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectTracking arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectTracking arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectTracking arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectTracking arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectTracking/3D point cloud semantic segmentation adjustment; - Adjust semantic segmentation masks in a 3D point cloud. arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudSemanticSegmentationhamazonka-sagemaker,A title for the task for your human workers.hamazonka-sagemaker1A description of the task for your human workers.hamazonka-sagemaker6The number of human workers that will label an object.hamazonka-sagemaker8The amount of time that a worker has to complete a task.If you create a custom labeling job, the maximum value for this parameter is 8 hours (28,800 seconds).&If you create a labeling job using a  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-task-types.htmlbuilt-in task type the maximum for this parameter depends on the task type you use: For  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-label-images.htmlimage and  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-label-text.htmltext= labeling jobs, the maximum is 8 hours (28,800 seconds). For  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-point-cloud.html3D point cloud and  >https://docs.aws.amazon.com/sagemaker/latest/dg/sms-video.html video frame labeling jobs, the maximum is 30 days (2952,000 seconds) for non-AL mode. For most users, the maximum is also 30 days.hamazonka-sagemakerarn:aws:lambda:us-east-1:432418664414:function:PRE-BoundingBox >arn:aws:lambda:us-east-2:266458841044:function:PRE-BoundingBox >arn:aws:lambda:us-west-2:081040173940:function:PRE-BoundingBox arn:aws:lambda:ca-central-1:918755190332:function:PRE-BoundingBox >arn:aws:lambda:eu-west-1:568282634449:function:PRE-BoundingBox >arn:aws:lambda:eu-west-2:487402164563:function:PRE-BoundingBox arn:aws:lambda:eu-central-1:203001061592:function:PRE-BoundingBox arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-BoundingBox arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-BoundingBox ?arn:aws:lambda:ap-south-1:565803892007:function:PRE-BoundingBox arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-BoundingBox arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-BoundingBoxImage classification - Uses a variant of the Expectation Maximization approach to estimate the true class of an image based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClass arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClass arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClass arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClass arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClass arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClass arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClass arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClass arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClass arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClass arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClass arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClass Multi-label image classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of an image based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClassMultiLabel arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClassMultiLabel arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClassMultiLabel arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClassMultiLabel arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClassMultiLabel arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClassMultiLabel arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClassMultiLabel arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClassMultiLabel arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClassMultiLabel arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClassMultiLabel arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClassMultiLabel arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClassMultiLabelSemantic segmentation - Treats each pixel in an image as a multi-class classification and treats pixel annotations from workers as "votes" for the correct label. arn:aws:lambda:us-east-1:432418664414:function:PRE-SemanticSegmentation arn:aws:lambda:us-east-2:266458841044:function:PRE-SemanticSegmentation arn:aws:lambda:us-west-2:081040173940:function:PRE-SemanticSegmentation arn:aws:lambda:ca-central-1:918755190332:function:PRE-SemanticSegmentation arn:aws:lambda:eu-west-1:568282634449:function:PRE-SemanticSegmentation arn:aws:lambda:eu-west-2:487402164563:function:PRE-SemanticSegmentation arn:aws:lambda:eu-central-1:203001061592:function:PRE-SemanticSegmentation arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-SemanticSegmentation arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-SemanticSegmentation arn:aws:lambda:ap-south-1:565803892007:function:PRE-SemanticSegmentation arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-SemanticSegmentation arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-SemanticSegmentationText classification - Uses a variant of the Expectation Maximization approach to estimate the true class of text based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClass arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClass arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClass arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClass arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClass arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClass arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClass arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClass arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClass arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClass arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClass arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClassMulti-label text classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of text based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClassMultiLabel arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClassMultiLabel arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClassMultiLabel arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClassMultiLabel arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClassMultiLabel arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClassMultiLabel arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClassMultiLabel arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClassMultiLabel arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClassMultiLabel arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClassMultiLabel arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClassMultiLabel arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClassMultiLabelNamed entity recognition - Groups similar selections and calculates aggregate boundaries, resolving to most-assigned label. arn:aws:lambda:us-east-1:432418664414:function:PRE-NamedEntityRecognition arn:aws:lambda:us-east-2:266458841044:function:PRE-NamedEntityRecognition arn:aws:lambda:us-west-2:081040173940:function:PRE-NamedEntityRecognition arn:aws:lambda:ca-central-1:918755190332:function:PRE-NamedEntityRecognition arn:aws:lambda:eu-west-1:568282634449:function:PRE-NamedEntityRecognition arn:aws:lambda:eu-west-2:487402164563:function:PRE-NamedEntityRecognition arn:aws:lambda:eu-central-1:203001061592:function:PRE-NamedEntityRecognition arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-NamedEntityRecognition arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-NamedEntityRecognition arn:aws:lambda:ap-south-1:565803892007:function:PRE-NamedEntityRecognition arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-NamedEntityRecognition arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-NamedEntityRecognitionVideo Classification - Use this task type when you need workers to classify videos using predefined labels that you specify. Workers are shown videos and are asked to choose one label for each video. arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoMultiClass arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoMultiClass arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoMultiClass arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoMultiClass arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoMultiClass arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoMultiClass arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoMultiClass arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoMultiClass arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoMultiClass arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoMultiClass arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoMultiClass arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoMultiClassVideo Frame Object Detection - Use this task type to have workers identify and locate objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to identify and localize various objects in a series of video frames, such as cars, bikes, and pedestrians. arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoObjectDetection arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoObjectDetection arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoObjectDetection arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoObjectDetection arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoObjectDetection arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoObjectDetection arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoObjectDetection arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoObjectDetection arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoObjectDetection arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoObjectDetection arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoObjectDetection arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoObjectDetectionVideo Frame Object Tracking - Use this task type to have workers track the movement of objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to track the movement of objects, such as cars, bikes, and pedestrians. arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoObjectTracking arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoObjectTracking arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoObjectTracking arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoObjectTracking arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoObjectTracking arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoObjectTracking arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoObjectTracking arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoObjectTracking arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoObjectTracking arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoObjectTracking arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoObjectTracking arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoObjectTracking3D Point Cloud ModalitiesUse the following pre-annotation lambdas for 3D point cloud labeling modality tasks. See  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-point-cloud-task-types.html3D Point Cloud Task types to learn more.3D Point Cloud Object Detection - Use this task type when you want workers to classify objects in a 3D point cloud by drawing 3D cuboids around objects. For example, you can use this task type to ask workers to identify different types of objects in a point cloud, such as cars, bikes, and pedestrians. arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectDetection arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectDetection arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectDetection arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectDetection arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectDetection arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectDetection arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectDetection arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectDetection arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectDetection arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectDetection arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectDetection arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectDetection3D Point Cloud Object Tracking - Use this task type when you want workers to draw 3D cuboids around objects that appear in a sequence of 3D point cloud frames. For example, you can use this task type to ask workers to track the movement of vehicles across multiple point cloud frames. arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectTracking arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectTracking arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectTracking arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectTracking arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectTracking arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectTracking arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectTracking arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectTracking arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectTracking arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectTracking arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectTracking arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectTracking$3D Point Cloud Semantic Segmentation - Use this task type when you want workers to create a point-level semantic segmentation masks by painting objects in a 3D point cloud using different colors where each color is assigned to one of the classes you specify. arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudSemanticSegmentation arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudSemanticSegmentation arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudSemanticSegmentation arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudSemanticSegmentation arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudSemanticSegmentation arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudSemanticSegmentation arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudSemanticSegmentation arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudSemanticSegmentation arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudSemanticSegmentation arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudSemanticSegmentation arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudSemanticSegmentation arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudSemanticSegmentationUse the following ARNs for Label Verification and Adjustment JobsUse label verification and adjustment jobs to review and adjust labels. To learn more, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-verification-data.htmlVerify and Adjust Labels .Bounding box verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgement for bounding box labels based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:PRE-VerificationBoundingBox arn:aws:lambda:us-east-2:266458841044:function:PRE-VerificationBoundingBox arn:aws:lambda:us-west-2:081040173940:function:PRE-VerificationBoundingBox arn:aws:lambda:eu-west-1:568282634449:function:PRE-VerificationBoundingBox arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VerificationBoundingBox arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VerificationBoundingBox arn:aws:lambda:ap-south-1:565803892007:function:PRE-VerificationBoundingBox arn:aws:lambda:eu-central-1:203001061592:function:PRE-VerificationBoundingBox arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VerificationBoundingBox arn:aws:lambda:eu-west-2:487402164563:function:PRE-VerificationBoundingBox arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VerificationBoundingBox arn:aws:lambda:ca-central-1:918755190332:function:PRE-VerificationBoundingBoxBounding box adjustment - Finds the most similar boxes from different workers based on the Jaccard index of the adjusted annotations. arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentBoundingBox arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentBoundingBox arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentBoundingBox arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentBoundingBox arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentBoundingBox arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentBoundingBox arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentBoundingBox arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentBoundingBox arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentBoundingBox arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentBoundingBox arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentBoundingBox arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentBoundingBox"Semantic segmentation verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgment for semantic segmentation labels based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:PRE-VerificationSemanticSegmentation arn:aws:lambda:us-east-2:266458841044:function:PRE-VerificationSemanticSegmentation arn:aws:lambda:us-west-2:081040173940:function:PRE-VerificationSemanticSegmentation arn:aws:lambda:ca-central-1:918755190332:function:PRE-VerificationSemanticSegmentation arn:aws:lambda:eu-west-1:568282634449:function:PRE-VerificationSemanticSegmentation arn:aws:lambda:eu-west-2:487402164563:function:PRE-VerificationSemanticSegmentation arn:aws:lambda:eu-central-1:203001061592:function:PRE-VerificationSemanticSegmentation arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VerificationSemanticSegmentation arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VerificationSemanticSegmentation arn:aws:lambda:ap-south-1:565803892007:function:PRE-VerificationSemanticSegmentation arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VerificationSemanticSegmentation arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VerificationSemanticSegmentation Semantic segmentation adjustment - Treats each pixel in an image as a multi-class classification and treats pixel adjusted annotations from workers as "votes" for the correct label. arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentSemanticSegmentation arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentSemanticSegmentation arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentSemanticSegmentation arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentSemanticSegmentation arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentSemanticSegmentation arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentSemanticSegmentation arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentSemanticSegmentation arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentSemanticSegmentation arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentSemanticSegmentation arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentSemanticSegmentation arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentSemanticSegmentation arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentSemanticSegmentation'Video Frame Object Detection Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to classify and localize objects in a sequence of video frames. arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentVideoObjectDetection arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentVideoObjectDetection arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentVideoObjectDetection arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentVideoObjectDetection arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentVideoObjectDetection arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentVideoObjectDetection arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentVideoObjectDetection arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentVideoObjectDetection arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentVideoObjectDetection arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentVideoObjectDetection arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentVideoObjectDetection arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentVideoObjectDetection&Video Frame Object Tracking Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to track object movement across a sequence of video frames. arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentVideoObjectTracking arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentVideoObjectTracking arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentVideoObjectTracking arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentVideoObjectTracking arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentVideoObjectTracking arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentVideoObjectTracking arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentVideoObjectTracking arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentVideoObjectTracking arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentVideoObjectTracking arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentVideoObjectTracking arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentVideoObjectTracking arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentVideoObjectTracking*3D point cloud object detection adjustment- - Adjust 3D cuboids in a point cloud frame. arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectDetection arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectDetection arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectDetection arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectDetection arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectDetection arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectDetection)3D point cloud object tracking adjustment> - Adjust 3D cuboids across a sequence of point cloud frames. arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectTracking arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectTracking arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectTracking arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectTracking arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectTracking arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectTracking/3D point cloud semantic segmentation adjustment; - Adjust semantic segmentation masks in a 3D point cloud. arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudSemanticSegmentationh, h/ - A title for the task for your human workers.h, h4 - A description of the task for your human workers.h, h9 - The number of human workers that will label an object.h, h; - The amount of time that a worker has to complete a task.If you create a custom labeling job, the maximum value for this parameter is 8 hours (28,800 seconds).&If you create a labeling job using a  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-task-types.htmlbuilt-in task type the maximum for this parameter depends on the task type you use: For  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-label-images.htmlimage and  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-label-text.htmltext= labeling jobs, the maximum is 8 hours (28,800 seconds). For  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-point-cloud.html3D point cloud and  >https://docs.aws.amazon.com/sagemaker/latest/dg/sms-video.html video frame labeling jobs, the maximum is 30 days (2952,000 seconds) for non-AL mode. For most users, the maximum is also 30 days.h, h? - Configures how labels are consolidated across human workers.hamazonka-sagemakerDefines the maximum number of data objects that can be labeled by human workers at the same time. Also referred to as batch size. Each object may have more than one worker at one time. The default value is 1000 objects. To increase the maximum value to 5000 objects, contact Amazon Web Services Support.hamazonka-sagemakerThe price that you pay for each task performed by an Amazon Mechanical Turk worker.hamazonka-sagemakerThe length of time that a task remains available for labeling by human workers. The default and maximum values for this parameter depend on the type of workforce you use.If you choose the Amazon Mechanical Turk workforce, the maximum is 12 hours (43,200 seconds). The default is 6 hours (21,600 seconds).If you choose a private or vendor workforce, the default value is 30 days (2592,000 seconds) for non-AL mode. For most users, the maximum is also 30 days.hamazonka-sagemakerKeywords used to describe the task so that workers on Amazon Mechanical Turk can discover the task.hamazonka-sagemakerThe Amazon Resource Name (ARN) of the work team assigned to complete the tasks.hamazonka-sagemakerInformation about the user interface that workers use to complete the labeling task.hamazonka-sagemakerThe Amazon Resource Name (ARN) of a Lambda function that is run before a data object is sent to a human worker. Use this function to provide input to a custom labeling job.For  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-task-types.htmlbuilt-in task types, use one of the following Amazon SageMaker Ground Truth Lambda function ARNs for PreHumanTaskLambdaArn&. For custom labeling workflows, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-custom-templates-step3.html#sms-custom-templates-step3-prelambdaPre-annotation Lambda. Bounding box - Finds the most similar boxes from different workers based on the Jaccard index of the boxes. >arn:aws:lambda:us-east-1:432418664414:function:PRE-BoundingBox >arn:aws:lambda:us-east-2:266458841044:function:PRE-BoundingBox >arn:aws:lambda:us-west-2:081040173940:function:PRE-BoundingBox arn:aws:lambda:ca-central-1:918755190332:function:PRE-BoundingBox >arn:aws:lambda:eu-west-1:568282634449:function:PRE-BoundingBox >arn:aws:lambda:eu-west-2:487402164563:function:PRE-BoundingBox arn:aws:lambda:eu-central-1:203001061592:function:PRE-BoundingBox arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-BoundingBox arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-BoundingBox ?arn:aws:lambda:ap-south-1:565803892007:function:PRE-BoundingBox arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-BoundingBox arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-BoundingBoxImage classification - Uses a variant of the Expectation Maximization approach to estimate the true class of an image based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClass arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClass arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClass arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClass arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClass arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClass arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClass arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClass arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClass arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClass arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClass arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClass Multi-label image classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of an image based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClassMultiLabel arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClassMultiLabel arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClassMultiLabel arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClassMultiLabel arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClassMultiLabel arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClassMultiLabel arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClassMultiLabel arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClassMultiLabel arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClassMultiLabel arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClassMultiLabel arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClassMultiLabel arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClassMultiLabelSemantic segmentation - Treats each pixel in an image as a multi-class classification and treats pixel annotations from workers as "votes" for the correct label. arn:aws:lambda:us-east-1:432418664414:function:PRE-SemanticSegmentation arn:aws:lambda:us-east-2:266458841044:function:PRE-SemanticSegmentation arn:aws:lambda:us-west-2:081040173940:function:PRE-SemanticSegmentation arn:aws:lambda:ca-central-1:918755190332:function:PRE-SemanticSegmentation arn:aws:lambda:eu-west-1:568282634449:function:PRE-SemanticSegmentation arn:aws:lambda:eu-west-2:487402164563:function:PRE-SemanticSegmentation arn:aws:lambda:eu-central-1:203001061592:function:PRE-SemanticSegmentation arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-SemanticSegmentation arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-SemanticSegmentation arn:aws:lambda:ap-south-1:565803892007:function:PRE-SemanticSegmentation arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-SemanticSegmentation arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-SemanticSegmentationText classification - Uses a variant of the Expectation Maximization approach to estimate the true class of text based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClass arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClass arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClass arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClass arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClass arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClass arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClass arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClass arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClass arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClass arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClass arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClassMulti-label text classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of text based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClassMultiLabel arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClassMultiLabel arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClassMultiLabel arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClassMultiLabel arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClassMultiLabel arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClassMultiLabel arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClassMultiLabel arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClassMultiLabel arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClassMultiLabel arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClassMultiLabel arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClassMultiLabel arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClassMultiLabelNamed entity recognition - Groups similar selections and calculates aggregate boundaries, resolving to most-assigned label. arn:aws:lambda:us-east-1:432418664414:function:PRE-NamedEntityRecognition arn:aws:lambda:us-east-2:266458841044:function:PRE-NamedEntityRecognition arn:aws:lambda:us-west-2:081040173940:function:PRE-NamedEntityRecognition arn:aws:lambda:ca-central-1:918755190332:function:PRE-NamedEntityRecognition arn:aws:lambda:eu-west-1:568282634449:function:PRE-NamedEntityRecognition arn:aws:lambda:eu-west-2:487402164563:function:PRE-NamedEntityRecognition arn:aws:lambda:eu-central-1:203001061592:function:PRE-NamedEntityRecognition arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-NamedEntityRecognition arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-NamedEntityRecognition arn:aws:lambda:ap-south-1:565803892007:function:PRE-NamedEntityRecognition arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-NamedEntityRecognition arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-NamedEntityRecognitionVideo Classification - Use this task type when you need workers to classify videos using predefined labels that you specify. Workers are shown videos and are asked to choose one label for each video. arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoMultiClass arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoMultiClass arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoMultiClass arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoMultiClass arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoMultiClass arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoMultiClass arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoMultiClass arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoMultiClass arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoMultiClass arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoMultiClass arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoMultiClass arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoMultiClassVideo Frame Object Detection - Use this task type to have workers identify and locate objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to identify and localize various objects in a series of video frames, such as cars, bikes, and pedestrians. arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoObjectDetection arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoObjectDetection arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoObjectDetection arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoObjectDetection arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoObjectDetection arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoObjectDetection arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoObjectDetection arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoObjectDetection arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoObjectDetection arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoObjectDetection arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoObjectDetection arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoObjectDetectionVideo Frame Object Tracking - Use this task type to have workers track the movement of objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to track the movement of objects, such as cars, bikes, and pedestrians. arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoObjectTracking arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoObjectTracking arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoObjectTracking arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoObjectTracking arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoObjectTracking arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoObjectTracking arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoObjectTracking arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoObjectTracking arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoObjectTracking arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoObjectTracking arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoObjectTracking arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoObjectTracking3D Point Cloud ModalitiesUse the following pre-annotation lambdas for 3D point cloud labeling modality tasks. See  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-point-cloud-task-types.html3D Point Cloud Task types to learn more.3D Point Cloud Object Detection - Use this task type when you want workers to classify objects in a 3D point cloud by drawing 3D cuboids around objects. For example, you can use this task type to ask workers to identify different types of objects in a point cloud, such as cars, bikes, and pedestrians. arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectDetection arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectDetection arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectDetection arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectDetection arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectDetection arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectDetection arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectDetection arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectDetection arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectDetection arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectDetection arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectDetection arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectDetection3D Point Cloud Object Tracking - Use this task type when you want workers to draw 3D cuboids around objects that appear in a sequence of 3D point cloud frames. For example, you can use this task type to ask workers to track the movement of vehicles across multiple point cloud frames. arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectTracking arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectTracking arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectTracking arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectTracking arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectTracking arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectTracking arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectTracking arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectTracking arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectTracking arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectTracking arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectTracking arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectTracking$3D Point Cloud Semantic Segmentation - Use this task type when you want workers to create a point-level semantic segmentation masks by painting objects in a 3D point cloud using different colors where each color is assigned to one of the classes you specify. arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudSemanticSegmentation arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudSemanticSegmentation arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudSemanticSegmentation arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudSemanticSegmentation arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudSemanticSegmentation arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudSemanticSegmentation arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudSemanticSegmentation arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudSemanticSegmentation arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudSemanticSegmentation arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudSemanticSegmentation arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudSemanticSegmentation arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudSemanticSegmentationUse the following ARNs for Label Verification and Adjustment JobsUse label verification and adjustment jobs to review and adjust labels. To learn more, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-verification-data.htmlVerify and Adjust Labels .Bounding box verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgement for bounding box labels based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:PRE-VerificationBoundingBox arn:aws:lambda:us-east-2:266458841044:function:PRE-VerificationBoundingBox arn:aws:lambda:us-west-2:081040173940:function:PRE-VerificationBoundingBox arn:aws:lambda:eu-west-1:568282634449:function:PRE-VerificationBoundingBox arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VerificationBoundingBox arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VerificationBoundingBox arn:aws:lambda:ap-south-1:565803892007:function:PRE-VerificationBoundingBox arn:aws:lambda:eu-central-1:203001061592:function:PRE-VerificationBoundingBox arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VerificationBoundingBox arn:aws:lambda:eu-west-2:487402164563:function:PRE-VerificationBoundingBox arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VerificationBoundingBox arn:aws:lambda:ca-central-1:918755190332:function:PRE-VerificationBoundingBoxBounding box adjustment - Finds the most similar boxes from different workers based on the Jaccard index of the adjusted annotations. arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentBoundingBox arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentBoundingBox arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentBoundingBox arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentBoundingBox arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentBoundingBox arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentBoundingBox arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentBoundingBox arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentBoundingBox arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentBoundingBox arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentBoundingBox arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentBoundingBox arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentBoundingBox"Semantic segmentation verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgment for semantic segmentation labels based on annotations from individual workers. arn:aws:lambda:us-east-1:432418664414:function:PRE-VerificationSemanticSegmentation arn:aws:lambda:us-east-2:266458841044:function:PRE-VerificationSemanticSegmentation arn:aws:lambda:us-west-2:081040173940:function:PRE-VerificationSemanticSegmentation arn:aws:lambda:ca-central-1:918755190332:function:PRE-VerificationSemanticSegmentation arn:aws:lambda:eu-west-1:568282634449:function:PRE-VerificationSemanticSegmentation arn:aws:lambda:eu-west-2:487402164563:function:PRE-VerificationSemanticSegmentation arn:aws:lambda:eu-central-1:203001061592:function:PRE-VerificationSemanticSegmentation arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VerificationSemanticSegmentation arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VerificationSemanticSegmentation arn:aws:lambda:ap-south-1:565803892007:function:PRE-VerificationSemanticSegmentation arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VerificationSemanticSegmentation arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VerificationSemanticSegmentation Semantic segmentation adjustment - Treats each pixel in an image as a multi-class classification and treats pixel adjusted annotations from workers as "votes" for the correct label. arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentSemanticSegmentation arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentSemanticSegmentation arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentSemanticSegmentation arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentSemanticSegmentation arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentSemanticSegmentation arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentSemanticSegmentation arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentSemanticSegmentation arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentSemanticSegmentation arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentSemanticSegmentation arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentSemanticSegmentation arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentSemanticSegmentation arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentSemanticSegmentation'Video Frame Object Detection Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to classify and localize objects in a sequence of video frames. arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentVideoObjectDetection arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentVideoObjectDetection arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentVideoObjectDetection arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentVideoObjectDetection arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentVideoObjectDetection arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentVideoObjectDetection arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentVideoObjectDetection arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentVideoObjectDetection arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentVideoObjectDetection arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentVideoObjectDetection arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentVideoObjectDetection arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentVideoObjectDetection&Video Frame Object Tracking Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to track object movement across a sequence of video frames. arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentVideoObjectTracking arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentVideoObjectTracking arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentVideoObjectTracking arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentVideoObjectTracking arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentVideoObjectTracking arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentVideoObjectTracking arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentVideoObjectTracking arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentVideoObjectTracking arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentVideoObjectTracking arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentVideoObjectTracking arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentVideoObjectTracking arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentVideoObjectTracking*3D point cloud object detection adjustment- - Adjust 3D cuboids in a point cloud frame. arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectDetection arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectDetection arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectDetection arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectDetection arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectDetection arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectDetection)3D point cloud object tracking adjustment> - Adjust 3D cuboids across a sequence of point cloud frames. arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectTracking arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectTracking arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectTracking arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectTracking arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectTracking arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectTracking/3D point cloud semantic segmentation adjustment; - Adjust semantic segmentation masks in a 3D point cloud. arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudSemanticSegmentationhamazonka-sagemaker,A title for the task for your human workers.hamazonka-sagemaker1A description of the task for your human workers.hamazonka-sagemaker6The number of human workers that will label an object.hamazonka-sagemaker8The amount of time that a worker has to complete a task.If you create a custom labeling job, the maximum value for this parameter is 8 hours (28,800 seconds).&If you create a labeling job using a  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-task-types.htmlbuilt-in task type the maximum for this parameter depends on the task type you use: For  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-label-images.htmlimage and  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-label-text.htmltext= labeling jobs, the maximum is 8 hours (28,800 seconds). For  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-point-cloud.html3D point cloud and  >https://docs.aws.amazon.com/sagemaker/latest/dg/sms-video.html video frame labeling jobs, the maximum is 30 days (2952,000 seconds) for non-AL mode. For most users, the maximum is also 30 days.hamazonka-sagemakerhttps://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.jamazonka-sagemakerCreate a value of j" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:j, j - Who created the project.j, j7 - A timestamp specifying when the project was created.j, j - Undocumented member.j, j - A timestamp container for when the project was last modified.j, j1 - The Amazon Resource Name (ARN) of the project.j, j" - The description of the project.j, j - The ID of the project.j, j - The name of the project.j, j - The status of the project.j, j - Undocumented member.j, j - Undocumented member.j, j - An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.jamazonka-sagemakerWho created the project.jamazonka-sagemaker4A timestamp specifying when the project was created.jamazonka-sagemakerUndocumented member.jamazonka-sagemaker=A timestamp container for when the project was last modified.jamazonka-sagemaker.The Amazon Resource Name (ARN) of the project.jamazonka-sagemakerThe description of the project.jamazonka-sagemakerThe ID of the project.jamazonka-sagemakerThe name of the project.jamazonka-sagemakerThe status of the project.jamazonka-sagemakerUndocumented member.jamazonka-sagemakerUndocumented member.jamazonka-sagemakerAn array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.jjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjj(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';jamazonka-sagemakerAn execution of a pipeline.See: j smart constructor.jamazonka-sagemaker,The creation time of the pipeline execution.jamazonka-sagemaker2If the execution failed, a message describing why.jamazonka-sagemaker7The time that the pipeline execution was last modified.jamazonka-sagemakerThe parallelism configuration applied to the pipeline execution.jamazonka-sagemakerThe Amazon Resource Name (ARN) of the pipeline that was executed.jamazonka-sagemaker9The Amazon Resource Name (ARN) of the pipeline execution.jamazonka-sagemaker*The description of the pipeline execution.jamazonka-sagemaker+The display name of the pipeline execution.jamazonka-sagemaker"The status of the pipeline status.jamazonka-sagemaker?Contains a list of pipeline parameters. This list can be empty.jamazonka-sagemakerCreate a value of j" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:j, j - Undocumented member.j, j/ - The creation time of the pipeline execution.j, j5 - If the execution failed, a message describing why.j, j - Undocumented member.j, j: - The time that the pipeline execution was last modified.j, j - The parallelism configuration applied to the pipeline execution.j, j - The Amazon Resource Name (ARN) of the pipeline that was executed.j, j< - The Amazon Resource Name (ARN) of the pipeline execution.j, j- - The description of the pipeline execution.j, j. - The display name of the pipeline execution.j, j% - The status of the pipeline status.j, j - Undocumented member.j, j - Contains a list of pipeline parameters. This list can be empty.jamazonka-sagemakerUndocumented member.jamazonka-sagemaker,The creation time of the pipeline execution.jamazonka-sagemaker2If the execution failed, a message describing why.jamazonka-sagemakerUndocumented member.jamazonka-sagemaker7The time that the pipeline execution was last modified.jamazonka-sagemakerThe parallelism configuration applied to the pipeline execution.jamazonka-sagemakerThe Amazon Resource Name (ARN) of the pipeline that was executed.jamazonka-sagemaker9The Amazon Resource Name (ARN) of the pipeline execution.jamazonka-sagemaker*The description of the pipeline execution.jamazonka-sagemaker+The display name of the pipeline execution.jamazonka-sagemaker"The status of the pipeline status.jamazonka-sagemakerUndocumented member.jamazonka-sagemaker?Contains a list of pipeline parameters. This list can be empty.jjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjj(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';jamazonka-sagemaker-A SageMaker Model Building Pipeline instance.See: j smart constructor.jamazonka-sagemaker"The creation time of the pipeline.jamazonka-sagemaker-The time that the pipeline was last modified.jamazonka-sagemaker(The time when the pipeline was last run.jamazonka-sagemaker6The parallelism configuration applied to the pipeline.jamazonka-sagemaker/The Amazon Resource Name (ARN) of the pipeline.jamazonka-sagemaker The description of the pipeline.jamazonka-sagemaker!The display name of the pipeline.jamazonka-sagemakerThe name of the pipeline.jamazonka-sagemakerThe status of the pipeline.jamazonka-sagemakerThe Amazon Resource Name (ARN) of the role that created the pipeline.jamazonka-sagemaker*A list of tags that apply to the pipeline.jamazonka-sagemakerCreate a value of j" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:j, j - Undocumented member.j, j% - The creation time of the pipeline.j, j - Undocumented member.j, j0 - The time that the pipeline was last modified.j, j+ - The time when the pipeline was last run.j, j9 - The parallelism configuration applied to the pipeline.j, j2 - The Amazon Resource Name (ARN) of the pipeline.j, j# - The description of the pipeline.j, j$ - The display name of the pipeline.j, j - The name of the pipeline.j, j - The status of the pipeline.j, j - The Amazon Resource Name (ARN) of the role that created the pipeline.j, j- - A list of tags that apply to the pipeline.jamazonka-sagemakerUndocumented member.jamazonka-sagemaker"The creation time of the pipeline.jamazonka-sagemakerUndocumented member.jamazonka-sagemaker-The time that the pipeline was last modified.jamazonka-sagemaker(The time when the pipeline was last run.jamazonka-sagemaker6The parallelism configuration applied to the pipeline.jamazonka-sagemaker/The Amazon Resource Name (ARN) of the pipeline.jamazonka-sagemaker The description of the pipeline.jamazonka-sagemaker!The display name of the pipeline.jamazonka-sagemakerThe name of the pipeline.jamazonka-sagemakerThe status of the pipeline.jamazonka-sagemakerThe Amazon Resource Name (ARN) of the role that created the pipeline.jamazonka-sagemaker*A list of tags that apply to the pipeline.jjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjj(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';jamazonka-sagemaker2A group of versioned models in the model registry.See: j smart constructor.jamazonka-sagemaker*The time that the model group was created.jamazonka-sagemaker2The Amazon Resource Name (ARN) of the model group.jamazonka-sagemaker$The description for the model group.jamazonka-sagemakerThe name of the model group.jamazonka-sagemakerThe status of the model group. This can be one of the following values.PENDING, - The model group is pending being created. IN_PROGRESS6 - The model group is in the process of being created. COMPLETED, - The model group was successfully created.FAILED - The model group failed.DELETING6 - The model group is in the process of being deleted. DELETE_FAILED. - SageMaker failed to delete the model group.jamazonka-sagemakerA list of the tags associated with the model group. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services resources in the +Amazon Web Services General Reference Guide.jamazonka-sagemakerCreate a value of j" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:j, j - Undocumented member.j, j- - The time that the model group was created.j, j5 - The Amazon Resource Name (ARN) of the model group.j, j' - The description for the model group.j, k - The name of the model group.j, k - The status of the model group. This can be one of the following values.PENDING, - The model group is pending being created. IN_PROGRESS6 - The model group is in the process of being created. COMPLETED, - The model group was successfully created.FAILED - The model group failed.DELETING6 - The model group is in the process of being deleted. DELETE_FAILED. - SageMaker failed to delete the model group.j, k - A list of the tags associated with the model group. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services resources in the +Amazon Web Services General Reference Guide.jamazonka-sagemakerUndocumented member.jamazonka-sagemaker*The time that the model group was created.jamazonka-sagemaker2The Amazon Resource Name (ARN) of the model group.jamazonka-sagemaker$The description for the model group.kamazonka-sagemakerThe name of the model group.kamazonka-sagemakerThe status of the model group. This can be one of the following values.PENDING, - The model group is pending being created. IN_PROGRESS6 - The model group is in the process of being created. COMPLETED, - The model group was successfully created.FAILED - The model group failed.DELETING6 - The model group is in the process of being deleted. DELETE_FAILED. - SageMaker failed to delete the model group.kamazonka-sagemakerA list of the tags associated with the model group. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services resources in the +Amazon Web Services General Reference Guide.jjjjjjjjjjjjjjkkkjjjjjjjjjjjjjjkkk(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';6kamazonka-sagemaker?A versioned model that can be deployed for SageMaker inference.See: k smart constructor.kamazonka-sagemaker7An array of additional Inference Specification objects.kamazonka-sagemaker6A description provided when the model approval is set.kamazonka-sagemakerWhether the model package is to be certified to be listed on Amazon Web Services Marketplace. For information about listing model packages on Amazon Web Services Marketplace, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-mkt-list.htmlList Your Algorithm or Model Package on Amazon Web Services Marketplace.kamazonka-sagemakerInformation about the user who created or modified an experiment, trial, trial component, lineage group, or project.kamazonka-sagemaker,The time that the model package was created.kamazonka-sagemaker.The metadata properties for the model package.kamazonka-sagemakerThe machine learning domain of your model package and its components. Common machine learning domains include computer vision and natural language processing.kamazonka-sagemakerRepresents the drift check baselines that can be used when the model monitor is set using the model package.kamazonka-sagemakerDefines how to perform inference generation after a training job is run.kamazonka-sagemakerInformation about the user who created or modified an experiment, trial, trial component, lineage group, or project.kamazonka-sagemaker-The last time the model package was modified.kamazonka-sagemakerMetadata properties of the tracking entity, trial, or trial component.kamazonka-sagemakerThe approval status of the model. This can be one of the following values.APPROVED - The model is approvedREJECTED - The model is rejected.PENDING_MANUAL_APPROVAL1 - The model is waiting for manual approval.kamazonka-sagemakerMetrics for the model.kamazonka-sagemaker4The Amazon Resource Name (ARN) of the model package.kamazonka-sagemaker%The description of the model package.kamazonka-sagemaker+The model group to which the model belongs.kamazonka-sagemakerThe name of the model.kamazonka-sagemakerThe status of the model package. This can be one of the following values.PENDING. - The model package is pending being created. IN_PROGRESS= - The model package is in the process of being created. COMPLETED. - The model package was successfully created.FAILED - The model package failed.DELETING8 - The model package is in the process of being deleted.kamazonka-sagemakerSpecifies the validation and image scan statuses of the model package.kamazonka-sagemaker(The version number of a versioned model.kamazonka-sagemakerThe Amazon Simple Storage Service path where the sample payload are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).kamazonka-sagemaker>A list of algorithms that were used to create a model package.kamazonka-sagemakerA list of the tags associated with the model package. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services resources in the +Amazon Web Services General Reference Guide.kamazonka-sagemakerThe machine learning task your model package accomplishes. Common machine learning tasks include object detection and image classification.kamazonka-sagemakerSpecifies batch transform jobs that SageMaker runs to validate your model package.kamazonka-sagemakerCreate a value of k" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:k, k: - An array of additional Inference Specification objects.k, k9 - A description provided when the model approval is set.k, k - Whether the model package is to be certified to be listed on Amazon Web Services Marketplace. For information about listing model packages on Amazon Web Services Marketplace, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-mkt-list.htmlList Your Algorithm or Model Package on Amazon Web Services Marketplace.k, k - Information about the user who created or modified an experiment, trial, trial component, lineage group, or project.k, k/ - The time that the model package was created.k, k1 - The metadata properties for the model package.k, k - The machine learning domain of your model package and its components. Common machine learning domains include computer vision and natural language processing.k, k - Represents the drift check baselines that can be used when the model monitor is set using the model package.k, k - Defines how to perform inference generation after a training job is run.k, k - Information about the user who created or modified an experiment, trial, trial component, lineage group, or project.k, k0 - The last time the model package was modified.k, k - Metadata properties of the tracking entity, trial, or trial component.k, k - The approval status of the model. This can be one of the following values.APPROVED - The model is approvedREJECTED - The model is rejected.PENDING_MANUAL_APPROVAL1 - The model is waiting for manual approval.k, k - Metrics for the model.k, k7 - The Amazon Resource Name (ARN) of the model package.k, k( - The description of the model package.k, k. - The model group to which the model belongs.k, k - The name of the model.k, k - The status of the model package. This can be one of the following values.PENDING. - The model package is pending being created. IN_PROGRESS= - The model package is in the process of being created. COMPLETED. - The model package was successfully created.FAILED - The model package failed.DELETING8 - The model package is in the process of being deleted.k, k - Specifies the validation and image scan statuses of the model package.k, k+ - The version number of a versioned model.k, k - The Amazon Simple Storage Service path where the sample payload are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).k, k - A list of algorithms that were used to create a model package.k, k - A list of the tags associated with the model package. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services resources in the +Amazon Web Services General Reference Guide.k, k - The machine learning task your model package accomplishes. Common machine learning tasks include object detection and image classification.k, k - Specifies batch transform jobs that SageMaker runs to validate your model package.kamazonka-sagemaker7An array of additional Inference Specification objects.kamazonka-sagemaker6A description provided when the model approval is set.kamazonka-sagemakerWhether the model package is to be certified to be listed on Amazon Web Services Marketplace. For information about listing model packages on Amazon Web Services Marketplace, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-mkt-list.htmlList Your Algorithm or Model Package on Amazon Web Services Marketplace.kamazonka-sagemakerInformation about the user who created or modified an experiment, trial, trial component, lineage group, or project.kamazonka-sagemaker,The time that the model package was created.kamazonka-sagemaker.The metadata properties for the model package.kamazonka-sagemakerThe machine learning domain of your model package and its components. Common machine learning domains include computer vision and natural language processing.kamazonka-sagemakerRepresents the drift check baselines that can be used when the model monitor is set using the model package.kamazonka-sagemakerDefines how to perform inference generation after a training job is run.kamazonka-sagemakerInformation about the user who created or modified an experiment, trial, trial component, lineage group, or project.kamazonka-sagemaker-The last time the model package was modified.kamazonka-sagemakerMetadata properties of the tracking entity, trial, or trial component.kamazonka-sagemakerThe approval status of the model. This can be one of the following values.APPROVED - The model is approvedREJECTED - The model is rejected.PENDING_MANUAL_APPROVAL1 - The model is waiting for manual approval.kamazonka-sagemakerMetrics for the model.kamazonka-sagemaker4The Amazon Resource Name (ARN) of the model package.kamazonka-sagemaker%The description of the model package.kamazonka-sagemaker+The model group to which the model belongs.kamazonka-sagemakerThe name of the model.kamazonka-sagemakerThe status of the model package. This can be one of the following values.PENDING. - The model package is pending being created. IN_PROGRESS= - The model package is in the process of being created. COMPLETED. - The model package was successfully created.FAILED - The model package failed.DELETING8 - The model package is in the process of being deleted.kamazonka-sagemakerSpecifies the validation and image scan statuses of the model package.kamazonka-sagemaker(The version number of a versioned model.kamazonka-sagemakerThe Amazon Simple Storage Service path where the sample payload are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).kamazonka-sagemaker>A list of algorithms that were used to create a model package.kamazonka-sagemakerA list of the tags associated with the model package. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services resources in the +Amazon Web Services General Reference Guide.kamazonka-sagemakerThe machine learning task your model package accomplishes. Common machine learning tasks include object detection and image classification.kamazonka-sagemakerSpecifies batch transform jobs that SageMaker runs to validate your model package.7kkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkk7kkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkk(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';kamazonka-sagemakerThe model card for a model displayed in the Amazon SageMaker Model Dashboard.See: k smart constructor.kamazonka-sagemaker;A timestamp that indicates when the model card was created.kamazonka-sagemakerA timestamp that indicates when the model card was last updated.kamazonka-sagemaker0The Amazon Resource Name (ARN) for a model card.kamazonka-sagemakerThe name of a model card.kamazonka-sagemakerThe model card status.kamazonka-sagemakerThe model card version.kamazonka-sagemakerFor models created in SageMaker, this is the model ARN. For models created outside of SageMaker, this is a user-customized string.kamazonka-sagemaker8A model card's risk rating. Can be low, medium, or high.kamazonka-sagemakerThe KMS Key ID (KMSKeyId+) for encryption of model card information.kamazonka-sagemaker&The tags associated with a model card.kamazonka-sagemakerCreate a value of k" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:k, k - Undocumented member.k, k> - A timestamp that indicates when the model card was created.k, k - Undocumented member.k, k - A timestamp that indicates when the model card was last updated.k, k3 - The Amazon Resource Name (ARN) for a model card.k, k - The name of a model card.k, k - The model card status.k, k - The model card version.k, k - For models created in SageMaker, this is the model ARN. For models created outside of SageMaker, this is a user-customized string.k, k; - A model card's risk rating. Can be low, medium, or high.k, k - The KMS Key ID (KMSKeyId+) for encryption of model card information.k, k) - The tags associated with a model card.kamazonka-sagemakerUndocumented member.kamazonka-sagemaker;A timestamp that indicates when the model card was created.kamazonka-sagemakerUndocumented member.kamazonka-sagemakerA timestamp that indicates when the model card was last updated.kamazonka-sagemaker0The Amazon Resource Name (ARN) for a model card.kamazonka-sagemakerThe name of a model card.kamazonka-sagemakerThe model card status.kamazonka-sagemakerThe model card version.kamazonka-sagemakerFor models created in SageMaker, this is the model ARN. For models created outside of SageMaker, this is a user-customized string.kamazonka-sagemaker8A model card's risk rating. Can be low, medium, or high.kamazonka-sagemakerThe KMS Key ID (KMSKeyId+) for encryption of model card information.kamazonka-sagemaker&The tags associated with a model card.kkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkk(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';^kamazonka-sagemakerAn Amazon SageMaker Model Card.See: k smart constructor.kamazonka-sagemaker1The content of the model card. Content uses the  https://docs.aws.amazon.com/sagemaker/latest/dg/model-cards-api-json-schema.htmlmodel card JSON schema and provided as a string.kamazonka-sagemaker2The date and time that the model card was created.kamazonka-sagemaker8The date and time that the model card was last modified.kamazonka-sagemaker1The Amazon Resource Name (ARN) of the model card.kamazonka-sagemaker"The unique name of the model card.kamazonka-sagemakerThe approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.Draft': The model card is a work in progress. PendingReview#: The model card is pending review.Approved: The model card is approved.Archived: The model card is archived. No more updates should be made to the model card, but it can still be exported.kamazonka-sagemakerThe version of the model card.kamazonka-sagemaker"The unique name (ID) of the model.kamazonka-sagemakerThe risk rating of the model. Different organizations might have different criteria for model card risk ratings. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/model-cards-risk-rating.html Risk ratings.kamazonka-sagemaker;The security configuration used to protect model card data.kamazonka-sagemaker;Key-value pairs used to manage metadata for the model card.kamazonka-sagemakerCreate a value of k" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:k, k4 - The content of the model card. Content uses the  https://docs.aws.amazon.com/sagemaker/latest/dg/model-cards-api-json-schema.htmlmodel card JSON schema and provided as a string.k, k - Undocumented member.k, k5 - The date and time that the model card was created.k, k - Undocumented member.k, k; - The date and time that the model card was last modified.k, k4 - The Amazon Resource Name (ARN) of the model card.k, l% - The unique name of the model card.k, l - The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.Draft': The model card is a work in progress. PendingReview#: The model card is pending review.Approved: The model card is approved.Archived: The model card is archived. No more updates should be made to the model card, but it can still be exported.k, l! - The version of the model card.k, l% - The unique name (ID) of the model.k, l - The risk rating of the model. Different organizations might have different criteria for model card risk ratings. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/model-cards-risk-rating.html Risk ratings.k, l> - The security configuration used to protect model card data.k, l> - Key-value pairs used to manage metadata for the model card.kamazonka-sagemaker1The content of the model card. Content uses the  https://docs.aws.amazon.com/sagemaker/latest/dg/model-cards-api-json-schema.htmlmodel card JSON schema and provided as a string.kamazonka-sagemakerUndocumented member.kamazonka-sagemaker2The date and time that the model card was created.kamazonka-sagemakerUndocumented member.kamazonka-sagemaker8The date and time that the model card was last modified.kamazonka-sagemaker1The Amazon Resource Name (ARN) of the model card.lamazonka-sagemaker"The unique name of the model card.lamazonka-sagemakerThe approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.Draft': The model card is a work in progress. PendingReview#: The model card is pending review.Approved: The model card is approved.Archived: The model card is archived. No more updates should be made to the model card, but it can still be exported.lamazonka-sagemakerThe version of the model card.lamazonka-sagemaker"The unique name (ID) of the model.lamazonka-sagemakerThe risk rating of the model. Different organizations might have different criteria for model card risk ratings. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/model-cards-risk-rating.html Risk ratings.lamazonka-sagemaker;The security configuration used to protect model card data.lamazonka-sagemaker;Key-value pairs used to manage metadata for the model card.kkkkkkkkkkkkkkkkkkkkkklllllllkkkkkkkkkkkkkkkkkkkkkklllllll(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';#nlamazonka-sagemaker>The properties of an experiment as returned by the Search API.See: l smart constructor.lamazonka-sagemakerWho created the experiment.lamazonka-sagemaker When the experiment was created.lamazonka-sagemaker"The description of the experiment.lamazonka-sagemaker,The name of the experiment as displayed. If  DisplayName isn't specified, ExperimentName is displayed.lamazonka-sagemaker1The Amazon Resource Name (ARN) of the experiment.lamazonka-sagemakerThe name of the experiment.lamazonka-sagemaker&When the experiment was last modified.lamazonka-sagemakerThe list of tags that are associated with the experiment. You can use Search API to search on the tags.lamazonka-sagemakerCreate a value of l" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:l, l - Who created the experiment.l, l# - When the experiment was created.l, l% - The description of the experiment.l, l/ - The name of the experiment as displayed. If  DisplayName isn't specified, ExperimentName is displayed.l, l4 - The Amazon Resource Name (ARN) of the experiment.l, l - The name of the experiment.l, l - Undocumented member.l, l) - When the experiment was last modified.l, l - Undocumented member.l, l - The list of tags that are associated with the experiment. You can use Search API to search on the tags.lamazonka-sagemakerWho created the experiment.lamazonka-sagemaker When the experiment was created.lamazonka-sagemaker"The description of the experiment.lamazonka-sagemaker,The name of the experiment as displayed. If  DisplayName isn't specified, ExperimentName is displayed.lamazonka-sagemaker1The Amazon Resource Name (ARN) of the experiment.lamazonka-sagemakerThe name of the experiment.lamazonka-sagemakerUndocumented member.lamazonka-sagemaker&When the experiment was last modified.lamazonka-sagemakerUndocumented member.lamazonka-sagemakerThe list of tags that are associated with the experiment. You can use Search API to search on the tags.llllllllllllllllllllllllllllllllllllllllllllll(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';,.lamazonka-sagemakerLists a summary of the properties of an association. An association is an entity that links other lineage or experiment entities. An example would be an association between a training job and a model.See: l smart constructor.lamazonka-sagemakerThe type of the association.lamazonka-sagemaker!When the association was created.lamazonka-sagemaker2The Amazon Resource Name (ARN) of the destination.lamazonka-sagemakerThe name of the destination.lamazonka-sagemakerThe destination type.lamazonka-sagemakerThe ARN of the source.lamazonka-sagemakerThe name of the source.lamazonka-sagemakerThe source type.lamazonka-sagemakerCreate a value of l" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:l, l - The type of the association.l, l - Undocumented member.l, l$ - When the association was created.l, l5 - The Amazon Resource Name (ARN) of the destination.l, l - The name of the destination.l, l - The destination type.l, l - The ARN of the source.l, l - The name of the source.l, l - The source type.lamazonka-sagemakerThe type of the association.lamazonka-sagemakerUndocumented member.lamazonka-sagemaker!When the association was created.lamazonka-sagemaker2The Amazon Resource Name (ARN) of the destination.lamazonka-sagemakerThe name of the destination.lamazonka-sagemakerThe destination type.lamazonka-sagemakerThe ARN of the source.lamazonka-sagemakerThe name of the source.lamazonka-sagemakerThe source type.llllllllllllllllllllllllllllllllllllllllll(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?-'llllllllllll(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?- lllllllllllllllllllllllllll(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';3 lamazonka-sagemakerThe user profile details.See: m smart constructor.lamazonka-sagemakerThe creation time.lamazonka-sagemakerThe domain ID.mamazonka-sagemakerThe last modified time.mamazonka-sagemaker The status.mamazonka-sagemakerThe user profile name.mamazonka-sagemakerCreate a value of l" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:l, m - The creation time.l, m - The domain ID.m, m - The last modified time.m, m - The status.m, m - The user profile name.mamazonka-sagemakerThe creation time.mamazonka-sagemakerThe domain ID.mamazonka-sagemakerThe last modified time.mamazonka-sagemaker The status.mamazonka-sagemakerThe user profile name. lmlmlmlmmmmmm lmlmlmlmmmmmm(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';DCmamazonka-sagemakerA collection of settings that apply to users of Amazon SageMaker Studio. These settings are specified when the CreateUserProfile API is called, and as DefaultUserSettings when the  CreateDomain API is called.SecurityGroups is aggregated when specified in both calls. For all other settings in  UserSettings, the values specified in CreateUserProfile* take precedence over those specified in  CreateDomain.See: m smart constructor.mamazonka-sagemakerThe Canvas app settings.mamazonka-sagemaker The execution role for the user.mamazonka-sagemaker"The Jupyter server's app settings.mamazonka-sagemaker The kernel gateway app settings.mamazonka-sagemaker,A collection of settings that configure the RSessionGateway app.mamazonka-sagemakerA collection of settings that configure user interaction with the RStudioServerPro app.mamazonka-sagemakerThe security groups for the Amazon Virtual Private Cloud (VPC) that Studio uses for communication.Optional when the !CreateDomain.AppNetworkAccessType parameter is set to PublicInternetOnly.Required when the !CreateDomain.AppNetworkAccessType parameter is set to VpcOnly.Amazon SageMaker adds a security group to allow NFS traffic from SageMaker Studio. Therefore, the number of security groups that you can specify is one less than the maximum number shown.mamazonka-sagemaker9Specifies options for sharing SageMaker Studio notebooks.mamazonka-sagemakerThe TensorBoard app settings.mamazonka-sagemakerCreate a value of m" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:m, m - The Canvas app settings.m, m# - The execution role for the user.m, m% - The Jupyter server's app settings.m, m# - The kernel gateway app settings.m, m/ - A collection of settings that configure the RSessionGateway app.m, m - A collection of settings that configure user interaction with the RStudioServerPro app.m, m - The security groups for the Amazon Virtual Private Cloud (VPC) that Studio uses for communication.Optional when the !CreateDomain.AppNetworkAccessType parameter is set to PublicInternetOnly.Required when the !CreateDomain.AppNetworkAccessType parameter is set to VpcOnly.Amazon SageMaker adds a security group to allow NFS traffic from SageMaker Studio. Therefore, the number of security groups that you can specify is one less than the maximum number shown.m, m< - Specifies options for sharing SageMaker Studio notebooks.m, m - The TensorBoard app settings.mamazonka-sagemakerThe Canvas app settings.mamazonka-sagemaker The execution role for the user.mamazonka-sagemaker"The Jupyter server's app settings.mamazonka-sagemaker The kernel gateway app settings.mamazonka-sagemaker,A collection of settings that configure the RSessionGateway app.mamazonka-sagemakerA collection of settings that configure user interaction with the RStudioServerPro app.mamazonka-sagemakerThe security groups for the Amazon Virtual Private Cloud (VPC) that Studio uses for communication.Optional when the !CreateDomain.AppNetworkAccessType parameter is set to PublicInternetOnly.Required when the !CreateDomain.AppNetworkAccessType parameter is set to VpcOnly.Amazon SageMaker adds a security group to allow NFS traffic from SageMaker Studio. Therefore, the number of security groups that you can specify is one less than the maximum number shown.mamazonka-sagemaker9Specifies options for sharing SageMaker Studio notebooks.mamazonka-sagemakerThe TensorBoard app settings.mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?E<mmmmmm mmmmmmmmm(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';O mamazonka-sagemaker=Specifies a production variant property type for an Endpoint.If you are updating an endpoint with the UpdateEndpointInput$RetainAllVariantProperties option set to true, the VariantProperty objects listed in UpdateEndpointInput$ExcludeRetainedVariantProperties override the existing variant properties of the endpoint.See: m smart constructor.mamazonka-sagemaker7The type of variant property. The supported values are:DesiredInstanceCount: Overrides the existing variant instance counts using the ProductionVariant$InitialInstanceCount values in the CreateEndpointConfigInput$ProductionVariants. DesiredWeight: Overrides the existing variant weights using the ProductionVariant$InitialVariantWeight values in the CreateEndpointConfigInput$ProductionVariants.DataCaptureConfig: (Not currently supported.)mamazonka-sagemakerCreate a value of m" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:m, m: - The type of variant property. The supported values are:DesiredInstanceCount: Overrides the existing variant instance counts using the ProductionVariant$InitialInstanceCount values in the CreateEndpointConfigInput$ProductionVariants. DesiredWeight: Overrides the existing variant weights using the ProductionVariant$InitialVariantWeight values in the CreateEndpointConfigInput$ProductionVariants.DataCaptureConfig: (Not currently supported.)mamazonka-sagemaker7The type of variant property. The supported values are:DesiredInstanceCount: Overrides the existing variant instance counts using the ProductionVariant$InitialInstanceCount values in the CreateEndpointConfigInput$ProductionVariants. DesiredWeight: Overrides the existing variant weights using the ProductionVariant$InitialVariantWeight values in the CreateEndpointConfigInput$ProductionVariants.DataCaptureConfig: (Not currently supported.)mamazonka-sagemakermmmmmmmmmmm(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?Ommmmmmmm mmmmmmmmmmmmm(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';Zmamazonka-sagemaker/Describes the status of the production variant.See: m smart constructor.mamazonka-sagemaker,The start time of the current status change.mamazonka-sagemaker>A message that describes the status of the production variant.mamazonka-sagemakerThe endpoint variant status which describes the current deployment stage status or operational status.Creating:: Creating inference resources for the production variant.Deleting: Terminating inference resources for the production variant.Updating/: Updating capacity for the production variant.ActivatingTraffic0: Turning on traffic for the production variant.Baking: Waiting period to monitor the CloudWatch alarms in the automatic rollback configuration.mamazonka-sagemakerCreate a value of m" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:m, m/ - The start time of the current status change.m, m - A message that describes the status of the production variant.m, m - The endpoint variant status which describes the current deployment stage status or operational status.Creating:: Creating inference resources for the production variant.Deleting: Terminating inference resources for the production variant.Updating/: Updating capacity for the production variant.ActivatingTraffic0: Turning on traffic for the production variant.Baking: Waiting period to monitor the CloudWatch alarms in the automatic rollback configuration.mamazonka-sagemaker,The start time of the current status change.mamazonka-sagemaker>A message that describes the status of the production variant.mamazonka-sagemakerThe endpoint variant status which describes the current deployment stage status or operational status.Creating:: Creating inference resources for the production variant.Deleting: Terminating inference resources for the production variant.Updating/: Updating capacity for the production variant.ActivatingTraffic0: Turning on traffic for the production variant.Baking: Waiting period to monitor the CloudWatch alarms in the automatic rollback configuration.mamazonka-sagemakerm mmmmmmmmm mmmmmmmmm(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';hmamazonka-sagemakerDescribes weight and capacities for a production variant associated with an endpoint. If you sent a request to the "UpdateEndpointWeightsAndCapacities! API and the endpoint status is Updating/, you get different desired and current values.See: n smart constructor.mamazonka-sagemaker4The number of instances associated with the variant.namazonka-sagemaker.The serverless configuration for the endpoint.namazonka-sagemaker'The weight associated with the variant.namazonka-sagemaker An array of  DeployedImage objects that specify the Amazon EC2 Container Registry paths of the inference images deployed on instances of this ProductionVariant.namazonka-sagemaker*The number of instances requested in the "UpdateEndpointWeightsAndCapacities request.namazonka-sagemaker?The serverless configuration requested for the endpoint update.namazonka-sagemaker+The requested weight, as specified in the "UpdateEndpointWeightsAndCapacities request.namazonka-sagemakerThe endpoint variant status which describes the current deployment stage status or operational status.namazonka-sagemakerThe name of the variant.namazonka-sagemakerCreate a value of m" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:m, n7 - The number of instances associated with the variant.n, n1 - The serverless configuration for the endpoint.n, n* - The weight associated with the variant.n, n - An array of  DeployedImage objects that specify the Amazon EC2 Container Registry paths of the inference images deployed on instances of this ProductionVariant.n, n- - The number of instances requested in the "UpdateEndpointWeightsAndCapacities request.n, n - The serverless configuration requested for the endpoint update.n, n. - The requested weight, as specified in the "UpdateEndpointWeightsAndCapacities request.n, n - The endpoint variant status which describes the current deployment stage status or operational status.n, n - The name of the variant.namazonka-sagemaker4The number of instances associated with the variant.namazonka-sagemaker.The serverless configuration for the endpoint.namazonka-sagemaker'The weight associated with the variant.namazonka-sagemaker An array of  DeployedImage objects that specify the Amazon EC2 Container Registry paths of the inference images deployed on instances of this ProductionVariant.namazonka-sagemaker*The number of instances requested in the "UpdateEndpointWeightsAndCapacities request.namazonka-sagemaker?The serverless configuration requested for the endpoint update.namazonka-sagemaker+The requested weight, as specified in the "UpdateEndpointWeightsAndCapacities request.namazonka-sagemakerThe endpoint variant status which describes the current deployment stage status or operational status.namazonka-sagemakerThe name of the variant.namazonka-sagemakernmnnnnnmnnnmnnnnnnnnnnmnnnnnmnnnmnnnnnnnnnn(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';namazonka-sagemakerThe production variant summary for a deployment when an endpoint is creating or updating with the  CreateEndpoint  or  UpdateEndpoint  operations. Describes the VariantStatus , weight and capacity for a production variant associated with an endpoint.See: n smart constructor.namazonka-sagemakerThe size of the Elastic Inference (EI) instance to use for the production variant. EI instances provide on-demand GPU computing for inference. For more information, see  7https://docs.aws.amazon.com/sagemaker/latest/dg/ei.html+Using Elastic Inference in Amazon SageMaker.namazonka-sagemaker4The number of instances associated with the variant.namazonka-sagemaker.The serverless configuration for the endpoint.namazonka-sagemaker'The weight associated with the variant.namazonka-sagemaker An array of  DeployedImage objects that specify the Amazon EC2 Container Registry paths of the inference images deployed on instances of this ProductionVariant.namazonka-sagemakerThe number of instances requested in this deployment, as specified in the endpoint configuration for the endpoint. The value is taken from the request to the  CreateEndpointConfig  operation.namazonka-sagemakerThe serverless configuration requested for this deployment, as specified in the endpoint configuration for the endpoint.namazonka-sagemakerThe requested weight for the variant in this deployment, as specified in the endpoint configuration for the endpoint. The value is taken from the request to the  CreateEndpointConfig  operation.namazonka-sagemaker2The type of instances associated with the variant.namazonka-sagemakerThe endpoint variant status which describes the current deployment stage status or operational status.namazonka-sagemakerThe name of the variant.namazonka-sagemakerCreate a value of n" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:n, n - The size of the Elastic Inference (EI) instance to use for the production variant. EI instances provide on-demand GPU computing for inference. For more information, see  7https://docs.aws.amazon.com/sagemaker/latest/dg/ei.html+Using Elastic Inference in Amazon SageMaker.n, n7 - The number of instances associated with the variant.n, n1 - The serverless configuration for the endpoint.n, n* - The weight associated with the variant.n, n - An array of  DeployedImage objects that specify the Amazon EC2 Container Registry paths of the inference images deployed on instances of this ProductionVariant.n, n - The number of instances requested in this deployment, as specified in the endpoint configuration for the endpoint. The value is taken from the request to the  CreateEndpointConfig  operation.n, n - The serverless configuration requested for this deployment, as specified in the endpoint configuration for the endpoint.n, n - The requested weight for the variant in this deployment, as specified in the endpoint configuration for the endpoint. The value is taken from the request to the  CreateEndpointConfig  operation.n, n5 - The type of instances associated with the variant.n, n - The endpoint variant status which describes the current deployment stage status or operational status.n, n - The name of the variant.namazonka-sagemakerThe size of the Elastic Inference (EI) instance to use for the production variant. EI instances provide on-demand GPU computing for inference. For more information, see  7https://docs.aws.amazon.com/sagemaker/latest/dg/ei.html+Using Elastic Inference in Amazon SageMaker.namazonka-sagemaker4The number of instances associated with the variant.namazonka-sagemaker.The serverless configuration for the endpoint.namazonka-sagemaker'The weight associated with the variant.namazonka-sagemaker An array of  DeployedImage objects that specify the Amazon EC2 Container Registry paths of the inference images deployed on instances of this ProductionVariant.namazonka-sagemakerThe number of instances requested in this deployment, as specified in the endpoint configuration for the endpoint. The value is taken from the request to the  CreateEndpointConfig  operation.namazonka-sagemakerThe serverless configuration requested for this deployment, as specified in the endpoint configuration for the endpoint.namazonka-sagemakerThe requested weight for the variant in this deployment, as specified in the endpoint configuration for the endpoint. The value is taken from the request to the  CreateEndpointConfig  operation.namazonka-sagemaker2The type of instances associated with the variant.namazonka-sagemakerThe endpoint variant status which describes the current deployment stage status or operational status.namazonka-sagemakerThe name of the variant.namazonka-sagemakernnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';v namazonka-sagemakerThe summary of an in-progress deployment when an endpoint is creating or updating with a new endpoint configuration.See: n smart constructor.namazonka-sagemakerAn array of PendingProductionVariantSummary objects, one for each model hosted behind this endpoint for the in-progress deployment.namazonka-sagemakerAn array of PendingProductionVariantSummary objects, one for each model hosted behind this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants! for the in-progress deployment.namazonka-sagemaker!The start time of the deployment.namazonka-sagemaker>The name of the endpoint configuration used in the deployment.namazonka-sagemakerCreate a value of n" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:n, n - An array of PendingProductionVariantSummary objects, one for each model hosted behind this endpoint for the in-progress deployment.n, n - An array of PendingProductionVariantSummary objects, one for each model hosted behind this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants! for the in-progress deployment.n, n$ - The start time of the deployment.n, n - The name of the endpoint configuration used in the deployment.namazonka-sagemakerAn array of PendingProductionVariantSummary objects, one for each model hosted behind this endpoint for the in-progress deployment.namazonka-sagemakerAn array of PendingProductionVariantSummary objects, one for each model hosted behind this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants! for the in-progress deployment.namazonka-sagemaker!The start time of the deployment.namazonka-sagemaker>The name of the endpoint configuration used in the deployment.namazonka-sagemakern nnnnnnnnnnn nnnnnnnnnnn(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?Gnnnnnnn nnnnnnnnnnn(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';Znamazonka-sagemaker7A lineage entity connected to the starting entity(ies).See: n smart constructor.namazonka-sagemaker>The Amazon Resource Name (ARN) of the lineage entity resource.namazonka-sagemaker+The type of resource of the lineage entity.namazonka-sagemaker6The type of the lineage entity resource. For example: DataSet, Model, Endpoint, etc...namazonka-sagemakerCreate a value of n" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:n, n - The Amazon Resource Name (ARN) of the lineage entity resource.n, n. - The type of resource of the lineage entity.n, n9 - The type of the lineage entity resource. For example: DataSet, Model, Endpoint, etc...namazonka-sagemaker>The Amazon Resource Name (ARN) of the lineage entity resource.namazonka-sagemaker+The type of resource of the lineage entity.namazonka-sagemaker6The type of the lineage entity resource. For example: DataSet, Model, Endpoint, etc... nnnnnnnnn nnnnnnnnn(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';namazonka-sagemakerSpecifies a VPC that your training jobs and hosted models have access to. Control access to and from your training and model containers by configuring the VPC. For more information, see  =https://docs.aws.amazon.com/sagemaker/latest/dg/host-vpc.html:Protect Endpoints by Using an Amazon Virtual Private Cloud and  >https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html>Protect Training Jobs by Using an Amazon Virtual Private Cloud.See: n smart constructor.namazonka-sagemakerThe VPC security group IDs, in the form sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.namazonka-sagemakerThe ID of the subnets in the VPC to which you want to connect your training job or model. For information about the availability of specific instance types, see  https://docs.aws.amazon.com/sagemaker/latest/dg/instance-types-az.html/Supported Instance Types and Availability Zones.namazonka-sagemakerCreate a value of n" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:n, n - The VPC security group IDs, in the form sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.n, n - The ID of the subnets in the VPC to which you want to connect your training job or model. For information about the availability of specific instance types, see  https://docs.aws.amazon.com/sagemaker/latest/dg/instance-types-az.html/Supported Instance Types and Availability Zones.namazonka-sagemakerThe VPC security group IDs, in the form sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.namazonka-sagemakerThe ID of the subnets in the VPC to which you want to connect your training job or model. For information about the availability of specific instance types, see  https://docs.aws.amazon.com/sagemaker/latest/dg/instance-types-az.html/Supported Instance Types and Availability Zones.namazonka-sagemakernamazonka-sagemakernnnnnnnnnnnnnnn(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';moamazonka-sagemaker*Contains information about a training job.See: o smart constructor.oamazonka-sagemakerInformation about the algorithm used for training, and algorithm metadata.oamazonka-sagemaker*The Amazon Resource Name (ARN) of the job.oamazonka-sagemakerThe billable time in seconds.oamazonka-sagemaker=A timestamp that indicates when the training job was created.oamazonka-sagemaker/Information about the debug rule configuration.oamazonka-sagemakerInformation about the evaluation status of the rules for the training job.oamazonka-sagemakerTo encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training.oamazonka-sagemakerWhen true, enables managed spot training using Amazon EC2 Spot instances to run training jobs instead of on-demand instances. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/model-managed-spot-training.htmlManaged Spot Training.oamazonka-sagemakerIf the  TrainingJob: was created with network isolation, the value is set to true. If network isolation is enabled, nodes can't communicate beyond the VPC they run in.oamazonka-sagemaker9The environment variables to set in the Docker container.oamazonka-sagemaker1If the training job failed, the reason it failed.oamazonka-sagemakerA list of final metric values that are set when the training job completes. Used only if the training job was configured to use metrics.oamazonka-sagemakerAlgorithm-specific parameters.oamazonka-sagemaker An array of Channel0 objects that describes each data input channel.oamazonka-sagemaker3The Amazon Resource Name (ARN) of the labeling job.oamazonka-sagemakerA timestamp that indicates when the status of the training job was last modified.oamazonka-sagemakerInformation about the Amazon S3 location that is configured for storing model artifacts.oamazonka-sagemakerThe S3 path where model artifacts that you configured when creating the job are stored. SageMaker creates subfolders for model artifacts.oamazonka-sagemakerResources, including ML compute instances and ML storage volumes, that are configured for model training.oamazonka-sagemakerThe number of times to retry the job when the job fails due to an InternalServerError.oamazonka-sagemakerThe Amazon Web Services Identity and Access Management (IAM) role configured for the training job.oamazonka-sagemakerProvides detailed information about the state of the training job. For detailed information about the secondary status of the training job, see  StatusMessage! under SecondaryStatusTransition.SageMaker provides primary statuses and secondary statuses that apply to each of them:  InProgress- Starting - Starting the training job. Downloading5 - An optional stage for algorithms that support File training input mode. It indicates that data is being downloaded to the ML storage volumes.Training - Training is in progress. Uploading - Training is complete and the model artifacts are being uploaded to the S3 location. Completed-  Completed" - The training job has completed.Failed- Failed - The training job has failed. The reason for the failure is returned in the  FailureReason field of DescribeTrainingJobResponse.Stopped- MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.Stopped - The training job has stopped.Stopping- Stopping - Stopping the training job.Valid values for SecondaryStatus are subject to change.6We no longer support the following secondary statuses: LaunchingMLInstances PreparingTrainingStack DownloadingTrainingImageoamazonka-sagemakerA history of all of the secondary statuses that the training job has transitioned through.oamazonka-sagemakerSpecifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.1To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.oamazonka-sagemakerAn array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.oamazonka-sagemakerIndicates the time when the training job ends on training instances. You are billed for the time interval between the value of TrainingStartTime and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when SageMaker detects a job failure.oamazonka-sagemaker3The Amazon Resource Name (ARN) of the training job.oamazonka-sagemakerThe name of the training job.oamazonka-sagemakerThe status of the training job.Training job statuses are: InProgress - The training is in progress. Completed" - The training job has completed.Failed - The training job has failed. To see the reason for the failure, see the  FailureReason! field in the response to a DescribeTrainingJobResponse call.Stopping - The training job is stopping.Stopped - The training job has stopped.#For more detailed information, see SecondaryStatus.oamazonka-sagemakerIndicates the time when the training job starts on training instances. You are billed for the time interval between this time and the value of TrainingEndTime. The start time in CloudWatch Logs might be later than this time. The difference is due to the time it takes to download the training data and to the size of the training container.oamazonka-sagemakerThe training time in seconds.oamazonka-sagemakerThe Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.oamazonka-sagemakerA VpcConfig object that specifies the VPC that this training job has access to. For more information, see  >https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html>Protect Training Jobs by Using an Amazon Virtual Private Cloud.oamazonka-sagemakerCreate a value of o" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:o, o - Information about the algorithm used for training, and algorithm metadata.o, o- - The Amazon Resource Name (ARN) of the job.o, o - The billable time in seconds.o, o - Undocumented member.o, o - A timestamp that indicates when the training job was created.o, o - Undocumented member.o, o2 - Information about the debug rule configuration.o, o - Information about the evaluation status of the rules for the training job.o, o - To encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training.o, o - When true, enables managed spot training using Amazon EC2 Spot instances to run training jobs instead of on-demand instances. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/model-managed-spot-training.htmlManaged Spot Training.o, o - If the  TrainingJob: was created with network isolation, the value is set to true. If network isolation is enabled, nodes can't communicate beyond the VPC they run in.o, o< - The environment variables to set in the Docker container.o, o - Undocumented member.o, o4 - If the training job failed, the reason it failed.o, o - A list of final metric values that are set when the training job completes. Used only if the training job was configured to use metrics.o, o! - Algorithm-specific parameters.o, o - An array of Channel0 objects that describes each data input channel.o, o6 - The Amazon Resource Name (ARN) of the labeling job.o, o - A timestamp that indicates when the status of the training job was last modified.o, o - Information about the Amazon S3 location that is configured for storing model artifacts.o, o - The S3 path where model artifacts that you configured when creating the job are stored. SageMaker creates subfolders for model artifacts.o, o - Resources, including ML compute instances and ML storage volumes, that are configured for model training.o, o - The number of times to retry the job when the job fails due to an InternalServerError.o, o - The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.o, o - Provides detailed information about the state of the training job. For detailed information about the secondary status of the training job, see  StatusMessage! under SecondaryStatusTransition.SageMaker provides primary statuses and secondary statuses that apply to each of them:  InProgress- Starting - Starting the training job. Downloading5 - An optional stage for algorithms that support File training input mode. It indicates that data is being downloaded to the ML storage volumes.Training - Training is in progress. Uploading - Training is complete and the model artifacts are being uploaded to the S3 location. Completed-  Completed" - The training job has completed.Failed- Failed - The training job has failed. The reason for the failure is returned in the  FailureReason field of DescribeTrainingJobResponse.Stopped- MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.Stopped - The training job has stopped.Stopping- Stopping - Stopping the training job.Valid values for SecondaryStatus are subject to change.6We no longer support the following secondary statuses: LaunchingMLInstances PreparingTrainingStack DownloadingTrainingImageo, o - A history of all of the secondary statuses that the training job has transitioned through.o, o - Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.1To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.o, o - An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.o, o - Undocumented member.o, o - Indicates the time when the training job ends on training instances. You are billed for the time interval between the value of TrainingStartTime and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when SageMaker detects a job failure.o, o6 - The Amazon Resource Name (ARN) of the training job.o, o - The name of the training job.o, o" - The status of the training job.Training job statuses are: InProgress - The training is in progress. Completed" - The training job has completed.Failed - The training job has failed. To see the reason for the failure, see the  FailureReason! field in the response to a DescribeTrainingJobResponse call.Stopping - The training job is stopping.Stopped - The training job has stopped.#For more detailed information, see SecondaryStatus.o, o - Indicates the time when the training job starts on training instances. You are billed for the time interval between this time and the value of TrainingEndTime. The start time in CloudWatch Logs might be later than this time. The difference is due to the time it takes to download the training data and to the size of the training container.o, o - The training time in seconds.o, o - The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.o, o - A VpcConfig object that specifies the VPC that this training job has access to. For more information, see  >https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html>Protect Training Jobs by Using an Amazon Virtual Private Cloud.oamazonka-sagemakerInformation about the algorithm used for training, and algorithm metadata.oamazonka-sagemaker*The Amazon Resource Name (ARN) of the job.oamazonka-sagemakerThe billable time in seconds.oamazonka-sagemakerUndocumented member.oamazonka-sagemaker=A timestamp that indicates when the training job was created.oamazonka-sagemakerUndocumented member.oamazonka-sagemaker/Information about the debug rule configuration.oamazonka-sagemakerInformation about the evaluation status of the rules for the training job.oamazonka-sagemakerTo encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training.oamazonka-sagemakerWhen true, enables managed spot training using Amazon EC2 Spot instances to run training jobs instead of on-demand instances. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/model-managed-spot-training.htmlManaged Spot Training.oamazonka-sagemakerIf the  TrainingJob: was created with network isolation, the value is set to true. If network isolation is enabled, nodes can't communicate beyond the VPC they run in.oamazonka-sagemaker9The environment variables to set in the Docker container.oamazonka-sagemakerUndocumented member.oamazonka-sagemaker1If the training job failed, the reason it failed.oamazonka-sagemakerA list of final metric values that are set when the training job completes. Used only if the training job was configured to use metrics.oamazonka-sagemakerAlgorithm-specific parameters.oamazonka-sagemaker An array of Channel0 objects that describes each data input channel.oamazonka-sagemaker3The Amazon Resource Name (ARN) of the labeling job.oamazonka-sagemakerA timestamp that indicates when the status of the training job was last modified.oamazonka-sagemakerInformation about the Amazon S3 location that is configured for storing model artifacts.oamazonka-sagemakerThe S3 path where model artifacts that you configured when creating the job are stored. SageMaker creates subfolders for model artifacts.oamazonka-sagemakerResources, including ML compute instances and ML storage volumes, that are configured for model training.oamazonka-sagemakerThe number of times to retry the job when the job fails due to an InternalServerError.oamazonka-sagemakerThe Amazon Web Services Identity and Access Management (IAM) role configured for the training job.oamazonka-sagemakerProvides detailed information about the state of the training job. For detailed information about the secondary status of the training job, see  StatusMessage! under SecondaryStatusTransition.SageMaker provides primary statuses and secondary statuses that apply to each of them:  InProgress- Starting - Starting the training job. Downloading5 - An optional stage for algorithms that support File training input mode. It indicates that data is being downloaded to the ML storage volumes.Training - Training is in progress. Uploading - Training is complete and the model artifacts are being uploaded to the S3 location. Completed-  Completed" - The training job has completed.Failed- Failed - The training job has failed. The reason for the failure is returned in the  FailureReason field of DescribeTrainingJobResponse.Stopped- MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.Stopped - The training job has stopped.Stopping- Stopping - Stopping the training job.Valid values for SecondaryStatus are subject to change.6We no longer support the following secondary statuses: LaunchingMLInstances PreparingTrainingStack DownloadingTrainingImageoamazonka-sagemakerA history of all of the secondary statuses that the training job has transitioned through.oamazonka-sagemakerSpecifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.1To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.oamazonka-sagemakerAn array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.oamazonka-sagemakerUndocumented member.oamazonka-sagemakerIndicates the time when the training job ends on training instances. You are billed for the time interval between the value of TrainingStartTime and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when SageMaker detects a job failure.oamazonka-sagemaker3The Amazon Resource Name (ARN) of the training job.oamazonka-sagemakerThe name of the training job.oamazonka-sagemakerThe status of the training job.Training job statuses are: InProgress - The training is in progress. Completed" - The training job has completed.Failed - The training job has failed. To see the reason for the failure, see the  FailureReason! field in the response to a DescribeTrainingJobResponse call.Stopping - The training job is stopping.Stopped - The training job has stopped.#For more detailed information, see SecondaryStatus.oamazonka-sagemakerIndicates the time when the training job starts on training instances. You are billed for the time interval between this time and the value of TrainingEndTime. The start time in CloudWatch Logs might be later than this time. The difference is due to the time it takes to download the training data and to the size of the training container.oamazonka-sagemakerThe training time in seconds.oamazonka-sagemakerThe Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.oamazonka-sagemakerA VpcConfig object that specifies the VPC that this training job has access to. For more information, see  >https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html>Protect Training Jobs by Using an Amazon Virtual Private Cloud.oooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooo(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';oamazonka-sagemakerNetworking options for a job, such as network traffic encryption between containers, whether to allow inbound and outbound network calls to and from containers, and the VPC subnets and security groups to use for VPC-enabled jobs.See: o smart constructor.oamazonka-sagemakerWhether to encrypt all communications between distributed processing jobs. Choose True to encrypt communications. Encryption provides greater security for distributed processing jobs, but the processing might take longer.oamazonka-sagemakerWhether to allow inbound and outbound network calls to and from the containers used for the processing job.oamazonka-sagemakerCreate a value of o" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:o, o - Whether to encrypt all communications between distributed processing jobs. Choose True to encrypt communications. Encryption provides greater security for distributed processing jobs, but the processing might take longer.o, o - Whether to allow inbound and outbound network calls to and from the containers used for the processing job.o, o - Undocumented member.oamazonka-sagemakerWhether to encrypt all communications between distributed processing jobs. Choose True to encrypt communications. Encryption provides greater security for distributed processing jobs, but the processing might take longer.oamazonka-sagemakerWhether to allow inbound and outbound network calls to and from the containers used for the processing job.oamazonka-sagemakerUndocumented member. ooooooooo ooooooooo(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';A(oamazonka-sagemakerAn Amazon SageMaker processing job that is used to analyze data and evaluate models. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/processing-job.html Process Data and Evaluate Models.See: p smart constructor.oamazonka-sagemakerThe Amazon Resource Name (ARN) of the AutoML job associated with this processing job.oamazonka-sagemaker(The time the processing job was created.oamazonka-sagemaker7Sets the environment variables in the Docker container.oamazonka-sagemakerA string, up to one KB in size, that contains metadata from the processing container when the processing job exits.oamazonka-sagemakerA string, up to one KB in size, that contains the reason a processing job failed, if it failed.oamazonka-sagemaker.The time the processing job was last modified.oamazonka-sagemakerThe ARN of a monitoring schedule for an endpoint associated with this processing job.oamazonka-sagemaker'The time that the processing job ended.oamazonka-sagemaker4List of input configurations for the processing job.oamazonka-sagemakerThe ARN of the processing job.oamazonka-sagemakerThe name of the processing job.oamazonka-sagemaker!The status of the processing job.oamazonka-sagemaker)The time that the processing job started.oamazonka-sagemaker6The ARN of the role used to create the processing job.oamazonka-sagemaker8An array of key-value pairs. For more information, see  https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURLUsing Cost Allocation Tags in the :Amazon Web Services Billing and Cost Management User Guide.pamazonka-sagemakerThe ARN of the training job associated with this processing job.pamazonka-sagemakerCreate a value of o" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:o, p - Undocumented member.o, p - The Amazon Resource Name (ARN) of the AutoML job associated with this processing job.o, p+ - The time the processing job was created.o, p: - Sets the environment variables in the Docker container.o, p - A string, up to one KB in size, that contains metadata from the processing container when the processing job exits.o, p - Undocumented member.o, p - A string, up to one KB in size, that contains the reason a processing job failed, if it failed.o, p1 - The time the processing job was last modified.o, p - The ARN of a monitoring schedule for an endpoint associated with this processing job.o, p - Undocumented member.o, p* - The time that the processing job ended.o, p7 - List of input configurations for the processing job.o, p! - The ARN of the processing job.o, p" - The name of the processing job.o, p$ - The status of the processing job.o, p - Undocumented member.o, p - Undocumented member.o, p, - The time that the processing job started.o, p9 - The ARN of the role used to create the processing job.o, p - Undocumented member.o, p; - An array of key-value pairs. For more information, see  https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURLUsing Cost Allocation Tags in the :Amazon Web Services Billing and Cost Management User Guide.p, p - The ARN of the training job associated with this processing job.pamazonka-sagemakerUndocumented member.pamazonka-sagemakerThe Amazon Resource Name (ARN) of the AutoML job associated with this processing job.pamazonka-sagemaker(The time the processing job was created.pamazonka-sagemaker7Sets the environment variables in the Docker container.pamazonka-sagemakerA string, up to one KB in size, that contains metadata from the processing container when the processing job exits.pamazonka-sagemakerUndocumented member.pamazonka-sagemakerA string, up to one KB in size, that contains the reason a processing job failed, if it failed.pamazonka-sagemaker.The time the processing job was last modified.pamazonka-sagemakerThe ARN of a monitoring schedule for an endpoint associated with this processing job.pamazonka-sagemakerUndocumented member.pamazonka-sagemaker'The time that the processing job ended.pamazonka-sagemaker4List of input configurations for the processing job.pamazonka-sagemakerThe ARN of the processing job.pamazonka-sagemakerThe name of the processing job.pamazonka-sagemaker!The status of the processing job.pamazonka-sagemakerUndocumented member.pamazonka-sagemakerUndocumented member.pamazonka-sagemaker)The time that the processing job started.pamazonka-sagemaker6The ARN of the role used to create the processing job.pamazonka-sagemakerUndocumented member.pamazonka-sagemaker8An array of key-value pairs. For more information, see  https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURLUsing Cost Allocation Tags in the :Amazon Web Services Billing and Cost Management User Guide.pamazonka-sagemakerThe ARN of the training job associated with this processing job./oooooooopoooooooooooooooppppppppppppppppppppppp/oooooooopoooooooooooooooppppppppppppppppppppppp(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';% pamazonka-sagemakerDetailed information about the source of a trial component. Either  ProcessingJob or  TrainingJob is returned.See: p smart constructor.pamazonka-sagemakerInformation about a processing job that's the source of a trial component.pamazonka-sagemaker-The Amazon Resource Name (ARN) of the source.pamazonka-sagemakerInformation about a training job that's the source of a trial component.pamazonka-sagemakerInformation about a transform job that's the source of a trial component.pamazonka-sagemakerCreate a value of p" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:p, p - Information about a processing job that's the source of a trial component.p, p0 - The Amazon Resource Name (ARN) of the source.p, p - Information about a training job that's the source of a trial component.p, p - Information about a transform job that's the source of a trial component.pamazonka-sagemakerInformation about a processing job that's the source of a trial component.pamazonka-sagemaker-The Amazon Resource Name (ARN) of the source.pamazonka-sagemakerInformation about a training job that's the source of a trial component.pamazonka-sagemakerInformation about a transform job that's the source of a trial component. ppppppppppp ppppppppppp(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';,)pamazonka-sagemakerThe properties of a trial component as returned by the Search API.See: p smart constructor.pamazonka-sagemaker Who created the trial component.pamazonka-sagemakerWhen the component was created.pamazonka-sagemaker+The name of the component as displayed. If  DisplayName isn't specified, TrialComponentName is displayed.pamazonka-sagemakerWhen the component ended.pamazonka-sagemaker%The input artifacts of the component.pamazonka-sagemaker%When the component was last modified.pamazonka-sagemaker=The Amazon Resource Name (ARN) of the lineage group resource.pamazonka-sagemakerThe metrics for the component.pamazonka-sagemaker&The output artifacts of the component.pamazonka-sagemaker%The hyperparameters of the component.pamazonka-sagemakerAn array of the parents of the component. A parent is a trial the component is associated with and the experiment the trial is part of. A component might not have any parents.pamazonka-sagemakerThe name of the experiment run.pamazonka-sagemakerThe Amazon Resource Name (ARN) and job type of the source of the component.pamazonka-sagemaker'Details of the source of the component.pamazonka-sagemakerWhen the component started.pamazonka-sagemakerThe list of tags that are associated with the component. You can use Search API to search on the tags.pamazonka-sagemaker6The Amazon Resource Name (ARN) of the trial component.pamazonka-sagemaker The name of the trial component.pamazonka-sagemakerCreate a value of p" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:p, p# - Who created the trial component.p, p" - When the component was created.p, p. - The name of the component as displayed. If  DisplayName isn't specified, TrialComponentName is displayed.p, p - When the component ended.p, p( - The input artifacts of the component.p, p - Undocumented member.p, p( - When the component was last modified.p, p - The Amazon Resource Name (ARN) of the lineage group resource.p, p - Undocumented member.p, p! - The metrics for the component.p, p) - The output artifacts of the component.p, p( - The hyperparameters of the component.p, p - An array of the parents of the component. A parent is a trial the component is associated with and the experiment the trial is part of. A component might not have any parents.p, p" - The name of the experiment run.p, p - The Amazon Resource Name (ARN) and job type of the source of the component.p, p* - Details of the source of the component.p, p - When the component started.p, p - Undocumented member.p, p - The list of tags that are associated with the component. You can use Search API to search on the tags.p, p9 - The Amazon Resource Name (ARN) of the trial component.p, p# - The name of the trial component.pamazonka-sagemaker Who created the trial component.pamazonka-sagemakerWhen the component was created.pamazonka-sagemaker+The name of the component as displayed. If  DisplayName isn't specified, TrialComponentName is displayed.pamazonka-sagemakerWhen the component ended.pamazonka-sagemaker%The input artifacts of the component.pamazonka-sagemakerUndocumented member.pamazonka-sagemaker%When the component was last modified.pamazonka-sagemaker=The Amazon Resource Name (ARN) of the lineage group resource.pamazonka-sagemakerUndocumented member.pamazonka-sagemakerThe metrics for the component.pamazonka-sagemaker&The output artifacts of the component.pamazonka-sagemaker%The hyperparameters of the component.pamazonka-sagemakerAn array of the parents of the component. A parent is a trial the component is associated with and the experiment the trial is part of. A component might not have any parents.pamazonka-sagemakerThe name of the experiment run.pamazonka-sagemakerThe Amazon Resource Name (ARN) and job type of the source of the component.pamazonka-sagemaker'Details of the source of the component.pamazonka-sagemakerWhen the component started.pamazonka-sagemakerUndocumented member.pamazonka-sagemakerThe list of tags that are associated with the component. You can use Search API to search on the tags.pamazonka-sagemaker6The Amazon Resource Name (ARN) of the trial component.pamazonka-sagemaker The name of the trial component.-ppppppppppppppppppppppppppppppppppppppppppppp-ppppppppppppppppppppppppppppppppppppppppppppp(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';=pamazonka-sagemakerDefines the monitoring job.See: p smart constructor.pamazonka-sagemakerBaseline configuration used to validate that the data conforms to the specified constraints and statisticspamazonka-sagemaker7Sets the environment variables in the Docker container.pamazonka-sagemaker3Specifies networking options for an monitoring job.pamazonka-sagemakerSpecifies a time limit for how long the monitoring job is allowed to run.pamazonka-sagemakerThe array of inputs for the monitoring job. Currently we support monitoring an Amazon SageMaker Endpoint.pamazonka-sagemakerThe array of outputs from the monitoring job to be uploaded to Amazon Simple Storage Service (Amazon S3).pamazonka-sagemakerIdentifies the resources, ML compute instances, and ML storage volumes to deploy for a monitoring job. In distributed processing, you specify more than one instance.pamazonka-sagemakerConfigures the monitoring job to run a specified Docker container image.pamazonka-sagemakerThe Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.pamazonka-sagemakerCreate a value of p" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:p, p - Baseline configuration used to validate that the data conforms to the specified constraints and statisticsp, p: - Sets the environment variables in the Docker container.p, p6 - Specifies networking options for an monitoring job.p, p - Specifies a time limit for how long the monitoring job is allowed to run.p, p - The array of inputs for the monitoring job. Currently we support monitoring an Amazon SageMaker Endpoint.p, p - The array of outputs from the monitoring job to be uploaded to Amazon Simple Storage Service (Amazon S3).p, p - Identifies the resources, ML compute instances, and ML storage volumes to deploy for a monitoring job. In distributed processing, you specify more than one instance.p, p - Configures the monitoring job to run a specified Docker container image.p, p - The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.pamazonka-sagemakerBaseline configuration used to validate that the data conforms to the specified constraints and statisticspamazonka-sagemaker7Sets the environment variables in the Docker container.pamazonka-sagemaker3Specifies networking options for an monitoring job.pamazonka-sagemakerSpecifies a time limit for how long the monitoring job is allowed to run.pamazonka-sagemakerThe array of inputs for the monitoring job. Currently we support monitoring an Amazon SageMaker Endpoint.pamazonka-sagemakerThe array of outputs from the monitoring job to be uploaded to Amazon Simple Storage Service (Amazon S3).pamazonka-sagemakerIdentifies the resources, ML compute instances, and ML storage volumes to deploy for a monitoring job. In distributed processing, you specify more than one instance.pamazonka-sagemakerConfigures the monitoring job to run a specified Docker container image.pamazonka-sagemakerThe Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.pamazonka-sagemakerpamazonka-sagemakerpamazonka-sagemakerpamazonka-sagemakerpamazonka-sagemakerppppppppppppppppppppppppppppppppppppppppppp(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';C1 qamazonka-sagemakerConfigures the monitoring schedule and defines the monitoring job.See: q smart constructor.qamazonka-sagemakerDefines the monitoring job.qamazonka-sagemaker6The name of the monitoring job definition to schedule.qamazonka-sagemaker6The type of the monitoring job definition to schedule.qamazonka-sagemaker#Configures the monitoring schedule.qamazonka-sagemakerCreate a value of q" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:q, q - Defines the monitoring job.q, q9 - The name of the monitoring job definition to schedule.q, q9 - The type of the monitoring job definition to schedule.q, q& - Configures the monitoring schedule.qamazonka-sagemakerDefines the monitoring job.qamazonka-sagemaker6The name of the monitoring job definition to schedule.qamazonka-sagemaker6The type of the monitoring job definition to schedule.qamazonka-sagemaker#Configures the monitoring schedule. qqqqqqqqqqq qqqqqqqqqqq(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';Tqamazonka-sagemakerA schedule for a model monitoring job. For information about model monitor, see  https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor.htmlAmazon SageMaker Model Monitor.See: q smart constructor.qamazonka-sagemaker2The time that the monitoring schedule was created.qamazonka-sagemaker2The endpoint that hosts the model being monitored.qamazonka-sagemaker8If the monitoring schedule failed, the reason it failed.qamazonka-sagemaker2The last time the monitoring schedule was changed.qamazonka-sagemaker:The Amazon Resource Name (ARN) of the monitoring schedule.qamazonka-sagemaker$The name of the monitoring schedule.qamazonka-sagemakerThe status of the monitoring schedule. This can be one of the following values.PENDING) - The schedule is pending being created.FAILED - The schedule failed. SCHEDULED) - The schedule was successfully created.STOPPED - The schedule was stopped.qamazonka-sagemaker6The type of the monitoring job definition to schedule.qamazonka-sagemakerA list of the tags associated with the monitoring schedlue. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services resources in the +Amazon Web Services General Reference Guide.qamazonka-sagemakerCreate a value of q" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:q, q5 - The time that the monitoring schedule was created.q, q5 - The endpoint that hosts the model being monitored.q, q; - If the monitoring schedule failed, the reason it failed.q, q5 - The last time the monitoring schedule was changed.q, q - Undocumented member.q, q= - The Amazon Resource Name (ARN) of the monitoring schedule.q, q - Undocumented member.q, q' - The name of the monitoring schedule.q, q - The status of the monitoring schedule. This can be one of the following values.PENDING) - The schedule is pending being created.FAILED - The schedule failed. SCHEDULED) - The schedule was successfully created.STOPPED - The schedule was stopped.q, q9 - The type of the monitoring job definition to schedule.q, q - A list of the tags associated with the monitoring schedlue. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services resources in the +Amazon Web Services General Reference Guide.qamazonka-sagemaker2The time that the monitoring schedule was created.qamazonka-sagemaker2The endpoint that hosts the model being monitored.qamazonka-sagemaker8If the monitoring schedule failed, the reason it failed.qamazonka-sagemaker2The last time the monitoring schedule was changed.qamazonka-sagemakerUndocumented member.qamazonka-sagemaker:The Amazon Resource Name (ARN) of the monitoring schedule.qamazonka-sagemakerUndocumented member.qamazonka-sagemaker$The name of the monitoring schedule.qamazonka-sagemakerThe status of the monitoring schedule. This can be one of the following values.PENDING) - The schedule is pending being created.FAILED - The schedule failed. SCHEDULED) - The schedule was successfully created.STOPPED - The schedule was stopped.qamazonka-sagemaker6The type of the monitoring job definition to schedule.qamazonka-sagemakerA list of the tags associated with the monitoring schedlue. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services resources in the +Amazon Web Services General Reference Guide.qqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqq(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';fqamazonka-sagemaker*A hosted endpoint for real-time inference.See: q smart constructor.qamazonka-sagemaker-If the endpoint failed, the reason it failed.qamazonka-sagemakerA list of monitoring schedules for the endpoint. For information about model monitoring, see  https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor.htmlAmazon SageMaker Model Monitor.qamazonka-sagemakerA list of the production variants hosted on the endpoint. Each production variant is a model.qamazonka-sagemakerA list of the shadow variants hosted on the endpoint. Each shadow variant is a model in shadow mode with production traffic replicated from the proudction variant.qamazonka-sagemakerA list of the tags associated with the endpoint. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services resources in the +Amazon Web Services General Reference Guide.qamazonka-sagemakerThe name of the endpoint.qamazonka-sagemaker/The Amazon Resource Name (ARN) of the endpoint.qamazonka-sagemaker8The endpoint configuration associated with the endpoint.qamazonka-sagemakerThe status of the endpoint.qamazonka-sagemaker'The time that the endpoint was created.qamazonka-sagemaker(The last time the endpoint was modified.qamazonka-sagemakerCreate a value of q" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:q, q - Undocumented member.q, q0 - If the endpoint failed, the reason it failed.q, q - A list of monitoring schedules for the endpoint. For information about model monitoring, see  https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor.htmlAmazon SageMaker Model Monitor.q, q - A list of the production variants hosted on the endpoint. Each production variant is a model.q, q - A list of the shadow variants hosted on the endpoint. Each shadow variant is a model in shadow mode with production traffic replicated from the proudction variant.q, q - A list of the tags associated with the endpoint. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services resources in the +Amazon Web Services General Reference Guide.q, q - The name of the endpoint.q, q2 - The Amazon Resource Name (ARN) of the endpoint.q, q; - The endpoint configuration associated with the endpoint.q, q - The status of the endpoint.q, q* - The time that the endpoint was created.q, q+ - The last time the endpoint was modified.qamazonka-sagemakerUndocumented member.qamazonka-sagemaker-If the endpoint failed, the reason it failed.qamazonka-sagemakerA list of monitoring schedules for the endpoint. For information about model monitoring, see  https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor.htmlAmazon SageMaker Model Monitor.qamazonka-sagemakerA list of the production variants hosted on the endpoint. Each production variant is a model.qamazonka-sagemakerA list of the shadow variants hosted on the endpoint. Each shadow variant is a model in shadow mode with production traffic replicated from the proudction variant.qamazonka-sagemakerA list of the tags associated with the endpoint. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services resources in the +Amazon Web Services General Reference Guide.qamazonka-sagemakerThe name of the endpoint.qamazonka-sagemaker/The Amazon Resource Name (ARN) of the endpoint.qamazonka-sagemaker8The endpoint configuration associated with the endpoint.qamazonka-sagemakerThe status of the endpoint.qamazonka-sagemaker'The time that the endpoint was created.qamazonka-sagemaker(The last time the endpoint was modified.qamazonka-sagemakerqamazonka-sagemakerqamazonka-sagemakerqamazonka-sagemakerqamazonka-sagemakerqamazonka-sagemakerqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqq(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';rqamazonka-sagemakerA monitoring schedule for a model displayed in the Amazon SageMaker Model Dashboard.See: q smart constructor.qamazonka-sagemakerA timestamp that indicates when the monitoring schedule was created.qamazonka-sagemaker The endpoint which is monitored.qamazonka-sagemaker0If a monitoring job failed, provides the reason.qamazonka-sagemakerA timestamp that indicates when the monitoring schedule was last updated.qamazonka-sagemakerA JSON array where each element is a summary for a monitoring alert.qamazonka-sagemaker8The Amazon Resource Name (ARN) of a monitoring schedule.qamazonka-sagemaker"The name of a monitoring schedule.qamazonka-sagemaker&The status of the monitoring schedule.qamazonka-sagemaker$The monitor type of a model monitor.qamazonka-sagemakerCreate a value of q" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:q, q - A timestamp that indicates when the monitoring schedule was created.q, q# - The endpoint which is monitored.q, q3 - If a monitoring job failed, provides the reason.q, q - A timestamp that indicates when the monitoring schedule was last updated.q, q - Undocumented member.q, q - A JSON array where each element is a summary for a monitoring alert.q, q; - The Amazon Resource Name (ARN) of a monitoring schedule.q, q - Undocumented member.q, q% - The name of a monitoring schedule.q, q) - The status of the monitoring schedule.q, q' - The monitor type of a model monitor.qamazonka-sagemakerA timestamp that indicates when the monitoring schedule was created.qamazonka-sagemaker The endpoint which is monitored.qamazonka-sagemaker0If a monitoring job failed, provides the reason.qamazonka-sagemakerA timestamp that indicates when the monitoring schedule was last updated.qamazonka-sagemakerUndocumented member.qamazonka-sagemakerA JSON array where each element is a summary for a monitoring alert.qamazonka-sagemaker8The Amazon Resource Name (ARN) of a monitoring schedule.qamazonka-sagemakerUndocumented member.qamazonka-sagemaker"The name of a monitoring schedule.qamazonka-sagemaker&The status of the monitoring schedule.qamazonka-sagemaker$The monitor type of a model monitor.qqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqq(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';zuqamazonka-sagemaker4The networking configuration for the monitoring job.See: q smart constructor.qamazonka-sagemakerWhether to encrypt all communications between the instances used for the monitoring jobs. Choose True to encrypt communications. Encryption provides greater security for distributed jobs, but the processing might take longer.qamazonka-sagemakerWhether to allow inbound and outbound network calls to and from the containers used for the monitoring job.qamazonka-sagemakerCreate a value of q" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:q, q - Whether to encrypt all communications between the instances used for the monitoring jobs. Choose True to encrypt communications. Encryption provides greater security for distributed jobs, but the processing might take longer.q, q - Whether to allow inbound and outbound network calls to and from the containers used for the monitoring job.q, q - Undocumented member.qamazonka-sagemakerWhether to encrypt all communications between the instances used for the monitoring jobs. Choose True to encrypt communications. Encryption provides greater security for distributed jobs, but the processing might take longer.qamazonka-sagemakerWhether to allow inbound and outbound network calls to and from the containers used for the monitoring job.qamazonka-sagemakerUndocumented member. qqqqqqqqq qqqqqqqqq(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';Pramazonka-sagemaker8The properties of a model as returned by the Search API.See: r smart constructor.ramazonka-sagemaker)The containers in the inference pipeline.ramazonka-sagemaker6A timestamp that indicates when the model was created.ramazonka-sagemakerIsolates the model container. No inbound or outbound network calls can be made to or from the model container.ramazonka-sagemakerThe Amazon Resource Name (ARN) of the IAM role that you specified for the model.ramazonka-sagemaker,The Amazon Resource Name (ARN) of the model.ramazonka-sagemakerThe name of the model.ramazonka-sagemakerA list of key-value pairs associated with the model. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services resources in the +Amazon Web Services General Reference Guide.ramazonka-sagemakerCreate a value of r" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:r, r, - The containers in the inference pipeline.r, r9 - A timestamp that indicates when the model was created.r, r - Isolates the model container. No inbound or outbound network calls can be made to or from the model container.r, r - The Amazon Resource Name (ARN) of the IAM role that you specified for the model.r, r - Undocumented member.r, r/ - The Amazon Resource Name (ARN) of the model.r, r - The name of the model.r, r - Undocumented member.r, r - A list of key-value pairs associated with the model. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services resources in the +Amazon Web Services General Reference Guide.r, r - Undocumented member.ramazonka-sagemaker)The containers in the inference pipeline.ramazonka-sagemaker6A timestamp that indicates when the model was created.ramazonka-sagemakerIsolates the model container. No inbound or outbound network calls can be made to or from the model container.ramazonka-sagemakerThe Amazon Resource Name (ARN) of the IAM role that you specified for the model.ramazonka-sagemakerUndocumented member.ramazonka-sagemaker,The Amazon Resource Name (ARN) of the model.ramazonka-sagemakerThe name of the model.ramazonka-sagemakerUndocumented member.ramazonka-sagemakerA list of key-value pairs associated with the model. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services resources in the +Amazon Web Services General Reference Guide.ramazonka-sagemakerUndocumented member.rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';[ ramazonka-sagemaker:A model displayed in the Amazon SageMaker Model Dashboard.See: r smart constructor.ramazonka-sagemaker The endpoints that host a model.ramazonka-sagemaker)A model displayed in the Model Dashboard.ramazonka-sagemakerThe model card for a model.ramazonka-sagemaker%The monitoring schedules for a model.ramazonka-sagemakerCreate a value of r" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:r, r# - The endpoints that host a model.r, r - Undocumented member.r, r, - A model displayed in the Model Dashboard.r, r - The model card for a model.r, r( - The monitoring schedules for a model.ramazonka-sagemaker The endpoints that host a model.ramazonka-sagemakerUndocumented member.ramazonka-sagemaker)A model displayed in the Model Dashboard.ramazonka-sagemakerThe model card for a model.ramazonka-sagemaker%The monitoring schedules for a model. rrrrrrrrrrrrr rrrrrrrrrrrrr(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';ramazonka-sagemakerConfigure encryption on the storage volume attached to the ML compute instance used to run automated data labeling model training and inference.See: r smart constructor.ramazonka-sagemakerThe Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the training and inference jobs used for automated data labeling.You can only specify a VolumeKmsKeyId when you create a labeling job with automated data labeling enabled using the API operation CreateLabelingJob. You cannot specify an Amazon Web Services KMS key to encrypt the storage volume used for automated data labeling model training and inference when you create a labeling job using the console. To learn more, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-security.html)Output Data and Storage Volume Encryption.The VolumeKmsKeyId% can be any of the following formats: KMS Key ID &"1234abcd-12ab-34cd-56ef-1234567890ab"'Amazon Resource Name (ARN) of a KMS Key "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"ramazonka-sagemakerCreate a value of r" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:r, r - The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the training and inference jobs used for automated data labeling.You can only specify a VolumeKmsKeyId when you create a labeling job with automated data labeling enabled using the API operation CreateLabelingJob. You cannot specify an Amazon Web Services KMS key to encrypt the storage volume used for automated data labeling model training and inference when you create a labeling job using the console. To learn more, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-security.html)Output Data and Storage Volume Encryption.The VolumeKmsKeyId% can be any of the following formats: KMS Key ID &"1234abcd-12ab-34cd-56ef-1234567890ab"'Amazon Resource Name (ARN) of a KMS Key "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"r, r - Undocumented member.ramazonka-sagemakerThe Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the training and inference jobs used for automated data labeling.You can only specify a VolumeKmsKeyId when you create a labeling job with automated data labeling enabled using the API operation CreateLabelingJob. You cannot specify an Amazon Web Services KMS key to encrypt the storage volume used for automated data labeling model training and inference when you create a labeling job using the console. To learn more, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-security.html)Output Data and Storage Volume Encryption.The VolumeKmsKeyId% can be any of the following formats: KMS Key ID &"1234abcd-12ab-34cd-56ef-1234567890ab"'Amazon Resource Name (ARN) of a KMS Key "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"ramazonka-sagemakerUndocumented member.rrrrrrrrrrrrrr(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';7ramazonka-sagemakerProvides configuration information for auto-labeling of your data objects. A LabelingJobAlgorithmsConfig8 object must be supplied in order to use auto-labeling.See: r smart constructor.ramazonka-sagemakerAt the end of an auto-label job Ground Truth sends the Amazon Resource Name (ARN) of the final model used for auto-labeling. You can use this model as the starting point for subsequent similar jobs by providing the ARN of the model here.ramazonka-sagemaker6Provides configuration information for a labeling job.ramazonka-sagemakerSpecifies the Amazon Resource Name (ARN) of the algorithm used for auto-labeling. You must select one of the following ARNs:Image classificationarn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/image-classificationText classificationarn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/text-classificationObject detectionarn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/object-detectionSemantic Segmentationarn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/semantic-segmentationramazonka-sagemakerCreate a value of r" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:r, r - At the end of an auto-label job Ground Truth sends the Amazon Resource Name (ARN) of the final model used for auto-labeling. You can use this model as the starting point for subsequent similar jobs by providing the ARN of the model here.r, r9 - Provides configuration information for a labeling job.r, r - Specifies the Amazon Resource Name (ARN) of the algorithm used for auto-labeling. You must select one of the following ARNs:Image classificationarn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/image-classificationText classificationarn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/text-classificationObject detectionarn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/object-detectionSemantic Segmentationarn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/semantic-segmentationramazonka-sagemakerAt the end of an auto-label job Ground Truth sends the Amazon Resource Name (ARN) of the final model used for auto-labeling. You can use this model as the starting point for subsequent similar jobs by providing the ARN of the model here.ramazonka-sagemaker6Provides configuration information for a labeling job.ramazonka-sagemakerSpecifies the Amazon Resource Name (ARN) of the algorithm used for auto-labeling. You must select one of the following ARNs:Image classificationarn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/image-classificationText classificationarn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/text-classificationObject detectionarn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/object-detectionSemantic Segmentationarn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/semantic-segmentationramazonka-sagemakerr rrrrrrrrr rrrrrrrrr(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';چ!ramazonka-sagemakerDefines the training jobs launched by a hyperparameter tuning job.See: r smart constructor.ramazonka-sagemakerThe job definition name.ramazonka-sagemakerTo encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training.ramazonka-sagemaker?A Boolean indicating whether managed spot training is enabled (True ) or not (False).ramazonka-sagemakerIsolates the training container. No inbound or outbound network calls can be made, except for calls between peers within a training cluster for distributed training. If network isolation is used for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.ramazonka-sagemakerThe configuration for the hyperparameter tuning resources, including the compute instances and storage volumes, used for training jobs launched by the tuning job. By default, storage volumes hold model artifacts and incremental states. Choose File for TrainingInputMode in the AlgorithmSpecification parameter to additionally store training data in the storage volume (optional).ramazonka-sagemakerAn array of Channel objects that specify the input for the training jobs that the tuning job launches.ramazonka-sagemakerThe resources, including the compute instances and storage volumes, to use for the training jobs that the tuning job launches.Storage volumes store model artifacts and incremental states. Training algorithms might also use storage volumes for scratch space. If you want SageMaker to use the storage volume to store the training data, choose File as the TrainingInputMode in the algorithm specification. For distributed training algorithms, specify an instance count greater than 1.If you want to use hyperparameter optimization with instance type flexibility, use "HyperParameterTuningResourceConfig instead.ramazonka-sagemakerThe number of times to retry the job when the job fails due to an InternalServerError.ramazonka-sagemakerSpecifies the values of hyperparameters that do not change for the tuning job.ramazonka-sagemakerThe VpcConfig object that specifies the VPC that you want the training jobs that this hyperparameter tuning job launches to connect to. Control access to and from your training container by configuring the VPC. For more information, see  >https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html>Protect Training Jobs by Using an Amazon Virtual Private Cloud.ramazonka-sagemakerThe HyperParameterAlgorithmSpecification object that specifies the resource algorithm to use for the training jobs that the tuning job launches.ramazonka-sagemakerThe Amazon Resource Name (ARN) of the IAM role associated with the training jobs that the tuning job launches.ramazonka-sagemakerSpecifies the path to the Amazon S3 bucket where you store model artifacts from the training jobs that the tuning job launches.ramazonka-sagemakerSpecifies a limit to how long a model hyperparameter training job can run. It also specifies how long a managed spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.ramazonka-sagemakerCreate a value of r" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:r, r - Undocumented member.r, r - The job definition name.r, r - To encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training.r, r - A Boolean indicating whether managed spot training is enabled (True ) or not (False).r, r - Isolates the training container. No inbound or outbound network calls can be made, except for calls between peers within a training cluster for distributed training. If network isolation is used for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.r, r - Undocumented member.r, r - The configuration for the hyperparameter tuning resources, including the compute instances and storage volumes, used for training jobs launched by the tuning job. By default, storage volumes hold model artifacts and incremental states. Choose File for TrainingInputMode in the AlgorithmSpecification parameter to additionally store training data in the storage volume (optional).r, r - An array of Channel objects that specify the input for the training jobs that the tuning job launches.r, r - The resources, including the compute instances and storage volumes, to use for the training jobs that the tuning job launches.Storage volumes store model artifacts and incremental states. Training algorithms might also use storage volumes for scratch space. If you want SageMaker to use the storage volume to store the training data, choose File as the TrainingInputMode in the algorithm specification. For distributed training algorithms, specify an instance count greater than 1.If you want to use hyperparameter optimization with instance type flexibility, use "HyperParameterTuningResourceConfig instead.r, r - The number of times to retry the job when the job fails due to an InternalServerError.r, r - Specifies the values of hyperparameters that do not change for the tuning job.r, r - Undocumented member.r, r - The VpcConfig object that specifies the VPC that you want the training jobs that this hyperparameter tuning job launches to connect to. Control access to and from your training container by configuring the VPC. For more information, see  >https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html>Protect Training Jobs by Using an Amazon Virtual Private Cloud.r, r - The HyperParameterAlgorithmSpecification object that specifies the resource algorithm to use for the training jobs that the tuning job launches.r, r - The Amazon Resource Name (ARN) of the IAM role associated with the training jobs that the tuning job launches.r, r - Specifies the path to the Amazon S3 bucket where you store model artifacts from the training jobs that the tuning job launches.r, r - Specifies a limit to how long a model hyperparameter training job can run. It also specifies how long a managed spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.ramazonka-sagemakerUndocumented member.ramazonka-sagemakerThe job definition name.ramazonka-sagemakerTo encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training.ramazonka-sagemaker?A Boolean indicating whether managed spot training is enabled (True ) or not (False).ramazonka-sagemakerIsolates the training container. No inbound or outbound network calls can be made, except for calls between peers within a training cluster for distributed training. If network isolation is used for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.ramazonka-sagemakerUndocumented member.ramazonka-sagemakerThe configuration for the hyperparameter tuning resources, including the compute instances and storage volumes, used for training jobs launched by the tuning job. By default, storage volumes hold model artifacts and incremental states. Choose File for TrainingInputMode in the AlgorithmSpecification parameter to additionally store training data in the storage volume (optional).ramazonka-sagemakerAn array of Channel objects that specify the input for the training jobs that the tuning job launches.ramazonka-sagemakerThe resources, including the compute instances and storage volumes, to use for the training jobs that the tuning job launches.Storage volumes store model artifacts and incremental states. Training algorithms might also use storage volumes for scratch space. If you want SageMaker to use the storage volume to store the training data, choose File as the TrainingInputMode in the algorithm specification. For distributed training algorithms, specify an instance count greater than 1.If you want to use hyperparameter optimization with instance type flexibility, use "HyperParameterTuningResourceConfig instead.ramazonka-sagemakerThe number of times to retry the job when the job fails due to an InternalServerError.ramazonka-sagemakerSpecifies the values of hyperparameters that do not change for the tuning job.ramazonka-sagemakerUndocumented member.ramazonka-sagemakerThe VpcConfig object that specifies the VPC that you want the training jobs that this hyperparameter tuning job launches to connect to. Control access to and from your training container by configuring the VPC. For more information, see  >https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html>Protect Training Jobs by Using an Amazon Virtual Private Cloud.ramazonka-sagemakerThe HyperParameterAlgorithmSpecification object that specifies the resource algorithm to use for the training jobs that the tuning job launches.ramazonka-sagemakerThe Amazon Resource Name (ARN) of the IAM role associated with the training jobs that the tuning job launches.ramazonka-sagemakerSpecifies the path to the Amazon S3 bucket where you store model artifacts from the training jobs that the tuning job launches.ramazonka-sagemakerSpecifies a limit to how long a model hyperparameter training job can run. It also specifies how long a managed spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.ramazonka-sagemakerramazonka-sagemakerramazonka-sagemakerramazonka-sagemakerr%rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr%rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';samazonka-sagemakerAn entity returned by the  https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_SearchRecord.html SearchRecord? API containing the properties of a hyperparameter tuning job.See: s smart constructor.samazonka-sagemaker6The time that a hyperparameter tuning job was created.samazonka-sagemakerThe error that was created when a hyperparameter tuning job failed.samazonka-sagemaker0The time that a hyperparameter tuning job ended.samazonka-sagemaker>The Amazon Resource Name (ARN) of a hyperparameter tuning job.samazonka-sagemaker(The name of a hyperparameter tuning job.samazonka-sagemaker*The status of a hyperparameter tuning job.samazonka-sagemakerhttps://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services resources.samazonka-sagemakerhttps://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services resources.s, s - Undocumented member.s, s? - The job definitions included in a hyperparameter tuning job.s, s - Undocumented member.s, s - Undocumented member.samazonka-sagemakerUndocumented member.samazonka-sagemaker6The time that a hyperparameter tuning job was created.samazonka-sagemakerThe error that was created when a hyperparameter tuning job failed.samazonka-sagemaker0The time that a hyperparameter tuning job ended.samazonka-sagemaker>The Amazon Resource Name (ARN) of a hyperparameter tuning job.samazonka-sagemakerUndocumented member.samazonka-sagemaker(The name of a hyperparameter tuning job.samazonka-sagemaker*The status of a hyperparameter tuning job.samazonka-sagemakerhttps://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services resources.samazonka-sagemakerUndocumented member.samazonka-sagemakerA single resource returned as part of the Search API response.See: s smart constructor.samazonka-sagemaker The properties of an experiment.samazonka-sagemaker9The feature metadata used to search through the features.samazonka-sagemaker.The properties of a hyperparameter tuning job.samazonka-sagemakerAn Amazon SageMaker Model Card that documents details about a machine learning model.samazonka-sagemakerThe properties of a project.samazonka-sagemaker!The properties of a training job.samazonka-sagemakerThe properties of a trial.samazonka-sagemaker$The properties of a trial component.samazonka-sagemakerCreate a value of s" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:s, s - Undocumented member.s, s# - The properties of an experiment.s, s - Undocumented member.s, s< - The feature metadata used to search through the features.s, s1 - The properties of a hyperparameter tuning job.s, s - Undocumented member.s, s - An Amazon SageMaker Model Card that documents details about a machine learning model.s, s - Undocumented member.s, s - Undocumented member.s, s - Undocumented member.s, s - Undocumented member.s, s - The properties of a project.s, s$ - The properties of a training job.s, s - The properties of a trial.s, s' - The properties of a trial component.samazonka-sagemakerUndocumented member.samazonka-sagemaker The properties of an experiment.samazonka-sagemakerUndocumented member.samazonka-sagemaker9The feature metadata used to search through the features.samazonka-sagemaker.The properties of a hyperparameter tuning job.samazonka-sagemakerUndocumented member.samazonka-sagemakerAn Amazon SageMaker Model Card that documents details about a machine learning model.samazonka-sagemakerUndocumented member.samazonka-sagemakerUndocumented member.samazonka-sagemakerUndocumented member.samazonka-sagemakerUndocumented member.samazonka-sagemakerThe properties of a project.samazonka-sagemaker!The properties of a training job.samazonka-sagemakerThe properties of a trial.samazonka-sagemaker$The properties of a trial component.!sssssssssssssssssssssssssssssssss!sssssssssssssssssssssssssssssssss(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';samazonka-sagemakerSecurity options.See: s smart constructor.samazonka-sagemaker?Whether to use traffic encryption between the container layers.samazonka-sagemaker$The key used to encrypt stored data.samazonka-sagemakerThe VPC configuration.samazonka-sagemakerCreate a value of s" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:s, s - Whether to use traffic encryption between the container layers.s, s' - The key used to encrypt stored data.s, s - The VPC configuration.samazonka-sagemaker?Whether to use traffic encryption between the container layers.samazonka-sagemaker$The key used to encrypt stored data.samazonka-sagemakerThe VPC configuration. sssssssss sssssssss(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&'; samazonka-sagemaker0A collection of settings used for an AutoML job.See: s smart constructor.samazonka-sagemakerThe configuration for generating a candidate for an AutoML job (optional).samazonka-sagemakerHow long an AutoML job is allowed to run, or how many candidates a job is allowed to generate.samazonka-sagemaker;The configuration for splitting the input training dataset.Type: AutoMLDataSplitConfigsamazonka-sagemakerThe method that Autopilot uses to train the data. You can either specify the mode manually or let Autopilot choose for you based on the dataset size by selecting AUTO. In AUTO mode, Autopilot chooses  ENSEMBLING( for datasets smaller than 100 MB, and HYPERPARAMETER_TUNING for larger ones.The  ENSEMBLING mode uses a multi-stack ensemble model to predict classification and regression tasks directly from your dataset. This machine learning mode combines several base models to produce an optimal predictive model. It then uses a stacking ensemble method to combine predictions from contributing members. A multi-stack ensemble model can provide better performance over a single model by combining the predictive capabilities of multiple models. See  https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-model-support-validation.html#autopilot-algorithm-suppprtAutopilot algorithm support( for a list of algorithms supported by  ENSEMBLING mode.The HYPERPARAMETER_TUNING (HPO) mode uses the best hyperparameters to train the best version of a model. HPO will automatically select an algorithm for the type of problem you want to solve. Then HPO finds the best hyperparameters according to your objective metric. See  https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-model-support-validation.html#autopilot-algorithm-suppprtAutopilot algorithm support( for a list of algorithms supported by HYPERPARAMETER_TUNING mode.samazonka-sagemakerThe security configuration for traffic encryption or Amazon VPC settings.samazonka-sagemakerCreate a value of s" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:s, s - The configuration for generating a candidate for an AutoML job (optional).s, s - How long an AutoML job is allowed to run, or how many candidates a job is allowed to generate.s, s> - The configuration for splitting the input training dataset.Type: AutoMLDataSplitConfigs, s - The method that Autopilot uses to train the data. You can either specify the mode manually or let Autopilot choose for you based on the dataset size by selecting AUTO. In AUTO mode, Autopilot chooses  ENSEMBLING( for datasets smaller than 100 MB, and HYPERPARAMETER_TUNING for larger ones.The  ENSEMBLING mode uses a multi-stack ensemble model to predict classification and regression tasks directly from your dataset. This machine learning mode combines several base models to produce an optimal predictive model. It then uses a stacking ensemble method to combine predictions from contributing members. A multi-stack ensemble model can provide better performance over a single model by combining the predictive capabilities of multiple models. See  https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-model-support-validation.html#autopilot-algorithm-suppprtAutopilot algorithm support( for a list of algorithms supported by  ENSEMBLING mode.The HYPERPARAMETER_TUNING (HPO) mode uses the best hyperparameters to train the best version of a model. HPO will automatically select an algorithm for the type of problem you want to solve. Then HPO finds the best hyperparameters according to your objective metric. See  https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-model-support-validation.html#autopilot-algorithm-suppprtAutopilot algorithm support( for a list of algorithms supported by HYPERPARAMETER_TUNING mode.s, s - The security configuration for traffic encryption or Amazon VPC settings.samazonka-sagemakerThe configuration for generating a candidate for an AutoML job (optional).samazonka-sagemakerHow long an AutoML job is allowed to run, or how many candidates a job is allowed to generate.samazonka-sagemaker;The configuration for splitting the input training dataset.Type: AutoMLDataSplitConfigsamazonka-sagemakerThe method that Autopilot uses to train the data. You can either specify the mode manually or let Autopilot choose for you based on the dataset size by selecting AUTO. In AUTO mode, Autopilot chooses  ENSEMBLING( for datasets smaller than 100 MB, and HYPERPARAMETER_TUNING for larger ones.The  ENSEMBLING mode uses a multi-stack ensemble model to predict classification and regression tasks directly from your dataset. This machine learning mode combines several base models to produce an optimal predictive model. It then uses a stacking ensemble method to combine predictions from contributing members. A multi-stack ensemble model can provide better performance over a single model by combining the predictive capabilities of multiple models. See  https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-model-support-validation.html#autopilot-algorithm-suppprtAutopilot algorithm support( for a list of algorithms supported by  ENSEMBLING mode.The HYPERPARAMETER_TUNING (HPO) mode uses the best hyperparameters to train the best version of a model. HPO will automatically select an algorithm for the type of problem you want to solve. Then HPO finds the best hyperparameters according to your objective metric. See  https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-model-support-validation.html#autopilot-algorithm-suppprtAutopilot algorithm support( for a list of algorithms supported by HYPERPARAMETER_TUNING mode.samazonka-sagemakerThe security configuration for traffic encryption or Amazon VPC settings. sssssssssssss sssssssssssss(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?zsttttst sttttsttttt(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';%tamazonka-sagemaker3Status and billing information about the warm pool.See: t smart constructor.tamazonka-sagemakerThe billable time in seconds used by the warm pool. Billable time refers to the absolute wall-clock time. Multiply %ResourceRetainedBillableTimeInSeconds by the number of instances ( InstanceCount) in your training cluster to get the total compute time SageMaker bills you if you run warm pool training. The formula is as follows: 5ResourceRetainedBillableTimeInSeconds * InstanceCount.tamazonka-sagemakerThe name of the matching training job that reused the warm pool.tamazonka-sagemakerThe status of the warm pool.InUse/: The warm pool is in use for the training job. Available: The warm pool is available to reuse for a matching training job.Reused;: The warm pool moved to a matching training job for reuse. Terminated: The warm pool is no longer available. Warm pools are unavailable if they are terminated by a user, terminated for a patch update, or terminated for exceeding the specified KeepAlivePeriodInSeconds.tamazonka-sagemakerCreate a value of t" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:t, t - The billable time in seconds used by the warm pool. Billable time refers to the absolute wall-clock time. Multiply %ResourceRetainedBillableTimeInSeconds by the number of instances ( InstanceCount) in your training cluster to get the total compute time SageMaker bills you if you run warm pool training. The formula is as follows: 5ResourceRetainedBillableTimeInSeconds * InstanceCount.t, t - The name of the matching training job that reused the warm pool.t, t - The status of the warm pool.InUse/: The warm pool is in use for the training job. Available: The warm pool is available to reuse for a matching training job.Reused;: The warm pool moved to a matching training job for reuse. Terminated: The warm pool is no longer available. Warm pools are unavailable if they are terminated by a user, terminated for a patch update, or terminated for exceeding the specified KeepAlivePeriodInSeconds.tamazonka-sagemakerThe billable time in seconds used by the warm pool. Billable time refers to the absolute wall-clock time. Multiply %ResourceRetainedBillableTimeInSeconds by the number of instances ( InstanceCount) in your training cluster to get the total compute time SageMaker bills you if you run warm pool training. The formula is as follows: 5ResourceRetainedBillableTimeInSeconds * InstanceCount.tamazonka-sagemakerThe name of the matching training job that reused the warm pool.tamazonka-sagemakerThe status of the warm pool.InUse/: The warm pool is in use for the training job. Available: The warm pool is available to reuse for a matching training job.Reused;: The warm pool moved to a matching training job for reuse. Terminated: The warm pool is no longer available. Warm pools are unavailable if they are terminated by a user, terminated for a patch update, or terminated for exceeding the specified KeepAlivePeriodInSeconds.tamazonka-sagemakert ttttttttt ttttttttt(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';0ftamazonka-sagemaker2Provides summary information about a training job.See: t smart constructor.tamazonka-sagemaker2Timestamp when the training job was last modified.tamazonka-sagemakerA timestamp that shows when the training job ended. This field is set only if the training job has one of the terminal statuses ( Completed, Failed, or Stopped).tamazonka-sagemaker=The status of the warm pool associated with the training job.tamazonka-sagemaker9The name of the training job that you want a summary for.tamazonka-sagemaker3The Amazon Resource Name (ARN) of the training job.tamazonka-sagemaker9A timestamp that shows when the training job was created.tamazonka-sagemakerThe status of the training job.tamazonka-sagemakerCreate a value of t" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:t, t5 - Timestamp when the training job was last modified.t, t - A timestamp that shows when the training job ended. This field is set only if the training job has one of the terminal statuses ( Completed, Failed, or Stopped).t, t - The status of the warm pool associated with the training job.t, t< - The name of the training job that you want a summary for.t, t6 - The Amazon Resource Name (ARN) of the training job.t, t< - A timestamp that shows when the training job was created.t, t" - The status of the training job.tamazonka-sagemaker2Timestamp when the training job was last modified.tamazonka-sagemakerA timestamp that shows when the training job ended. This field is set only if the training job has one of the terminal statuses ( Completed, Failed, or Stopped).tamazonka-sagemaker=The status of the warm pool associated with the training job.tamazonka-sagemaker9The name of the training job that you want a summary for.tamazonka-sagemaker3The Amazon Resource Name (ARN) of the training job.tamazonka-sagemaker9A timestamp that shows when the training job was created.tamazonka-sagemakerThe status of the training job.tamazonka-sagemakertamazonka-sagemakertamazonka-sagemakertamazonka-sagemakerttttttttttttttttttttttttttttttttttt(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred";?1Otttttttt ttttttttttttt(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%&';7tamazonka-sagemaker7The VPC object you use to create or update a workforce.See: t smart constructor.tamazonka-sagemakerThe VPC security group IDs, in the form sg-xxxxxxxx. The security groups must be for the same VPC as specified in the subnet.tamazonka-sagemaker:The ID of the subnets in the VPC that you want to connect.tamazonka-sagemaker - The Amazon Marketplace identifier for a vendor's work team.u, u - The URI of the labeling job's user interface. Workers open this URI to start labeling your data objects.u, u3 - The Amazon Resource Name (ARN) of the workforce.u, u - The name of the work team.u, u - A list of MemberDefinition objects that contains objects that identify the workers that make up the work team.Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP). For private workforces created using Amazon Cognito use CognitoMemberDefinition. For workforces created using your own OIDC identity provider (IdP) use OidcMemberDefinition.u, u - The Amazon Resource Name (ARN) that identifies the work team.u, u" - A description of the work team.uamazonka-sagemaker=The date and time that the work team was created (timestamp).uamazonka-sagemakerThe date and time that the work team was last updated (timestamp).uamazonka-sagemakerConfigures SNS notifications of available or expiring work items for work teams.uamazonka-sagemaker;The Amazon Marketplace identifier for a vendor's work team.uamazonka-sagemakerThe URI of the labeling job's user interface. Workers open this URI to start labeling your data objects.uamazonka-sagemaker0The Amazon Resource Name (ARN) of the workforce.uamazonka-sagemakerThe name of the work team.uamazonka-sagemaker A list of MemberDefinition objects that contains objects that identify the workers that make up the work team.Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP). For private workforces created using Amazon Cognito use CognitoMemberDefinition. For workforces created using your own OIDC identity provider (IdP) use OidcMemberDefinition.uamazonka-sagemaker=The Amazon Resource Name (ARN) that identifies the work team.uamazonka-sagemakerA description of the work team.uamazonka-sagemakeruamazonka-sagemakeruamazonka-sagemakeruamazonka-sagemakeruuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuu(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%hFuamazonka-sagemaker API version  2017-07-243 of the Amazon SageMaker Service SDK configuration.uamazonka-sagemakerThere was a conflict when you attempted to modify a SageMaker entity such as an  Experiment or Artifact.uamazonka-sagemaker"Resource being accessed is in use.uamazonka-sagemakerYou have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.uamazonka-sagemaker#Resource being access is not found.8-.45/01236789:;<=EFGHIJKSTUVW`dcabx~}|{yz   !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!""!!!"""""""""""""""""""""""""""""""""""""""""##""##############################################$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&&&&&&&&&&&&&&&&&&&&%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''(((((((((((((((((((((((((((((((((((((((((((((((((((((((()))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))***))****************************+**+++++++++++++++++++++++++++++++++++++++++++,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,---------------------------------------------------........................................../.......////////////////////////////////////00000000000000000000000000000000000000000000000000000000000000001111111111111111111111111111111111111111111121222222222222222222222222222222222222222222222222222222222222333333333333333333333333333333333333333333333333333333333333444334444444444444444444444444444444444444444444555555555555555555555555555555555555555555555555555666666666666666666666666666666666666666666666666666666677777777777777777777777777777777777777777777777777788888888888888888888888888888888888888888888888889989999999999999999999999999999999999999999999999999:::::::::::::::::::::::::::::::::::::::::::::::::::::;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;<<;;;<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<=====================================================>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>??????????????????????????????????????????????????????????????@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCDCCCCCCCCDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEFFFFFFFFFFFFFFFFFGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFGGGGGGGGGGGGGGGGGGGGGGGGGGGHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLMMLLMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQRRQRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUVUVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVWWWWWWWWWWWWWWWWWWWWWWWWWXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[\\\\\\\\\\\\\\\\\\\\\\\\\\[[[[[[[[\\\\\\\\\\\\\\\\\\\\\\\\\\]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^___________________________________________________________________````````````````````````````````````````````````___```````````````````````````````````aaaa``aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaabbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbcccccccccccccccccccccbbbbbbbbbbbbbcccccccccccccccccccccccccccccccccccccccccccccccccccccccccdddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggghhhhghhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiijjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllmlmlmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmnnnmnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnoooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooopoooooooppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrsssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssttttstttttttttttttttttttttttttttttttttttttttttttttttttttttttttuutuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuu`dcabdcx~}|{yz~}|{    !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!""!!!""!""""""""""""""""""""""""""""""""""##""######################$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$%%%%%%%%&&&&&&&&&&&&&&&&&&&&%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&&&&&&&&&&&&&&&&&&&&%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&&&&&&&&&&&&&&&&((((((((((((((()))))))))))))))))))))***))**********************************************+**++++++++++++++++++++++++----------------........................../......./.....//////////////////////////0000111111111111111122222222222222222222223333333333333333333334443344444444444444444445555555555555555555555555556666666667777777777777777888888888888888888889999999999999999999999999999999:::::::::::::::::::::::::::::::::;;;;;;;;;;;;;;;;;<<;;;<<;==============================>>>>>>>>>>>?????????????@@@@@@@@@@@@@@AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABBBBBBBBBBBBBBBBBBBBBBBBBBBCCCCCCCCCCCCCCDDDDDDDEEEEEEEFFFFFFFFFFFFFFFFGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFHHHHHHHHHHHHHHIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIJJJJJJJJJJJJJJLLLLLLLLLLLLLLLLLLLLLLMMMMMMMMMMMMMMMMMMMMMMMMMNNNNNNNOOOOOOOQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQRRQRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRSSSSSSSSSSSSSSSSSSTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTUUUUUUUUVUVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ[[[[[[[[\\\\\\\\\\\\\\\\\\\\\\\\\\[[[[[[[[\\\\\\\\\\\\\\\\\\\\\\\\\\[[[[[[\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\]]]]]]]]]^^^^^__________````````````````````````````````````````````````___````````````````````````````````````````````````_aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabcccccccccccccccccccccbbbbbbbbbbbbbcccccccccccccccccccccbbbbbbbbbbbcccccccccccccfffffffffffffllllllllllllllllllllllllmmmmmmmmmmmmmmmmmmmmmmnnnnnnnnnnnsttttstttttttttttttttttt-.45/01236789:;<=cccccccccccccccccEFGHIJKSTUVW_________________eeeeeeeeeeeeeeee'''''''''''''lllllllllllllllllllll;;;;;;;;;;;;;;;;;;;;;;;;; ssssssssssssssssssssss cccccccccccccccccccCCDCCCCCCCCDDDDDDDDDDDDDD---------^^^^^^^^^ >>>>>>>>> ,,,,,,,]]]]] ________________________________  ]]]]]]]]]]]]]]]]]]]]]]]]]OOOOOOOOOOOOOOOOOOOOO &&&&&&'''888888888DDDDDDDSSSSSSSNNNNNNNNNNNNNAAAAAAABBBBBBBBBBRRRRRRRRRRRRRQQQQQQQQQQQ^^^^^^^YYYYYYYYYYYPPPPPPPPPPPPPPPPPP-----------,,,,,,---,,,,,,,,,,,,,,,,,,,,,YYYYYYYYYYYYYYYqqqqqqqqqqqqqqqqqqqqqqqqqqqCCCCCCCCCCCCCCCCCCCCCCCGGGGGGGGGGGGGGGGGGGG%%%%%%%lllllllllllllllllllllll,,,,,[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[<<<<<<<<<<<<<========= hhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhh___________?????????????????rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrraaabaaaaaabbbbbbbbbbbbbbbbb`````````ggggggggggggggggggg sssssssssssssssssssssssssssssssssss!!!!!bbbbbbbbbbbbbbbbbbbbbbb???????``aaaa``aaaaaaa!!!!!!!"""""""""""""""""""OOOOOOO#################################$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$MMMMMMMMMLLLLLLLLLLLLLLLLLLLLLLLMMMMMMMMMMMccccccccccccc%%%%%%%%%%%`````````%%%%%&&&&&&&&&&&&&&&&&&QQQQQQQQQPPPPPPPPP''''''''''''''''''''''''''''''''''''rrrrrrrrr'''''((((((('''''''''''''''(((((((((((((((((((((((rrrrrrr((((((((((((((((()))))))))))))))))))))))))))>>>>>>>))))))))))))))))))))<<<<<<<++++++++++++++++++++,,,,,,,,,,,+++++++,,,,,,,,,rrrrrrrrrrrrrrrrrrrrrrr--------------6666666DDDDDDDDDkkkkkkkkkkkkkkkkkkkkkklllllll---........................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=====ooooooooo::::::::::::::::::::::::::::::::;;;;;;;;;;;;;;;;;;;;;[[[[[[[[[[[<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<============]]]]]]]]]]]]]=======>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>????????????nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn?????????jjjjjjjjjjjjjjjjjjjjjjjjjjjjj?????????jjjjjjjjjjjjjjjjjjjjjjjjjjjjjgghhhhghhhhhhhhhhhhhhhhggggggggggggggggggggggggggggggg@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@AAAAAAAAAAA@@@@@NNNNNNNNNNNoooooooooooooooopooooooopppppppppppppppppppppppBBBBBBBBBBBBBBBBBBBBBBBBEEEEEEEEEEEEEEEEEEBBBBBCCCCCCCCCCCCCCCDDEEEEEEEEEEEEHHHHHHHHHHHHHHHHHHHHHHHHHFFFFFFFGGGGGGGmmmmmmmmmmmnnnmnnnnnnnnnnnnnnnHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHRRRRRRRRRRRRRjjjjjjjjjjjjjjjjjjjjjjjjjjjIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIhhhhhJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJPPPPPPPJJJJJJJPPPPPPPPPPPPPPPPPPPPPPJJJJJKKKKKKKKKKKKKKKKKKKKKKKKMMMMMMMMMMM^^^^^^^^^^^^^^^^^^^^^KKKKKKKKKKKKKKKKKLLLLLLLLLLLLLLLLLLLLMMLLMMMMMNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNOOOOOOOOOOOOOOOOOOOOO```````````````OOOOOOOOOPPPPPPPPPPPPPPQQQQQQQQQQSSSSSSSSSSSSSSSSSSSSSSSSSSSTTTTTTTTTTTsssssssssssssssssssssssssssssssssTTTTTTTTTTTTTTTTUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUXXXXXXXXXXXXXXXXXYYYYYYYYYYYYYXXXXXXXZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ[[[[[[[[[[[[\\\\\\]]]]]]]]]]]]]]]]]]]]]]^^^^^^^^^^^^^^^^^^oooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooaaaaaaaaaaaaaaabbbbbbbbbbbbbbbbbbtttttttttttttttttbbbbbbbbbbbbbbbbbbbddddddddddddddddeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeffffffeeeeeeeeeeeeeeeeedddddddddddddddddddddddddddddddddddddddddddddddddiiiiiiiiiiiiiiiiiiiiiiiiiijpppppppppppppppppppppppppppppppppppppppppppppfffffffffffffffffffffffffffffffffffiiiiiiiiiiiiifffffffpppppppppppfffffffiiiiiiiiiiiiiiiiiiiiiiiiifggggggggggggggggggggggggggggggghhhhhhhhhhhhhhhhiiiiiiiiiiiiiiiiiiiiillmlmlmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmnnnnnnnnnnnnnnnntttttttttttuutuuuuuuuuuuuuuuuuuuuuttttttttttttttttttttuuuuuuuuuuuuuuuuuuuuuuu(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';uamazonka-sagemakerSee: u smart constructor.uamazonka-sagemakerSee: u smart constructor.uamazonka-sagemaker,The name of the batch transform job to stop.uamazonka-sagemakerCreate a value of u" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:u, u/ - The name of the batch transform job to stop.uamazonka-sagemaker,The name of the batch transform job to stop.uamazonka-sagemakerCreate a value of u" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.uamazonka-sagemakeruuuuuuuuuuuuuuuuu(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';Iuamazonka-sagemakerSee: u smart constructor.uamazonka-sagemakerSee: u smart constructor.uamazonka-sagemaker%The name of the training job to stop.uamazonka-sagemakerCreate a value of u" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:u, u( - The name of the training job to stop.uamazonka-sagemaker%The name of the training job to stop.uamazonka-sagemakerCreate a value of u" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.uamazonka-sagemakeruuuuuuuuuuuuuuuuu(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';uamazonka-sagemakerSee: u smart constructor.uamazonka-sagemakerSee: u smart constructor.uamazonka-sagemaker'The name of the processing job to stop.uamazonka-sagemakerCreate a value of u" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:u, u* - The name of the processing job to stop.uamazonka-sagemaker'The name of the processing job to stop.uamazonka-sagemakerCreate a value of u" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.uamazonka-sagemakeruuuuuuuuuuuuuuuuu(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&'; vamazonka-sagemakerSee: v smart constructor.vamazonka-sagemaker9The Amazon Resource Name (ARN) of the pipeline execution.vamazonka-sagemaker The response's http status code.vamazonka-sagemakerSee: v smart constructor.vamazonka-sagemaker9The Amazon Resource Name (ARN) of the pipeline execution.vamazonka-sagemakerA unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than once.vamazonka-sagemakerCreate a value of v" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:v, v< - The Amazon Resource Name (ARN) of the pipeline execution.v, v - A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than once.vamazonka-sagemaker9The Amazon Resource Name (ARN) of the pipeline execution.vamazonka-sagemakerA unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than once.vamazonka-sagemakerCreate a value of v" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:v, v< - The Amazon Resource Name (ARN) of the pipeline execution.v, v# - The response's http status code.vamazonka-sagemaker9The Amazon Resource Name (ARN) of the pipeline execution.vamazonka-sagemaker The response's http status code.vamazonka-sagemakervamazonka-sagemakervvamazonka-sagemakervvvvvvvvvvvvvvvvvvvvvvvvvvvvv(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';vamazonka-sagemakerSee: v smart constructor.vamazonka-sagemakerSee: v smart constructor.vamazonka-sagemaker/The name of the notebook instance to terminate.vamazonka-sagemakerCreate a value of v" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:v, v2 - The name of the notebook instance to terminate.vamazonka-sagemaker/The name of the notebook instance to terminate.vamazonka-sagemakerCreate a value of v" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.vamazonka-sagemakervvvvvvvvvvvvvvvvv(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';[vamazonka-sagemakerSee: v smart constructor.vamazonka-sagemakerSee: v smart constructor.vamazonka-sagemaker!The name of the schedule to stop.vamazonka-sagemakerCreate a value of v" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:v, v$ - The name of the schedule to stop.vamazonka-sagemaker!The name of the schedule to stop.vamazonka-sagemakerCreate a value of v" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.vamazonka-sagemakervvvvvvvvvvvvvvvvv(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';vamazonka-sagemakerSee: v smart constructor.vamazonka-sagemakerSee: v smart constructor.vamazonka-sagemaker%The name of the labeling job to stop.vamazonka-sagemakerCreate a value of v" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:v, v( - The name of the labeling job to stop.vamazonka-sagemaker%The name of the labeling job to stop.vamazonka-sagemakerCreate a value of v" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.vamazonka-sagemakervvvvvvvvvvvvvvvvv(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&'; vamazonka-sagemakerSee: v smart constructor.vamazonka-sagemakerSee: v smart constructor.vamazonka-sagemaker%The name of the job you want to stop.vamazonka-sagemakerCreate a value of v" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:v, v( - The name of the job you want to stop.vamazonka-sagemaker%The name of the job you want to stop.vamazonka-sagemakerCreate a value of v" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.vamazonka-sagemakervvvvvvvvvvvvvvvvv(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';4wamazonka-sagemakerSee: w smart constructor.wamazonka-sagemaker The response's http status code.wamazonka-sagemaker,The ARN of the stopped inference experiment.wamazonka-sagemakerSee: w smart constructor.wamazonka-sagemaker An array of ModelVariantConfig objects. There is one for each variant that you want to deploy after the inference experiment stops. Each ModelVariantConfig describes the infrastructure configuration for deploying the corresponding variant.wamazonka-sagemakerThe desired state of the experiment after stopping. The possible states are the following: Completed': The experiment completed successfully Cancelled: The experiment was canceledwamazonka-sagemaker'The reason for stopping the experiment.wamazonka-sagemaker-The name of the inference experiment to stop.wamazonka-sagemakerArray of key-value pairs, with names of variants mapped to actions. The possible actions are the following:Promote5 - Promote the shadow variant to a production variantRemove - Delete the variantRetain - Keep the variant as it iswamazonka-sagemakerCreate a value of w" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:w, w - An array of ModelVariantConfig objects. There is one for each variant that you want to deploy after the inference experiment stops. Each ModelVariantConfig describes the infrastructure configuration for deploying the corresponding variant.w, w - The desired state of the experiment after stopping. The possible states are the following: Completed': The experiment completed successfully Cancelled: The experiment was canceledw, w* - The reason for stopping the experiment.w, w0 - The name of the inference experiment to stop.w, w - Array of key-value pairs, with names of variants mapped to actions. The possible actions are the following:Promote5 - Promote the shadow variant to a production variantRemove - Delete the variantRetain - Keep the variant as it iswamazonka-sagemaker An array of ModelVariantConfig objects. There is one for each variant that you want to deploy after the inference experiment stops. Each ModelVariantConfig describes the infrastructure configuration for deploying the corresponding variant.wamazonka-sagemakerThe desired state of the experiment after stopping. The possible states are the following: Completed': The experiment completed successfully Cancelled: The experiment was canceledwamazonka-sagemaker'The reason for stopping the experiment.wamazonka-sagemaker-The name of the inference experiment to stop.wamazonka-sagemakerArray of key-value pairs, with names of variants mapped to actions. The possible actions are the following:Promote5 - Promote the shadow variant to a production variantRemove - Delete the variantRetain - Keep the variant as it iswamazonka-sagemakerCreate a value of w" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:w, w# - The response's http status code.w, w/ - The ARN of the stopped inference experiment.wamazonka-sagemaker The response's http status code.wamazonka-sagemaker,The ARN of the stopped inference experiment.wamazonka-sagemakerwwamazonka-sagemakerwamazonka-sagemakerwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwww(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&'; wamazonka-sagemakerSee: w smart constructor.wamazonka-sagemakerSee: w smart constructor.wamazonka-sagemaker#The name of the tuning job to stop.wamazonka-sagemakerCreate a value of w" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:w, w& - The name of the tuning job to stop.wamazonka-sagemaker#The name of the tuning job to stop.wamazonka-sagemakerCreate a value of w" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.wamazonka-sagemakerwwwwwwwwwwwwwwwww(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';%|wamazonka-sagemakerSee: w smart constructor.wamazonka-sagemakerSee: w smart constructor.wamazonka-sagemaker#The name of the edge packaging job.wamazonka-sagemakerCreate a value of w" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:w, w& - The name of the edge packaging job.wamazonka-sagemaker#The name of the edge packaging job.wamazonka-sagemakerCreate a value of w" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.wamazonka-sagemakerwwwwwwwwwwwwwwwww(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';*wamazonka-sagemakerSee: w smart constructor.wamazonka-sagemakerSee: w smart constructor.wamazonka-sagemaker-The name of the edge deployment plan to stop.wamazonka-sagemakerThe name of the stage to stop.wamazonka-sagemakerCreate a value of w" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:w, w0 - The name of the edge deployment plan to stop.w, w! - The name of the stage to stop.wamazonka-sagemaker-The name of the edge deployment plan to stop.wamazonka-sagemakerThe name of the stage to stop.wamazonka-sagemakerCreate a value of w" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.wamazonka-sagemakerwamazonka-sagemakerw wwwwwwwwww wwwwwwwwww(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';/wamazonka-sagemakerSee: w smart constructor.wamazonka-sagemakerSee: w smart constructor.wamazonka-sagemaker.The name of the model compilation job to stop.wamazonka-sagemakerCreate a value of w" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:w, w1 - The name of the model compilation job to stop.wamazonka-sagemaker.The name of the model compilation job to stop.wamazonka-sagemakerCreate a value of w" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.wamazonka-sagemakerwwwwwwwwwwwwwwwww(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';4;xamazonka-sagemakerSee: x smart constructor.xamazonka-sagemakerSee: x smart constructor.xamazonka-sagemaker*The name of the object you are requesting.xamazonka-sagemakerCreate a value of x" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:x, x- - The name of the object you are requesting.xamazonka-sagemaker*The name of the object you are requesting.xamazonka-sagemakerCreate a value of x" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.xamazonka-sagemakerxxxxxxxxxxxxxxxxx(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';AWxamazonka-sagemakerSee: x smart constructor.xamazonka-sagemaker9The Amazon Resource Name (ARN) of the pipeline execution.xamazonka-sagemaker The response's http status code.xamazonka-sagemakerSee: x smart constructor.xamazonka-sagemakerThis configuration, if specified, overrides the parallelism configuration of the parent pipeline for this specific run.xamazonka-sagemaker*The description of the pipeline execution.xamazonka-sagemaker+The display name of the pipeline execution.xamazonka-sagemaker?Contains a list of pipeline parameters. This list can be empty.xamazonka-sagemakerThe name of the pipeline.xamazonka-sagemakerA unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than once.xamazonka-sagemakerCreate a value of x" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:x, x - This configuration, if specified, overrides the parallelism configuration of the parent pipeline for this specific run.x, x- - The description of the pipeline execution.x, x. - The display name of the pipeline execution.x, x - Contains a list of pipeline parameters. This list can be empty.x, x - The name of the pipeline.x, x - A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than once.xamazonka-sagemakerThis configuration, if specified, overrides the parallelism configuration of the parent pipeline for this specific run.xamazonka-sagemaker*The description of the pipeline execution.xamazonka-sagemaker+The display name of the pipeline execution.xamazonka-sagemaker?Contains a list of pipeline parameters. This list can be empty.xamazonka-sagemakerThe name of the pipeline.xamazonka-sagemakerA unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than once.xamazonka-sagemakerCreate a value of x" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:x, x< - The Amazon Resource Name (ARN) of the pipeline execution.x, x# - The response's http status code.xamazonka-sagemaker9The Amazon Resource Name (ARN) of the pipeline execution.xamazonka-sagemaker The response's http status code.xamazonka-sagemakerxamazonka-sagemakerxxamazonka-sagemakerxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';F3xamazonka-sagemakerSee: x smart constructor.xamazonka-sagemakerSee: x smart constructor.xamazonka-sagemaker+The name of the notebook instance to start.xamazonka-sagemakerCreate a value of x" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:x, x. - The name of the notebook instance to start.xamazonka-sagemaker+The name of the notebook instance to start.xamazonka-sagemakerCreate a value of x" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.xamazonka-sagemakerxxxxxxxxxxxxxxxxx(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';Jxamazonka-sagemakerSee: x smart constructor.xamazonka-sagemakerSee: x smart constructor.xamazonka-sagemaker"The name of the schedule to start.xamazonka-sagemakerCreate a value of x" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:x, x% - The name of the schedule to start.xamazonka-sagemaker"The name of the schedule to start.xamazonka-sagemakerCreate a value of x" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.xamazonka-sagemakerxxxxxxxxxxxxxxxxx(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';Q xamazonka-sagemakerSee: y smart constructor.xamazonka-sagemaker The response's http status code.xamazonka-sagemaker5The ARN of the started inference experiment to start.xamazonka-sagemakerSee: y smart constructor.yamazonka-sagemaker.The name of the inference experiment to start.yamazonka-sagemakerCreate a value of x" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:x, y1 - The name of the inference experiment to start.yamazonka-sagemaker.The name of the inference experiment to start.yamazonka-sagemakerCreate a value of x" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:x, y# - The response's http status code.x, y8 - The ARN of the started inference experiment to start.yamazonka-sagemaker The response's http status code.yamazonka-sagemaker5The ARN of the started inference experiment to start.yamazonka-sagemakerxyamazonka-sagemakerxamazonka-sagemakerx xxxxxxyyyyyy xxyyyxxxxyyy(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';W(yamazonka-sagemakerSee: y smart constructor.yamazonka-sagemakerSee: y smart constructor.yamazonka-sagemaker.The name of the edge deployment plan to start.yamazonka-sagemakerThe name of the stage to start.yamazonka-sagemakerCreate a value of y" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:y, y1 - The name of the edge deployment plan to start.y, y" - The name of the stage to start.yamazonka-sagemaker.The name of the edge deployment plan to start.yamazonka-sagemakerThe name of the stage to start.yamazonka-sagemakerCreate a value of y" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.yamazonka-sagemakeryamazonka-sagemakery yyyyyyyyyy yyyyyyyyyy(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';a0yamazonka-sagemakerSee: y smart constructor.yamazonka-sagemaker9The Amazon Resource Name (ARN) of the pipeline execution.yamazonka-sagemaker The response's http status code.yamazonka-sagemakerSee: y smart constructor.yamazonka-sagemakerA unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.yamazonka-sagemaker5A list of the output parameters of the callback step.yamazonka-sagemaker7The pipeline generated token from the Amazon SQS queue.yamazonka-sagemakerCreate a value of y" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:y, y - A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.y, y8 - A list of the output parameters of the callback step.y, y: - The pipeline generated token from the Amazon SQS queue.yamazonka-sagemakerA unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.yamazonka-sagemaker5A list of the output parameters of the callback step.yamazonka-sagemaker7The pipeline generated token from the Amazon SQS queue.yamazonka-sagemakerCreate a value of y" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:y, y< - The Amazon Resource Name (ARN) of the pipeline execution.y, y# - The response's http status code.yamazonka-sagemaker9The Amazon Resource Name (ARN) of the pipeline execution.yamazonka-sagemaker The response's http status code.yamazonka-sagemakeryyamazonka-sagemakeryyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyy(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';k,yamazonka-sagemakerSee: y smart constructor.yamazonka-sagemaker9The Amazon Resource Name (ARN) of the pipeline execution.yamazonka-sagemaker The response's http status code.yamazonka-sagemakerSee: y smart constructor.yamazonka-sagemakerA unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.yamazonka-sagemaker)A message describing why the step failed.yamazonka-sagemaker7The pipeline generated token from the Amazon SQS queue.yamazonka-sagemakerCreate a value of y" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:y, y - A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.y, y, - A message describing why the step failed.y, y: - The pipeline generated token from the Amazon SQS queue.yamazonka-sagemakerA unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.yamazonka-sagemaker)A message describing why the step failed.yamazonka-sagemaker7The pipeline generated token from the Amazon SQS queue.yamazonka-sagemakerCreate a value of y" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:y, y< - The Amazon Resource Name (ARN) of the pipeline execution.y, y# - The response's http status code.yamazonka-sagemaker9The Amazon Resource Name (ARN) of the pipeline execution.yamazonka-sagemaker The response's http status code.yamazonka-sagemakeryyamazonka-sagemakeryyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyy(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';yamazonka-sagemakerSee: z smart constructor.yamazonka-sagemakerIf the result of the previous Search request was truncated, the response includes a NextToken. To retrieve the next set of results, use the token in the next request.yamazonka-sagemaker A list of  SearchRecord objects.yamazonka-sagemaker The response's http status code.yamazonka-sagemakerSee: y smart constructor.yamazonka-sagemaker(The maximum number of results to return.yamazonka-sagemaker If more than  MaxResults resources match the specified SearchExpression, the response includes a  NextToken. The  NextToken can be passed to the next  SearchRequest! to continue retrieving results.yamazonka-sagemakerA Boolean conditional statement. Resources must satisfy this condition to be included in search results. You must provide at least one subexpression, filter, or nested filter. The maximum number of recursive SubExpressions,  NestedFilters, and Filters that can be included in a SearchExpression object is 50.yamazonka-sagemaker3The name of the resource property used to sort the  SearchResults. The default is LastModifiedTime.yamazonka-sagemakerHow  SearchResults are ordered. Valid values are  Ascending or  Descending. The default is  Descending.yamazonka-sagemaker8The name of the Amazon SageMaker resource to search for.yamazonka-sagemakerCreate a value of y" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:y, y+ - The maximum number of results to return.y, y - If more than  MaxResults resources match the specified SearchExpression, the response includes a  NextToken. The  NextToken can be passed to the next  SearchRequest! to continue retrieving results.y, z - A Boolean conditional statement. Resources must satisfy this condition to be included in search results. You must provide at least one subexpression, filter, or nested filter. The maximum number of recursive SubExpressions,  NestedFilters, and Filters that can be included in a SearchExpression object is 50.y, z6 - The name of the resource property used to sort the  SearchResults. The default is LastModifiedTime.y, z - How  SearchResults are ordered. Valid values are  Ascending or  Descending. The default is  Descending.y, z; - The name of the Amazon SageMaker resource to search for.yamazonka-sagemaker(The maximum number of results to return.yamazonka-sagemaker If more than  MaxResults resources match the specified SearchExpression, the response includes a  NextToken. The  NextToken can be passed to the next  SearchRequest! to continue retrieving results.zamazonka-sagemakerA Boolean conditional statement. Resources must satisfy this condition to be included in search results. You must provide at least one subexpression, filter, or nested filter. The maximum number of recursive SubExpressions,  NestedFilters, and Filters that can be included in a SearchExpression object is 50.zamazonka-sagemaker3The name of the resource property used to sort the  SearchResults. The default is LastModifiedTime.zamazonka-sagemakerHow  SearchResults are ordered. Valid values are  Ascending or  Descending. The default is  Descending.zamazonka-sagemaker8The name of the Amazon SageMaker resource to search for.zamazonka-sagemakerCreate a value of y" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:y, z! - If the result of the previous Search request was truncated, the response includes a NextToken. To retrieve the next set of results, use the token in the next request.y, z - A list of  SearchRecord objects.y, z# - The response's http status code.zamazonka-sagemakerIf the result of the previous Search request was truncated, the response includes a NextToken. To retrieve the next set of results, use the token in the next request.zamazonka-sagemaker A list of  SearchRecord objects.zamazonka-sagemaker The response's http status code.yamazonka-sagemakeryzamazonka-sagemakeryyyyyyyyyyyyyyyyyzzzzzzzzyyyyyyyyyyyzzzzyyyyyzzzz(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';zamazonka-sagemakerSee: z smart constructor.zamazonka-sagemaker9The Amazon Resource Name (ARN) of the pipeline execution.zamazonka-sagemaker The response's http status code.zamazonka-sagemakerSee: z smart constructor.zamazonka-sagemakerThis configuration, if specified, overrides the parallelism configuration of the parent pipeline.zamazonka-sagemaker9The Amazon Resource Name (ARN) of the pipeline execution.zamazonka-sagemakerA unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than once.zamazonka-sagemakerCreate a value of z" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:z, z - This configuration, if specified, overrides the parallelism configuration of the parent pipeline.z, z< - The Amazon Resource Name (ARN) of the pipeline execution.z, z - A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than once.zamazonka-sagemakerThis configuration, if specified, overrides the parallelism configuration of the parent pipeline.zamazonka-sagemaker9The Amazon Resource Name (ARN) of the pipeline execution.zamazonka-sagemakerA unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than once.zamazonka-sagemakerCreate a value of z" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:z, z< - The Amazon Resource Name (ARN) of the pipeline execution.z, z# - The response's http status code.zamazonka-sagemaker9The Amazon Resource Name (ARN) of the pipeline execution.zamazonka-sagemaker The response's http status code.zamazonka-sagemakerzamazonka-sagemakerzzamazonka-sagemakerzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzz(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';zamazonka-sagemakerSee: z smart constructor.zamazonka-sagemaker The response's http status code.zamazonka-sagemaker:A Liquid template that renders the HTML for the worker UI.zamazonka-sagemakerA list of one or more RenderingError objects if any were encountered while rendering the template. If there were no errors, the list is empty.zamazonka-sagemakerSee: z smart constructor.zamazonka-sagemakerThe HumanTaskUiArn= of the worker UI that you want to render. Do not provide a HumanTaskUiArn if you use the  UiTemplate parameter.See a list of available Human Ui Amazon Resource Names (ARNs) in UiConfig.zamazonka-sagemakerA Template4 object containing the worker UI template to render.zamazonka-sagemakerA RenderableTask3 object containing a representative task to render.zamazonka-sagemakerThe Amazon Resource Name (ARN) that has access to the S3 objects that are used by the template.zamazonka-sagemakerCreate a value of z" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:z, z - The HumanTaskUiArn= of the worker UI that you want to render. Do not provide a HumanTaskUiArn if you use the  UiTemplate parameter.See a list of available Human Ui Amazon Resource Names (ARNs) in UiConfig.z, z - A Template4 object containing the worker UI template to render.z, z - A RenderableTask3 object containing a representative task to render.z, z - The Amazon Resource Name (ARN) that has access to the S3 objects that are used by the template.zamazonka-sagemakerThe HumanTaskUiArn= of the worker UI that you want to render. Do not provide a HumanTaskUiArn if you use the  UiTemplate parameter.See a list of available Human Ui Amazon Resource Names (ARNs) in UiConfig.zamazonka-sagemakerA Template4 object containing the worker UI template to render.zamazonka-sagemakerA RenderableTask3 object containing a representative task to render.zamazonka-sagemakerThe Amazon Resource Name (ARN) that has access to the S3 objects that are used by the template.zamazonka-sagemakerCreate a value of z" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:z, z# - The response's http status code.z, z= - A Liquid template that renders the HTML for the worker UI.z, z - A list of one or more RenderingError objects if any were encountered while rendering the template. If there were no errors, the list is empty.zamazonka-sagemaker The response's http status code.zamazonka-sagemaker:A Liquid template that renders the HTML for the worker UI.zamazonka-sagemakerA list of one or more RenderingError objects if any were encountered while rendering the template. If there were no errors, the list is empty.zamazonka-sagemakerzamazonka-sagemakerzzamazonka-sagemakerzamazonka-sagemakerzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzz(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&'; zamazonka-sagemakerSee: z smart constructor.zamazonka-sagemakerSee: z smart constructor.zamazonka-sagemaker!The tags associated with devices.zamazonka-sagemakerThe name of the fleet.zamazonka-sagemaker:A list of devices to register with SageMaker Edge Manager.zamazonka-sagemakerCreate a value of z" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:z, z$ - The tags associated with devices.z, z - The name of the fleet.z, z= - A list of devices to register with SageMaker Edge Manager.zamazonka-sagemaker!The tags associated with devices.zamazonka-sagemakerThe name of the fleet.zamazonka-sagemaker:A list of devices to register with SageMaker Edge Manager.zamazonka-sagemakerCreate a value of z" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.zamazonka-sagemakerz zzzzzzzzzzzz zzzzzzzzzzzz(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';zamazonka-sagemakerSee: { smart constructor.zamazonka-sagemaker6A list of edges that connect vertices in the response.zamazonka-sagemaker7Limits the number of vertices in the response. Use the  NextToken8 in a response to to retrieve the next page of results.zamazonka-sagemakerA list of vertices connected to the start entity(ies) in the lineage graph.zamazonka-sagemaker The response's http status code.zamazonka-sagemakerSee: { smart constructor.{amazonka-sagemakerAssociations between lineage entities have a direction. This parameter determines the direction from the StartArn(s) that the query traverses.{amazonka-sagemakerA set of filtering parameters that allow you to specify which entities should be returned.Properties - Key-value pairs to match on the lineage entities' properties.LineageTypes - A set of lineage entity types to match on. For example: TrialComponent, Artifact, or Context.9CreatedBefore - Filter entities created before this date.;ModifiedBefore - Filter entities modified before this date.9ModifiedAfter - Filter entities modified after this date.{amazonka-sagemakerSetting this value to True< retrieves not only the entities of interest but also the  https://docs.aws.amazon.com/sagemaker/latest/dg/lineage-tracking-entities.html Associations+ and lineage entities on the path. Set to False8 to only return lineage entities that match your query.{amazonka-sagemaker4The maximum depth in lineage relationships from the  StartArns: that are traversed. Depth is a measure of the number of  Associations from the StartArn entity to the matched results.{amazonka-sagemaker6Limits the number of vertices in the results. Use the  NextToken8 in a response to to retrieve the next page of results.{amazonka-sagemaker6Limits the number of vertices in the request. Use the  NextToken8 in a response to to retrieve the next page of results.{amazonka-sagemakerA list of resource Amazon Resource Name (ARN) that represent the starting point for your lineage query.{amazonka-sagemakerCreate a value of z" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:{, { - Associations between lineage entities have a direction. This parameter determines the direction from the StartArn(s) that the query traverses.z, { - A set of filtering parameters that allow you to specify which entities should be returned.Properties - Key-value pairs to match on the lineage entities' properties.LineageTypes - A set of lineage entity types to match on. For example: TrialComponent, Artifact, or Context.9CreatedBefore - Filter entities created before this date.;ModifiedBefore - Filter entities modified before this date.9ModifiedAfter - Filter entities modified after this date.{, { - Setting this value to True< retrieves not only the entities of interest but also the  https://docs.aws.amazon.com/sagemaker/latest/dg/lineage-tracking-entities.html Associations+ and lineage entities on the path. Set to False8 to only return lineage entities that match your query.{, {7 - The maximum depth in lineage relationships from the  StartArns: that are traversed. Depth is a measure of the number of  Associations from the StartArn entity to the matched results.{, {9 - Limits the number of vertices in the results. Use the  NextToken8 in a response to to retrieve the next page of results.z, {9 - Limits the number of vertices in the request. Use the  NextToken8 in a response to to retrieve the next page of results.{, { - A list of resource Amazon Resource Name (ARN) that represent the starting point for your lineage query.{amazonka-sagemakerAssociations between lineage entities have a direction. This parameter determines the direction from the StartArn(s) that the query traverses.{amazonka-sagemakerA set of filtering parameters that allow you to specify which entities should be returned.Properties - Key-value pairs to match on the lineage entities' properties.LineageTypes - A set of lineage entity types to match on. For example: TrialComponent, Artifact, or Context.9CreatedBefore - Filter entities created before this date.;ModifiedBefore - Filter entities modified before this date.9ModifiedAfter - Filter entities modified after this date.{amazonka-sagemakerSetting this value to True< retrieves not only the entities of interest but also the  https://docs.aws.amazon.com/sagemaker/latest/dg/lineage-tracking-entities.html Associations+ and lineage entities on the path. Set to False8 to only return lineage entities that match your query.{amazonka-sagemaker4The maximum depth in lineage relationships from the  StartArns: that are traversed. Depth is a measure of the number of  Associations from the StartArn entity to the matched results.{amazonka-sagemaker6Limits the number of vertices in the results. Use the  NextToken8 in a response to to retrieve the next page of results.{amazonka-sagemaker6Limits the number of vertices in the request. Use the  NextToken8 in a response to to retrieve the next page of results.{amazonka-sagemakerA list of resource Amazon Resource Name (ARN) that represent the starting point for your lineage query.{amazonka-sagemakerCreate a value of z" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:z, {9 - A list of edges that connect vertices in the response.z, {: - Limits the number of vertices in the response. Use the  NextToken8 in a response to to retrieve the next page of results.z, { - A list of vertices connected to the start entity(ies) in the lineage graph.z, {# - The response's http status code.{amazonka-sagemaker6A list of edges that connect vertices in the response.{amazonka-sagemaker7Limits the number of vertices in the response. Use the  NextToken8 in a response to to retrieve the next page of results.{amazonka-sagemakerA list of vertices connected to the start entity(ies) in the lineage graph.{amazonka-sagemaker The response's http status code.{amazonka-sagemakerzzzzzzzzz{{{{{{{{{{{{{{{{{{{{zz{{{{{{{{{{{{{{{zzzzzz{{{{{(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&'; {amazonka-sagemakerSee: { smart constructor.{amazonka-sagemaker The response's http status code.{amazonka-sagemaker:The Amazon Resource Name (ARN) of the model package group.{amazonka-sagemakerSee: { smart constructor.{amazonka-sagemaker8The name of the model group to add a resource policy to.{amazonka-sagemaker(The resource policy for the model group.{amazonka-sagemakerCreate a value of {" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:{, {; - The name of the model group to add a resource policy to.{, {+ - The resource policy for the model group.{amazonka-sagemaker8The name of the model group to add a resource policy to.{amazonka-sagemaker(The resource policy for the model group.{amazonka-sagemakerCreate a value of {" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:{, {# - The response's http status code.{, {= - The Amazon Resource Name (ARN) of the model package group.{amazonka-sagemaker The response's http status code.{amazonka-sagemaker:The Amazon Resource Name (ARN) of the model package group.{amazonka-sagemaker{amazonka-sagemaker{{amazonka-sagemaker{amazonka-sagemaker{{{{{{{{{{{{{{{{{{{{{{{{{{{{{(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';]{amazonka-sagemakerSee: { smart constructor.{amazonka-sagemakerIf the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of work teams, use it in the subsequent request.{amazonka-sagemaker The response's http status code.{amazonka-sagemaker An array of Workteam& objects, each describing a work team.{amazonka-sagemakerSee: { smart constructor.{amazonka-sagemakerThe maximum number of work teams to return in each page of the response.{amazonka-sagemakerA string in the work team's name. This filter returns only work teams whose name contains the specified string.{amazonka-sagemakerIf the result of the previous  ListWorkteams1 request was truncated, the response includes a  NextToken. To retrieve the next set of labeling jobs, use the token in the next request.{amazonka-sagemaker-The field to sort results by. The default is  CreationTime.{amazonka-sagemaker+The sort order for results. The default is  Ascending.{amazonka-sagemakerCreate a value of {" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:{, { - The maximum number of work teams to return in each page of the response.{, { - A string in the work team's name. This filter returns only work teams whose name contains the specified string.{, {! - If the result of the previous  ListWorkteams1 request was truncated, the response includes a  NextToken. To retrieve the next set of labeling jobs, use the token in the next request.{, {0 - The field to sort results by. The default is  CreationTime.{, {. - The sort order for results. The default is  Ascending.{amazonka-sagemakerThe maximum number of work teams to return in each page of the response.{amazonka-sagemakerA string in the work team's name. This filter returns only work teams whose name contains the specified string.{amazonka-sagemakerIf the result of the previous  ListWorkteams1 request was truncated, the response includes a  NextToken. To retrieve the next set of labeling jobs, use the token in the next request.{amazonka-sagemaker-The field to sort results by. The default is  CreationTime.{amazonka-sagemaker+The sort order for results. The default is  Ascending.{amazonka-sagemakerCreate a value of {" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:{, { - If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of work teams, use it in the subsequent request.{, {# - The response's http status code.{, { - An array of Workteam& objects, each describing a work team.{amazonka-sagemakerIf the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of work teams, use it in the subsequent request.{amazonka-sagemaker The response's http status code.{amazonka-sagemaker An array of Workteam& objects, each describing a work team.{amazonka-sagemaker{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';߻{amazonka-sagemakerSee: { smart constructor.{amazonka-sagemakerA token to resume pagination.{amazonka-sagemaker The response's http status code.{amazonka-sagemaker3A list containing information about your workforce.{amazonka-sagemakerSee: { smart constructor.{amazonka-sagemaker:The maximum number of workforces returned in the response.{amazonka-sagemakerA filter you can use to search for workforces using part of the workforce name.{amazonka-sagemakerA token to resume pagination.{amazonka-sagemaker:Sort workforces using the workforce name or creation date.{amazonka-sagemaker1Sort workforces in ascending or descending order.{amazonka-sagemakerCreate a value of {" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:{, {= - The maximum number of workforces returned in the response.{, { - A filter you can use to search for workforces using part of the workforce name.{, { - A token to resume pagination.{, {= - Sort workforces using the workforce name or creation date.{, {4 - Sort workforces in ascending or descending order.{amazonka-sagemaker:The maximum number of workforces returned in the response.{amazonka-sagemakerA filter you can use to search for workforces using part of the workforce name.{amazonka-sagemakerA token to resume pagination.{amazonka-sagemaker:Sort workforces using the workforce name or creation date.{amazonka-sagemaker1Sort workforces in ascending or descending order.{amazonka-sagemakerCreate a value of {" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:{, { - A token to resume pagination.{, {# - The response's http status code.{, {6 - A list containing information about your workforce.{amazonka-sagemakerA token to resume pagination.{amazonka-sagemaker The response's http status code.{amazonka-sagemaker3A list containing information about your workforce.{amazonka-sagemaker{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';|amazonka-sagemakerSee: | smart constructor.|amazonka-sagemakerIf the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.|amazonka-sagemakerThe list of user profiles.|amazonka-sagemaker The response's http status code.|amazonka-sagemakerSee: | smart constructor.|amazonka-sagemaker+A parameter by which to filter the results.|amazonka-sagemaker'Returns a list up to a specified limit.|amazonka-sagemakerIf the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.|amazonka-sagemakerThe parameter by which to sort the results. The default is CreationTime.|amazonka-sagemaker9The sort order for the results. The default is Ascending.|amazonka-sagemaker+A parameter by which to filter the results.|amazonka-sagemakerCreate a value of |" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:|, |. - A parameter by which to filter the results.|, |* - Returns a list up to a specified limit.|, | - If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.|, | - The parameter by which to sort the results. The default is CreationTime.|, |< - The sort order for the results. The default is Ascending.|, |. - A parameter by which to filter the results.|amazonka-sagemaker+A parameter by which to filter the results.|amazonka-sagemaker'Returns a list up to a specified limit.|amazonka-sagemakerIf the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.|amazonka-sagemakerThe parameter by which to sort the results. The default is CreationTime.|amazonka-sagemaker9The sort order for the results. The default is Ascending.|amazonka-sagemaker+A parameter by which to filter the results.|amazonka-sagemakerCreate a value of |" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:|, | - If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.|, | - The list of user profiles.|, |# - The response's http status code.|amazonka-sagemakerIf the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.|amazonka-sagemakerThe list of user profiles.|amazonka-sagemaker The response's http status code.|amazonka-sagemaker|||||||||||||||||||||||||||||||||||||||||||||||||(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';|amazonka-sagemakerSee: | smart constructor.|amazonka-sagemaker=A token for getting the next set of trials, if there are any.|amazonka-sagemaker'A list of the summaries of your trials.|amazonka-sagemaker The response's http status code.|amazonka-sagemakerSee: | smart constructor.|amazonka-sagemakerA filter that returns only trials created after the specified time.|amazonka-sagemakerA filter that returns only trials created before the specified time.|amazonka-sagemakerA filter that returns only trials that are part of the specified experiment.|amazonka-sagemakerThe maximum number of trials to return in the response. The default value is 10.|amazonka-sagemakerIf the previous call to  ListTrials didn't return the full set of trials, the call returns a token for getting the next set of trials.|amazonka-sagemaker8The property used to sort results. The default value is  CreationTime.|amazonka-sagemaker%The sort order. The default value is  Descending.|amazonka-sagemakerA filter that returns only trials that are associated with the specified trial component.|amazonka-sagemakerCreate a value of |" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:|, | - A filter that returns only trials created after the specified time.|, | - A filter that returns only trials created before the specified time.|, | - A filter that returns only trials that are part of the specified experiment.|, | - The maximum number of trials to return in the response. The default value is 10.|, | - If the previous call to  ListTrials didn't return the full set of trials, the call returns a token for getting the next set of trials.|, |; - The property used to sort results. The default value is  CreationTime.|, |( - The sort order. The default value is  Descending.|, | - A filter that returns only trials that are associated with the specified trial component.|amazonka-sagemakerA filter that returns only trials created after the specified time.|amazonka-sagemakerA filter that returns only trials created before the specified time.|amazonka-sagemakerA filter that returns only trials that are part of the specified experiment.|amazonka-sagemakerThe maximum number of trials to return in the response. The default value is 10.|amazonka-sagemakerIf the previous call to  ListTrials didn't return the full set of trials, the call returns a token for getting the next set of trials.|amazonka-sagemaker8The property used to sort results. The default value is  CreationTime.|amazonka-sagemaker%The sort order. The default value is  Descending.|amazonka-sagemakerA filter that returns only trials that are associated with the specified trial component.|amazonka-sagemakerCreate a value of |" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:|, | - A token for getting the next set of trials, if there are any.|, |* - A list of the summaries of your trials.|, |# - The response's http status code.|amazonka-sagemaker=A token for getting the next set of trials, if there are any.|amazonka-sagemaker'A list of the summaries of your trials.|amazonka-sagemaker The response's http status code.|amazonka-sagemaker|||||||||||||||||||||||||||||||||||||||||||||||||||||||||(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';|amazonka-sagemakerSee: } smart constructor.|amazonka-sagemakerA token for getting the next set of components, if there are any.|amazonka-sagemaker1A list of the summaries of your trial components.|amazonka-sagemaker The response's http status code.|amazonka-sagemakerSee: | smart constructor.|amazonka-sagemakerA filter that returns only components created after the specified time.|amazonka-sagemakerA filter that returns only components created before the specified time.|amazonka-sagemakerA filter that returns only components that are part of the specified experiment. If you specify ExperimentName, you can't filter by  SourceArn or  TrialName.|amazonka-sagemakerThe maximum number of components to return in the response. The default value is 10.|amazonka-sagemakerIf the previous call to ListTrialComponents didn't return the full set of components, the call returns a token for getting the next set of components.|amazonka-sagemaker8The property used to sort results. The default value is  CreationTime.|amazonka-sagemaker%The sort order. The default value is  Descending.|amazonka-sagemakerA filter that returns only components that have the specified source Amazon Resource Name (ARN). If you specify  SourceArn, you can't filter by ExperimentName or  TrialName.|amazonka-sagemakerA filter that returns only components that are part of the specified trial. If you specify  TrialName, you can't filter by ExperimentName or  SourceArn.|amazonka-sagemakerCreate a value of |" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:|, | - A filter that returns only components created after the specified time.|, | - A filter that returns only components created before the specified time.|, | - A filter that returns only components that are part of the specified experiment. If you specify ExperimentName, you can't filter by  SourceArn or  TrialName.|, | - The maximum number of components to return in the response. The default value is 10.|, | - If the previous call to ListTrialComponents didn't return the full set of components, the call returns a token for getting the next set of components.|, |; - The property used to sort results. The default value is  CreationTime.|, |( - The sort order. The default value is  Descending.|, | - A filter that returns only components that have the specified source Amazon Resource Name (ARN). If you specify  SourceArn, you can't filter by ExperimentName or  TrialName.|, | - A filter that returns only components that are part of the specified trial. If you specify  TrialName, you can't filter by ExperimentName or  SourceArn.|amazonka-sagemakerA filter that returns only components created after the specified time.|amazonka-sagemakerA filter that returns only components created before the specified time.|amazonka-sagemakerA filter that returns only components that are part of the specified experiment. If you specify ExperimentName, you can't filter by  SourceArn or  TrialName.|amazonka-sagemakerThe maximum number of components to return in the response. The default value is 10.|amazonka-sagemakerIf the previous call to ListTrialComponents didn't return the full set of components, the call returns a token for getting the next set of components.|amazonka-sagemaker8The property used to sort results. The default value is  CreationTime.|amazonka-sagemaker%The sort order. The default value is  Descending.|amazonka-sagemakerA filter that returns only components that have the specified source Amazon Resource Name (ARN). If you specify  SourceArn, you can't filter by ExperimentName or  TrialName.|amazonka-sagemakerA filter that returns only components that are part of the specified trial. If you specify  TrialName, you can't filter by ExperimentName or  SourceArn.}amazonka-sagemakerCreate a value of |" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:|, } - A token for getting the next set of components, if there are any.|, }4 - A list of the summaries of your trial components.|, }# - The response's http status code.}amazonka-sagemakerA token for getting the next set of components, if there are any.}amazonka-sagemaker1A list of the summaries of your trial components.}amazonka-sagemaker The response's http status code.}amazonka-sagemaker|||||||||||||||||||||||||||}}}}||||||||||||||||||||||||||}}}}(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';*}amazonka-sagemakerSee: } smart constructor.}amazonka-sagemakerIf the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of transform jobs, use it in the next request.}amazonka-sagemaker The response's http status code.}amazonka-sagemaker An array of TransformJobSummary objects.}amazonka-sagemakerSee: } smart constructor.}amazonka-sagemakerA filter that returns only transform jobs created after the specified time.}amazonka-sagemakerA filter that returns only transform jobs created before the specified time.}amazonka-sagemakerA filter that returns only transform jobs modified after the specified time.}amazonka-sagemakerA filter that returns only transform jobs modified before the specified time.}amazonka-sagemakerThe maximum number of transform jobs to return in the response. The default value is 10.}amazonka-sagemakerA string in the transform job name. This filter returns only transform jobs whose name contains the specified string.}amazonka-sagemakerIf the result of the previous ListTransformJobs1 request was truncated, the response includes a  NextToken. To retrieve the next set of transform jobs, use the token in the next request.}amazonka-sagemaker-The field to sort results by. The default is  CreationTime.}amazonka-sagemaker+The sort order for results. The default is  Descending.}amazonka-sagemakerA filter that retrieves only transform jobs with a specific status.}amazonka-sagemakerCreate a value of }" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:}, } - A filter that returns only transform jobs created after the specified time.}, } - A filter that returns only transform jobs created before the specified time.}, } - A filter that returns only transform jobs modified after the specified time.}, } - A filter that returns only transform jobs modified before the specified time.}, } - The maximum number of transform jobs to return in the response. The default value is 10.}, } - A string in the transform job name. This filter returns only transform jobs whose name contains the specified string.}, }! - If the result of the previous ListTransformJobs1 request was truncated, the response includes a  NextToken. To retrieve the next set of transform jobs, use the token in the next request.}, }0 - The field to sort results by. The default is  CreationTime.}, }. - The sort order for results. The default is  Descending.}, } - A filter that retrieves only transform jobs with a specific status.}amazonka-sagemakerA filter that returns only transform jobs created after the specified time.}amazonka-sagemakerA filter that returns only transform jobs created before the specified time.}amazonka-sagemakerA filter that returns only transform jobs modified after the specified time.}amazonka-sagemakerA filter that returns only transform jobs modified before the specified time.}amazonka-sagemakerThe maximum number of transform jobs to return in the response. The default value is 10.}amazonka-sagemakerA string in the transform job name. This filter returns only transform jobs whose name contains the specified string.}amazonka-sagemakerIf the result of the previous ListTransformJobs1 request was truncated, the response includes a  NextToken. To retrieve the next set of transform jobs, use the token in the next request.}amazonka-sagemaker-The field to sort results by. The default is  CreationTime.}amazonka-sagemaker+The sort order for results. The default is  Descending.}amazonka-sagemakerA filter that retrieves only transform jobs with a specific status.}amazonka-sagemakerCreate a value of }" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:}, } - If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of transform jobs, use it in the next request.}, }# - The response's http status code.}, } - An array of TransformJobSummary objects.}amazonka-sagemakerIf the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of transform jobs, use it in the next request.}amazonka-sagemaker The response's http status code.}amazonka-sagemaker An array of TransformJobSummary objects.}amazonka-sagemaker} }}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}} }}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';>}amazonka-sagemakerSee: } smart constructor.}amazonka-sagemakerIf the result of this *ListTrainingJobsForHyperParameterTuningJob1 request was truncated, the response includes a  NextToken. To retrieve the next set of training jobs, use the token in the next request.}amazonka-sagemaker The response's http status code.}amazonka-sagemakerA list of TrainingJobSummary objects that describe the training jobs that the *ListTrainingJobsForHyperParameterTuningJob request returned.}amazonka-sagemakerSee: } smart constructor.}amazonka-sagemakerThe maximum number of training jobs to return. The default value is 10.}amazonka-sagemakerIf the result of the previous *ListTrainingJobsForHyperParameterTuningJob1 request was truncated, the response includes a  NextToken. To retrieve the next set of training jobs, use the token in the next request.}amazonka-sagemaker-The field to sort results by. The default is Name.If the value of this field is FinalObjectiveMetricValue, any training jobs that did not return an objective metric are not listed.}amazonka-sagemaker+The sort order for results. The default is  Ascending.}amazonka-sagemakerA filter that returns only training jobs with the specified status.}amazonka-sagemakerThe name of the tuning job whose training jobs you want to list.}amazonka-sagemakerCreate a value of }" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:}, } - The maximum number of training jobs to return. The default value is 10.}, }" - If the result of the previous *ListTrainingJobsForHyperParameterTuningJob1 request was truncated, the response includes a  NextToken. To retrieve the next set of training jobs, use the token in the next request.}, }0 - The field to sort results by. The default is Name.If the value of this field is FinalObjectiveMetricValue, any training jobs that did not return an objective metric are not listed.}, }. - The sort order for results. The default is  Ascending.}, } - A filter that returns only training jobs with the specified status.}, } - The name of the tuning job whose training jobs you want to list.}amazonka-sagemakerThe maximum number of training jobs to return. The default value is 10.}amazonka-sagemakerIf the result of the previous *ListTrainingJobsForHyperParameterTuningJob1 request was truncated, the response includes a  NextToken. To retrieve the next set of training jobs, use the token in the next request.}amazonka-sagemaker-The field to sort results by. The default is Name.If the value of this field is FinalObjectiveMetricValue, any training jobs that did not return an objective metric are not listed.}amazonka-sagemaker+The sort order for results. The default is  Ascending.}amazonka-sagemakerA filter that returns only training jobs with the specified status.}amazonka-sagemakerThe name of the tuning job whose training jobs you want to list.}amazonka-sagemakerCreate a value of }" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:}, } - If the result of this *ListTrainingJobsForHyperParameterTuningJob1 request was truncated, the response includes a  NextToken. To retrieve the next set of training jobs, use the token in the next request.}, }# - The response's http status code.}, } - A list of TrainingJobSummary objects that describe the training jobs that the *ListTrainingJobsForHyperParameterTuningJob request returned.}amazonka-sagemakerIf the result of this *ListTrainingJobsForHyperParameterTuningJob1 request was truncated, the response includes a  NextToken. To retrieve the next set of training jobs, use the token in the next request.}amazonka-sagemaker The response's http status code.}amazonka-sagemakerA list of TrainingJobSummary objects that describe the training jobs that the *ListTrainingJobsForHyperParameterTuningJob request returned.}amazonka-sagemaker}}amazonka-sagemaker}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';V0 }amazonka-sagemakerSee: ~ smart constructor.}amazonka-sagemakerIf the response is truncated, SageMaker returns this token. To retrieve the next set of training jobs, use it in the subsequent request.}amazonka-sagemaker The response's http status code.}amazonka-sagemaker An array of TrainingJobSummary& objects, each listing a training job.}amazonka-sagemakerSee: ~ smart constructor.}amazonka-sagemakerA filter that returns only training jobs created after the specified time (timestamp).}amazonka-sagemakerA filter that returns only training jobs created before the specified time (timestamp).}amazonka-sagemakerA filter that returns only training jobs modified after the specified time (timestamp).}amazonka-sagemakerA filter that returns only training jobs modified before the specified time (timestamp).}amazonka-sagemaker>The maximum number of training jobs to return in the response.}amazonka-sagemakerA string in the training job name. This filter returns only training jobs whose name contains the specified string.}amazonka-sagemakerIf the result of the previous ListTrainingJobs1 request was truncated, the response includes a  NextToken. To retrieve the next set of training jobs, use the token in the next request.}amazonka-sagemaker-The field to sort results by. The default is  CreationTime.}amazonka-sagemaker+The sort order for results. The default is  Ascending.}amazonka-sagemakerA filter that retrieves only training jobs with a specific status.~amazonka-sagemakerA filter that retrieves only training jobs with a specific warm pool status.~amazonka-sagemakerCreate a value of }" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:}, ~ - A filter that returns only training jobs created after the specified time (timestamp).}, ~ - A filter that returns only training jobs created before the specified time (timestamp).}, ~ - A filter that returns only training jobs modified after the specified time (timestamp).}, ~ - A filter that returns only training jobs modified before the specified time (timestamp).}, ~ - The maximum number of training jobs to return in the response.}, ~ - A string in the training job name. This filter returns only training jobs whose name contains the specified string.}, ~! - If the result of the previous ListTrainingJobs1 request was truncated, the response includes a  NextToken. To retrieve the next set of training jobs, use the token in the next request.}, ~0 - The field to sort results by. The default is  CreationTime.}, ~. - The sort order for results. The default is  Ascending.}, ~ - A filter that retrieves only training jobs with a specific status.~, ~ - A filter that retrieves only training jobs with a specific warm pool status.~amazonka-sagemakerA filter that returns only training jobs created after the specified time (timestamp).~amazonka-sagemakerA filter that returns only training jobs created before the specified time (timestamp).~amazonka-sagemakerA filter that returns only training jobs modified after the specified time (timestamp).~amazonka-sagemakerA filter that returns only training jobs modified before the specified time (timestamp).~amazonka-sagemaker>The maximum number of training jobs to return in the response.~amazonka-sagemakerA string in the training job name. This filter returns only training jobs whose name contains the specified string.~amazonka-sagemakerIf the result of the previous ListTrainingJobs1 request was truncated, the response includes a  NextToken. To retrieve the next set of training jobs, use the token in the next request.~amazonka-sagemaker-The field to sort results by. The default is  CreationTime.~amazonka-sagemaker+The sort order for results. The default is  Ascending.~amazonka-sagemakerA filter that retrieves only training jobs with a specific status.~amazonka-sagemakerA filter that retrieves only training jobs with a specific warm pool status.~amazonka-sagemakerCreate a value of }" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:}, ~ - If the response is truncated, SageMaker returns this token. To retrieve the next set of training jobs, use it in the subsequent request.}, ~# - The response's http status code.}, ~ - An array of TrainingJobSummary& objects, each listing a training job.~amazonka-sagemakerIf the response is truncated, SageMaker returns this token. To retrieve the next set of training jobs, use it in the subsequent request.~amazonka-sagemaker The response's http status code.~amazonka-sagemaker An array of TrainingJobSummary& objects, each listing a training job.~amazonka-sagemaker}"}}}}}}}}}}}}}}}}}~~~~~~~~~~~~~~~~~"}}}}}}}}}}}}~~~~~~~~~~~~~}}}}}~~~~(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';b~amazonka-sagemakerSee: ~ smart constructor.~amazonka-sagemakerIf response is truncated, SageMaker includes a token in the response. You can use this token in your subsequent request to fetch next set of tokens.~amazonka-sagemaker An array of Tag* objects, each with a tag key and a value.~amazonka-sagemaker The response's http status code.~amazonka-sagemakerSee: ~ smart constructor.~amazonka-sagemaker!Maximum number of tags to return.~amazonka-sagemaker If the response to the previous ListTags request is truncated, SageMaker returns this token. To retrieve the next set of tags, use it in the subsequent request.~amazonka-sagemakerThe Amazon Resource Name (ARN) of the resource whose tags you want to retrieve.~amazonka-sagemakerCreate a value of ~" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:~, ~$ - Maximum number of tags to return.~, ~# - If the response to the previous ListTags request is truncated, SageMaker returns this token. To retrieve the next set of tags, use it in the subsequent request.~, ~ - The Amazon Resource Name (ARN) of the resource whose tags you want to retrieve.~amazonka-sagemaker!Maximum number of tags to return.~amazonka-sagemaker If the response to the previous ListTags request is truncated, SageMaker returns this token. To retrieve the next set of tags, use it in the subsequent request.~amazonka-sagemakerThe Amazon Resource Name (ARN) of the resource whose tags you want to retrieve.~amazonka-sagemakerCreate a value of ~" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:~, ~ - If response is truncated, SageMaker includes a token in the response. You can use this token in your subsequent request to fetch next set of tokens.~, ~ - An array of Tag* objects, each with a tag key and a value.~, ~# - The response's http status code.~amazonka-sagemakerIf response is truncated, SageMaker includes a token in the response. You can use this token in your subsequent request to fetch next set of tokens.~amazonka-sagemaker An array of Tag* objects, each with a tag key and a value.~amazonka-sagemaker The response's http status code.~amazonka-sagemaker~~amazonka-sagemaker~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';p~amazonka-sagemakerSee: ~ smart constructor.~amazonka-sagemakerIf the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of work teams, use it in the subsequent request.~amazonka-sagemaker The response's http status code.~amazonka-sagemaker An array of Workteam& objects, each describing a work team.~amazonka-sagemakerSee: ~ smart constructor.~amazonka-sagemakerThe maximum number of work teams to return in each page of the response.~amazonka-sagemakerA string in the work team name. This filter returns only work teams whose name contains the specified string.~amazonka-sagemakerIf the result of the previous ListSubscribedWorkteams1 request was truncated, the response includes a  NextToken. To retrieve the next set of labeling jobs, use the token in the next request.~amazonka-sagemakerCreate a value of ~" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:~, ~ - The maximum number of work teams to return in each page of the response.~, ~ - A string in the work team name. This filter returns only work teams whose name contains the specified string.~, ~! - If the result of the previous ListSubscribedWorkteams1 request was truncated, the response includes a  NextToken. To retrieve the next set of labeling jobs, use the token in the next request.~amazonka-sagemakerThe maximum number of work teams to return in each page of the response.~amazonka-sagemakerA string in the work team name. This filter returns only work teams whose name contains the specified string.~amazonka-sagemakerIf the result of the previous ListSubscribedWorkteams1 request was truncated, the response includes a  NextToken. To retrieve the next set of labeling jobs, use the token in the next request.~amazonka-sagemakerCreate a value of ~" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:~, ~ - If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of work teams, use it in the subsequent request.~, ~# - The response's http status code.~, ~ - An array of Workteam& objects, each describing a work team.~amazonka-sagemakerIf the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of work teams, use it in the subsequent request.~amazonka-sagemaker The response's http status code.~amazonka-sagemaker An array of Workteam& objects, each describing a work team.~amazonka-sagemaker~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';L~amazonka-sagemakerSee:  smart constructor.~amazonka-sagemaker>A token for getting the next set of actions, if there are any.~amazonka-sagemaker8A list of Lifecycle Configurations and their properties.~amazonka-sagemaker The response's http status code.~amazonka-sagemakerSee: ~ smart constructor.~amazonka-sagemakerA parameter to search for the App Type to which the Lifecycle Configuration is attached.~amazonka-sagemakerA filter that returns only Lifecycle Configurations created on or after the specified time.~amazonka-sagemakerA filter that returns only Lifecycle Configurations created on or before the specified time.~amazonka-sagemakerThe maximum number of Studio Lifecycle Configurations to return in the response. The default value is 10.~amazonka-sagemakerA filter that returns only Lifecycle Configurations modified after the specified time.~amazonka-sagemakerA filter that returns only Lifecycle Configurations modified before the specified time.~amazonka-sagemakerA string in the Lifecycle Configuration name. This filter returns only Lifecycle Configurations whose name contains the specified string.~amazonka-sagemakerIf the previous call to ListStudioLifecycleConfigs didn't return the full set of Lifecycle Configurations, the call returns a token for getting the next set of Lifecycle Configurations.~amazonka-sagemakerThe property used to sort results. The default value is CreationTime.~amazonka-sagemaker0The sort order. The default value is Descending.~amazonka-sagemakerCreate a value of ~" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:~, ~ - A parameter to search for the App Type to which the Lifecycle Configuration is attached.~, ~ - A filter that returns only Lifecycle Configurations created on or after the specified time.~, ~ - A filter that returns only Lifecycle Configurations created on or before the specified time.~, ~ - The maximum number of Studio Lifecycle Configurations to return in the response. The default value is 10.~, ~ - A filter that returns only Lifecycle Configurations modified after the specified time.~, ~ - A filter that returns only Lifecycle Configurations modified before the specified time.~,  - A string in the Lifecycle Configuration name. This filter returns only Lifecycle Configurations whose name contains the specified string.~,  - If the previous call to ListStudioLifecycleConfigs didn't return the full set of Lifecycle Configurations, the call returns a token for getting the next set of Lifecycle Configurations.~,  - The property used to sort results. The default value is CreationTime.~, 3 - The sort order. The default value is Descending.~amazonka-sagemakerA parameter to search for the App Type to which the Lifecycle Configuration is attached.~amazonka-sagemakerA filter that returns only Lifecycle Configurations created on or after the specified time.~amazonka-sagemakerA filter that returns only Lifecycle Configurations created on or before the specified time.~amazonka-sagemakerThe maximum number of Studio Lifecycle Configurations to return in the response. The default value is 10.~amazonka-sagemakerA filter that returns only Lifecycle Configurations modified after the specified time.~amazonka-sagemakerA filter that returns only Lifecycle Configurations modified before the specified time.amazonka-sagemakerA string in the Lifecycle Configuration name. This filter returns only Lifecycle Configurations whose name contains the specified string.amazonka-sagemakerIf the previous call to ListStudioLifecycleConfigs didn't return the full set of Lifecycle Configurations, the call returns a token for getting the next set of Lifecycle Configurations.amazonka-sagemakerThe property used to sort results. The default value is CreationTime.amazonka-sagemaker0The sort order. The default value is Descending.amazonka-sagemakerCreate a value of ~" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:~,  - A token for getting the next set of actions, if there are any.~, ; - A list of Lifecycle Configurations and their properties.~, # - The response's http status code.amazonka-sagemaker>A token for getting the next set of actions, if there are any.amazonka-sagemaker8A list of Lifecycle Configurations and their properties.amazonka-sagemaker The response's http status code.amazonka-sagemaker~ ~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~~~~~~~(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';,amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker7The token to use when calling the next page of results.amazonka-sagemaker The response's http status code.amazonka-sagemaker4List of summaries of devices allocated to the stage.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker6Toggle for excluding devices deployed in other stages.amazonka-sagemaker)The maximum number of requests to select.amazonka-sagemakerThe response from the last list when returning a list large enough to neeed tokening.amazonka-sagemaker%The name of the edge deployment plan.amazonka-sagemaker(The name of the stage in the deployment.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 9 - Toggle for excluding devices deployed in other stages., , - The maximum number of requests to select.,  - The response from the last list when returning a list large enough to neeed tokening., ( - The name of the edge deployment plan., + - The name of the stage in the deployment.amazonka-sagemaker6Toggle for excluding devices deployed in other stages.amazonka-sagemaker)The maximum number of requests to select.amazonka-sagemakerThe response from the last list when returning a list large enough to neeed tokening.amazonka-sagemaker%The name of the edge deployment plan.amazonka-sagemaker(The name of the stage in the deployment.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, : - The token to use when calling the next page of results., # - The response's http status code., 7 - List of summaries of devices allocated to the stage.amazonka-sagemaker7The token to use when calling the next page of results.amazonka-sagemaker The response's http status code.amazonka-sagemaker4List of summaries of devices allocated to the stage.amazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';&amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerIf the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.amazonka-sagemakerThe list of spaces.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker(A parameter to search for the Domain ID.amazonka-sagemaker'Returns a list up to a specified limit.amazonka-sagemakerIf the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.amazonka-sagemaker - The maximum number of parameters to return in the response., ! - If the result of the previous "ListPipelineParametersForExecution1 request was truncated, the response includes a  NextToken. To retrieve the next set of parameters, use the token in the next request., < - The Amazon Resource Name (ARN) of the pipeline execution.amazonka-sagemaker;The maximum number of parameters to return in the response.amazonka-sagemakerIf the result of the previous "ListPipelineParametersForExecution1 request was truncated, the response includes a  NextToken. To retrieve the next set of parameters, use the token in the next request.amazonka-sagemaker9The Amazon Resource Name (ARN) of the pipeline execution.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, ! - If the result of the previous "ListPipelineParametersForExecution1 request was truncated, the response includes a  NextToken. To retrieve the next set of parameters, use the token in the next request.,  - Contains a list of pipeline parameters. This list can be empty., # - The response's http status code.amazonka-sagemakerIf the result of the previous "ListPipelineParametersForExecution1 request was truncated, the response includes a  NextToken. To retrieve the next set of parameters, use the token in the next request.amazonka-sagemaker?Contains a list of pipeline parameters. This list can be empty.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerIf the result of the previous ListPipelineExecutions1 request was truncated, the response includes a  NextToken. To retrieve the next set of pipeline executions, use the token in the next request.amazonka-sagemakerContains a sorted list of pipeline execution summary objects matching the specified filters. Each run summary includes the Amazon Resource Name (ARN) of the pipeline execution, the run date, and the status. This list can be empty.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerA filter that returns the pipeline executions that were created after a specified time.amazonka-sagemakerA filter that returns the pipeline executions that were created before a specified time.amazonka-sagemakerThe maximum number of pipeline executions to return in the response.amazonka-sagemakerIf the result of the previous ListPipelineExecutions1 request was truncated, the response includes a  NextToken. To retrieve the next set of pipeline executions, use the token in the next request.amazonka-sagemaker3The field by which to sort results. The default is  CreatedTime.amazonka-sagemakerThe sort order for results.amazonka-sagemakerThe name of the pipeline.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - A filter that returns the pipeline executions that were created after a specified time.,  - A filter that returns the pipeline executions that were created before a specified time.,  - The maximum number of pipeline executions to return in the response., ! - If the result of the previous ListPipelineExecutions1 request was truncated, the response includes a  NextToken. To retrieve the next set of pipeline executions, use the token in the next request., 6 - The field by which to sort results. The default is  CreatedTime.,  - The sort order for results.,  - The name of the pipeline.amazonka-sagemakerA filter that returns the pipeline executions that were created after a specified time.amazonka-sagemakerA filter that returns the pipeline executions that were created before a specified time.amazonka-sagemakerThe maximum number of pipeline executions to return in the response.amazonka-sagemakerIf the result of the previous ListPipelineExecutions1 request was truncated, the response includes a  NextToken. To retrieve the next set of pipeline executions, use the token in the next request.amazonka-sagemaker3The field by which to sort results. The default is  CreatedTime.amazonka-sagemakerThe sort order for results.amazonka-sagemakerThe name of the pipeline.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, ! - If the result of the previous ListPipelineExecutions1 request was truncated, the response includes a  NextToken. To retrieve the next set of pipeline executions, use the token in the next request.,  - Contains a sorted list of pipeline execution summary objects matching the specified filters. Each run summary includes the Amazon Resource Name (ARN) of the pipeline execution, the run date, and the status. This list can be empty., # - The response's http status code.amazonka-sagemakerIf the result of the previous ListPipelineExecutions1 request was truncated, the response includes a  NextToken. To retrieve the next set of pipeline executions, use the token in the next request.amazonka-sagemakerContains a sorted list of pipeline execution summary objects matching the specified filters. Each run summary includes the Amazon Resource Name (ARN) of the pipeline execution, the run date, and the status. This list can be empty.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';amazonka-sagemakerSee: ́ smart constructor.amazonka-sagemakerIf the result of the previous ListPipelineExecutionSteps1 request was truncated, the response includes a  NextToken. To retrieve the next set of pipeline execution steps, use the token in the next request.amazonka-sagemaker A list of PipeLineExecutionStep objects. Each PipeLineExecutionStep consists of StepName, StartTime, EndTime, StepStatus, and Metadata. Metadata is an object with properties for each job that contains relevant information about the job created by the step.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee: ȁ smart constructor.āamazonka-sagemakerThe maximum number of pipeline execution steps to return in the response.Łamazonka-sagemakerIf the result of the previous ListPipelineExecutionSteps1 request was truncated, the response includes a  NextToken. To retrieve the next set of pipeline execution steps, use the token in the next request.Ɓamazonka-sagemaker9The Amazon Resource Name (ARN) of the pipeline execution.ǁamazonka-sagemaker3The field by which to sort results. The default is  CreatedTime.ȁamazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:ā, Ɂ - The maximum number of pipeline execution steps to return in the response., ʁ! - If the result of the previous ListPipelineExecutionSteps1 request was truncated, the response includes a  NextToken. To retrieve the next set of pipeline execution steps, use the token in the next request., ˁ< - The Amazon Resource Name (ARN) of the pipeline execution.ǁ, ́6 - The field by which to sort results. The default is  CreatedTime.Ɂamazonka-sagemakerThe maximum number of pipeline execution steps to return in the response.ʁamazonka-sagemakerIf the result of the previous ListPipelineExecutionSteps1 request was truncated, the response includes a  NextToken. To retrieve the next set of pipeline execution steps, use the token in the next request.ˁamazonka-sagemaker9The Amazon Resource Name (ARN) of the pipeline execution.́amazonka-sagemaker3The field by which to sort results. The default is  CreatedTime.́amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, ΁! - If the result of the previous ListPipelineExecutionSteps1 request was truncated, the response includes a  NextToken. To retrieve the next set of pipeline execution steps, use the token in the next request., ρ - A list of PipeLineExecutionStep objects. Each PipeLineExecutionStep consists of StepName, StartTime, EndTime, StepStatus, and Metadata. Metadata is an object with properties for each job that contains relevant information about the job created by the step., Ё# - The response's http status code.΁amazonka-sagemakerIf the result of the previous ListPipelineExecutionSteps1 request was truncated, the response includes a  NextToken. To retrieve the next set of pipeline execution steps, use the token in the next request.ρamazonka-sagemaker A list of PipeLineExecutionStep objects. Each PipeLineExecutionStep consists of StepName, StartTime, EndTime, StepStatus, and Metadata. Metadata is an object with properties for each job that contains relevant information about the job created by the step.Ёamazonka-sagemaker The response's http status code.́amazonka-sagemakerÁƁāŁǁȁɁʁˁ́́΁ρЁÁƁāŁǁȁɁʁˁ́́΁ρЁ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';2a$amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker If the response to the previous ListNotebookInstances request was truncated, SageMaker returns this token. To retrieve the next set of notebook instances, use the token in the next request.amazonka-sagemaker An array of NotebookInstanceSummary* objects, one for each notebook instance.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerA filter that returns only notebook instances with associated with the specified git repository.amazonka-sagemakerA filter that returns only notebook instances that were created after the specified time (timestamp).amazonka-sagemakerA filter that returns only notebook instances that were created before the specified time (timestamp).amazonka-sagemakerA string in the name or URL of a Git repository associated with this notebook instance. This filter returns only notebook instances associated with a git repository with a name that contains the specified string.amazonka-sagemakerA filter that returns only notebook instances that were modified after the specified time (timestamp).amazonka-sagemakerA filter that returns only notebook instances that were modified before the specified time (timestamp).amazonka-sagemaker3The maximum number of notebook instances to return.amazonka-sagemakerA string in the notebook instances' name. This filter returns only notebook instances whose name contains the specified string.amazonka-sagemakerIf the previous call to the ListNotebookInstances( is truncated, the response includes a  NextToken-. You can use this token in your subsequent ListNotebookInstances6 request to fetch the next set of notebook instances.You might specify a filter or a sort order in your request. When response is truncated, you must use the same values for the filer and sort order in the next request.amazonka-sagemakerA string in the name of a notebook instances lifecycle configuration associated with this notebook instance. This filter returns only notebook instances associated with a lifecycle configuration with a name that contains the specified string.amazonka-sagemaker-The field to sort results by. The default is Name.amazonka-sagemakerThe sort order for results.amazonka-sagemakerA filter that returns only notebook instances with the specified status.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - A filter that returns only notebook instances with associated with the specified git repository.,  - A filter that returns only notebook instances that were created after the specified time (timestamp).,  - A filter that returns only notebook instances that were created before the specified time (timestamp).,  - A string in the name or URL of a Git repository associated with this notebook instance. This filter returns only notebook instances associated with a git repository with a name that contains the specified string.,  - A filter that returns only notebook instances that were modified after the specified time (timestamp).,  - A filter that returns only notebook instances that were modified before the specified time (timestamp)., 6 - The maximum number of notebook instances to return.,  - A string in the notebook instances' name. This filter returns only notebook instances whose name contains the specified string.,  - If the previous call to the ListNotebookInstances( is truncated, the response includes a  NextToken-. You can use this token in your subsequent ListNotebookInstances6 request to fetch the next set of notebook instances.You might specify a filter or a sort order in your request. When response is truncated, you must use the same values for the filer and sort order in the next request.,  - A string in the name of a notebook instances lifecycle configuration associated with this notebook instance. This filter returns only notebook instances associated with a lifecycle configuration with a name that contains the specified string., 0 - The field to sort results by. The default is Name.,  - The sort order for results.,  - A filter that returns only notebook instances with the specified status.amazonka-sagemakerA filter that returns only notebook instances with associated with the specified git repository.amazonka-sagemakerA filter that returns only notebook instances that were created after the specified time (timestamp).amazonka-sagemakerA filter that returns only notebook instances that were created before the specified time (timestamp).amazonka-sagemakerA string in the name or URL of a Git repository associated with this notebook instance. This filter returns only notebook instances associated with a git repository with a name that contains the specified string.amazonka-sagemakerA filter that returns only notebook instances that were modified after the specified time (timestamp).amazonka-sagemakerA filter that returns only notebook instances that were modified before the specified time (timestamp).amazonka-sagemaker3The maximum number of notebook instances to return.amazonka-sagemakerA string in the notebook instances' name. This filter returns only notebook instances whose name contains the specified string.amazonka-sagemakerIf the previous call to the ListNotebookInstances( is truncated, the response includes a  NextToken-. You can use this token in your subsequent ListNotebookInstances6 request to fetch the next set of notebook instances.You might specify a filter or a sort order in your request. When response is truncated, you must use the same values for the filer and sort order in the next request.amazonka-sagemakerA string in the name of a notebook instances lifecycle configuration associated with this notebook instance. This filter returns only notebook instances associated with a lifecycle configuration with a name that contains the specified string.amazonka-sagemaker-The field to sort results by. The default is Name.amazonka-sagemakerThe sort order for results.amazonka-sagemakerA filter that returns only notebook instances with the specified status.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - If the response to the previous ListNotebookInstances request was truncated, SageMaker returns this token. To retrieve the next set of notebook instances, use the token in the next request.,  - An array of NotebookInstanceSummary* objects, one for each notebook instance., # - The response's http status code.amazonka-sagemaker If the response to the previous ListNotebookInstances request was truncated, SageMaker returns this token. To retrieve the next set of notebook instances, use the token in the next request.amazonka-sagemaker An array of NotebookInstanceSummary* objects, one for each notebook instance.amazonka-sagemaker The response's http status code.amazonka-sagemaker&&(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';Iamazonka-sagemakerSee:  smart constructor.amazonka-sagemakerIf the response is truncated, SageMaker returns this token. To get the next set of lifecycle configurations, use it in the next request.amazonka-sagemaker An array of &NotebookInstanceLifecycleConfiguration2 objects, each listing a lifecycle configuration.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerA filter that returns only lifecycle configurations that were created after the specified time (timestamp).amazonka-sagemakerA filter that returns only lifecycle configurations that were created before the specified time (timestamp).amazonka-sagemakerA filter that returns only lifecycle configurations that were modified after the specified time (timestamp).amazonka-sagemakerA filter that returns only lifecycle configurations that were modified before the specified time (timestamp).amazonka-sagemakerThe maximum number of lifecycle configurations to return in the response.amazonka-sagemakerA string in the lifecycle configuration name. This filter returns only lifecycle configurations whose name contains the specified string.amazonka-sagemakerIf the result of a $ListNotebookInstanceLifecycleConfigs1 request was truncated, the response includes a  NextToken. To get the next set of lifecycle configurations, use the token in the next request.amazonka-sagemaker*Sorts the list of results. The default is  CreationTime.amazonka-sagemakerThe sort order for results.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - A filter that returns only lifecycle configurations that were created after the specified time (timestamp).,  - A filter that returns only lifecycle configurations that were created before the specified time (timestamp).,  - A filter that returns only lifecycle configurations that were modified after the specified time (timestamp).,  - A filter that returns only lifecycle configurations that were modified before the specified time (timestamp).,  - The maximum number of lifecycle configurations to return in the response.,  - A string in the lifecycle configuration name. This filter returns only lifecycle configurations whose name contains the specified string.,  - If the result of a $ListNotebookInstanceLifecycleConfigs1 request was truncated, the response includes a  NextToken. To get the next set of lifecycle configurations, use the token in the next request., - - Sorts the list of results. The default is  CreationTime.,  - The sort order for results.amazonka-sagemakerA filter that returns only lifecycle configurations that were created after the specified time (timestamp).amazonka-sagemakerA filter that returns only lifecycle configurations that were created before the specified time (timestamp).amazonka-sagemakerA filter that returns only lifecycle configurations that were modified after the specified time (timestamp).amazonka-sagemakerA filter that returns only lifecycle configurations that were modified before the specified time (timestamp).amazonka-sagemakerThe maximum number of lifecycle configurations to return in the response.amazonka-sagemakerA string in the lifecycle configuration name. This filter returns only lifecycle configurations whose name contains the specified string.amazonka-sagemakerIf the result of a $ListNotebookInstanceLifecycleConfigs1 request was truncated, the response includes a  NextToken. To get the next set of lifecycle configurations, use the token in the next request.amazonka-sagemaker*Sorts the list of results. The default is  CreationTime.amazonka-sagemakerThe sort order for results.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - If the response is truncated, SageMaker returns this token. To get the next set of lifecycle configurations, use it in the next request.,  - An array of &NotebookInstanceLifecycleConfiguration2 objects, each listing a lifecycle configuration., # - The response's http status code.amazonka-sagemakerIf the response is truncated, SageMaker returns this token. To get the next set of lifecycle configurations, use it in the next request.amazonka-sagemaker An array of &NotebookInstanceLifecycleConfiguration2 objects, each listing a lifecycle configuration.amazonka-sagemaker The response's http status code.amazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';c$Ȃamazonka-sagemakerSee:  smart constructor.ʂamazonka-sagemakerIf the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of jobs, use it in the subsequent request.˂amazonka-sagemaker The response's http status code.̂amazonka-sagemakerA JSON array in which each element is a summary for a monitoring schedule.͂amazonka-sagemakerSee: ܂ smart constructor.ςamazonka-sagemakerA filter that returns only monitoring schedules created after a specified time.Ђamazonka-sagemakerA filter that returns only monitoring schedules created before a specified time.тamazonka-sagemaker3Name of a specific endpoint to fetch schedules for.҂amazonka-sagemakerA filter that returns only monitoring schedules modified after a specified time.ӂamazonka-sagemakerA filter that returns only monitoring schedules modified before a specified time.Ԃamazonka-sagemakerThe maximum number of jobs to return in the response. The default value is 10.Ղamazonka-sagemakerGets a list of the monitoring schedules for the specified monitoring job definition.ւamazonka-sagemakerA filter that returns only the monitoring schedules for the specified monitoring type.ׂamazonka-sagemakerFilter for monitoring schedules whose name contains a specified string.؂amazonka-sagemakerThe token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.قamazonka-sagemakerWhether to sort results by Status,  CreationTime,  ScheduledTime field. The default is  CreationTime.ڂamazonka-sagemakerWhether to sort the results in  Ascending or  Descending order. The default is  Descending.ۂamazonka-sagemakerA filter that returns only monitoring schedules modified before a specified time.܂amazonka-sagemakerCreate a value of ͂" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:ς, ݂ - A filter that returns only monitoring schedules created after a specified time.Ђ, ނ - A filter that returns only monitoring schedules created before a specified time.͂, ߂6 - Name of a specific endpoint to fetch schedules for.҂,  - A filter that returns only monitoring schedules modified after a specified time.ӂ,  - A filter that returns only monitoring schedules modified before a specified time.Ԃ,  - The maximum number of jobs to return in the response. The default value is 10.͂,  - Gets a list of the monitoring schedules for the specified monitoring job definition.ւ,  - A filter that returns only the monitoring schedules for the specified monitoring type.ׂ,  - Filter for monitoring schedules whose name contains a specified string.͂,  - The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.ق,  - Whether to sort results by Status,  CreationTime,  ScheduledTime field. The default is  CreationTime.ڂ, " - Whether to sort the results in  Ascending or  Descending order. The default is  Descending.ۂ,  - A filter that returns only monitoring schedules modified before a specified time.݂amazonka-sagemakerA filter that returns only monitoring schedules created after a specified time.ނamazonka-sagemakerA filter that returns only monitoring schedules created before a specified time.߂amazonka-sagemaker3Name of a specific endpoint to fetch schedules for.amazonka-sagemakerA filter that returns only monitoring schedules modified after a specified time.amazonka-sagemakerA filter that returns only monitoring schedules modified before a specified time.amazonka-sagemakerThe maximum number of jobs to return in the response. The default value is 10.amazonka-sagemakerGets a list of the monitoring schedules for the specified monitoring job definition.amazonka-sagemakerA filter that returns only the monitoring schedules for the specified monitoring type.amazonka-sagemakerFilter for monitoring schedules whose name contains a specified string.amazonka-sagemakerThe token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.amazonka-sagemakerWhether to sort results by Status,  CreationTime,  ScheduledTime field. The default is  CreationTime.amazonka-sagemakerWhether to sort the results in  Ascending or  Descending order. The default is  Descending.amazonka-sagemakerA filter that returns only monitoring schedules modified before a specified time.amazonka-sagemakerCreate a value of Ȃ" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:͂,  - If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of jobs, use it in the subsequent request.˂, # - The response's http status code.̂,  - A JSON array in which each element is a summary for a monitoring schedule.amazonka-sagemakerIf the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of jobs, use it in the subsequent request.amazonka-sagemaker The response's http status code.amazonka-sagemakerA JSON array in which each element is a summary for a monitoring schedule.amazonka-sagemaker˂&Ȃɂ˂ʂ̂͂΂قтՂԂ؂ڂׂςЂ҂ӂۂւ܂݂ނ߂&͂΂قтՂԂ؂ڂׂςЂ҂ӂۂւ܂݂ނ߂Ȃɂ˂ʂ̂(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';~:(amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerIf the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of jobs, use it in the subsequent requesamazonka-sagemaker The response's http status code.amazonka-sagemakerA JSON array in which each element is a summary for a monitoring execution.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker?A filter that returns only jobs created after a specified time.amazonka-sagemakerA filter that returns only jobs created before a specified time.amazonka-sagemaker.Name of a specific endpoint to fetch jobs for.amazonka-sagemakerA filter that returns only jobs modified before a specified time.amazonka-sagemakerA filter that returns only jobs modified after a specified time.amazonka-sagemakerThe maximum number of jobs to return in the response. The default value is 10.amazonka-sagemakerGets a list of the monitoring job runs of the specified monitoring job definitions.amazonka-sagemaker.Name of a specific schedule to fetch jobs for.amazonka-sagemakerA filter that returns only the monitoring job runs of the specified monitoring type.amazonka-sagemakerThe token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.amazonka-sagemaker1Filter for jobs scheduled after a specified time.amazonka-sagemaker2Filter for jobs scheduled before a specified time.amazonka-sagemakerWhether to sort results by Status,  CreationTime,  ScheduledTime field. The default is  CreationTime.amazonka-sagemakerWhether to sort the results in  Ascending or  Descending order. The default is  Descending.amazonka-sagemaker9A filter that retrieves only jobs with a specific status.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - A filter that returns only jobs created after a specified time.,  - A filter that returns only jobs created before a specified time., 1 - Name of a specific endpoint to fetch jobs for.,  - A filter that returns only jobs modified before a specified time.,  - A filter that returns only jobs modified after a specified time.,  - The maximum number of jobs to return in the response. The default value is 10.,  - Gets a list of the monitoring job runs of the specified monitoring job definitions., 1 - Name of a specific schedule to fetch jobs for.,  - A filter that returns only the monitoring job runs of the specified monitoring type.,  - The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request., 4 - Filter for jobs scheduled after a specified time., 5 - Filter for jobs scheduled before a specified time.,  - Whether to sort results by Status,  CreationTime,  ScheduledTime field. The default is  CreationTime., " - Whether to sort the results in  Ascending or  Descending order. The default is  Descending., < - A filter that retrieves only jobs with a specific status.amazonka-sagemaker?A filter that returns only jobs created after a specified time.amazonka-sagemakerA filter that returns only jobs created before a specified time.amazonka-sagemaker.Name of a specific endpoint to fetch jobs for.amazonka-sagemakerA filter that returns only jobs modified before a specified time.amazonka-sagemakerA filter that returns only jobs modified after a specified time.amazonka-sagemakerThe maximum number of jobs to return in the response. The default value is 10.amazonka-sagemakerGets a list of the monitoring job runs of the specified monitoring job definitions.amazonka-sagemaker.Name of a specific schedule to fetch jobs for.amazonka-sagemakerA filter that returns only the monitoring job runs of the specified monitoring type.amazonka-sagemakerThe token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.amazonka-sagemaker1Filter for jobs scheduled after a specified time.amazonka-sagemaker2Filter for jobs scheduled before a specified time.amazonka-sagemakerWhether to sort results by Status,  CreationTime,  ScheduledTime field. The default is  CreationTime.amazonka-sagemakerWhether to sort the results in  Ascending or  Descending order. The default is  Descending.amazonka-sagemaker9A filter that retrieves only jobs with a specific status.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of jobs, use it in the subsequent reques, # - The response's http status code.,  - A JSON array in which each element is a summary for a monitoring execution.amazonka-sagemakerIf the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of jobs, use it in the subsequent requesamazonka-sagemaker The response's http status code.amazonka-sagemakerA JSON array in which each element is a summary for a monitoring execution.amazonka-sagemaker**(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';amazonka-sagemakerSee: ȃ smart constructor.amazonka-sagemakerA JSON array where each element is a summary for a monitoring alert.amazonka-sagemakerIf the response is truncated, SageMaker returns this token. To retrieve the next set of alerts, use it in the subsequent request.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee: ă smart constructor.amazonka-sagemaker=The maximum number of results to display. The default is 100.ƒamazonka-sagemakerIf the result of the previous ListMonitoringAlerts1 request was truncated, the response includes a  NextToken. To retrieve the next set of alerts in the history, use the token in the next request.Ãamazonka-sagemaker"The name of a monitoring schedule.ăamazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, Ń - The maximum number of results to display. The default is 100., ƃ! - If the result of the previous ListMonitoringAlerts1 request was truncated, the response includes a  NextToken. To retrieve the next set of alerts in the history, use the token in the next request., ǃ% - The name of a monitoring schedule.Ńamazonka-sagemaker=The maximum number of results to display. The default is 100.ƃamazonka-sagemakerIf the result of the previous ListMonitoringAlerts1 request was truncated, the response includes a  NextToken. To retrieve the next set of alerts in the history, use the token in the next request.ǃamazonka-sagemaker"The name of a monitoring schedule.ȃamazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, Ƀ - A JSON array where each element is a summary for a monitoring alert., ʃ - If the response is truncated, SageMaker returns this token. To retrieve the next set of alerts, use it in the subsequent request., ˃# - The response's http status code.Ƀamazonka-sagemakerA JSON array where each element is a summary for a monitoring alert.ʃamazonka-sagemakerIf the response is truncated, SageMaker returns this token. To retrieve the next set of alerts, use it in the subsequent request.˃amazonka-sagemaker The response's http status code.ăamazonka-sagemakerȃamazonka-sagemakerÃăŃƃǃȃɃʃ˃ÃăŃƃǃȃɃʃ˃(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';!݃amazonka-sagemakerSee:  smart constructor.߃amazonka-sagemaker1An alert history for a model monitoring schedule.amazonka-sagemakerIf the response is truncated, SageMaker returns this token. To retrieve the next set of alerts, use it in the subsequent request.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerA filter that returns only alerts created on or after the specified time.amazonka-sagemakerA filter that returns only alerts created on or before the specified time.amazonka-sagemaker=The maximum number of results to display. The default is 100.amazonka-sagemakerThe name of a monitoring alert.amazonka-sagemaker"The name of a monitoring schedule.amazonka-sagemakerIf the result of the previous ListMonitoringAlertHistory1 request was truncated, the response includes a  NextToken. To retrieve the next set of alerts in the history, use the token in the next request.amazonka-sagemaker/The field used to sort results. The default is  CreationTime.amazonka-sagemakerThe sort order, whether  Ascending or  Descending(, of the alert history. The default is  Descending.amazonka-sagemaker;A filter that retrieves only alerts with a specific status.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - A filter that returns only alerts created on or after the specified time.,  - A filter that returns only alerts created on or before the specified time.,  - The maximum number of results to display. The default is 100., " - The name of a monitoring alert., % - The name of a monitoring schedule., ! - If the result of the previous ListMonitoringAlertHistory1 request was truncated, the response includes a  NextToken. To retrieve the next set of alerts in the history, use the token in the next request., 2 - The field used to sort results. The default is  CreationTime.,  - The sort order, whether  Ascending or  Descending(, of the alert history. The default is  Descending., > - A filter that retrieves only alerts with a specific status.amazonka-sagemakerA filter that returns only alerts created on or after the specified time.amazonka-sagemakerA filter that returns only alerts created on or before the specified time.amazonka-sagemaker=The maximum number of results to display. The default is 100.amazonka-sagemakerThe name of a monitoring alert.amazonka-sagemaker"The name of a monitoring schedule.amazonka-sagemakerIf the result of the previous ListMonitoringAlertHistory1 request was truncated, the response includes a  NextToken. To retrieve the next set of alerts in the history, use the token in the next request.amazonka-sagemaker/The field used to sort results. The default is  CreationTime.amazonka-sagemakerThe sort order, whether  Ascending or  Descending(, of the alert history. The default is  Descending.amazonka-sagemaker;A filter that retrieves only alerts with a specific status.amazonka-sagemakerCreate a value of ݃" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:߃, 4 - An alert history for a model monitoring schedule.,  - If the response is truncated, SageMaker returns this token. To retrieve the next set of alerts, use it in the subsequent request., # - The response's http status code.amazonka-sagemaker1An alert history for a model monitoring schedule.amazonka-sagemakerIf the response is truncated, SageMaker returns this token. To retrieve the next set of alerts, use it in the subsequent request.amazonka-sagemaker The response's http status code.amazonka-sagemaker݃ރ߃݃ރ߃(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerIf the response is truncated, SageMaker returns this token. To retrieve the next set of models, use it in the subsequent request.amazonka-sagemaker The response's http status code.amazonka-sagemaker An array of  ModelSummary& objects, each of which lists a model.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerA filter that returns only models with a creation time greater than or equal to the specified time (timestamp).amazonka-sagemakerA filter that returns only models created before the specified time (timestamp).amazonka-sagemaker7The maximum number of models to return in the response.amazonka-sagemakerA string in the model name. This filter returns only models whose name contains the specified string.amazonka-sagemakerIf the response to a previous  ListModels1 request was truncated, the response includes a  NextToken. To retrieve the next set of models, use the token in the next request.amazonka-sagemaker*Sorts the list of results. The default is  CreationTime.amazonka-sagemaker+The sort order for results. The default is  Descending.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - A filter that returns only models with a creation time greater than or equal to the specified time (timestamp).,  - A filter that returns only models created before the specified time (timestamp)., : - The maximum number of models to return in the response.,  - A string in the model name. This filter returns only models whose name contains the specified string., ! - If the response to a previous  ListModels1 request was truncated, the response includes a  NextToken. To retrieve the next set of models, use the token in the next request., - - Sorts the list of results. The default is  CreationTime., . - The sort order for results. The default is  Descending.amazonka-sagemakerA filter that returns only models with a creation time greater than or equal to the specified time (timestamp).amazonka-sagemakerA filter that returns only models created before the specified time (timestamp).amazonka-sagemaker7The maximum number of models to return in the response.amazonka-sagemakerA string in the model name. This filter returns only models whose name contains the specified string.amazonka-sagemakerIf the response to a previous  ListModels1 request was truncated, the response includes a  NextToken. To retrieve the next set of models, use the token in the next request.amazonka-sagemaker*Sorts the list of results. The default is  CreationTime.amazonka-sagemaker+The sort order for results. The default is  Descending.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - If the response is truncated, SageMaker returns this token. To retrieve the next set of models, use it in the subsequent request., # - The response's http status code.,  - An array of  ModelSummary& objects, each of which lists a model.amazonka-sagemakerIf the response is truncated, SageMaker returns this token. To retrieve the next set of models, use it in the subsequent request.amazonka-sagemaker The response's http status code.amazonka-sagemaker An array of  ModelSummary& objects, each of which lists a model.amazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';ǽamazonka-sagemakerSee: τ smart constructor.amazonka-sagemakerIf the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of model quality monitoring job definitions, use it in the next request.amazonka-sagemaker The response's http status code.amazonka-sagemakerA list of summaries of model quality monitoring job definitions.amazonka-sagemakerSee: Ƅ smart constructor.amazonka-sagemakerA filter that returns only model quality monitoring job definitions created after the specified time.amazonka-sagemakerA filter that returns only model quality monitoring job definitions created before the specified time.amazonka-sagemakerA filter that returns only model quality monitoring job definitions that are associated with the specified endpoint.amazonka-sagemaker6The maximum number of results to return in a call to ListModelQualityJobDefinitions.„amazonka-sagemakerA string in the transform job name. This filter returns only model quality monitoring job definitions whose name contains the specified string.Äamazonka-sagemakerIf the result of the previous ListModelQualityJobDefinitions1 request was truncated, the response includes a  NextToken. To retrieve the next set of model quality monitoring job definitions, use the token in the next request.Ąamazonka-sagemaker-The field to sort results by. The default is  CreationTime.ńamazonka-sagemaker+The sort order for results. The default is  Descending.Ƅamazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, DŽ - A filter that returns only model quality monitoring job definitions created after the specified time., Ȅ - A filter that returns only model quality monitoring job definitions created before the specified time., Ʉ - A filter that returns only model quality monitoring job definitions that are associated with the specified endpoint., ʄ9 - The maximum number of results to return in a call to ListModelQualityJobDefinitions.„, ˄ - A string in the transform job name. This filter returns only model quality monitoring job definitions whose name contains the specified string., ̄! - If the result of the previous ListModelQualityJobDefinitions1 request was truncated, the response includes a  NextToken. To retrieve the next set of model quality monitoring job definitions, use the token in the next request.Ą, ̈́0 - The field to sort results by. The default is  CreationTime.ń, ΄. - The sort order for results. The default is  Descending.DŽamazonka-sagemakerA filter that returns only model quality monitoring job definitions created after the specified time.Ȅamazonka-sagemakerA filter that returns only model quality monitoring job definitions created before the specified time.Ʉamazonka-sagemakerA filter that returns only model quality monitoring job definitions that are associated with the specified endpoint.ʄamazonka-sagemaker6The maximum number of results to return in a call to ListModelQualityJobDefinitions.˄amazonka-sagemakerA string in the transform job name. This filter returns only model quality monitoring job definitions whose name contains the specified string.̄amazonka-sagemakerIf the result of the previous ListModelQualityJobDefinitions1 request was truncated, the response includes a  NextToken. To retrieve the next set of model quality monitoring job definitions, use the token in the next request.̈́amazonka-sagemaker-The field to sort results by. The default is  CreationTime.΄amazonka-sagemaker+The sort order for results. The default is  Descending.τamazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, Є - If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of model quality monitoring job definitions, use it in the next request., ф# - The response's http status code., ҄ - A list of summaries of model quality monitoring job definitions.Єamazonka-sagemakerIf the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of model quality monitoring job definitions, use it in the next request.фamazonka-sagemaker The response's http status code.҄amazonka-sagemakerA list of summaries of model quality monitoring job definitions.τamazonka-sagemakerĄÄń„ƄDŽȄɄʄ˄̄̈́΄τЄф҄ĄÄń„ƄDŽȄɄʄ˄̄̈́΄τЄф҄(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerIf the response is truncated, SageMaker returns this token. To retrieve the next set of model packages, use it in the subsequent request.amazonka-sagemaker The response's http status code.amazonka-sagemaker An array of ModelPackageSummary/ objects, each of which lists a model package.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerA filter that returns only model packages created after the specified time (timestamp).amazonka-sagemakerA filter that returns only model packages created before the specified time (timestamp).amazonka-sagemaker?The maximum number of model packages to return in the response.amazonka-sagemakerA filter that returns only the model packages with the specified approval status.amazonka-sagemakerA filter that returns only model versions that belong to the specified model group.amazonka-sagemakerA filter that returns only the model packages of the specified type. This can be one of the following values. UNVERSIONED - List only unversioined models. This is the default value if no ModelPackageType is specified. VERSIONED - List only versioned models.BOTH. - List both versioned and unversioned models.amazonka-sagemakerA string in the model package name. This filter returns only model packages whose name contains the specified string.amazonka-sagemakerIf the response to a previous ListModelPackages1 request was truncated, the response includes a  NextToken. To retrieve the next set of model packages, use the token in the next request.amazonka-sagemaker - Only list model card export jobs with the specified status., ? - List export jobs for the model card with the specified name.amazonka-sagemakerOnly list model card export jobs that were created after the time specified.amazonka-sagemakerOnly list model card export jobs that were created before the time specified.amazonka-sagemaker5The maximum number of model card export jobs to list.amazonka-sagemakerOnly list model card export jobs with names that contain the specified string.amazonka-sagemaker?List export jobs for the model card with the specified version.amazonka-sagemakerIf the response to a previous ListModelCardExportJobs1 request was truncated, the response includes a  NextToken. To retrieve the next set of model card export jobs, use the token in the next request.amazonka-sagemakerSort model card export jobs by either name or creation time. Sorts by creation time by default.amazonka-sagemaker=Sort model card export jobs by ascending or descending order.amazonka-sagemaker;Only list model card export jobs with the specified status.amazonka-sagemakerAn array of objects describing the human task user interfaces.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerA filter that returns only human task user interfaces with a creation time greater than or equal to the specified timestamp.amazonka-sagemakerA filter that returns only human task user interfaces that were created before the specified timestamp.amazonka-sagemakerThe total number of items to return. If the total number of available items is more than the value specified in  MaxResults , then a  NextToken will be provided in the output that you can use to resume pagination.amazonka-sagemakerA token to resume pagination.amazonka-sagemakerAn optional value that specifies whether you want the results sorted in  Ascending or  Descending order.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - A filter that returns only human task user interfaces with a creation time greater than or equal to the specified timestamp.,  - A filter that returns only human task user interfaces that were created before the specified timestamp.,  - The total number of items to return. If the total number of available items is more than the value specified in  MaxResults , then a  NextToken will be provided in the output that you can use to resume pagination.,  - A token to resume pagination.,  - An optional value that specifies whether you want the results sorted in  Ascending or  Descending order.amazonka-sagemakerA filter that returns only human task user interfaces with a creation time greater than or equal to the specified timestamp.amazonka-sagemakerA filter that returns only human task user interfaces that were created before the specified timestamp.amazonka-sagemakerThe total number of items to return. If the total number of available items is more than the value specified in  MaxResults , then a  NextToken will be provided in the output that you can use to resume pagination.amazonka-sagemakerA token to resume pagination.amazonka-sagemakerAn optional value that specifies whether you want the results sorted in  Ascending or  Descending order.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - A token to resume pagination., # - The response's http status code.,  - An array of objects describing the human task user interfaces.amazonka-sagemakerA token to resume pagination.amazonka-sagemaker The response's http status code.amazonka-sagemaker>An array of objects describing the human task user interfaces.amazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';9damazonka-sagemakerSee:  smart constructor.amazonka-sagemakerIf the response is truncated, SageMaker returns this token. To retrieve the next set of hubs, use it in the subsequent request.amazonka-sagemaker The response's http status code.amazonka-sagemaker!The summaries of the listed hubs.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker:Only list hubs that were created after the time specified.amazonka-sagemaker;Only list hubs that were created before the time specified.amazonka-sagemakerOnly list hubs that were last modified after the time specified.amazonka-sagemakerOnly list hubs that were last modified before the time specified.amazonka-sagemaker#The maximum number of hubs to list.amazonka-sagemaker - Only list hubs that were created before the time specified.,  - Only list hubs that were last modified after the time specified.,  - Only list hubs that were last modified before the time specified., & - The maximum number of hubs to list., ? - Only list hubs with names that contain the specified string., ! - If the response to a previous ListHubs1 request was truncated, the response includes a  NextToken. To retrieve the next set of hubs, use the token in the next request., - - Sort hubs by either name or creation time., . - Sort hubs by ascending or descending order.amazonka-sagemaker:Only list hubs that were created after the time specified.amazonka-sagemaker;Only list hubs that were created before the time specified.amazonka-sagemakerOnly list hubs that were last modified after the time specified.amazonka-sagemakerOnly list hubs that were last modified before the time specified.amazonka-sagemaker#The maximum number of hubs to list.amazonka-sagemaker - Sort hub content versions by ascending or descending order., 7 - The name of the hub to list the content versions of., / - The type of hub content to list versions of.,  - The name of the hub content.amazonka-sagemakerOnly list hub content versions that were created after the time specified.amazonka-sagemakerOnly list hub content versions that were created before the time specified.amazonka-sagemaker3The maximum number of hub content versions to list.amazonka-sagemaker2The upper bound of the hub content schema version.amazonka-sagemaker4The lower bound of the hub content versions to list.amazonka-sagemakerIf the response to a previous ListHubContentVersions1 request was truncated, the response includes a  NextToken. To retrieve the next set of hub content versions, use the token in the next request.amazonka-sagemaker:Sort hub content versions by either name or creation time.amazonka-sagemaker;Sort hub content versions by ascending or descending order.amazonka-sagemaker4The name of the hub to list the content versions of.amazonka-sagemaker,The type of hub content to list versions of.amazonka-sagemakerThe name of the hub content.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - If the response is truncated, SageMaker returns this token. To retrieve the next set of hub content versions, use it in the subsequent request., # - The response's http status code., 4 - The summaries of the listed hub content versions.amazonka-sagemakerIf the response is truncated, SageMaker returns this token. To retrieve the next set of hub content versions, use it in the subsequent request.amazonka-sagemaker The response's http status code.amazonka-sagemaker1The summaries of the listed hub content versions.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker""(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';qramazonka-sagemakerSee:  smart constructor.amazonka-sagemakerA token to resume pagination.amazonka-sagemaker The response's http status code.amazonka-sagemaker4An array of objects describing the flow definitions.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerA filter that returns only flow definitions with a creation time greater than or equal to the specified timestamp.amazonka-sagemakerA filter that returns only flow definitions that were created before the specified timestamp.amazonka-sagemakerThe total number of items to return. If the total number of available items is more than the value specified in  MaxResults , then a  NextToken will be provided in the output that you can use to resume pagination.amazonka-sagemakerA token to resume pagination.amazonka-sagemakerAn optional value that specifies whether you want the results sorted in  Ascending or  Descending order.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - A filter that returns only flow definitions with a creation time greater than or equal to the specified timestamp.,  - A filter that returns only flow definitions that were created before the specified timestamp.,  - The total number of items to return. If the total number of available items is more than the value specified in  MaxResults , then a  NextToken will be provided in the output that you can use to resume pagination.,  - A token to resume pagination.,  - An optional value that specifies whether you want the results sorted in  Ascending or  Descending order.amazonka-sagemakerA filter that returns only flow definitions with a creation time greater than or equal to the specified timestamp.amazonka-sagemakerA filter that returns only flow definitions that were created before the specified timestamp.amazonka-sagemakerThe total number of items to return. If the total number of available items is more than the value specified in  MaxResults , then a  NextToken will be provided in the output that you can use to resume pagination.amazonka-sagemakerA token to resume pagination.amazonka-sagemakerAn optional value that specifies whether you want the results sorted in  Ascending or  Descending order.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - A token to resume pagination., # - The response's http status code., 7 - An array of objects describing the flow definitions.amazonka-sagemakerA token to resume pagination.amazonka-sagemaker The response's http status code.amazonka-sagemaker4An array of objects describing the flow definitions.amazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';njamazonka-sagemakerSee:  smart constructor.Ɍamazonka-sagemaker A token to resume pagination of ListFeatureGroups results.ʌamazonka-sagemaker The response's http status code.ˌamazonka-sagemakerA summary of feature groups.̌amazonka-sagemakerSee: ׌ smart constructor.Όamazonka-sagemaker!Use this parameter to search for  FeatureGroups*s created after a specific date and time.όamazonka-sagemaker!Use this parameter to search for  FeatureGroups+s created before a specific date and time.Ќamazonka-sagemakerA  FeatureGroup status. Filters by  FeatureGroup status.ьamazonka-sagemaker*The maximum number of results returned by ListFeatureGroups.Ҍamazonka-sagemaker,A string that partially matches one or more  FeatureGroups names. Filters  FeatureGroup s by name.ӌamazonka-sagemaker A token to resume pagination of ListFeatureGroups results.Ԍamazonka-sagemakerAn  OfflineStore status. Filters by  OfflineStore status.Ռamazonka-sagemaker4The value on which the feature group list is sorted.֌amazonka-sagemaker-The order in which feature groups are listed.׌amazonka-sagemakerCreate a value of ̌" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:Ό, ،$ - Use this parameter to search for  FeatureGroups*s created after a specific date and time.ό, ٌ$ - Use this parameter to search for  FeatureGroups+s created before a specific date and time.Ќ, ڌ - A  FeatureGroup status. Filters by  FeatureGroup status.ь, ی- - The maximum number of results returned by ListFeatureGroups.Ҍ, ܌/ - A string that partially matches one or more  FeatureGroups names. Filters  FeatureGroup s by name.̌, ݌# - A token to resume pagination of ListFeatureGroups results.Ԍ, ތ - An  OfflineStore status. Filters by  OfflineStore status.Ռ, ߌ7 - The value on which the feature group list is sorted.֌, 0 - The order in which feature groups are listed.،amazonka-sagemaker!Use this parameter to search for  FeatureGroups*s created after a specific date and time.ٌamazonka-sagemaker!Use this parameter to search for  FeatureGroups+s created before a specific date and time.ڌamazonka-sagemakerA  FeatureGroup status. Filters by  FeatureGroup status.یamazonka-sagemaker*The maximum number of results returned by ListFeatureGroups.܌amazonka-sagemaker,A string that partially matches one or more  FeatureGroups names. Filters  FeatureGroup s by name.݌amazonka-sagemaker A token to resume pagination of ListFeatureGroups results.ތamazonka-sagemakerAn  OfflineStore status. Filters by  OfflineStore status.ߌamazonka-sagemaker4The value on which the feature group list is sorted.amazonka-sagemaker-The order in which feature groups are listed.amazonka-sagemakerCreate a value of nj" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:̌, # - A token to resume pagination of ListFeatureGroups results.ʌ, # - The response's http status code.ˌ,  - A summary of feature groups.amazonka-sagemaker A token to resume pagination of ListFeatureGroups results.amazonka-sagemaker The response's http status code.amazonka-sagemakerA summary of feature groups.amazonka-sagemakerʌnjȌʌɌˌ̌͌Ռьӌ֌ҌΌόЌԌ׌،ٌڌی܌݌ތߌ̌͌Ռьӌ֌ҌΌόЌԌ׌،ٌڌی܌݌ތߌnjȌʌɌˌ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker,A list of the summaries of your experiments.amazonka-sagemakerA token for getting the next set of experiments, if there are any.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerA filter that returns only experiments created after the specified time.amazonka-sagemakerA filter that returns only experiments created before the specified time.amazonka-sagemakerThe maximum number of experiments to return in the response. The default value is 10.amazonka-sagemakerIf the previous call to ListExperiments didn't return the full set of experiments, the call returns a token for getting the next set of experiments.amazonka-sagemaker8The property used to sort results. The default value is  CreationTime.amazonka-sagemaker%The sort order. The default value is  Descending.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - A filter that returns only experiments created after the specified time.,  - A filter that returns only experiments created before the specified time.,  - The maximum number of experiments to return in the response. The default value is 10.,  - If the previous call to ListExperiments didn't return the full set of experiments, the call returns a token for getting the next set of experiments., ; - The property used to sort results. The default value is  CreationTime., ( - The sort order. The default value is  Descending.amazonka-sagemakerA filter that returns only experiments created after the specified time.amazonka-sagemakerA filter that returns only experiments created before the specified time.amazonka-sagemakerThe maximum number of experiments to return in the response. The default value is 10.amazonka-sagemakerIf the previous call to ListExperiments didn't return the full set of experiments, the call returns a token for getting the next set of experiments.amazonka-sagemaker8The property used to sort results. The default value is  CreationTime.amazonka-sagemaker%The sort order. The default value is  Descending.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, / - A list of the summaries of your experiments.,  - A token for getting the next set of experiments, if there are any., # - The response's http status code.amazonka-sagemaker,A list of the summaries of your experiments.amazonka-sagemakerA token for getting the next set of experiments, if there are any.amazonka-sagemaker The response's http status code.amazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerIf the response is truncated, SageMaker returns this token. To retrieve the next set of training jobs, use it in the subsequent request.amazonka-sagemaker The response's http status code.amazonka-sagemakerAn array or endpoint objects.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerA filter that returns only endpoints with a creation time greater than or equal to the specified time (timestamp).amazonka-sagemakerA filter that returns only endpoints that were created before the specified time (timestamp).amazonka-sagemakerA filter that returns only endpoints that were modified after the specified timestamp.amazonka-sagemakerA filter that returns only endpoints that were modified before the specified timestamp.amazonka-sagemakerThe maximum number of endpoints to return in the response. This value defaults to 10.amazonka-sagemakerA string in endpoint names. This filter returns only endpoints whose name contains the specified string.amazonka-sagemakerIf the result of a  ListEndpoints1 request was truncated, the response includes a  NextToken. To retrieve the next set of endpoints, use the token in the next request.amazonka-sagemaker*Sorts the list of results. The default is  CreationTime.amazonka-sagemaker+The sort order for results. The default is  Descending.amazonka-sagemaker?A filter that returns only endpoints with the specified status.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - A filter that returns only endpoints with a creation time greater than or equal to the specified time (timestamp).,  - A filter that returns only endpoints that were created before the specified time (timestamp).,  - A filter that returns only endpoints that were modified after the specified timestamp.,  - A filter that returns only endpoints that were modified before the specified timestamp.,  - The maximum number of endpoints to return in the response. This value defaults to 10.,  - A string in endpoint names. This filter returns only endpoints whose name contains the specified string.,  - If the result of a  ListEndpoints1 request was truncated, the response includes a  NextToken. To retrieve the next set of endpoints, use the token in the next request., - - Sorts the list of results. The default is  CreationTime., . - The sort order for results. The default is  Descending.,  - A filter that returns only endpoints with the specified status.amazonka-sagemakerA filter that returns only endpoints with a creation time greater than or equal to the specified time (timestamp).amazonka-sagemakerA filter that returns only endpoints that were created before the specified time (timestamp).amazonka-sagemakerA filter that returns only endpoints that were modified after the specified timestamp.amazonka-sagemakerA filter that returns only endpoints that were modified before the specified timestamp.amazonka-sagemakerThe maximum number of endpoints to return in the response. This value defaults to 10.amazonka-sagemakerA string in endpoint names. This filter returns only endpoints whose name contains the specified string.amazonka-sagemakerIf the result of a  ListEndpoints1 request was truncated, the response includes a  NextToken. To retrieve the next set of endpoints, use the token in the next request.amazonka-sagemaker*Sorts the list of results. The default is  CreationTime.amazonka-sagemaker+The sort order for results. The default is  Descending.amazonka-sagemaker?A filter that returns only endpoints with the specified status.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - If the response is truncated, SageMaker returns this token. To retrieve the next set of training jobs, use it in the subsequent request., # - The response's http status code.,  - An array or endpoint objects.amazonka-sagemakerIf the response is truncated, SageMaker returns this token. To retrieve the next set of training jobs, use it in the subsequent request.amazonka-sagemaker The response's http status code.amazonka-sagemakerAn array or endpoint objects.amazonka-sagemaker  (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';IЍamazonka-sagemakerSee:  smart constructor.ҍamazonka-sagemakerIf the response is truncated, SageMaker returns this token. To retrieve the next set of endpoint configurations, use it in the subsequent requestӍamazonka-sagemaker The response's http status code.ԍamazonka-sagemaker$An array of endpoint configurations.Սamazonka-sagemakerSee: ލ smart constructor.׍amazonka-sagemakerA filter that returns only endpoint configurations with a creation time greater than or equal to the specified time (timestamp).؍amazonka-sagemakerA filter that returns only endpoint configurations created before the specified time (timestamp).ٍamazonka-sagemaker>The maximum number of training jobs to return in the response.ڍamazonka-sagemakerA string in the endpoint configuration name. This filter returns only endpoint configurations whose name contains the specified string.ۍamazonka-sagemakerIf the result of the previous ListEndpointConfig1 request was truncated, the response includes a  NextToken. To retrieve the next set of endpoint configurations, use the token in the next request.܍amazonka-sagemaker-The field to sort results by. The default is  CreationTime.ݍamazonka-sagemaker+The sort order for results. The default is  Descending.ލamazonka-sagemakerCreate a value of Ս" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:׍, ߍ - A filter that returns only endpoint configurations with a creation time greater than or equal to the specified time (timestamp).؍,  - A filter that returns only endpoint configurations created before the specified time (timestamp).ٍ,  - The maximum number of training jobs to return in the response.ڍ,  - A string in the endpoint configuration name. This filter returns only endpoint configurations whose name contains the specified string.Ս, ! - If the result of the previous ListEndpointConfig1 request was truncated, the response includes a  NextToken. To retrieve the next set of endpoint configurations, use the token in the next request.܍, 0 - The field to sort results by. The default is  CreationTime.ݍ, . - The sort order for results. The default is  Descending.ߍamazonka-sagemakerA filter that returns only endpoint configurations with a creation time greater than or equal to the specified time (timestamp).amazonka-sagemakerA filter that returns only endpoint configurations created before the specified time (timestamp).amazonka-sagemaker>The maximum number of training jobs to return in the response.amazonka-sagemakerA string in the endpoint configuration name. This filter returns only endpoint configurations whose name contains the specified string.amazonka-sagemakerIf the result of the previous ListEndpointConfig1 request was truncated, the response includes a  NextToken. To retrieve the next set of endpoint configurations, use the token in the next request.amazonka-sagemaker-The field to sort results by. The default is  CreationTime.amazonka-sagemaker+The sort order for results. The default is  Descending.amazonka-sagemakerCreate a value of Ѝ" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:Ս,  - If the response is truncated, SageMaker returns this token. To retrieve the next set of endpoint configurations, use it in the subsequent requestӍ, # - The response's http status code.ԍ, ' - An array of endpoint configurations.amazonka-sagemakerIf the response is truncated, SageMaker returns this token. To retrieve the next set of endpoint configurations, use it in the subsequent requestamazonka-sagemaker The response's http status code.amazonka-sagemaker$An array of endpoint configurations.amazonka-sagemakerӍЍэӍҍԍՍ֍܍ٍۍݍڍ׍؍ލߍՍ֍܍ٍۍݍڍ׍؍ލߍЍэӍҍԍ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&'; amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker3Token to use when calling the next page of results.amazonka-sagemaker The response's http status code.amazonka-sagemaker!Summaries of edge packaging jobs.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker;Select jobs where the job was created after specified time.amazonka-sagemakerSelects edge deployment plans with names containing this name.amazonka-sagemakerThe response from the last list when returning a list large enough to need tokening.amazonka-sagemakerThe column by which to sort the edge deployment plans. Can be one of NAME, DEVICEFLEETNAME,  CREATIONTIME, LASTMODIFIEDTIME.amazonka-sagemaker7The direction of the sorting (ascending or descending).amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 9 - Selects edge deployment plans created after this time., : - Selects edge deployment plans created before this time., Ž - Selects edge deployment plans with a device fleet name containing this name., Î - Selects edge deployment plans that were last updated after this time., Ď - Selects edge deployment plans that were last updated before this time., Ŏ; - The maximum number of results to select (50 by default)., Ǝ - Selects edge deployment plans with names containing this name., ǎ - The response from the last list when returning a list large enough to need tokening., Ȏ - The column by which to sort the edge deployment plans. Can be one of NAME, DEVICEFLEETNAME,  CREATIONTIME, LASTMODIFIEDTIME., Ɏ: - The direction of the sorting (ascending or descending).amazonka-sagemaker6Selects edge deployment plans created after this time.amazonka-sagemaker7Selects edge deployment plans created before this time.Žamazonka-sagemakerSelects edge deployment plans with a device fleet name containing this name.Îamazonka-sagemakerSelects edge deployment plans that were last updated after this time.Ďamazonka-sagemakerSelects edge deployment plans that were last updated before this time.Ŏamazonka-sagemaker8The maximum number of results to select (50 by default).Ǝamazonka-sagemaker>Selects edge deployment plans with names containing this name.ǎamazonka-sagemakerThe response from the last list when returning a list large enough to need tokening.Ȏamazonka-sagemakerThe column by which to sort the edge deployment plans. Can be one of NAME, DEVICEFLEETNAME,  CREATIONTIME, LASTMODIFIEDTIME.Ɏamazonka-sagemaker7The direction of the sorting (ascending or descending).ʎamazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, ˎ: - The token to use when calling the next page of results., ̎# - The response's http status code., ͎. - List of summaries of edge deployment plans.ˎamazonka-sagemaker7The token to use when calling the next page of results.̎amazonka-sagemaker The response's http status code.͎amazonka-sagemaker+List of summaries of edge deployment plans.ʎamazonka-sagemaker ŽÎĎŎƎǎȎɎʎˎ͎̎ ŽÎĎŎƎǎȎɎʎˎ͎̎(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';]ߎamazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe list of domains.amazonka-sagemakerIf the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker'Returns a list up to a specified limit.amazonka-sagemakerIf the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, * - Returns a list up to a specified limit.,  - If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.amazonka-sagemaker'Returns a list up to a specified limit.amazonka-sagemakerIf the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.amazonka-sagemakerCreate a value of ߎ" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The list of domains.,  - If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results., # - The response's http status code.amazonka-sagemakerThe list of domains.amazonka-sagemakerIf the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.amazonka-sagemaker The response's http status code.amazonka-sagemakerߎߎ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe response from the last list when returning a list large enough to need tokening.amazonka-sagemaker The response's http status code.amazonka-sagemakerSummary of devices.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerFilter for fleets containing this name in their device fleet name.amazonka-sagemaker/Select fleets where the job was updated after Xamazonka-sagemaker$Maximum number of results to select.amazonka-sagemakerA filter that searches devices that contains this name in any of their models.amazonka-sagemakerThe response from the last list when returning a list large enough to need tokening.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - Filter for fleets containing this name in their device fleet name., 2 - Select fleets where the job was updated after X, ' - Maximum number of results to select.,  - A filter that searches devices that contains this name in any of their models.,  - The response from the last list when returning a list large enough to need tokening.amazonka-sagemakerFilter for fleets containing this name in their device fleet name.amazonka-sagemaker/Select fleets where the job was updated after Xamazonka-sagemaker$Maximum number of results to select.amazonka-sagemakerA filter that searches devices that contains this name in any of their models.amazonka-sagemakerThe response from the last list when returning a list large enough to need tokening.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The response from the last list when returning a list large enough to need tokening., # - The response's http status code.,  - Summary of devices.amazonka-sagemakerThe response from the last list when returning a list large enough to need tokening.amazonka-sagemaker The response's http status code.amazonka-sagemakerSummary of devices.amazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';uamazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe response from the last list when returning a list large enough to need tokening.amazonka-sagemaker The response's http status code.amazonka-sagemakerSummary of the device fleet.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerFilter fleets where packaging job was created after specified time.amazonka-sagemakerFilter fleets where the edge packaging job was created before specified time.amazonka-sagemaker/Select fleets where the job was updated after Xamazonka-sagemaker0Select fleets where the job was updated before Xamazonka-sagemaker(The maximum number of results to select.amazonka-sagemakerFilter for fleets containing this name in their fleet device name.amazonka-sagemakerThe response from the last list when returning a list large enough to need tokening.amazonka-sagemakerThe column to sort by.amazonka-sagemakerWhat direction to sort in.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - Filter fleets where packaging job was created after specified time.,  - Filter fleets where the edge packaging job was created before specified time., 2 - Select fleets where the job was updated after X, 3 - Select fleets where the job was updated before X, + - The maximum number of results to select.,  - Filter for fleets containing this name in their fleet device name.,  - The response from the last list when returning a list large enough to need tokening.,  - The column to sort by.,  - What direction to sort in.amazonka-sagemakerFilter fleets where packaging job was created after specified time.amazonka-sagemakerFilter fleets where the edge packaging job was created before specified time.amazonka-sagemaker/Select fleets where the job was updated after Xamazonka-sagemaker0Select fleets where the job was updated before Xamazonka-sagemaker(The maximum number of results to select.amazonka-sagemakerFilter for fleets containing this name in their fleet device name.amazonka-sagemakerThe response from the last list when returning a list large enough to need tokening.amazonka-sagemakerThe column to sort by.amazonka-sagemakerWhat direction to sort in.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The response from the last list when returning a list large enough to need tokening., Ï# - The response's http status code., ď - Summary of the device fleet.amazonka-sagemakerThe response from the last list when returning a list large enough to need tokening.Ïamazonka-sagemaker The response's http status code.ďamazonka-sagemakerSummary of the device fleet.amazonka-sagemakerÏďÏď(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';֏amazonka-sagemakerSee:  smart constructor.؏amazonka-sagemakerIf the result of the previous ListDataQualityJobDefinitions1 request was truncated, the response includes a  NextToken. To retrieve the next set of data quality monitoring job definitions, use the token in the next request.ُamazonka-sagemaker The response's http status code.ڏamazonka-sagemaker2A list of data quality monitoring job definitions.ۏamazonka-sagemakerSee:  smart constructor.ݏamazonka-sagemakerA filter that returns only data quality monitoring job definitions created after the specified time.ޏamazonka-sagemakerA filter that returns only data quality monitoring job definitions created before the specified time.ߏamazonka-sagemakerA filter that lists the data quality job definitions associated with the specified endpoint.amazonka-sagemakerThe maximum number of data quality monitoring job definitions to return in the response.amazonka-sagemakerA string in the data quality monitoring job definition name. This filter returns only data quality monitoring job definitions whose name contains the specified string.amazonka-sagemakerIf the result of the previous ListDataQualityJobDefinitions1 request was truncated, the response includes a  NextToken. To retrieve the next set of transform jobs, use the token in the next request.>amazonka-sagemaker-The field to sort results by. The default is  CreationTime.amazonka-sagemaker+The sort order for results. The default is  Descending.amazonka-sagemakerCreate a value of ۏ" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:ݏ,  - A filter that returns only data quality monitoring job definitions created after the specified time.ޏ,  - A filter that returns only data quality monitoring job definitions created before the specified time.ۏ,  - A filter that lists the data quality job definitions associated with the specified endpoint.,  - The maximum number of data quality monitoring job definitions to return in the response.,  - A string in the data quality monitoring job definition name. This filter returns only data quality monitoring job definitions whose name contains the specified string.ۏ, ! - If the result of the previous ListDataQualityJobDefinitions1 request was truncated, the response includes a  NextToken. To retrieve the next set of transform jobs, use the token in the next request.>, 0 - The field to sort results by. The default is  CreationTime., . - The sort order for results. The default is  Descending.amazonka-sagemakerA filter that returns only data quality monitoring job definitions created after the specified time.amazonka-sagemakerA filter that returns only data quality monitoring job definitions created before the specified time.amazonka-sagemakerA filter that lists the data quality job definitions associated with the specified endpoint.amazonka-sagemakerThe maximum number of data quality monitoring job definitions to return in the response.amazonka-sagemakerA string in the data quality monitoring job definition name. This filter returns only data quality monitoring job definitions whose name contains the specified string.amazonka-sagemakerIf the result of the previous ListDataQualityJobDefinitions1 request was truncated, the response includes a  NextToken. To retrieve the next set of transform jobs, use the token in the next request.>amazonka-sagemaker-The field to sort results by. The default is  CreationTime.amazonka-sagemaker+The sort order for results. The default is  Descending.amazonka-sagemakerCreate a value of ֏" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:ۏ, ! - If the result of the previous ListDataQualityJobDefinitions1 request was truncated, the response includes a  NextToken. To retrieve the next set of data quality monitoring job definitions, use the token in the next request.ُ, # - The response's http status code.ڏ, 5 - A list of data quality monitoring job definitions.amazonka-sagemakerIf the result of the previous ListDataQualityJobDefinitions1 request was truncated, the response includes a  NextToken. To retrieve the next set of data quality monitoring job definitions, use the token in the next request.amazonka-sagemaker The response's http status code.amazonka-sagemaker2A list of data quality monitoring job definitions.amazonka-sagemakerُ֏׏ُ؏ڏۏ܏ߏݏޏۏ܏ߏݏޏ֏׏ُ؏ڏ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';/^amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker(A list of contexts and their properties.amazonka-sagemaker?A token for getting the next set of contexts, if there are any.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker:A filter that returns only contexts of the specified type.amazonka-sagemakerA filter that returns only contexts created on or after the specified time.amazonka-sagemakerA filter that returns only contexts created on or before the specified time.amazonka-sagemakerThe maximum number of contexts to return in the response. The default value is 10.amazonka-sagemakerIf the previous call to  ListContexts didn't return the full set of contexts, the call returns a token for getting the next set of contexts.amazonka-sagemaker8The property used to sort results. The default value is  CreationTime.amazonka-sagemaker%The sort order. The default value is  Descending.amazonka-sagemakerA filter that returns only contexts with the specified source URI.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, = - A filter that returns only contexts of the specified type.,  - A filter that returns only contexts created on or after the specified time.,  - A filter that returns only contexts created on or before the specified time.,  - The maximum number of contexts to return in the response. The default value is 10.,  - If the previous call to  ListContexts didn't return the full set of contexts, the call returns a token for getting the next set of contexts., ; - The property used to sort results. The default value is  CreationTime., ( - The sort order. The default value is  Descending.,  - A filter that returns only contexts with the specified source URI.amazonka-sagemaker:A filter that returns only contexts of the specified type.amazonka-sagemakerA filter that returns only contexts created on or after the specified time.amazonka-sagemakerA filter that returns only contexts created on or before the specified time.amazonka-sagemakerThe maximum number of contexts to return in the response. The default value is 10.amazonka-sagemakerIf the previous call to  ListContexts didn't return the full set of contexts, the call returns a token for getting the next set of contexts.amazonka-sagemaker8The property used to sort results. The default value is  CreationTime.amazonka-sagemaker%The sort order. The default value is  Descending.amazonka-sagemakerA filter that returns only contexts with the specified source URI.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, + - A list of contexts and their properties.,  - A token for getting the next set of contexts, if there are any., # - The response's http status code.amazonka-sagemaker(A list of contexts and their properties.amazonka-sagemaker?A token for getting the next set of contexts, if there are any.amazonka-sagemaker The response's http status code.amazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';GBamazonka-sagemakerSee: ̐ smart constructor.amazonka-sagemaker - The parameter by which to sort the results. The default is  Descending., 2 - The sort order for the results. The default is  Ascending., 8 - List the candidates for the job and filter by status.,  - List the candidates created for the job by providing the job's name.amazonka-sagemaker=List the candidates for the job and filter by candidate name.amazonka-sagemaker2List the job's candidates up to a specified limit.amazonka-sagemakerIf the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.amazonka-sagemaker;The parameter by which to sort the results. The default is  Descending.amazonka-sagemaker/The sort order for the results. The default is  Ascending.amazonka-sagemaker5List the candidates for the job and filter by status.amazonka-sagemakerList the candidates created for the job by providing the job's name.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - If the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results., # - The response's http status code.,  - Summaries about the AutoMLCandidates.amazonka-sagemakerIf the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.amazonka-sagemaker The response's http status code.amazonka-sagemakerSummaries about the AutoMLCandidates.amazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';amazonka-sagemakerSee: ב smart constructor.amazonka-sagemakerIf the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.amazonka-sagemaker The response's http status code.amazonka-sagemakerReturns a summary list of jobs.amazonka-sagemakerSee: ̑ smart constructor.‘amazonka-sagemaker0Request a list of jobs, using a filter for time.Ñamazonka-sagemaker0Request a list of jobs, using a filter for time.đamazonka-sagemaker0Request a list of jobs, using a filter for time.őamazonka-sagemaker0Request a list of jobs, using a filter for time.Ƒamazonka-sagemaker/Request a list of jobs up to a specified limit.Ǒamazonka-sagemaker7Request a list of jobs, using a search filter for name.ȑamazonka-sagemakerIf the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.ɑamazonka-sagemaker;The parameter by which to sort the results. The default is Name.ʑamazonka-sagemaker/The sort order for the results. The default is  Descending.ˑamazonka-sagemaker2Request a list of jobs, using a filter for status.̑amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:‘, ͑3 - Request a list of jobs, using a filter for time.Ñ, Α3 - Request a list of jobs, using a filter for time.đ, ϑ3 - Request a list of jobs, using a filter for time.ő, Б3 - Request a list of jobs, using a filter for time.Ƒ, ё2 - Request a list of jobs up to a specified limit.Ǒ, ґ: - Request a list of jobs, using a search filter for name., ӑ - If the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.ɑ, ԑ> - The parameter by which to sort the results. The default is Name.ʑ, Ց2 - The sort order for the results. The default is  Descending.ˑ, ֑5 - Request a list of jobs, using a filter for status.͑amazonka-sagemaker0Request a list of jobs, using a filter for time.Αamazonka-sagemaker0Request a list of jobs, using a filter for time.ϑamazonka-sagemaker0Request a list of jobs, using a filter for time.Бamazonka-sagemaker0Request a list of jobs, using a filter for time.ёamazonka-sagemaker/Request a list of jobs up to a specified limit.ґamazonka-sagemaker7Request a list of jobs, using a search filter for name.ӑamazonka-sagemakerIf the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.ԑamazonka-sagemaker;The parameter by which to sort the results. The default is Name.Ցamazonka-sagemaker/The sort order for the results. The default is  Descending.֑amazonka-sagemaker2Request a list of jobs, using a filter for status.בamazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, ؑ - If the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results., ّ# - The response's http status code., ڑ" - Returns a summary list of jobs.ؑamazonka-sagemakerIf the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.ّamazonka-sagemaker The response's http status code.ڑamazonka-sagemakerReturns a summary list of jobs.בamazonka-sagemaker ɑƑȑʑǑ‘Ñđőˑ̑͑ΑϑБёґӑԑՑ֑בّؑڑ ɑƑȑʑǑ‘Ñđőˑ̑͑ΑϑБёґӑԑՑ֑בّؑڑ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&'; amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker,A list of associations and their properties.amazonka-sagemakerA token for getting the next set of associations, if there are any.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker>A filter that returns only associations of the specified type.amazonka-sagemakerA filter that returns only associations created on or after the specified time.amazonka-sagemakerA filter that returns only associations created on or before the specified time.amazonka-sagemakerA filter that returns only associations with the specified destination Amazon Resource Name (ARN).amazonka-sagemakerA filter that returns only associations with the specified destination type.amazonka-sagemakerThe maximum number of associations to return in the response. The default value is 10.amazonka-sagemakerIf the previous call to ListAssociations didn't return the full set of associations, the call returns a token for getting the next set of associations.amazonka-sagemaker8The property used to sort results. The default value is  CreationTime.amazonka-sagemaker%The sort order. The default value is  Descending.amazonka-sagemakerA filter that returns only associations with the specified source ARN.amazonka-sagemakerA filter that returns only associations with the specified source type.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - A filter that returns only associations of the specified type.,  - A filter that returns only associations created on or after the specified time.,  - A filter that returns only associations created on or before the specified time.,  - A filter that returns only associations with the specified destination Amazon Resource Name (ARN).,  - A filter that returns only associations with the specified destination type.,  - The maximum number of associations to return in the response. The default value is 10.,  - If the previous call to ListAssociations didn't return the full set of associations, the call returns a token for getting the next set of associations., ; - The property used to sort results. The default value is  CreationTime., ( - The sort order. The default value is  Descending.,  - A filter that returns only associations with the specified source ARN.,  - A filter that returns only associations with the specified source type.amazonka-sagemaker>A filter that returns only associations of the specified type.amazonka-sagemakerA filter that returns only associations created on or after the specified time.amazonka-sagemakerA filter that returns only associations created on or before the specified time.amazonka-sagemakerA filter that returns only associations with the specified destination Amazon Resource Name (ARN).amazonka-sagemakerA filter that returns only associations with the specified destination type.amazonka-sagemakerThe maximum number of associations to return in the response. The default value is 10.amazonka-sagemakerIf the previous call to ListAssociations didn't return the full set of associations, the call returns a token for getting the next set of associations.amazonka-sagemaker8The property used to sort results. The default value is  CreationTime.amazonka-sagemaker%The sort order. The default value is  Descending.amazonka-sagemakerA filter that returns only associations with the specified source ARN.amazonka-sagemakerA filter that returns only associations with the specified source type.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, / - A list of associations and their properties.,  - A token for getting the next set of associations, if there are any., # - The response's http status code.amazonka-sagemaker,A list of associations and their properties.amazonka-sagemakerA token for getting the next set of associations, if there are any.amazonka-sagemaker The response's http status code.amazonka-sagemaker""(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';^amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker)A list of artifacts and their properties.amazonka-sagemakerA token for getting the next set of artifacts, if there are any.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker;A filter that returns only artifacts of the specified type.amazonka-sagemakerA filter that returns only artifacts created on or after the specified time.amazonka-sagemakerA filter that returns only artifacts created on or before the specified time.amazonka-sagemakerThe maximum number of artifacts to return in the response. The default value is 10.amazonka-sagemakerIf the previous call to  ListArtifacts didn't return the full set of artifacts, the call returns a token for getting the next set of artifacts.amazonka-sagemaker8The property used to sort results. The default value is  CreationTime.amazonka-sagemaker%The sort order. The default value is  Descending.amazonka-sagemakerA filter that returns only artifacts with the specified source URI.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, > - A filter that returns only artifacts of the specified type.,  - A filter that returns only artifacts created on or after the specified time.,  - A filter that returns only artifacts created on or before the specified time.,  - The maximum number of artifacts to return in the response. The default value is 10.,  - If the previous call to  ListArtifacts didn't return the full set of artifacts, the call returns a token for getting the next set of artifacts., ; - The property used to sort results. The default value is  CreationTime., ( - The sort order. The default value is  Descending.,  - A filter that returns only artifacts with the specified source URI.amazonka-sagemaker;A filter that returns only artifacts of the specified type.amazonka-sagemakerA filter that returns only artifacts created on or after the specified time.amazonka-sagemakerA filter that returns only artifacts created on or before the specified time.amazonka-sagemakerThe maximum number of artifacts to return in the response. The default value is 10.amazonka-sagemakerIf the previous call to  ListArtifacts didn't return the full set of artifacts, the call returns a token for getting the next set of artifacts.amazonka-sagemaker8The property used to sort results. The default value is  CreationTime.amazonka-sagemaker%The sort order. The default value is  Descending.amazonka-sagemakerA filter that returns only artifacts with the specified source URI.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, , - A list of artifacts and their properties.,  - A token for getting the next set of artifacts, if there are any., # - The response's http status code.amazonka-sagemaker)A list of artifacts and their properties.amazonka-sagemakerA token for getting the next set of artifacts, if there are any.amazonka-sagemaker The response's http status code.amazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';̒amazonka-sagemakerSee:  smart constructor.Βamazonka-sagemakerThe list of apps.ϒamazonka-sagemakerIf the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.Вamazonka-sagemaker The response's http status code.ђamazonka-sagemakerSee: ڒ smart constructor.Ӓamazonka-sagemaker(A parameter to search for the domain ID.Ԓamazonka-sagemaker'Returns a list up to a specified limit.Ւamazonka-sagemakerIf the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.֒amazonka-sagemakerThe parameter by which to sort the results. The default is CreationTime.גamazonka-sagemaker9The sort order for the results. The default is Ascending.ؒamazonka-sagemaker(A parameter to search by space name. If UserProfileNameEquals( is set, then this value cannot be set.ْamazonka-sagemaker/A parameter to search by user profile name. If SpaceNameEquals( is set, then this value cannot be set.ڒamazonka-sagemakerCreate a value of ђ" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:Ӓ, ے+ - A parameter to search for the domain ID.Ԓ, ܒ* - Returns a list up to a specified limit.ђ, ݒ - If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.֒, ޒ - The parameter by which to sort the results. The default is CreationTime.ג, ߒ< - The sort order for the results. The default is Ascending.ؒ, + - A parameter to search by space name. If UserProfileNameEquals( is set, then this value cannot be set.ْ, 2 - A parameter to search by user profile name. If SpaceNameEquals( is set, then this value cannot be set.ےamazonka-sagemaker(A parameter to search for the domain ID.ܒamazonka-sagemaker'Returns a list up to a specified limit.ݒamazonka-sagemakerIf the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.ޒamazonka-sagemakerThe parameter by which to sort the results. The default is CreationTime.ߒamazonka-sagemaker9The sort order for the results. The default is Ascending.amazonka-sagemaker(A parameter to search by space name. If UserProfileNameEquals( is set, then this value cannot be set.amazonka-sagemaker/A parameter to search by user profile name. If SpaceNameEquals( is set, then this value cannot be set.amazonka-sagemakerCreate a value of ̒" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:Β,  - The list of apps.ђ,  - If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.В, # - The response's http status code.amazonka-sagemakerThe list of apps.amazonka-sagemakerIf the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.amazonka-sagemaker The response's http status code.amazonka-sagemakerВ̒͒ВϒΒђҒ֒ԒՒגӒْؒڒےܒݒޒߒђҒ֒ԒՒגӒْؒڒےܒݒޒߒ̒͒ВϒΒ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';϶amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker/A list of AppImageConfigs and their properties.amazonka-sagemakerA token for getting the next set of AppImageConfigs, if there are any.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerA filter that returns only AppImageConfigs created on or after the specified time.amazonka-sagemakerA filter that returns only AppImageConfigs created on or before the specified time.amazonka-sagemakerThe maximum number of AppImageConfigs to return in the response. The default value is 10.amazonka-sagemakerA filter that returns only AppImageConfigs modified on or after the specified time.amazonka-sagemakerA filter that returns only AppImageConfigs modified on or before the specified time.amazonka-sagemakerA filter that returns only AppImageConfigs whose name contains the specified string.amazonka-sagemakerIf the previous call to  ListImages didn't return the full set of AppImageConfigs, the call returns a token for getting the next set of AppImageConfigs.amazonka-sagemaker8The property used to sort results. The default value is  CreationTime.amazonka-sagemaker%The sort order. The default value is  Descending.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - A filter that returns only AppImageConfigs created on or after the specified time.,  - A filter that returns only AppImageConfigs created on or before the specified time.,  - The maximum number of AppImageConfigs to return in the response. The default value is 10.,  - A filter that returns only AppImageConfigs modified on or after the specified time.,  - A filter that returns only AppImageConfigs modified on or before the specified time.,  - A filter that returns only AppImageConfigs whose name contains the specified string.,  - If the previous call to  ListImages didn't return the full set of AppImageConfigs, the call returns a token for getting the next set of AppImageConfigs., ; - The property used to sort results. The default value is  CreationTime., ( - The sort order. The default value is  Descending.amazonka-sagemakerA filter that returns only AppImageConfigs created on or after the specified time.amazonka-sagemakerA filter that returns only AppImageConfigs created on or before the specified time.amazonka-sagemakerThe maximum number of AppImageConfigs to return in the response. The default value is 10.amazonka-sagemakerA filter that returns only AppImageConfigs modified on or after the specified time.amazonka-sagemakerA filter that returns only AppImageConfigs modified on or before the specified time.amazonka-sagemakerA filter that returns only AppImageConfigs whose name contains the specified string.amazonka-sagemakerIf the previous call to  ListImages didn't return the full set of AppImageConfigs, the call returns a token for getting the next set of AppImageConfigs.amazonka-sagemaker8The property used to sort results. The default value is  CreationTime.amazonka-sagemaker%The sort order. The default value is  Descending.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 2 - A list of AppImageConfigs and their properties.,  - A token for getting the next set of AppImageConfigs, if there are any., # - The response's http status code.amazonka-sagemaker/A list of AppImageConfigs and their properties.amazonka-sagemakerA token for getting the next set of AppImageConfigs, if there are any.amazonka-sagemaker The response's http status code.amazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&'; amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerA token for getting the next set of aliases, if more aliases exist.amazonka-sagemaker*A list of SageMaker image version aliases.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe alias of the image version.amazonka-sagemaker(The maximum number of aliases to return.amazonka-sagemakerIf the previous call to  ListAliases didn't return the full set of aliases, the call returns a token for retrieving the next set of aliases.amazonka-sagemakerThe version of the image. If image version is not specified, the aliases of all versions of the image are listed.amazonka-sagemakerThe name of the image.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, " - The alias of the image version., + - The maximum number of aliases to return.,  - If the previous call to  ListAliases didn't return the full set of aliases, the call returns a token for retrieving the next set of aliases.,  - The version of the image. If image version is not specified, the aliases of all versions of the image are listed.,  - The name of the image.amazonka-sagemakerThe alias of the image version.amazonka-sagemaker(The maximum number of aliases to return.amazonka-sagemakerIf the previous call to  ListAliases didn't return the full set of aliases, the call returns a token for retrieving the next set of aliases.amazonka-sagemakerThe version of the image. If image version is not specified, the aliases of all versions of the image are listed.amazonka-sagemakerThe name of the image.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - A token for getting the next set of aliases, if more aliases exist., - - A list of SageMaker image version aliases., # - The response's http status code.amazonka-sagemakerA token for getting the next set of aliases, if more aliases exist.amazonka-sagemaker*A list of SageMaker image version aliases.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';͓amazonka-sagemakerSee:  smart constructor.ϓamazonka-sagemakerIf the response is truncated, SageMaker returns this token. To retrieve the next set of algorithms, use it in the subsequent request.Гamazonka-sagemaker The response's http status code.ѓamazonka-sagemaker >An array of @AlgorithmSummary@ objects, each of which lists an algorithm.ғamazonka-sagemakerSee: ۓ smart constructor.ԓamazonka-sagemakerA filter that returns only algorithms created after the specified time (timestamp).Փamazonka-sagemakerA filter that returns only algorithms created before the specified time (timestamp).֓amazonka-sagemaker;The maximum number of algorithms to return in the response.דamazonka-sagemakerA string in the algorithm name. This filter returns only algorithms whose name contains the specified string.ؓamazonka-sagemakerIf the response to a previous ListAlgorithms1 request was truncated, the response includes a  NextToken. To retrieve the next set of algorithms, use the token in the next request.ٓamazonka-sagemaker - The maximum number of algorithms to return in the response.ד, ߓ - A string in the algorithm name. This filter returns only algorithms whose name contains the specified string.ғ, ! - If the response to a previous ListAlgorithms1 request was truncated, the response includes a  NextToken. To retrieve the next set of algorithms, use the token in the next request.ٓ, ? - The parameter by which to sort the results. The default is  CreationTime.ړ, 2 - The sort order for the results. The default is  Ascending.ܓamazonka-sagemakerA filter that returns only algorithms created after the specified time (timestamp).ݓamazonka-sagemakerA filter that returns only algorithms created before the specified time (timestamp).ޓamazonka-sagemaker;The maximum number of algorithms to return in the response.ߓamazonka-sagemakerA string in the algorithm name. This filter returns only algorithms whose name contains the specified string.amazonka-sagemakerIf the response to a previous ListAlgorithms1 request was truncated, the response includes a  NextToken. To retrieve the next set of algorithms, use the token in the next request.amazonka-sagemakerAn array of AlgorithmSummary, objects, each of which lists an algorithm.amazonka-sagemakerIf the response is truncated, SageMaker returns this token. To retrieve the next set of algorithms, use it in the subsequent request.amazonka-sagemaker The response's http status code.amazonka-sagemaker >An array of @AlgorithmSummary@ objects, each of which lists an algorithm.amazonka-sagemakerГ͓ΓГϓѓғӓٓ֓ؓړדԓՓۓܓݓޓߓғӓٓ֓ؓړדԓՓۓܓݓޓߓ͓ΓГϓѓ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&'; amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker'A list of actions and their properties.amazonka-sagemaker>A token for getting the next set of actions, if there are any.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker9A filter that returns only actions of the specified type.amazonka-sagemakerA filter that returns only actions created on or after the specified time.amazonka-sagemakerA filter that returns only actions created on or before the specified time.amazonka-sagemakerThe maximum number of actions to return in the response. The default value is 10.amazonka-sagemakerIf the previous call to  ListActions didn't return the full set of actions, the call returns a token for getting the next set of actions.amazonka-sagemaker8The property used to sort results. The default value is  CreationTime.amazonka-sagemaker%The sort order. The default value is  Descending.amazonka-sagemakerA filter that returns only actions with the specified source URI.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, < - A filter that returns only actions of the specified type.,  - A filter that returns only actions created on or after the specified time.,  - A filter that returns only actions created on or before the specified time.,  - The maximum number of actions to return in the response. The default value is 10.,  - If the previous call to  ListActions didn't return the full set of actions, the call returns a token for getting the next set of actions., ; - The property used to sort results. The default value is  CreationTime., ( - The sort order. The default value is  Descending.,  - A filter that returns only actions with the specified source URI.amazonka-sagemaker9A filter that returns only actions of the specified type.amazonka-sagemakerA filter that returns only actions created on or after the specified time.amazonka-sagemakerA filter that returns only actions created on or before the specified time.amazonka-sagemakerThe maximum number of actions to return in the response. The default value is 10.amazonka-sagemakerIf the previous call to  ListActions didn't return the full set of actions, the call returns a token for getting the next set of actions.amazonka-sagemaker8The property used to sort results. The default value is  CreationTime.amazonka-sagemaker%The sort order. The default value is  Descending.amazonka-sagemakerA filter that returns only actions with the specified source URI.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, * - A list of actions and their properties.,  - A token for getting the next set of actions, if there are any., # - The response's http status code.amazonka-sagemaker'A list of actions and their properties.amazonka-sagemaker>A token for getting the next set of actions, if there are any.amazonka-sagemaker The response's http status code.amazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';  amazonka-sagemakerSee: Ô smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemaker6The ARN of the hub that the content was imported into.amazonka-sagemaker-The ARN of the hub content that was imported.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker+A description of the hub content to import.amazonka-sagemaker.The display name of the hub content to import.amazonka-sagemaker9Markdown files associated with the hub content to import.amazonka-sagemaker+The searchable keywords of the hub content.amazonka-sagemaker)The version of the hub content to import.amazonka-sagemaker)Any tags associated with the hub content.amazonka-sagemaker&The name of the hub content to import.amazonka-sagemaker"The type of hub content to import.amazonka-sagemaker0The version of the hub content schema to import.amazonka-sagemaker+The name of the hub to import content into.amazonka-sagemakerThe hub content document that describes information about the hub content such as type, associated containers, scripts, and more.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, . - A description of the hub content to import., 1 - The display name of the hub content to import., < - Markdown files associated with the hub content to import., . - The searchable keywords of the hub content., , - The version of the hub content to import., , - Any tags associated with the hub content., ) - The name of the hub content to import., % - The type of hub content to import., 3 - The version of the hub content schema to import., . - The name of the hub to import content into., ” - The hub content document that describes information about the hub content such as type, associated containers, scripts, and more.amazonka-sagemaker+A description of the hub content to import.amazonka-sagemaker.The display name of the hub content to import.amazonka-sagemaker9Markdown files associated with the hub content to import.amazonka-sagemaker+The searchable keywords of the hub content.amazonka-sagemaker)The version of the hub content to import.amazonka-sagemaker)Any tags associated with the hub content.amazonka-sagemaker&The name of the hub content to import.amazonka-sagemaker"The type of hub content to import.amazonka-sagemaker0The version of the hub content schema to import.amazonka-sagemaker+The name of the hub to import content into.”amazonka-sagemakerThe hub content document that describes information about the hub content such as type, associated containers, scripts, and more.Ôamazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, Ĕ# - The response's http status code., Ŕ9 - The ARN of the hub that the content was imported into., Ɣ0 - The ARN of the hub content that was imported.Ĕamazonka-sagemaker The response's http status code.Ŕamazonka-sagemaker6The ARN of the hub that the content was imported into.Ɣamazonka-sagemaker-The ARN of the hub content that was imported.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakerÔamazonka-sagemakeramazonka-sagemakeramazonka-sagemaker"”ÔĔŔƔ"”ÔĔŔƔ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';  הamazonka-sagemakerSee:  smart constructor.ٔamazonka-sagemakerA list of property names for a Resource that match a SuggestionQuery.ڔamazonka-sagemaker The response's http status code.۔amazonka-sagemakerSee: ߔ smart constructor.ݔamazonka-sagemaker - The Amazon Resource Name (ARN) of the AutoML transform job.,  - Specifies the number of records to include in a mini-batch for an HTTP inference request. A record // is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.+To enable the batch strategy, you must set  SplitType to Line, RecordIO, or TFRecord.,  - Configuration to control how SageMaker captures inference data.,  - Undocumented member.,  - The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.,  - Undocumented member.,  - If the transform job failed,  FailureReason describes why it failed. A transform job creates a log file, which includes error messages, and stores it as an Amazon S3 object. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/logging-cloudwatch.html2Log Amazon SageMaker Events with Amazon CloudWatch.,  - The Amazon Resource Name (ARN) of the Amazon SageMaker Ground Truth labeling job that created the transform or training job.,  - The maximum number of parallel requests on each instance node that can be launched in a transform job. The default value is 1., > - The maximum payload size, in MB, used in the transform job.,  - The timeout and maximum number of retries for processing a transform job invocation., ˜ - Indicates when the transform job has been completed, or has stopped or failed. You are billed for the time interval between this time and the value of TransformStartTime., Ø - Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job., Ę - Indicates when the transform job starts on ML instances. You are billed for the time interval between this time and the value of TransformEndTime., Ř# - The response's http status code., Ƙ! - The name of the transform job., ǘ7 - The Amazon Resource Name (ARN) of the transform job., Ș - The status of the transform job. If the transform job failed, the reason is returned in the  FailureReason field., ɘ3 - The name of the model used in the transform job., ʘ - Describes the dataset to be transformed and the Amazon S3 location where it is stored., ˘ - Describes the resources, including ML instance types and ML instance count, to use for the transform job., ̘= - A timestamp that shows when the transform Job was created.amazonka-sagemaker;The Amazon Resource Name (ARN) of the AutoML transform job.amazonka-sagemakerSpecifies the number of records to include in a mini-batch for an HTTP inference request. A record // is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.+To enable the batch strategy, you must set  SplitType to Line, RecordIO, or TFRecord.amazonka-sagemaker?Configuration to control how SageMaker captures inference data.amazonka-sagemakerUndocumented member.amazonka-sagemakerThe environment variables to set in the Docker container. We support up to 16 key and values entries in the map.amazonka-sagemakerUndocumented member.amazonka-sagemakerIf the transform job failed,  FailureReason describes why it failed. A transform job creates a log file, which includes error messages, and stores it as an Amazon S3 object. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/logging-cloudwatch.html2Log Amazon SageMaker Events with Amazon CloudWatch.amazonka-sagemakerThe Amazon Resource Name (ARN) of the Amazon SageMaker Ground Truth labeling job that created the transform or training job.amazonka-sagemakerThe maximum number of parallel requests on each instance node that can be launched in a transform job. The default value is 1.amazonka-sagemaker;The maximum payload size, in MB, used in the transform job.amazonka-sagemakerThe timeout and maximum number of retries for processing a transform job invocation.˜amazonka-sagemakerIndicates when the transform job has been completed, or has stopped or failed. You are billed for the time interval between this time and the value of TransformStartTime.Øamazonka-sagemakerIdentifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.Ęamazonka-sagemakerIndicates when the transform job starts on ML instances. You are billed for the time interval between this time and the value of TransformEndTime.Řamazonka-sagemaker The response's http status code.Ƙamazonka-sagemakerThe name of the transform job.ǘamazonka-sagemaker4The Amazon Resource Name (ARN) of the transform job.Șamazonka-sagemakerThe status of the transform job. If the transform job failed, the reason is returned in the  FailureReason field.ɘamazonka-sagemaker0The name of the model used in the transform job.ʘamazonka-sagemakerDescribes the dataset to be transformed and the Amazon S3 location where it is stored.˘amazonka-sagemakerDescribes the resources, including ML instance types and ML instance count, to use for the transform job.̘amazonka-sagemaker:A timestamp that shows when the transform Job was created.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker4˜ØĘŘƘǘȘɘʘ˘̘4˜ØĘŘƘǘȘɘʘ˘̘(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';!)ݘamazonka-sagemakerSee:  smart constructor.ߘamazonka-sagemaker0The Amazon Resource Name (ARN) of an AutoML job.amazonka-sagemakerThe billable time in seconds. Billable time refers to the absolute wall-clock time. Multiply BillableTimeInSeconds by the number of instances ( InstanceCount) in your training cluster to get the total compute time SageMaker bills you if you run distributed training. The formula is as follows: %BillableTimeInSeconds * InstanceCount .You can calculate the savings from using managed spot training using the formula 9(1 - BillableTimeInSeconds / TrainingTimeInSeconds) * 100. For example, if BillableTimeInSeconds is 100 and TrainingTimeInSeconds is 500, the savings is 80%.amazonka-sagemakerConfiguration information for Amazon SageMaker Debugger rules for debugging output tensors.amazonka-sagemakerEvaluation status of Amazon SageMaker Debugger rules for debugging on a training job.amazonka-sagemakerTo encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithms in distributed training.amazonka-sagemaker?A Boolean indicating whether managed spot training is enabled (True ) or not (False).amazonka-sagemakerIf you want to allow inbound or outbound network calls, except for calls between peers within a training cluster for distributed training, choose True. If you enable network isolation for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.amazonka-sagemaker9The environment variables to set in the Docker container.amazonka-sagemaker1If the training job failed, the reason it failed.amazonka-sagemakerA collection of  MetricData objects that specify the names, values, and dates and times that the training algorithm emitted to Amazon CloudWatch.amazonka-sagemakerAlgorithm-specific parameters.amazonka-sagemaker An array of Channel0 objects that describes each data input channel.amazonka-sagemakerThe Amazon Resource Name (ARN) of the SageMaker Ground Truth labeling job that created the transform or training job.amazonka-sagemakerA timestamp that indicates when the status of the training job was last modified.amazonka-sagemakerThe S3 path where model artifacts that you configured when creating the job are stored. SageMaker creates subfolders for model artifacts.amazonka-sagemakerConfiguration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.amazonka-sagemakerEvaluation status of Amazon SageMaker Debugger rules for profiling on a training job.amazonka-sagemaker#Profiling status of a training job.amazonka-sagemakerThe number of times to retry the job when the job fails due to an InternalServerError.amazonka-sagemakerThe Amazon Web Services Identity and Access Management (IAM) role configured for the training job.amazonka-sagemakerA history of all of the secondary statuses that the training job has transitioned through.amazonka-sagemakerIndicates the time when the training job ends on training instances. You are billed for the time interval between the value of TrainingStartTime and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when SageMaker detects a job failure.amazonka-sagemakerIndicates the time when the training job starts on training instances. You are billed for the time interval between this time and the value of TrainingEndTime. The start time in CloudWatch Logs might be later than this time. The difference is due to the time it takes to download the training data and to the size of the training container.amazonka-sagemakerThe training time in seconds.amazonka-sagemakerThe Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.amazonka-sagemakerA VpcConfig object that specifies the VPC that this training job has access to. For more information, see  >https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html>Protect Training Jobs by Using an Amazon Virtual Private Cloud.amazonka-sagemaker=The status of the warm pool associated with the training job.amazonka-sagemaker The response's http status code.amazonka-sagemakerName of the model training job.amazonka-sagemaker3The Amazon Resource Name (ARN) of the training job.amazonka-sagemakerInformation about the Amazon S3 location that is configured for storing model artifacts.amazonka-sagemakerThe status of the training job.7SageMaker provides the following training job statuses: InProgress - The training is in progress. Completed" - The training job has completed.Failed - The training job has failed. To see the reason for the failure, see the  FailureReason! field in the response to a DescribeTrainingJobResponse call.Stopping - The training job is stopping.Stopped - The training job has stopped.#For more detailed information, see SecondaryStatus.amazonka-sagemakerProvides detailed information about the state of the training job. For detailed information on the secondary status of the training job, see  StatusMessage! under SecondaryStatusTransition.SageMaker provides primary statuses and secondary statuses that apply to each of them:  InProgress- Starting - Starting the training job. Downloading5 - An optional stage for algorithms that support File training input mode. It indicates that data is being downloaded to the ML storage volumes.Training - Training is in progress. Interrupted - The job stopped because the managed spot training instances were interrupted. Uploading - Training is complete and the model artifacts are being uploaded to the S3 location. Completed-  Completed" - The training job has completed.Failed- Failed - The training job has failed. The reason for the failure is returned in the  FailureReason field of DescribeTrainingJobResponse.Stopped- MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.MaxWaitTimeExceeded - The job stopped because it exceeded the maximum allowed wait time.Stopped - The training job has stopped.Stopping- Stopping - Stopping the training job.Valid values for SecondaryStatus are subject to change.6We no longer support the following secondary statuses: LaunchingMLInstances PreparingTraining DownloadingTrainingImageamazonka-sagemakerInformation about the algorithm used for training, and algorithm metadata.amazonka-sagemakerResources, including ML compute instances and ML storage volumes, that are configured for model training.amazonka-sagemakerSpecifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.1To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.amazonka-sagemaker=A timestamp that indicates when the training job was created.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe name of the training job.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The name of the training job.amazonka-sagemakerThe name of the training job.amazonka-sagemakerCreate a value of ݘ" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:ݘ, 3 - The Amazon Resource Name (ARN) of an AutoML job.ݘ,  - The billable time in seconds. Billable time refers to the absolute wall-clock time. Multiply BillableTimeInSeconds by the number of instances ( InstanceCount) in your training cluster to get the total compute time SageMaker bills you if you run distributed training. The formula is as follows: %BillableTimeInSeconds * InstanceCount .You can calculate the savings from using managed spot training using the formula 9(1 - BillableTimeInSeconds / TrainingTimeInSeconds) * 100. For example, if BillableTimeInSeconds is 100 and TrainingTimeInSeconds is 500, the savings is 80%.ݘ,  - Undocumented member.ݘ,  - Undocumented member.ݘ,  - Configuration information for Amazon SageMaker Debugger rules for debugging output tensors.ݘ,  - Evaluation status of Amazon SageMaker Debugger rules for debugging on a training job.ݘ,  - To encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithms in distributed training.ݘ,  - A Boolean indicating whether managed spot training is enabled (True ) or not (False).ݘ,  - If you want to allow inbound or outbound network calls, except for calls between peers within a training cluster for distributed training, choose True. If you enable network isolation for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.ݘ, < - The environment variables to set in the Docker container.ݘ,  - Undocumented member.ݘ, 4 - If the training job failed, the reason it failed.ݘ,  - A collection of  MetricData objects that specify the names, values, and dates and times that the training algorithm emitted to Amazon CloudWatch.ݘ, ! - Algorithm-specific parameters.ݘ,  - An array of Channel0 objects that describes each data input channel.ݘ,  - The Amazon Resource Name (ARN) of the SageMaker Ground Truth labeling job that created the transform or training job.ݘ,  - A timestamp that indicates when the status of the training job was last modified.ݘ,  - The S3 path where model artifacts that you configured when creating the job are stored. SageMaker creates subfolders for model artifacts.,  - Undocumented member.,  - Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.,  - Evaluation status of Amazon SageMaker Debugger rules for profiling on a training job., & - Profiling status of a training job.ݘ,  - The number of times to retry the job when the job fails due to an InternalServerError.ݘ,  - The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.ݘ,  - A history of all of the secondary statuses that the training job has transitioned through.ݘ,  - Undocumented member.ݘ,  - Indicates the time when the training job ends on training instances. You are billed for the time interval between the value of TrainingStartTime and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when SageMaker detects a job failure.ݘ,  - Indicates the time when the training job starts on training instances. You are billed for the time interval between this time and the value of TrainingEndTime. The start time in CloudWatch Logs might be later than this time. The difference is due to the time it takes to download the training data and to the size of the training container.ݘ,  - The training time in seconds.ݘ,  - The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.ݘ,  - A VpcConfig object that specifies the VPC that this training job has access to. For more information, see  >https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html>Protect Training Jobs by Using an Amazon Virtual Private Cloud.ݘ,  - The status of the warm pool associated with the training job., # - The response's http status code., " - Name of the model training job.ݘ, 6 - The Amazon Resource Name (ARN) of the training job.ݘ,  - Information about the Amazon S3 location that is configured for storing model artifacts.ݘ, " - The status of the training job.7SageMaker provides the following training job statuses: InProgress - The training is in progress. Completed" - The training job has completed.Failed - The training job has failed. To see the reason for the failure, see the  FailureReason! field in the response to a DescribeTrainingJobResponse call.Stopping - The training job is stopping.Stopped - The training job has stopped.#For more detailed information, see SecondaryStatus.ݘ,  - Provides detailed information about the state of the training job. For detailed information on the secondary status of the training job, see  StatusMessage! under SecondaryStatusTransition.SageMaker provides primary statuses and secondary statuses that apply to each of them:  InProgress- Starting - Starting the training job. Downloading5 - An optional stage for algorithms that support File training input mode. It indicates that data is being downloaded to the ML storage volumes.Training - Training is in progress. Interrupted - The job stopped because the managed spot training instances were interrupted. Uploading - Training is complete and the model artifacts are being uploaded to the S3 location. Completed-  Completed" - The training job has completed.Failed- Failed - The training job has failed. The reason for the failure is returned in the  FailureReason field of DescribeTrainingJobResponse.Stopped- MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.MaxWaitTimeExceeded - The job stopped because it exceeded the maximum allowed wait time.Stopped - The training job has stopped.Stopping- Stopping - Stopping the training job.Valid values for SecondaryStatus are subject to change.6We no longer support the following secondary statuses: LaunchingMLInstances PreparingTraining DownloadingTrainingImageݘ,  - Information about the algorithm used for training, and algorithm metadata.ݘ,  - Resources, including ML compute instances and ML storage volumes, that are configured for model training.ݘ,  - Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.1To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.ݘ,  - A timestamp that indicates when the training job was created.amazonka-sagemaker0The Amazon Resource Name (ARN) of an AutoML job.amazonka-sagemakerThe billable time in seconds. Billable time refers to the absolute wall-clock time. Multiply BillableTimeInSeconds by the number of instances ( InstanceCount) in your training cluster to get the total compute time SageMaker bills you if you run distributed training. The formula is as follows: %BillableTimeInSeconds * InstanceCount .You can calculate the savings from using managed spot training using the formula 9(1 - BillableTimeInSeconds / TrainingTimeInSeconds) * 100. For example, if BillableTimeInSeconds is 100 and TrainingTimeInSeconds is 500, the savings is 80%.amazonka-sagemakerUndocumented member.amazonka-sagemakerUndocumented member.amazonka-sagemakerConfiguration information for Amazon SageMaker Debugger rules for debugging output tensors.amazonka-sagemakerEvaluation status of Amazon SageMaker Debugger rules for debugging on a training job.amazonka-sagemakerTo encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithms in distributed training.amazonka-sagemaker?A Boolean indicating whether managed spot training is enabled (True ) or not (False).amazonka-sagemakerIf you want to allow inbound or outbound network calls, except for calls between peers within a training cluster for distributed training, choose True. If you enable network isolation for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.amazonka-sagemaker9The environment variables to set in the Docker container.amazonka-sagemakerUndocumented member.amazonka-sagemaker1If the training job failed, the reason it failed.amazonka-sagemakerA collection of  MetricData objects that specify the names, values, and dates and times that the training algorithm emitted to Amazon CloudWatch.amazonka-sagemakerAlgorithm-specific parameters.amazonka-sagemaker An array of Channel0 objects that describes each data input channel.amazonka-sagemakerThe Amazon Resource Name (ARN) of the SageMaker Ground Truth labeling job that created the transform or training job.amazonka-sagemakerA timestamp that indicates when the status of the training job was last modified.amazonka-sagemakerThe S3 path where model artifacts that you configured when creating the job are stored. SageMaker creates subfolders for model artifacts.amazonka-sagemakerUndocumented member.amazonka-sagemakerConfiguration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.amazonka-sagemakerEvaluation status of Amazon SageMaker Debugger rules for profiling on a training job.amazonka-sagemaker#Profiling status of a training job.amazonka-sagemakerThe number of times to retry the job when the job fails due to an InternalServerError.amazonka-sagemakerThe Amazon Web Services Identity and Access Management (IAM) role configured for the training job.amazonka-sagemakerA history of all of the secondary statuses that the training job has transitioned through.amazonka-sagemakerUndocumented member.amazonka-sagemakerIndicates the time when the training job ends on training instances. You are billed for the time interval between the value of TrainingStartTime and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when SageMaker detects a job failure.amazonka-sagemakerIndicates the time when the training job starts on training instances. You are billed for the time interval between this time and the value of TrainingEndTime. The start time in CloudWatch Logs might be later than this time. The difference is due to the time it takes to download the training data and to the size of the training container.amazonka-sagemakerThe training time in seconds.amazonka-sagemakerThe Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.amazonka-sagemakerA VpcConfig object that specifies the VPC that this training job has access to. For more information, see  >https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html>Protect Training Jobs by Using an Amazon Virtual Private Cloud.amazonka-sagemaker=The status of the warm pool associated with the training job.amazonka-sagemaker The response's http status code.amazonka-sagemakerName of the model training job.amazonka-sagemaker3The Amazon Resource Name (ARN) of the training job.amazonka-sagemakerInformation about the Amazon S3 location that is configured for storing model artifacts.amazonka-sagemakerThe status of the training job.7SageMaker provides the following training job statuses: InProgress - The training is in progress. Completed" - The training job has completed.Failed - The training job has failed. To see the reason for the failure, see the  FailureReason! field in the response to a DescribeTrainingJobResponse call.Stopping - The training job is stopping.Stopped - The training job has stopped.#For more detailed information, see SecondaryStatus.amazonka-sagemakerProvides detailed information about the state of the training job. For detailed information on the secondary status of the training job, see  StatusMessage! under SecondaryStatusTransition.SageMaker provides primary statuses and secondary statuses that apply to each of them:  InProgress- Starting - Starting the training job. Downloading5 - An optional stage for algorithms that support File training input mode. It indicates that data is being downloaded to the ML storage volumes.Training - Training is in progress. Interrupted - The job stopped because the managed spot training instances were interrupted. Uploading - Training is complete and the model artifacts are being uploaded to the S3 location. Completed-  Completed" - The training job has completed.Failed- Failed - The training job has failed. The reason for the failure is returned in the  FailureReason field of DescribeTrainingJobResponse.Stopped- MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.MaxWaitTimeExceeded - The job stopped because it exceeded the maximum allowed wait time.Stopped - The training job has stopped.Stopping- Stopping - Stopping the training job.Valid values for SecondaryStatus are subject to change.6We no longer support the following secondary statuses: LaunchingMLInstances PreparingTraining DownloadingTrainingImageamazonka-sagemakerInformation about the algorithm used for training, and algorithm metadata.amazonka-sagemakerResources, including ML compute instances and ML storage volumes, that are configured for model training.amazonka-sagemakerSpecifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.1To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.amazonka-sagemaker=A timestamp that indicates when the training job was created.amazonka-sagemaker amazonka-sagemakeramazonka-sagemakeramazonka-sagemakerݘamazonka-sagemakerݘamazonka-sagemakerݘamazonka-sagemakerݘamazonka-sagemakerݘamazonka-sagemakerݘamazonka-sagemakerݘ amazonka-sagemakerݘݘޘߘݘޘߘ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';!2 əamazonka-sagemakerSee: ҙ smart constructor.˙amazonka-sagemaker The response's http status code.̙amazonka-sagemakerA Workteam8 instance that contains information about the work team.͙amazonka-sagemakerSee: Й smart constructor.ϙamazonka-sagemakerThe Amazon Resource Name (ARN) of the subscribed work team to describe.Йamazonka-sagemakerCreate a value of ͙" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:͙, љ - The Amazon Resource Name (ARN) of the subscribed work team to describe.љamazonka-sagemakerThe Amazon Resource Name (ARN) of the subscribed work team to describe.ҙamazonka-sagemakerCreate a value of ə" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:˙, ә# - The response's http status code.̙, ԙ - A Workteam8 instance that contains information about the work team.әamazonka-sagemaker The response's http status code.ԙamazonka-sagemakerA Workteam8 instance that contains information about the work team.Йamazonka-sagemaker͙ҙamazonka-sagemaker˙amazonka-sagemaker̙ əʙ˙̙͙ΙϙЙљҙәԙ ͙ΙϙЙљəʙ˙̙ҙәԙ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';!?Oamazonka-sagemakerSee:  smart constructor.amazonka-sagemaker8The creation time of the Studio Lifecycle Configuration.amazonka-sagemakerThis value is equivalent to CreationTime because Studio Lifecycle Configurations are immutable.amazonka-sagemaker=The App type that the Lifecycle Configuration is attached to.amazonka-sagemaker3The ARN of the Lifecycle Configuration to describe.amazonka-sagemaker:The content of your Studio Lifecycle Configuration script.amazonka-sagemakerThe name of the Studio Lifecycle Configuration that is described.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker;The name of the Studio Lifecycle Configuration to describe.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, > - The name of the Studio Lifecycle Configuration to describe.amazonka-sagemaker;The name of the Studio Lifecycle Configuration to describe.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, ; - The creation time of the Studio Lifecycle Configuration.,  - This value is equivalent to CreationTime because Studio Lifecycle Configurations are immutable.,  - The App type that the Lifecycle Configuration is attached to., 6 - The ARN of the Lifecycle Configuration to describe., = - The content of your Studio Lifecycle Configuration script.,  - The name of the Studio Lifecycle Configuration that is described., # - The response's http status code.amazonka-sagemaker8The creation time of the Studio Lifecycle Configuration.amazonka-sagemakerThis value is equivalent to CreationTime because Studio Lifecycle Configurations are immutable.amazonka-sagemaker=The App type that the Lifecycle Configuration is attached to.amazonka-sagemaker3The ARN of the Lifecycle Configuration to describe.amazonka-sagemaker:The content of your Studio Lifecycle Configuration script.amazonka-sagemakerThe name of the Studio Lifecycle Configuration that is described.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';!Lamazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe creation time.amazonka-sagemaker The ID of the associated Domain.amazonka-sagemakerThe failure reason.amazonka-sagemakerThe ID of the space's profile in the Amazon Elastic File System volume.amazonka-sagemakerThe last modified time.amazonka-sagemaker'The space's Amazon Resource Name (ARN).amazonka-sagemakerThe name of the space.amazonka-sagemakerA collection of space settings.amazonka-sagemaker The status.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The ID of the associated Domain.amazonka-sagemakerThe name of the space.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The ID of the associated Domain.,  - The name of the space.amazonka-sagemaker The ID of the associated Domain.amazonka-sagemakerThe name of the space.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The creation time., # - The ID of the associated Domain.,  - The failure reason.,  - The ID of the space's profile in the Amazon Elastic File System volume.,  - The last modified time., * - The space's Amazon Resource Name (ARN).,  - The name of the space., " - A collection of space settings.,  - The status., # - The response's http status code.amazonka-sagemakerThe creation time.amazonka-sagemaker The ID of the associated Domain.amazonka-sagemakerThe failure reason.amazonka-sagemakerThe ID of the space's profile in the Amazon Elastic File System volume.amazonka-sagemakerThe last modified time.amazonka-sagemaker'The space's Amazon Resource Name (ARN).amazonka-sagemakerThe name of the space.amazonka-sagemakerA collection of space settings.amazonka-sagemaker The status.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';!\amazonka-sagemakerSee: ̚ smart constructor.amazonka-sagemaker-The timestamp when project was last modified.amazonka-sagemakerThe description of the project.amazonka-sagemaker8Information about a provisioned service catalog product.amazonka-sagemaker The response's http status code.amazonka-sagemaker.The Amazon Resource Name (ARN) of the project.šamazonka-sagemakerThe name of the project.Úamazonka-sagemakerThe ID of the project.Ěamazonka-sagemakerInformation used to provision a service catalog product. For information, see  https://docs.aws.amazon.com/servicecatalog/latest/adminguide/introduction.html+What is Amazon Web Services Service Catalog.Śamazonka-sagemakerThe status of the project.ƚamazonka-sagemaker&The time when the project was created.ǚamazonka-sagemakerSee: ʚ smart constructor.ɚamazonka-sagemaker$The name of the project to describe.ʚamazonka-sagemakerCreate a value of ǚ" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:ǚ, ˚' - The name of the project to describe.˚amazonka-sagemaker$The name of the project to describe.̚amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, ͚ - Undocumented member., Κ - Undocumented member., Ϛ0 - The timestamp when project was last modified., К" - The description of the project., њ; - Information about a provisioned service catalog product., Қ# - The response's http status code., Ӛ1 - The Amazon Resource Name (ARN) of the project.ǚ, Ԛ - The name of the project., ՚ - The ID of the project., ֚ - Information used to provision a service catalog product. For information, see  https://docs.aws.amazon.com/servicecatalog/latest/adminguide/introduction.html+What is Amazon Web Services Service Catalog., ך - The status of the project., ؚ) - The time when the project was created.͚amazonka-sagemakerUndocumented member.Κamazonka-sagemakerUndocumented member.Ϛamazonka-sagemaker-The timestamp when project was last modified.Кamazonka-sagemakerThe description of the project.њamazonka-sagemaker8Information about a provisioned service catalog product.Қamazonka-sagemaker The response's http status code.Ӛamazonka-sagemaker.The Amazon Resource Name (ARN) of the project.Ԛamazonka-sagemakerThe name of the project.՚amazonka-sagemakerThe ID of the project.֚amazonka-sagemakerInformation used to provision a service catalog product. For information, see  https://docs.aws.amazon.com/servicecatalog/latest/adminguide/introduction.html+What is Amazon Web Services Service Catalog.ךamazonka-sagemakerThe status of the project.ؚamazonka-sagemaker&The time when the project was created.ʚamazonka-sagemakerǚ̚amazonka-sagemakeramazonka-sagemakeramazonka-sagemakerǚamazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker ƚÚšŚĚǚȚɚʚ˚͚̚ΚϚКњҚӚԚ՚֚ךؚ ǚȚɚʚ˚ƚÚšŚĚ͚̚ΚϚКњҚӚԚ՚֚ךؚ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';!|2amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker=The ARN of an AutoML job associated with this processing job.amazonka-sagemaker6The environment variables set in the Docker container.amazonka-sagemakerAn optional string, up to one KB in size, that contains metadata from the processing container when the processing job exits.amazonka-sagemaker;The configuration information used to create an experiment.amazonka-sagemakerA string, up to one KB in size, that contains the reason a processing job failed, if it failed.amazonka-sagemaker7The time at which the processing job was last modified.amazonka-sagemakerThe ARN of a monitoring schedule for an endpoint associated with this processing job.amazonka-sagemaker(Networking options for a processing job.amazonka-sagemaker/The time at which the processing job completed.amazonka-sagemaker The inputs for a processing job.amazonka-sagemaker,Output configuration for the processing job.amazonka-sagemaker-The time at which the processing job started.amazonka-sagemakerThe Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.amazonka-sagemakerThe time limit for how long the processing job is allowed to run.amazonka-sagemaker>The ARN of a training job associated with this processing job.amazonka-sagemaker The response's http status code.amazonka-sagemakerThe name of the processing job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.amazonka-sagemakerIdentifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.amazonka-sagemakerConfigures the processing job to run a specified container image.amazonka-sagemaker5The Amazon Resource Name (ARN) of the processing job.amazonka-sagemaker(Provides the status of a processing job.amazonka-sagemaker1The time at which the processing job was created.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe name of the processing job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The name of the processing job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.amazonka-sagemakerThe name of the processing job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The ARN of an AutoML job associated with this processing job., 9 - The environment variables set in the Docker container.,  - An optional string, up to one KB in size, that contains metadata from the processing container when the processing job exits., > - The configuration information used to create an experiment.,  - A string, up to one KB in size, that contains the reason a processing job failed, if it failed., : - The time at which the processing job was last modified.,  - The ARN of a monitoring schedule for an endpoint associated with this processing job., + - Networking options for a processing job., 2 - The time at which the processing job completed., # - The inputs for a processing job., / - Output configuration for the processing job., 0 - The time at which the processing job started.,  - The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.,  - The time limit for how long the processing job is allowed to run.,  - The ARN of a training job associated with this processing job., # - The response's http status code.,  - The name of the processing job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.,  - Identifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.,  - Configures the processing job to run a specified container image., 8 - The Amazon Resource Name (ARN) of the processing job., + - Provides the status of a processing job., 4 - The time at which the processing job was created.amazonka-sagemaker=The ARN of an AutoML job associated with this processing job.amazonka-sagemaker6The environment variables set in the Docker container.amazonka-sagemakerAn optional string, up to one KB in size, that contains metadata from the processing container when the processing job exits.amazonka-sagemaker;The configuration information used to create an experiment.amazonka-sagemakerA string, up to one KB in size, that contains the reason a processing job failed, if it failed.amazonka-sagemaker7The time at which the processing job was last modified.amazonka-sagemakerThe ARN of a monitoring schedule for an endpoint associated with this processing job.amazonka-sagemaker(Networking options for a processing job.amazonka-sagemaker/The time at which the processing job completed.amazonka-sagemaker The inputs for a processing job.amazonka-sagemaker,Output configuration for the processing job.amazonka-sagemaker-The time at which the processing job started.amazonka-sagemakerThe Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.amazonka-sagemakerThe time limit for how long the processing job is allowed to run.amazonka-sagemaker>The ARN of a training job associated with this processing job.amazonka-sagemaker The response's http status code.amazonka-sagemakerThe name of the processing job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.amazonka-sagemakerIdentifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.amazonka-sagemakerConfigures the processing job to run a specified container image.amazonka-sagemaker5The Amazon Resource Name (ARN) of the processing job.amazonka-sagemaker(Provides the status of a processing job.amazonka-sagemaker1The time at which the processing job was created.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker44(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';!amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker1The time when the pipeline execution was created.amazonka-sagemaker2If the execution failed, a message describing why.amazonka-sagemaker7The time when the pipeline execution was modified last.amazonka-sagemaker6The parallelism configuration applied to the pipeline.amazonka-sagemaker/The Amazon Resource Name (ARN) of the pipeline.amazonka-sagemaker9The Amazon Resource Name (ARN) of the pipeline execution.amazonka-sagemaker*The description of the pipeline execution.amazonka-sagemaker+The display name of the pipeline execution.amazonka-sagemaker%The status of the pipeline execution.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker9The Amazon Resource Name (ARN) of the pipeline execution.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, < - The Amazon Resource Name (ARN) of the pipeline execution.amazonka-sagemaker9The Amazon Resource Name (ARN) of the pipeline execution.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, › - Undocumented member., Û4 - The time when the pipeline execution was created., ě5 - If the execution failed, a message describing why., ś - Undocumented member., ƛ: - The time when the pipeline execution was modified last., Ǜ9 - The parallelism configuration applied to the pipeline., ț2 - The Amazon Resource Name (ARN) of the pipeline., ɛ< - The Amazon Resource Name (ARN) of the pipeline execution., ʛ- - The description of the pipeline execution., ˛. - The display name of the pipeline execution., ̛( - The status of the pipeline execution., ͛ - Undocumented member., Λ# - The response's http status code.›amazonka-sagemakerUndocumented member.Ûamazonka-sagemaker1The time when the pipeline execution was created.ěamazonka-sagemaker2If the execution failed, a message describing why.śamazonka-sagemakerUndocumented member.ƛamazonka-sagemaker7The time when the pipeline execution was modified last.Ǜamazonka-sagemaker6The parallelism configuration applied to the pipeline.țamazonka-sagemaker/The Amazon Resource Name (ARN) of the pipeline.ɛamazonka-sagemaker9The Amazon Resource Name (ARN) of the pipeline execution.ʛamazonka-sagemaker*The description of the pipeline execution.˛amazonka-sagemaker+The display name of the pipeline execution.̛amazonka-sagemaker%The status of the pipeline execution.͛amazonka-sagemakerUndocumented member.Λamazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemaker"›ÛěśƛǛțɛʛ˛̛͛Λ"›ÛěśƛǛțɛʛ˛̛͛Λ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';! ߛamazonka-sagemakerSee:  smart constructor.amazonka-sagemaker'The time when the pipeline was created.amazonka-sagemakerThe JSON pipeline definition.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker9The Amazon Resource Name (ARN) of the pipeline execution.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, < - The Amazon Resource Name (ARN) of the pipeline execution.amazonka-sagemaker9The Amazon Resource Name (ARN) of the pipeline execution.amazonka-sagemakerCreate a value of ߛ" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:ߛ, * - The time when the pipeline was created.,  - The JSON pipeline definition., # - The response's http status code.amazonka-sagemaker'The time when the pipeline was created.amazonka-sagemakerThe JSON pipeline definition.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemakerߛߛ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';!i amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker'The time when the pipeline was created.amazonka-sagemaker-The time when the pipeline was last modified.amazonka-sagemaker(The time when the pipeline was last run.amazonka-sagemakerThe Amazon Resource Name (ARN) of the lifecycle configuration.amazonka-sagemaker(The name of the lifecycle configuration.amazonka-sagemakerThe shell script that runs only once, when you create a notebook instance.amazonka-sagemakerThe shell script that runs every time you start a notebook instance, including when you create the notebook instance.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker4The name of the lifecycle configuration to describe.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 7 - The name of the lifecycle configuration to describe.amazonka-sagemaker4The name of the lifecycle configuration to describe.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - A timestamp that tells when the lifecycle configuration was created.,  - A timestamp that tells when the lifecycle configuration was last modified., œ - The Amazon Resource Name (ARN) of the lifecycle configuration., Ü+ - The name of the lifecycle configuration., Ĝ - The shell script that runs only once, when you create a notebook instance., Ŝ - The shell script that runs every time you start a notebook instance, including when you create the notebook instance., Ɯ# - The response's http status code.amazonka-sagemakerA timestamp that tells when the lifecycle configuration was created.amazonka-sagemakerA timestamp that tells when the lifecycle configuration was last modified.œamazonka-sagemaker>The Amazon Resource Name (ARN) of the lifecycle configuration.Üamazonka-sagemaker(The name of the lifecycle configuration.Ĝamazonka-sagemakerThe shell script that runs only once, when you create a notebook instance.Ŝamazonka-sagemakerThe shell script that runs every time you start a notebook instance, including when you create the notebook instance.Ɯamazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemakerœÜĜŜƜœÜĜŜƜ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';!4לamazonka-sagemakerSee:  smart constructor.ٜamazonka-sagemakerA list of the Elastic Inference (EI) instance types associated with this notebook instance. Currently only one EI instance type can be associated with a notebook instance. For more information, see  7https://docs.aws.amazon.com/sagemaker/latest/dg/ei.html+Using Elastic Inference in Amazon SageMaker.ڜamazonka-sagemakerAn array of up to three Git repositories associated with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in  https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.htmlAmazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html>Associating Git Repositories with SageMaker Notebook Instances.ۜamazonka-sagemakerA timestamp. Use this parameter to return the time when the notebook instance was createdܜamazonka-sagemakerThe Git repository associated with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in  https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.htmlAmazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html>Associating Git Repositories with SageMaker Notebook Instances.ݜamazonka-sagemakerDescribes whether SageMaker provides internet access to the notebook instance. If this value is set to Disabled, the notebook instance does not have internet access, and cannot connect to SageMaker training and endpoint services.For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/appendix-additional-considerations.html#appendix-notebook-and-internet-access2Notebook Instances Are Internet-Enabled by Default.ޜamazonka-sagemaker If status is Failed, the reason it failed.ߜamazonka-sagemaker>Information on the IMDS configuration of the notebook instanceamazonka-sagemakerThe type of ML compute instance running on the notebook instance.amazonka-sagemakerThe Amazon Web Services KMS key ID SageMaker uses to encrypt data when storing it on the ML storage volume attached to the instance.amazonka-sagemakerA timestamp. Use this parameter to retrieve the time when the notebook instance was last modified.amazonka-sagemakerThe network interface IDs that SageMaker created at the time of creating the instance.amazonka-sagemaker8The Amazon Resource Name (ARN) of the notebook instance.amazonka-sagemakerReturns the name of a notebook instance lifecycle configuration.For information about notebook instance lifestyle configurations, see https://docs.aws.amazon.com/sagemaker/latest/dg/notebook-lifecycle-config.html2Step 2.1: (Optional) Customize a Notebook Instanceamazonka-sagemaker,The name of the SageMaker notebook instance.amazonka-sagemaker$The status of the notebook instance.amazonka-sagemakerThe platform identifier of the notebook instance runtime environment.amazonka-sagemakerThe Amazon Resource Name (ARN) of the IAM role associated with the instance.amazonka-sagemakerWhether root access is enabled or disabled for users of the notebook instance.Lifecycle configurations need root access to be able to set up a notebook instance. Because of this, lifecycle configurations associated with a notebook instance always run with root access even if you disable root access for users.amazonka-sagemaker#The IDs of the VPC security groups.amazonka-sagemakerThe ID of the VPC subnet.amazonka-sagemakerThe URL that you use to connect to the Jupyter notebook that is running in your notebook instance.amazonka-sagemakerThe size, in GB, of the ML storage volume attached to the notebook instance.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe name of the notebook instance that you want information about.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The name of the notebook instance that you want information about.amazonka-sagemakerThe name of the notebook instance that you want information about.amazonka-sagemakerCreate a value of ל" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:ٜ,  - A list of the Elastic Inference (EI) instance types associated with this notebook instance. Currently only one EI instance type can be associated with a notebook instance. For more information, see  7https://docs.aws.amazon.com/sagemaker/latest/dg/ei.html+Using Elastic Inference in Amazon SageMaker.ל,  - An array of up to three Git repositories associated with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in  https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.htmlAmazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html>Associating Git Repositories with SageMaker Notebook Instances.ל,  - A timestamp. Use this parameter to return the time when the notebook instance was createdל,  - The Git repository associated with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in  https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.htmlAmazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html>Associating Git Repositories with SageMaker Notebook Instances.ݜ,  - Describes whether SageMaker provides internet access to the notebook instance. If this value is set to Disabled, the notebook instance does not have internet access, and cannot connect to SageMaker training and endpoint services.For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/appendix-additional-considerations.html#appendix-notebook-and-internet-access2Notebook Instances Are Internet-Enabled by Default.ל,  - If status is Failed, the reason it failed.ߜ,  - Information on the IMDS configuration of the notebook instanceל,  - The type of ML compute instance running on the notebook instance.ל,  - The Amazon Web Services KMS key ID SageMaker uses to encrypt data when storing it on the ML storage volume attached to the instance.ל,  - A timestamp. Use this parameter to retrieve the time when the notebook instance was last modified.,  - The network interface IDs that SageMaker created at the time of creating the instance.ל, ; - The Amazon Resource Name (ARN) of the notebook instance.ל,  - Returns the name of a notebook instance lifecycle configuration.For information about notebook instance lifestyle configurations, see https://docs.aws.amazon.com/sagemaker/latest/dg/notebook-lifecycle-config.html2Step 2.1: (Optional) Customize a Notebook Instance, / - The name of the SageMaker notebook instance.ל, ' - The status of the notebook instance.,  - The platform identifier of the notebook instance runtime environment.ל,  - The Amazon Resource Name (ARN) of the IAM role associated with the instance.,  - Whether root access is enabled or disabled for users of the notebook instance.Lifecycle configurations need root access to be able to set up a notebook instance. Because of this, lifecycle configurations associated with a notebook instance always run with root access even if you disable root access for users.ל, & - The IDs of the VPC security groups.,  - The ID of the VPC subnet.ל,  - The URL that you use to connect to the Jupyter notebook that is running in your notebook instance.ל,  - The size, in GB, of the ML storage volume attached to the notebook instance., # - The response's http status code.amazonka-sagemakerA list of the Elastic Inference (EI) instance types associated with this notebook instance. Currently only one EI instance type can be associated with a notebook instance. For more information, see  7https://docs.aws.amazon.com/sagemaker/latest/dg/ei.html+Using Elastic Inference in Amazon SageMaker.amazonka-sagemakerAn array of up to three Git repositories associated with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in  https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.htmlAmazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html>Associating Git Repositories with SageMaker Notebook Instances.amazonka-sagemakerA timestamp. Use this parameter to return the time when the notebook instance was createdamazonka-sagemakerThe Git repository associated with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in  https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.htmlAmazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html>Associating Git Repositories with SageMaker Notebook Instances.amazonka-sagemakerDescribes whether SageMaker provides internet access to the notebook instance. If this value is set to Disabled, the notebook instance does not have internet access, and cannot connect to SageMaker training and endpoint services.For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/appendix-additional-considerations.html#appendix-notebook-and-internet-access2Notebook Instances Are Internet-Enabled by Default.amazonka-sagemaker If status is Failed, the reason it failed.amazonka-sagemaker>Information on the IMDS configuration of the notebook instanceamazonka-sagemakerThe type of ML compute instance running on the notebook instance.amazonka-sagemakerThe Amazon Web Services KMS key ID SageMaker uses to encrypt data when storing it on the ML storage volume attached to the instance.amazonka-sagemakerA timestamp. Use this parameter to retrieve the time when the notebook instance was last modified.amazonka-sagemakerThe network interface IDs that SageMaker created at the time of creating the instance.amazonka-sagemaker8The Amazon Resource Name (ARN) of the notebook instance.amazonka-sagemakerReturns the name of a notebook instance lifecycle configuration.For information about notebook instance lifestyle configurations, see https://docs.aws.amazon.com/sagemaker/latest/dg/notebook-lifecycle-config.html2Step 2.1: (Optional) Customize a Notebook Instanceamazonka-sagemaker,The name of the SageMaker notebook instance.amazonka-sagemaker$The status of the notebook instance.amazonka-sagemakerThe platform identifier of the notebook instance runtime environment.amazonka-sagemakerThe Amazon Resource Name (ARN) of the IAM role associated with the instance.amazonka-sagemakerWhether root access is enabled or disabled for users of the notebook instance.Lifecycle configurations need root access to be able to set up a notebook instance. Because of this, lifecycle configurations associated with a notebook instance always run with root access even if you disable root access for users.amazonka-sagemaker#The IDs of the VPC security groups.amazonka-sagemakerThe ID of the VPC subnet.amazonka-sagemakerThe URL that you use to connect to the Jupyter notebook that is running in your notebook instance.amazonka-sagemakerThe size, in GB, of the ML storage volume attached to the notebook instance.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemaker6ל؜ޜۜڜܜٜݜߜ6ל؜ޜۜڜܜٜݜߜ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';"amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker0The name of the endpoint for the monitoring job.amazonka-sagemakerA string, up to one KB in size, that contains the reason a monitoring job failed, if it failed.amazonka-sagemakerDescribes metadata on the last execution to run, if there was one.amazonka-sagemakerThe type of the monitoring job that this schedule runs. This is one of the following values. DATA_QUALITY5 - The schedule is for a data quality monitoring job. MODEL_QUALITY; - The schedule is for a model quality monitoring job. MODEL_BIAS- - The schedule is for a bias monitoring job.MODEL_EXPLAINABILITY= - The schedule is for an explainability monitoring job.amazonka-sagemaker The response's http status code.amazonka-sagemaker:The Amazon Resource Name (ARN) of the monitoring schedule.amazonka-sagemaker Name of the monitoring schedule.amazonka-sagemaker The status of an monitoring job.amazonka-sagemaker1The time at which the monitoring job was created.amazonka-sagemaker7The time at which the monitoring job was last modified.amazonka-sagemakerThe configuration object that specifies the monitoring schedule and defines the monitoring job.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker1Name of a previously created monitoring schedule.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 4 - Name of a previously created monitoring schedule.amazonka-sagemaker1Name of a previously created monitoring schedule.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 3 - The name of the endpoint for the monitoring job.,  - A string, up to one KB in size, that contains the reason a monitoring job failed, if it failed.,  - Describes metadata on the last execution to run, if there was one.,  - The type of the monitoring job that this schedule runs. This is one of the following values. DATA_QUALITY5 - The schedule is for a data quality monitoring job. MODEL_QUALITY; - The schedule is for a model quality monitoring job. MODEL_BIAS- - The schedule is for a bias monitoring job.MODEL_EXPLAINABILITY= - The schedule is for an explainability monitoring job., # - The response's http status code., = - The Amazon Resource Name (ARN) of the monitoring schedule., # - Name of the monitoring schedule., # - The status of an monitoring job., 4 - The time at which the monitoring job was created., : - The time at which the monitoring job was last modified.,  - The configuration object that specifies the monitoring schedule and defines the monitoring job.amazonka-sagemaker0The name of the endpoint for the monitoring job.amazonka-sagemakerA string, up to one KB in size, that contains the reason a monitoring job failed, if it failed.amazonka-sagemakerDescribes metadata on the last execution to run, if there was one.amazonka-sagemakerThe type of the monitoring job that this schedule runs. This is one of the following values. DATA_QUALITY5 - The schedule is for a data quality monitoring job. MODEL_QUALITY; - The schedule is for a model quality monitoring job. MODEL_BIAS- - The schedule is for a bias monitoring job.MODEL_EXPLAINABILITY= - The schedule is for an explainability monitoring job.amazonka-sagemaker The response's http status code.amazonka-sagemaker:The Amazon Resource Name (ARN) of the monitoring schedule.amazonka-sagemaker Name of the monitoring schedule.amazonka-sagemaker The status of an monitoring job.amazonka-sagemaker1The time at which the monitoring job was created.amazonka-sagemaker7The time at which the monitoring job was last modified.amazonka-sagemakerThe configuration object that specifies the monitoring schedule and defines the monitoring job.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';"V˝amazonka-sagemakerSee: ޝ smart constructor.͝amazonka-sagemaker3The baseline configuration for a model quality job.Νamazonka-sagemaker+Networking options for a model quality job.Нamazonka-sagemaker The response's http status code.ѝamazonka-sagemaker8The Amazon Resource Name (ARN) of the model quality job.ҝamazonka-sagemakerThe name of the quality job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.ӝamazonka-sagemaker4The time at which the model quality job was created.ԝamazonka-sagemakerConfigures the model quality job to run a specified Docker container image.՝amazonka-sagemaker!Inputs for the model quality job.؝amazonka-sagemakerThe Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.ٝamazonka-sagemakerSee: ܝ smart constructor.۝amazonka-sagemakerThe name of the model quality job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.ܝamazonka-sagemakerCreate a value of ٝ" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:ٝ, ݝ - The name of the model quality job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.ݝamazonka-sagemakerThe name of the model quality job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.ޝamazonka-sagemakerCreate a value of ˝" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:͝, ߝ6 - The baseline configuration for a model quality job.˝, . - Networking options for a model quality job.˝,  - Undocumented member.Н, # - The response's http status code.ѝ, ; - The Amazon Resource Name (ARN) of the model quality job.ٝ,  - The name of the quality job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.˝, 7 - The time at which the model quality job was created.ԝ,  - Configures the model quality job to run a specified Docker container image.՝, $ - Inputs for the model quality job.֝,  - Undocumented member.ם,  - Undocumented member.˝,  - The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.ߝamazonka-sagemaker3The baseline configuration for a model quality job.amazonka-sagemaker+Networking options for a model quality job.amazonka-sagemakerUndocumented member.amazonka-sagemaker The response's http status code.amazonka-sagemaker8The Amazon Resource Name (ARN) of the model quality job.amazonka-sagemakerThe name of the quality job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.amazonka-sagemaker4The time at which the model quality job was created.amazonka-sagemakerConfigures the model quality job to run a specified Docker container image.amazonka-sagemaker!Inputs for the model quality job.amazonka-sagemakerUndocumented member.amazonka-sagemakerUndocumented member.amazonka-sagemakerThe Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.ܝamazonka-sagemakerٝޝ amazonka-sagemakerНamazonka-sagemakerѝamazonka-sagemakerٝamazonka-sagemaker˝amazonka-sagemakerԝamazonka-sagemaker՝amazonka-sagemaker֝amazonka-sagemakerםamazonka-sagemaker˝ ˝̝ӝ؝ϝΝНҝ͝ѝԝ՝֝םٝڝ۝ܝݝޝߝ ٝڝ۝ܝݝ˝̝ӝ؝ϝΝНҝ͝ѝԝ՝֝םޝߝ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';"vamazonka-sagemakerSee:  smart constructor.amazonka-sagemaker!A description of the model group.amazonka-sagemaker The response's http status code.amazonka-sagemakerThe name of the model group.amazonka-sagemaker2The Amazon Resource Name (ARN) of the model group.amazonka-sagemaker*The time that the model group was created.amazonka-sagemakerThe status of the model group.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker)The name of gthe model group to describe.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, , - The name of gthe model group to describe.amazonka-sagemaker)The name of gthe model group to describe.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, $ - A description of the model group., # - The response's http status code.,  - The name of the model group., 5 - The Amazon Resource Name (ARN) of the model group., - - The time that the model group was created.,  - Undocumented member., ! - The status of the model group.amazonka-sagemaker!A description of the model group.amazonka-sagemaker The response's http status code.amazonka-sagemakerThe name of the model group.amazonka-sagemaker2The Amazon Resource Name (ARN) of the model group.amazonka-sagemaker*The time that the model group was created.amazonka-sagemakerUndocumented member.amazonka-sagemakerThe status of the model group.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';"H7amazonka-sagemakerSee: ž smart constructor.amazonka-sagemakerAn array of additional Inference Specification objects. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.amazonka-sagemaker.A description provided for the model approval.amazonka-sagemakerWhether the model package is certified for listing on Amazon Web Services Marketplace.amazonka-sagemakerThe metadata properties associated with the model package versions.amazonka-sagemakerThe machine learning domain of the model package you specified. Common machine learning domains include computer vision and natural language processing.amazonka-sagemakerRepresents the drift check baselines that can be used when the model monitor is set using the model package. For more information, see the topic on  https://docs.aws.amazon.com/sagemaker/latest/dg/pipelines-quality-clarify-baseline-lifecycle.html#pipelines-quality-clarify-baseline-drift-detectionDrift Detection against Previous Baselines in SageMaker Pipelines in the  Amazon SageMaker Developer Guide.amazonka-sagemakerDetails about inference jobs that can be run with models based on this model package.amazonka-sagemaker2The last time that the model package was modified.amazonka-sagemaker)The approval status of the model package.amazonka-sagemakerMetrics for the model.amazonka-sagemaker%A brief summary of the model package.amazonka-sagemakerIf the model is a versioned model, the name of the model group that the versioned model belongs to.amazonka-sagemaker!The version of the model package.amazonka-sagemakerThe Amazon Simple Storage Service (Amazon S3) path where the sample payload are stored. This path points to a single gzip compressed tar archive (.tar.gz suffix).amazonka-sagemakerDetails about the algorithm that was used to create the model package.amazonka-sagemakerThe machine learning task you specified that your model package accomplishes. Common machine learning tasks include object detection and image classification.amazonka-sagemakerConfigurations for one or more transform jobs that SageMaker runs to test the model package.amazonka-sagemaker The response's http status code.amazonka-sagemaker.The name of the model package being described.amazonka-sagemaker4The Amazon Resource Name (ARN) of the model package.amazonka-sagemaker:A timestamp specifying when the model package was created.amazonka-sagemaker(The current status of the model package.amazonka-sagemaker6Details about the current status of the model package.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe name or Amazon Resource Name (ARN) of the model package to describe.When you specify a name, the name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The name or Amazon Resource Name (ARN) of the model package to describe.When you specify a name, the name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).amazonka-sagemakerThe name or Amazon Resource Name (ARN) of the model package to describe.When you specify a name, the name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).žamazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, Þ - An array of additional Inference Specification objects. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts., Ğ1 - A description provided for the model approval., Ş - Whether the model package is certified for listing on Amazon Web Services Marketplace., ƞ - Undocumented member., Ǟ - The metadata properties associated with the model package versions., Ȟ - The machine learning domain of the model package you specified. Common machine learning domains include computer vision and natural language processing., ɞ - Represents the drift check baselines that can be used when the model monitor is set using the model package. For more information, see the topic on  https://docs.aws.amazon.com/sagemaker/latest/dg/pipelines-quality-clarify-baseline-lifecycle.html#pipelines-quality-clarify-baseline-drift-detectionDrift Detection against Previous Baselines in SageMaker Pipelines in the  Amazon SageMaker Developer Guide., ʞ - Details about inference jobs that can be run with models based on this model package., ˞ - Undocumented member., ̞5 - The last time that the model package was modified., ͞ - Undocumented member., Ξ, - The approval status of the model package., Ϟ - Metrics for the model., О( - A brief summary of the model package., ў - If the model is a versioned model, the name of the model group that the versioned model belongs to., Ҟ$ - The version of the model package., Ӟ - The Amazon Simple Storage Service (Amazon S3) path where the sample payload are stored. This path points to a single gzip compressed tar archive (.tar.gz suffix)., Ԟ - Details about the algorithm that was used to create the model package., ՞ - The machine learning task you specified that your model package accomplishes. Common machine learning tasks include object detection and image classification., ֞ - Configurations for one or more transform jobs that SageMaker runs to test the model package., מ# - The response's http status code., ؞1 - The name of the model package being described., ٞ7 - The Amazon Resource Name (ARN) of the model package., ڞ= - A timestamp specifying when the model package was created., ۞+ - The current status of the model package., ܞ9 - Details about the current status of the model package.Þamazonka-sagemakerAn array of additional Inference Specification objects. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.Ğamazonka-sagemaker.A description provided for the model approval.Şamazonka-sagemakerWhether the model package is certified for listing on Amazon Web Services Marketplace.ƞamazonka-sagemakerUndocumented member.Ǟamazonka-sagemakerThe metadata properties associated with the model package versions.Ȟamazonka-sagemakerThe machine learning domain of the model package you specified. Common machine learning domains include computer vision and natural language processing.ɞamazonka-sagemakerRepresents the drift check baselines that can be used when the model monitor is set using the model package. For more information, see the topic on  https://docs.aws.amazon.com/sagemaker/latest/dg/pipelines-quality-clarify-baseline-lifecycle.html#pipelines-quality-clarify-baseline-drift-detectionDrift Detection against Previous Baselines in SageMaker Pipelines in the  Amazon SageMaker Developer Guide.ʞamazonka-sagemakerDetails about inference jobs that can be run with models based on this model package.˞amazonka-sagemakerUndocumented member.̞amazonka-sagemaker2The last time that the model package was modified.͞amazonka-sagemakerUndocumented member.Ξamazonka-sagemaker)The approval status of the model package.Ϟamazonka-sagemakerMetrics for the model.Оamazonka-sagemaker%A brief summary of the model package.ўamazonka-sagemakerIf the model is a versioned model, the name of the model group that the versioned model belongs to.Ҟamazonka-sagemaker!The version of the model package.Ӟamazonka-sagemakerThe Amazon Simple Storage Service (Amazon S3) path where the sample payload are stored. This path points to a single gzip compressed tar archive (.tar.gz suffix).Ԟamazonka-sagemakerDetails about the algorithm that was used to create the model package.՞amazonka-sagemakerThe machine learning task you specified that your model package accomplishes. Common machine learning tasks include object detection and image classification.֞amazonka-sagemakerConfigurations for one or more transform jobs that SageMaker runs to test the model package.מamazonka-sagemaker The response's http status code.؞amazonka-sagemaker.The name of the model package being described.ٞamazonka-sagemaker4The Amazon Resource Name (ARN) of the model package.ڞamazonka-sagemaker:A timestamp specifying when the model package was created.۞amazonka-sagemaker(The current status of the model package.ܞamazonka-sagemaker6Details about the current status of the model package.amazonka-sagemakeržamazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker<žÞĞŞƞǞȞɞʞ˞̞͞ΞϞОўҞӞԞ՞֞מ؞ٞڞ۞ܞ<žÞĞŞƞǞȞɞʞ˞̞͞ΞϞОўҞӞԞ՞֞מ؞ٞڞ۞ܞ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';"]\amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker:The baseline configuration for a model explainability job.amazonka-sagemaker2Networking options for a model explainability job.amazonka-sagemaker The response's http status code.amazonka-sagemaker?The Amazon Resource Name (ARN) of the model explainability job.amazonka-sagemakerThe name of the explainability job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.amazonka-sagemaker;The time at which the model explainability job was created.amazonka-sagemakerConfigures the model explainability job to run a specified Docker container image.amazonka-sagemaker(Inputs for the model explainability job.amazonka-sagemakerThe Amazon Resource Name (ARN) of the Amazon Web Services Identity and Access Management (IAM) role that has read permission to the input data location and write permission to the output data location in Amazon S3.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe name of the model explainability job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The name of the model explainability job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.amazonka-sagemakerThe name of the model explainability job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, = - The baseline configuration for a model explainability job., 5 - Networking options for a model explainability job.,  - Undocumented member., # - The response's http status code.,  - The Amazon Resource Name (ARN) of the model explainability job.,  - The name of the explainability job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account., > - The time at which the model explainability job was created.,  - Configures the model explainability job to run a specified Docker container image., + - Inputs for the model explainability job.,  - Undocumented member.,  - Undocumented member.,  - The Amazon Resource Name (ARN) of the Amazon Web Services Identity and Access Management (IAM) role that has read permission to the input data location and write permission to the output data location in Amazon S3.amazonka-sagemaker:The baseline configuration for a model explainability job.amazonka-sagemaker2Networking options for a model explainability job.amazonka-sagemakerUndocumented member.amazonka-sagemaker The response's http status code.amazonka-sagemaker?The Amazon Resource Name (ARN) of the model explainability job.amazonka-sagemakerThe name of the explainability job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.amazonka-sagemaker;The time at which the model explainability job was created.amazonka-sagemakerConfigures the model explainability job to run a specified Docker container image.amazonka-sagemaker(Inputs for the model explainability job.amazonka-sagemakerUndocumented member.amazonka-sagemakerUndocumented member.amazonka-sagemakerThe Amazon Resource Name (ARN) of the Amazon Web Services Identity and Access Management (IAM) role that has read permission to the input data location and write permission to the output data location in Amazon S3.amazonka-sagemaker amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker  (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';"ramazonka-sagemakerSee:  smart constructor.amazonka-sagemaker"The exported model card artifacts.amazonka-sagemaker1The failure reason if the model export job fails.amazonka-sagemaker The response's http status code.amazonka-sagemaker2The name of the model card export job to describe.amazonka-sagemakerThe date and time that the model export job was last modified.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe Amazon Resource Name (ARN) of the model card export job to describe.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The Amazon Resource Name (ARN) of the model card export job to describe.amazonka-sagemakerThe Amazon Resource Name (ARN) of the model card export job to describe.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, % - The exported model card artifacts., 4 - The failure reason if the model export job fails., # - The response's http status code., 5 - The name of the model card export job to describe., ? - The Amazon Resource Name (ARN) of the model card export job., 6 - The completion status of the model card export job. InProgress+: The model card export job is in progress. Completed(: The model card export job is complete.Failed: The model card export job failed. To see the reason for the failure, see the  FailureReason! field in the response to a DescribeModelCardExportJob call.,  - The name of the model card that the model export job exports.,  - The version of the model card that the model export job exports., 0 - The export output details for the model card., ; - The date and time that the model export job was created.,  - The date and time that the model export job was last modified.amazonka-sagemaker"The exported model card artifacts.amazonka-sagemaker1The failure reason if the model export job fails.amazonka-sagemaker The response's http status code.amazonka-sagemaker2The name of the model card export job to describe.amazonka-sagemakerThe date and time that the model export job was last modified.amazonka-sagemaker amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';"˟amazonka-sagemakerSee:  smart constructor.Οamazonka-sagemaker3The date and time the model card was last modified.ϟamazonka-sagemaker3The processing status of model card deletion. The ModelCardProcessingStatus2 updates throughout the different deletion steps. DeletePending': Model card deletion request received.DeleteInProgress%: Model card deletion is in progress.ContentDeleted: Deleted model card content.ExportJobsDeleted>: Deleted all export jobs associated with the model card.DeleteCompleted&: Successfully deleted the model card. DeleteFailed": The model card failed to delete.Пamazonka-sagemaker>The security configuration used to protect model card content.џamazonka-sagemaker The response's http status code.ҟamazonka-sagemaker1The Amazon Resource Name (ARN) of the model card.ӟamazonka-sagemakerThe name of the model card.ԟamazonka-sagemakerThe version of the model card.՟amazonka-sagemakerThe content of the model card.֟amazonka-sagemakerThe approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.Draft': The model card is a work in progress. PendingReview#: The model card is pending review.Approved: The model card is approved.Archived: The model card is archived. No more updates should be made to the model card, but it can still be exported.ןamazonka-sagemaker-The date and time the model card was created.ٟamazonka-sagemakerSee: ݟ smart constructor.۟amazonka-sagemakerThe version of the model card to describe. If a version is not provided, then the latest version of the model card is described.ܟamazonka-sagemaker'The name of the model card to describe.ݟamazonka-sagemakerCreate a value of ٟ" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:ٟ, ޟ - The version of the model card to describe. If a version is not provided, then the latest version of the model card is described.ٟ, ߟ* - The name of the model card to describe.ޟamazonka-sagemakerThe version of the model card to describe. If a version is not provided, then the latest version of the model card is described.ߟamazonka-sagemaker'The name of the model card to describe.amazonka-sagemakerCreate a value of ˟" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:˟,  - Undocumented member.˟, 6 - The date and time the model card was last modified.ϟ, 6 - The processing status of model card deletion. The ModelCardProcessingStatus2 updates throughout the different deletion steps. DeletePending': Model card deletion request received.DeleteInProgress%: Model card deletion is in progress.ContentDeleted: Deleted model card content.ExportJobsDeleted>: Deleted all export jobs associated with the model card.DeleteCompleted&: Successfully deleted the model card. DeleteFailed": The model card failed to delete.˟,  - The security configuration used to protect model card content.џ, # - The response's http status code.˟, 4 - The Amazon Resource Name (ARN) of the model card.ٟ,  - The name of the model card.ٟ, ! - The version of the model card.˟, ! - The content of the model card.˟,  - The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.Draft': The model card is a work in progress. PendingReview#: The model card is pending review.Approved: The model card is approved.Archived: The model card is archived. No more updates should be made to the model card, but it can still be exported.˟, 0 - The date and time the model card was created.˟,  - Undocumented member.amazonka-sagemakerUndocumented member.amazonka-sagemaker3The date and time the model card was last modified.amazonka-sagemaker3The processing status of model card deletion. The ModelCardProcessingStatus2 updates throughout the different deletion steps. DeletePending': Model card deletion request received.DeleteInProgress%: Model card deletion is in progress.ContentDeleted: Deleted model card content.ExportJobsDeleted>: Deleted all export jobs associated with the model card.DeleteCompleted&: Successfully deleted the model card. DeleteFailed": The model card failed to delete.amazonka-sagemaker>The security configuration used to protect model card content.amazonka-sagemaker The response's http status code.amazonka-sagemaker1The Amazon Resource Name (ARN) of the model card.amazonka-sagemakerThe name of the model card.amazonka-sagemakerThe version of the model card.amazonka-sagemakerThe content of the model card.amazonka-sagemakerThe approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.Draft': The model card is a work in progress. PendingReview#: The model card is pending review.Approved: The model card is approved.Archived: The model card is archived. No more updates should be made to the model card, but it can still be exported.amazonka-sagemaker-The date and time the model card was created.amazonka-sagemakerUndocumented member.ݟamazonka-sagemakerٟamazonka-sagemakerџamazonka-sagemaker˟amazonka-sagemakerٟamazonka-sagemakerٟamazonka-sagemaker˟amazonka-sagemaker˟amazonka-sagemaker˟amazonka-sagemaker˟"˟̟՟ןΟӟԟҟ֟П؟͟џϟٟڟܟ۟ݟޟߟ"ٟڟܟ۟ݟޟߟ˟̟՟ןΟӟԟҟ֟П؟͟џϟ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';"amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker0The baseline configuration for a model bias job.amazonka-sagemaker(Networking options for a model bias job.amazonka-sagemaker The response's http status code.amazonka-sagemaker5The Amazon Resource Name (ARN) of the model bias job.amazonka-sagemakerThe name of the bias job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.amazonka-sagemaker1The time at which the model bias job was created.amazonka-sagemakerConfigures the model bias job to run a specified Docker container image.amazonka-sagemakerInputs for the model bias job.amazonka-sagemakerThe Amazon Resource Name (ARN) of the Amazon Web Services Identity and Access Management (IAM) role that has read permission to the input data location and write permission to the output data location in Amazon S3.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe name of the model bias job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The name of the model bias job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.amazonka-sagemakerThe name of the model bias job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 3 - The baseline configuration for a model bias job., + - Networking options for a model bias job.,  - Undocumented member., # - The response's http status code., 8 - The Amazon Resource Name (ARN) of the model bias job.,  - The name of the bias job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account., 4 - The time at which the model bias job was created.,  - Configures the model bias job to run a specified Docker container image., ! - Inputs for the model bias job.,  - Undocumented member.,  - Undocumented member.,  - The Amazon Resource Name (ARN) of the Amazon Web Services Identity and Access Management (IAM) role that has read permission to the input data location and write permission to the output data location in Amazon S3.amazonka-sagemaker0The baseline configuration for a model bias job.amazonka-sagemaker(Networking options for a model bias job.amazonka-sagemakerUndocumented member.amazonka-sagemaker The response's http status code.amazonka-sagemaker5The Amazon Resource Name (ARN) of the model bias job.amazonka-sagemakerThe name of the bias job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.amazonka-sagemaker1The time at which the model bias job was created.amazonka-sagemakerConfigures the model bias job to run a specified Docker container image.amazonka-sagemakerInputs for the model bias job.amazonka-sagemakerUndocumented member.amazonka-sagemakerUndocumented member.amazonka-sagemakerThe Amazon Resource Name (ARN) of the Amazon Web Services Identity and Access Management (IAM) role that has read permission to the input data location and write permission to the output data location in Amazon S3.amazonka-sagemaker amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker  (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';"amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker)The containers in the inference pipeline.amazonka-sagemakerIf True, no inbound or outbound network calls can be made to or from the model container.amazonka-sagemakerSpecifies details of how containers in a multi-container endpoint are called.amazonka-sagemakerThe location of the primary inference code, associated artifacts, and custom environment map that the inference code uses when it is deployed in production.amazonka-sagemakerA VpcConfig object that specifies the VPC that this model has access to. For more information, see =https://docs.aws.amazon.com/sagemaker/latest/dg/host-vpc.html:Protect Endpoints by Using an Amazon Virtual Private Cloudamazonka-sagemaker The response's http status code.amazonka-sagemakerName of the SageMaker model.amazonka-sagemakerThe Amazon Resource Name (ARN) of the IAM role that you specified for the model.amazonka-sagemaker2A timestamp that shows when the model was created.amazonka-sagemaker,The Amazon Resource Name (ARN) of the model.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe name of the model.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The name of the model.amazonka-sagemakerThe name of the model.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, , - The containers in the inference pipeline.,  - If True, no inbound or outbound network calls can be made to or from the model container.,  - Specifies details of how containers in a multi-container endpoint are called.,  - The location of the primary inference code, associated artifacts, and custom environment map that the inference code uses when it is deployed in production.,   - A VpcConfig object that specifies the VPC that this model has access to. For more information, see =https://docs.aws.amazon.com/sagemaker/latest/dg/host-vpc.html:Protect Endpoints by Using an Amazon Virtual Private Cloud, à# - The response's http status code., Ġ - Name of the SageMaker model., Š - The Amazon Resource Name (ARN) of the IAM role that you specified for the model., Ơ5 - A timestamp that shows when the model was created., Ǡ/ - The Amazon Resource Name (ARN) of the model.amazonka-sagemaker)The containers in the inference pipeline.amazonka-sagemakerIf True, no inbound or outbound network calls can be made to or from the model container.amazonka-sagemakerSpecifies details of how containers in a multi-container endpoint are called.amazonka-sagemakerThe location of the primary inference code, associated artifacts, and custom environment map that the inference code uses when it is deployed in production. amazonka-sagemakerA VpcConfig object that specifies the VPC that this model has access to. For more information, see =https://docs.aws.amazon.com/sagemaker/latest/dg/host-vpc.html:Protect Endpoints by Using an Amazon Virtual Private Cloudàamazonka-sagemaker The response's http status code.Ġamazonka-sagemakerName of the SageMaker model.Šamazonka-sagemakerThe Amazon Resource Name (ARN) of the IAM role that you specified for the model.Ơamazonka-sagemaker2A timestamp that shows when the model was created.Ǡamazonka-sagemaker,The Amazon Resource Name (ARN) of the model.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker àĠŠƠǠ àĠŠƠǠ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';"rؠamazonka-sagemakerSee:  smart constructor.۠amazonka-sagemaker#The creation time of lineage group.ܠamazonka-sagemaker%The description of the lineage group.ݠamazonka-sagemaker&The display name of the lineage group.ߠamazonka-sagemaker,The last modified time of the lineage group.amazonka-sagemaker4The Amazon Resource Name (ARN) of the lineage group.amazonka-sagemakerThe name of the lineage group.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe name of the lineage group.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, ! - The name of the lineage group.amazonka-sagemakerThe name of the lineage group.amazonka-sagemakerCreate a value of ؠ" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:ؠ,  - Undocumented member.ؠ, & - The creation time of lineage group.ؠ, ( - The description of the lineage group.ؠ, ) - The display name of the lineage group.ؠ,  - Undocumented member.ؠ, / - The last modified time of the lineage group.ؠ, 7 - The Amazon Resource Name (ARN) of the lineage group., ! - The name of the lineage group., # - The response's http status code.amazonka-sagemakerUndocumented member.amazonka-sagemaker#The creation time of lineage group.amazonka-sagemaker%The description of the lineage group.amazonka-sagemaker&The display name of the lineage group.amazonka-sagemakerUndocumented member.amazonka-sagemaker,The last modified time of the lineage group.amazonka-sagemaker4The Amazon Resource Name (ARN) of the lineage group.amazonka-sagemakerThe name of the lineage group.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemakerؠ٠ܠ۠ߠݠڠޠؠ٠ܠ۠ߠݠڠޠ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';",amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker-If the job failed, the reason that it failed.amazonka-sagemakerhttps://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.amazonka-sagemaker The response's http status code.amazonka-sagemaker*The processing status of the labeling job.amazonka-sagemakerProvides a breakdown of the number of data objects labeled by humans, the number of objects labeled by machine, the number of objects than couldn't be labeled, and the total number of objects labeled.amazonka-sagemaker4The date and time that the labeling job was created.amazonka-sagemaker9The date and time that the labeling job was last updated.amazonka-sagemakerhttps://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources., # - The response's http status code., - - The processing status of the labeling job.,  - Provides a breakdown of the number of data objects labeled by humans, the number of objects labeled by machine, the number of objects than couldn't be labeled, and the total number of objects labeled., 7 - The date and time that the labeling job was created., < - The date and time that the labeling job was last updated., ? - A unique identifier for work done as part of a labeling job., = - The name assigned to the labeling job when it was created., 6 - The Amazon Resource Name (ARN) of the labeling job.,  - Input configuration information for the labeling job, such as the Amazon S3 location of the data objects and the location of the manifest file that describes the data objects.,  - The location of the job's output data and the Amazon Web Services Key Management Service key ID for the key used to encrypt the output data, if any.,  - The Amazon Resource Name (ARN) that SageMaker assumes to perform tasks on your behalf during data labeling.,  - Configuration information required for human workers to complete a labeling task.amazonka-sagemaker-If the job failed, the reason that it failed.amazonka-sagemakerhttps://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.amazonka-sagemaker The response's http status code.amazonka-sagemaker*The processing status of the labeling job.amazonka-sagemakerProvides a breakdown of the number of data objects labeled by humans, the number of objects labeled by machine, the number of objects than couldn't be labeled, and the total number of objects labeled.amazonka-sagemaker4The date and time that the labeling job was created.amazonka-sagemaker9The date and time that the labeling job was last updated.amazonka-sagemakerThe timestamp at which the inference experiment was completed.amazonka-sagemakerThe timestamp at which the inference experiment was completed.amazonka-sagemaker - The machine learning framework vended in the image version., آ& - Indicates CPU or GPU compatibility.CPU+: The image version is compatible with CPU.GPU+: The image version is compatible with GPU., ٢6 - The supported programming language and its version., ڢ3 - The maintainer description of the image version., ۢ - The stability of the image version specified by the maintainer. NOT_PROVIDED: The maintainers did not provide a status for image version stability.STABLE: The image version is stable.TO_BE_ARCHIVED: The image version is set to be archived. Custom image versions that are set to be archived are automatically archived after three months.ARCHIVED: The image version is archived. Archived image versions are not searchable and are no longer actively supported.â, ܢ - The version number.¢, ݢ# - The response's http status code.͢amazonka-sagemakerThe registry path of the container image on which this image version is based.΢amazonka-sagemakerThe registry path of the container image that contains this image version.Ϣamazonka-sagemakerWhen the version was created.Тamazonka-sagemakerWhen a create or delete operation fails, the reason for the failure.Ѣamazonka-sagemaker Indicates Horovod compatibility.Ңamazonka-sagemaker-The ARN of the image the version is based on.Ӣamazonka-sagemakerThe ARN of the version.Ԣamazonka-sagemakerThe status of the version.բamazonka-sagemaker+Indicates SageMaker job type compatibility.TRAINING: The image version is compatible with SageMaker training jobs. INFERENCE: The image version is compatible with SageMaker inference jobs.NOTEBOOK_KERNEL: The image version is compatible with SageMaker notebook kernels.֢amazonka-sagemaker#When the version was last modified.עamazonka-sagemaker;The machine learning framework vended in the image version.آamazonka-sagemaker#Indicates CPU or GPU compatibility.CPU+: The image version is compatible with CPU.GPU+: The image version is compatible with GPU.٢amazonka-sagemaker3The supported programming language and its version.ڢamazonka-sagemaker0The maintainer description of the image version.ۢamazonka-sagemaker?The stability of the image version specified by the maintainer. NOT_PROVIDED: The maintainers did not provide a status for image version stability.STABLE: The image version is stable.TO_BE_ARCHIVED: The image version is set to be archived. Custom image versions that are set to be archived are automatically archived after three months.ARCHIVED: The image version is archived. Archived image versions are not searchable and are no longer actively supported.ܢamazonka-sagemakerThe version number.ݢamazonka-sagemaker The response's http status code.Ȣamazonka-sagemakerâ̢amazonka-sagemaker¢.¢âĢƢǢŢȢɢʢˢ̢͢΢ϢТѢҢӢԢբ֢עآ٢ڢۢܢݢ.âĢƢǢŢȢɢʢˢ¢̢͢΢ϢТѢҢӢԢբ֢עآ٢ڢۢܢݢ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';#Wamazonka-sagemakerSee:  smart constructor.amazonka-sagemakerWhen the image was created.amazonka-sagemakerThe description of the image.amazonka-sagemaker#The name of the image as displayed.amazonka-sagemakerWhen a create, update, or delete operation fails, the reason for the failure.amazonka-sagemakerThe ARN of the image.amazonka-sagemakerThe name of the image.amazonka-sagemakerThe status of the image.amazonka-sagemaker!When the image was last modified.amazonka-sagemakerThe ARN of the IAM role that enables Amazon SageMaker to perform tasks on your behalf.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker"The name of the image to describe.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, % - The name of the image to describe.amazonka-sagemaker"The name of the image to describe.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - When the image was created.,  - The description of the image., & - The name of the image as displayed.,  - When a create, update, or delete operation fails, the reason for the failure.,  - The ARN of the image.,  - The name of the image.,  - The status of the image., $ - When the image was last modified.,  - The ARN of the IAM role that enables Amazon SageMaker to perform tasks on your behalf., # - The response's http status code.amazonka-sagemakerWhen the image was created.amazonka-sagemakerThe description of the image.amazonka-sagemaker#The name of the image as displayed.amazonka-sagemakerWhen a create, update, or delete operation fails, the reason for the failure.amazonka-sagemakerThe ARN of the image.amazonka-sagemakerThe name of the image.amazonka-sagemakerThe status of the image.amazonka-sagemaker!When the image was last modified.amazonka-sagemakerThe ARN of the IAM role that enables Amazon SageMaker to perform tasks on your behalf.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';#w&amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerA TrainingJobSummary object that describes the training job that completed with the best current HyperParameterTuningJobObjective.amazonka-sagemaker/If the tuning job failed, the reason it failed.amazonka-sagemaker,The date and time that the tuning job ended.amazonka-sagemakerThe date and time that the status of the tuning job was modified.amazonka-sagemakerIf the hyperparameter tuning job is an warm start tuning job with a  WarmStartType of IDENTICAL_DATA_AND_ALGORITHM, this is the TrainingJobSummary for the training job with the best objective metric value of all training jobs launched by this tuning job and all parent jobs specified for the warm start tuning job.amazonka-sagemakerThe HyperParameterTrainingJobDefinition object that specifies the definition of the training jobs that this tuning job launches.amazonka-sagemakerA list of the HyperParameterTrainingJobDefinition objects launched for this tuning job.amazonka-sagemakerThe configuration for starting the hyperparameter parameter tuning job using one or more previous tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.amazonka-sagemaker The response's http status code.amazonka-sagemakerThe name of the tuning job.amazonka-sagemaker1The Amazon Resource Name (ARN) of the tuning job.amazonka-sagemakerThe HyperParameterTuningJobConfig object that specifies the configuration of the tuning job.amazonka-sagemakerThe status of the tuning job: InProgress, Completed, Failed, Stopping, or Stopped.amazonka-sagemaker.The date and time that the tuning job started.amazonka-sagemakerThe TrainingJobStatusCounters object that specifies the number of training jobs, categorized by status, that this tuning job launched.amazonka-sagemakerThe ObjectiveStatusCounters object that specifies the number of training jobs, categorized by the status of their final objective metric, that this tuning job launched.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe name of the tuning job.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The name of the tuning job.amazonka-sagemakerThe name of the tuning job.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - A TrainingJobSummary object that describes the training job that completed with the best current HyperParameterTuningJobObjective., 2 - If the tuning job failed, the reason it failed., / - The date and time that the tuning job ended.,  - The date and time that the status of the tuning job was modified.,  - If the hyperparameter tuning job is an warm start tuning job with a  WarmStartType of IDENTICAL_DATA_AND_ALGORITHM, this is the TrainingJobSummary for the training job with the best objective metric value of all training jobs launched by this tuning job and all parent jobs specified for the warm start tuning job.,  - The HyperParameterTrainingJobDefinition object that specifies the definition of the training jobs that this tuning job launches.,  - A list of the HyperParameterTrainingJobDefinition objects launched for this tuning job.,  - The configuration for starting the hyperparameter parameter tuning job using one or more previous tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job., # - The response's http status code.,  - The name of the tuning job., 4 - The Amazon Resource Name (ARN) of the tuning job.,  - The HyperParameterTuningJobConfig object that specifies the configuration of the tuning job.,  - The status of the tuning job: InProgress, Completed, Failed, Stopping, or Stopped., 1 - The date and time that the tuning job started.,  - The TrainingJobStatusCounters object that specifies the number of training jobs, categorized by status, that this tuning job launched.,  - The ObjectiveStatusCounters object that specifies the number of training jobs, categorized by the status of their final objective metric, that this tuning job launched.amazonka-sagemakerA TrainingJobSummary object that describes the training job that completed with the best current HyperParameterTuningJobObjective.amazonka-sagemaker/If the tuning job failed, the reason it failed.amazonka-sagemaker,The date and time that the tuning job ended.amazonka-sagemakerThe date and time that the status of the tuning job was modified.amazonka-sagemakerIf the hyperparameter tuning job is an warm start tuning job with a  WarmStartType of IDENTICAL_DATA_AND_ALGORITHM, this is the TrainingJobSummary for the training job with the best objective metric value of all training jobs launched by this tuning job and all parent jobs specified for the warm start tuning job.amazonka-sagemakerThe HyperParameterTrainingJobDefinition object that specifies the definition of the training jobs that this tuning job launches.amazonka-sagemakerA list of the HyperParameterTrainingJobDefinition objects launched for this tuning job.amazonka-sagemakerThe configuration for starting the hyperparameter parameter tuning job using one or more previous tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.amazonka-sagemaker The response's http status code.amazonka-sagemakerThe name of the tuning job.amazonka-sagemaker1The Amazon Resource Name (ARN) of the tuning job.amazonka-sagemakerThe HyperParameterTuningJobConfig object that specifies the configuration of the tuning job.amazonka-sagemakerThe status of the tuning job: InProgress, Completed, Failed, Stopping, or Stopped.amazonka-sagemaker.The date and time that the tuning job started.amazonka-sagemakerThe TrainingJobStatusCounters object that specifies the number of training jobs, categorized by status, that this tuning job launched.amazonka-sagemakerThe ObjectiveStatusCounters object that specifies the number of training jobs, categorized by the status of their final objective metric, that this tuning job launched.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(((c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';#ңamazonka-sagemakerSee: ߣ smart constructor.ԣamazonka-sagemakerThe status of the human task user interface (worker task template). Valid values are listed below.գamazonka-sagemaker The response's http status code.֣amazonka-sagemakerThe Amazon Resource Name (ARN) of the human task user interface (worker task template).ףamazonka-sagemakerThe name of the human task user interface (worker task template).أamazonka-sagemaker=The timestamp when the human task user interface was created.ڣamazonka-sagemakerSee: ݣ smart constructor.ܣamazonka-sagemakerThe name of the human task user interface (worker task template) you want information about.ݣamazonka-sagemakerCreate a value of ڣ" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:ڣ, ޣ - The name of the human task user interface (worker task template) you want information about.ޣamazonka-sagemakerThe name of the human task user interface (worker task template) you want information about.ߣamazonka-sagemakerCreate a value of ң" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:ԣ,  - The status of the human task user interface (worker task template). Valid values are listed below.գ, # - The response's http status code.ң,  - The Amazon Resource Name (ARN) of the human task user interface (worker task template).ڣ,  - The name of the human task user interface (worker task template).ң,  - The timestamp when the human task user interface was created.٣,  - Undocumented member.amazonka-sagemakerThe status of the human task user interface (worker task template). Valid values are listed below.amazonka-sagemaker The response's http status code.amazonka-sagemakerThe Amazon Resource Name (ARN) of the human task user interface (worker task template).amazonka-sagemakerThe name of the human task user interface (worker task template).amazonka-sagemaker=The timestamp when the human task user interface was created.amazonka-sagemakerUndocumented member.ݣamazonka-sagemakerڣߣamazonka-sagemakerգamazonka-sagemakerңamazonka-sagemakerڣamazonka-sagemakerңamazonka-sagemaker٣ңӣأף֣գ٣ԣڣۣܣݣޣߣڣۣܣݣޣңӣأף֣գ٣ԣߣ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';#M.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker3The failure reason if importing hub content failed.amazonka-sagemakerThe location of any dependencies that the hub content has, such as scripts, model artifacts, datasets, or notebooks.amazonka-sagemaker!A description of the hub content.amazonka-sagemaker$The display name of the hub content.amazonka-sagemaker9Markdown files associated with the hub content to import.amazonka-sagemaker,The searchable keywords for the hub content.amazonka-sagemaker The response's http status code.amazonka-sagemakerThe name of the hub content.amazonka-sagemaker2The Amazon Resource Name (ARN) of the hub content.amazonka-sagemakerThe version of the hub content.amazonka-sagemakerThe type of hub content.amazonka-sagemaker0The document schema version for the hub content.amazonka-sagemaker.The name of the hub that contains the content.amazonka-sagemakerThe Amazon Resource Name (ARN) of the hub that contains the content.amazonka-sagemakerThe hub content document that describes information about the hub content such as type, associated containers, scripts, and more.amazonka-sagemakerThe status of the hub content.amazonka-sagemaker/The date and time that hub content was created.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker'The version of the content to describe.amazonka-sagemaker:The name of the hub that contains the content to describe.amazonka-sagemakerThe type of content in the hub.amazonka-sagemaker$The name of the content to describe.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, * - The version of the content to describe., = - The name of the hub that contains the content to describe., " - The type of content in the hub., ' - The name of the content to describe.amazonka-sagemaker'The version of the content to describe.amazonka-sagemaker:The name of the hub that contains the content to describe.amazonka-sagemakerThe type of content in the hub.amazonka-sagemaker$The name of the content to describe.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 6 - The failure reason if importing hub content failed.,  - The location of any dependencies that the hub content has, such as scripts, model artifacts, datasets, or notebooks., $ - A description of the hub content., ' - The display name of the hub content., < - Markdown files associated with the hub content to import., / - The searchable keywords for the hub content., # - The response's http status code.,  - The name of the hub content., 5 - The Amazon Resource Name (ARN) of the hub content., " - The version of the hub content.,  - The type of hub content., 3 - The document schema version for the hub content., 1 - The name of the hub that contains the content.,  - The Amazon Resource Name (ARN) of the hub that contains the content.,  - The hub content document that describes information about the hub content such as type, associated containers, scripts, and more., ! - The status of the hub content., 2 - The date and time that hub content was created.amazonka-sagemaker3The failure reason if importing hub content failed.amazonka-sagemakerThe location of any dependencies that the hub content has, such as scripts, model artifacts, datasets, or notebooks.amazonka-sagemaker!A description of the hub content.amazonka-sagemaker$The display name of the hub content.amazonka-sagemaker9Markdown files associated with the hub content to import.amazonka-sagemaker,The searchable keywords for the hub content.amazonka-sagemaker The response's http status code.amazonka-sagemakerThe name of the hub content.amazonka-sagemaker2The Amazon Resource Name (ARN) of the hub content.amazonka-sagemakerThe version of the hub content.amazonka-sagemakerThe type of hub content.amazonka-sagemaker0The document schema version for the hub content.amazonka-sagemaker.The name of the hub that contains the content.amazonka-sagemakerThe Amazon Resource Name (ARN) of the hub that contains the content.amazonka-sagemakerThe hub content document that describes information about the hub content such as type, associated containers, scripts, and more.amazonka-sagemakerThe status of the hub content.amazonka-sagemaker/The date and time that hub content was created.amazonka-sagemakeramazonka-sagemakeramazonka-sagemaker amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker amazonka-sagemaker amazonka-sagemaker00(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';#amazonka-sagemakerSee: Ȥ smart constructor.amazonka-sagemaker3The failure reason if importing hub content failed.amazonka-sagemakerA description of the hub.amazonka-sagemakerThe display name of the hub.amazonka-sagemaker$The searchable keywords for the hub.amazonka-sagemaker0The Amazon S3 storage configuration for the hub.amazonka-sagemaker The response's http status code.amazonka-sagemakerThe name of the hub.amazonka-sagemaker*The Amazon Resource Name (ARN) of the hub.amazonka-sagemakerThe status of the hub.amazonka-sagemaker+The date and time that the hub was created.¤amazonka-sagemaker1The date and time that the hub was last modified.äamazonka-sagemakerSee: Ƥ smart constructor.Ťamazonka-sagemaker The name of the hub to describe.Ƥamazonka-sagemakerCreate a value of ä" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:ä, Ǥ# - The name of the hub to describe.Ǥamazonka-sagemaker The name of the hub to describe.Ȥamazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, ɤ6 - The failure reason if importing hub content failed., ʤ - A description of the hub., ˤ - The display name of the hub., ̤' - The searchable keywords for the hub., ͤ3 - The Amazon S3 storage configuration for the hub., Τ# - The response's http status code.ä, Ϥ - The name of the hub., Ф- - The Amazon Resource Name (ARN) of the hub., Ѥ - The status of the hub., Ҥ. - The date and time that the hub was created., Ӥ4 - The date and time that the hub was last modified.ɤamazonka-sagemaker3The failure reason if importing hub content failed.ʤamazonka-sagemakerA description of the hub.ˤamazonka-sagemakerThe display name of the hub.̤amazonka-sagemaker$The searchable keywords for the hub.ͤamazonka-sagemaker0The Amazon S3 storage configuration for the hub.Τamazonka-sagemaker The response's http status code.Ϥamazonka-sagemakerThe name of the hub.Фamazonka-sagemaker*The Amazon Resource Name (ARN) of the hub.Ѥamazonka-sagemakerThe status of the hub.Ҥamazonka-sagemaker+The date and time that the hub was created.Ӥamazonka-sagemaker1The date and time that the hub was last modified.Ƥamazonka-sagemakeräȤamazonka-sagemakeramazonka-sagemakeräamazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker¤äĤŤƤǤȤɤʤˤ̤ͤΤϤФѤҤӤäĤŤƤǤ¤Ȥɤʤˤ̤ͤΤϤФѤҤӤ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';#amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker'The reason your flow definition failed.amazonka-sagemakerAn object containing information about what triggers a human review workflow.amazonka-sagemakerContainer for configuring the source of human task requests. Used to specify if Amazon Rekognition or Amazon Textract is used as an integration source.amazonka-sagemaker The response's http status code.amazonka-sagemaker5The Amazon Resource Name (ARN) of the flow defintion.amazonka-sagemaker6The Amazon Resource Name (ARN) of the flow definition.amazonka-sagemakerThe status of the flow definition. Valid values are listed below.amazonka-sagemaker3The timestamp when the flow definition was created.amazonka-sagemakerAn object containing information about who works on the task, the workforce task price, and other task details.amazonka-sagemaker7An object containing information about the output file.amazonka-sagemakerThe Amazon Resource Name (ARN) of the Amazon Web Services Identity and Access Management (IAM) execution role for the flow definition.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The name of the flow definition.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The name of the flow definition.amazonka-sagemaker The name of the flow definition.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, * - The reason your flow definition failed.,  - An object containing information about what triggers a human review workflow.,  - Container for configuring the source of human task requests. Used to specify if Amazon Rekognition or Amazon Textract is used as an integration source., # - The response's http status code., 8 - The Amazon Resource Name (ARN) of the flow defintion., 9 - The Amazon Resource Name (ARN) of the flow definition.,  - The status of the flow definition. Valid values are listed below., 6 - The timestamp when the flow definition was created.,  - An object containing information about who works on the task, the workforce task price, and other task details., : - An object containing information about the output file.,  - The Amazon Resource Name (ARN) of the Amazon Web Services Identity and Access Management (IAM) execution role for the flow definition.amazonka-sagemaker'The reason your flow definition failed.amazonka-sagemakerAn object containing information about what triggers a human review workflow.amazonka-sagemakerContainer for configuring the source of human task requests. Used to specify if Amazon Rekognition or Amazon Textract is used as an integration source.amazonka-sagemaker The response's http status code.amazonka-sagemaker5The Amazon Resource Name (ARN) of the flow defintion.amazonka-sagemaker6The Amazon Resource Name (ARN) of the flow definition.amazonka-sagemakerThe status of the flow definition. Valid values are listed below.amazonka-sagemaker3The timestamp when the flow definition was created.amazonka-sagemakerAn object containing information about who works on the task, the workforce task price, and other task details.amazonka-sagemaker7An object containing information about the output file.amazonka-sagemakerThe Amazon Resource Name (ARN) of the Amazon Web Services Identity and Access Management (IAM) execution role for the flow definition.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';#Гamazonka-sagemakerSee:  smart constructor.amazonka-sagemaker2The description you added to describe the feature.amazonka-sagemaker;The key-value pairs that you added to describe the feature.amazonka-sagemaker The response's http status code.amazonka-sagemakerThe Amazon Resource Number (ARN) of the feature group that contains the feature.amazonka-sagemaker4The name of the feature group that you've specified.amazonka-sagemaker.The name of the feature that you've specified.amazonka-sagemakerThe data type of the feature.amazonka-sagemaker4A timestamp indicating when the feature was created.amazonka-sagemakerA timestamp indicating when the metadata for the feature group was modified. For example, if you add a parameter describing the feature, the timestamp changes to reflect the last time youamazonka-sagemakerSee:  smart constructor.amazonka-sagemaker5The name of the feature group containing the feature.amazonka-sagemakerThe name of the feature.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 8 - The name of the feature group containing the feature.,  - The name of the feature.amazonka-sagemaker5The name of the feature group containing the feature.amazonka-sagemakerThe name of the feature.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 5 - The description you added to describe the feature., > - The key-value pairs that you added to describe the feature., # - The response's http status code.,  - The Amazon Resource Number (ARN) of the feature group that contains the feature., 7 - The name of the feature group that you've specified., 1 - The name of the feature that you've specified.,  - The data type of the feature., 7 - A timestamp indicating when the feature was created.,  - A timestamp indicating when the metadata for the feature group was modified. For example, if you add a parameter describing the feature, the timestamp changes to reflect the last time youamazonka-sagemaker2The description you added to describe the feature.amazonka-sagemaker;The key-value pairs that you added to describe the feature.amazonka-sagemaker The response's http status code.amazonka-sagemakerThe Amazon Resource Number (ARN) of the feature group that contains the feature.amazonka-sagemaker4The name of the feature group that you've specified.amazonka-sagemaker.The name of the feature that you've specified.amazonka-sagemakerThe data type of the feature.amazonka-sagemaker4A timestamp indicating when the feature was created.amazonka-sagemakerA timestamp indicating when the metadata for the feature group was modified. For example, if you add a parameter describing the feature, the timestamp changes to reflect the last time youamazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';#H,amazonka-sagemakerSee: ٥ smart constructor.amazonka-sagemaker-A free form description of the feature group.amazonka-sagemakerThe reason that the  FeatureGroup! failed to be replicated in the  OfflineStore$. This is failure can occur because:The  FeatureGroup could not be created in the  OfflineStore.The  FeatureGroup could not be deleted from the  OfflineStore.¥amazonka-sagemaker The status of the feature group.åamazonka-sagemaker?A timestamp indicating when the feature group was last updated.ĥamazonka-sagemakerA value indicating whether the update made to the feature group was successful.ťamazonka-sagemakerThe configuration of the offline store. It includes the following configurations:(Amazon S3 location of the offline store.'Configuration of the Glue data catalog."Table format of the offline store.Option to disable the automatic creation of a Glue table for the offline store.Encryption configuration.ƥamazonka-sagemakerThe status of the  OfflineStore-. Notifies you if replicating data into the  OfflineStore has failed. Returns either: Active or Blockedǥamazonka-sagemakerThe configuration for the  OnlineStore.ȥamazonka-sagemakerThe size of the  OnlineStore in bytes.ɥamazonka-sagemakerThe Amazon Resource Name (ARN) of the IAM execution role used to persist data into the OfflineStore if an OfflineStoreConfig is provided.ʥamazonka-sagemaker The response's http status code.˥amazonka-sagemaker&The Amazon Resource Name (ARN) of the  FeatureGroup.̥amazonka-sagemakerhe name of the  FeatureGroup.ͥamazonka-sagemakerThe name of the Feature used for RecordIdentifier, whose value uniquely identifies a record stored in the feature store.Υamazonka-sagemaker(The name of the feature that stores the  EventTime of a Record in a  FeatureGroup.An  EventTime is a point in time when a new event occurs that corresponds to the creation or update of a Record in a  FeatureGroup. All Records in the  FeatureGroup have a corresponding  EventTime.ϥamazonka-sagemakerA list of the Features in the  FeatureGroup . Each feature is defined by a  FeatureName and  FeatureType.Хamazonka-sagemaker2A timestamp indicating when SageMaker created the  FeatureGroup.ѥamazonka-sagemaker,A token to resume pagination of the list of Features (FeatureDefinitions).ҥamazonka-sagemakerSee: ֥ smart constructor.ԥamazonka-sagemaker,A token to resume pagination of the list of Features (FeatureDefinitions ). 2,500 Features are returned by default.եamazonka-sagemakerThe name of the  FeatureGroup you want described.֥amazonka-sagemakerCreate a value of ҥ" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:ҥ, ץ/ - A token to resume pagination of the list of Features (FeatureDefinitions ). 2,500 Features are returned by default.ҥ, إ - The name of the  FeatureGroup you want described.ץamazonka-sagemaker,A token to resume pagination of the list of Features (FeatureDefinitions ). 2,500 Features are returned by default.إamazonka-sagemakerThe name of the  FeatureGroup you want described.٥amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, ڥ0 - A free form description of the feature group., ۥ - The reason that the  FeatureGroup! failed to be replicated in the  OfflineStore$. This is failure can occur because:The  FeatureGroup could not be created in the  OfflineStore.The  FeatureGroup could not be deleted from the  OfflineStore., ܥ# - The status of the feature group., ݥ - A timestamp indicating when the feature group was last updated., ޥ - A value indicating whether the update made to the feature group was successful., ߥ - The configuration of the offline store. It includes the following configurations:(Amazon S3 location of the offline store.'Configuration of the Glue data catalog."Table format of the offline store.Option to disable the automatic creation of a Glue table for the offline store.Encryption configuration.,  - The status of the  OfflineStore-. Notifies you if replicating data into the  OfflineStore has failed. Returns either: Active or Blocked,  - The configuration for the  OnlineStore.ȥ,  - The size of the  OnlineStore in bytes.,  - The Amazon Resource Name (ARN) of the IAM execution role used to persist data into the OfflineStore if an OfflineStoreConfig is provided.ʥ, # - The response's http status code., ) - The Amazon Resource Name (ARN) of the  FeatureGroup.ҥ,  - he name of the  FeatureGroup.,  - The name of the Feature used for RecordIdentifier, whose value uniquely identifies a record stored in the feature store., + - The name of the feature that stores the  EventTime of a Record in a  FeatureGroup.An  EventTime is a point in time when a new event occurs that corresponds to the creation or update of a Record in a  FeatureGroup. All Records in the  FeatureGroup have a corresponding  EventTime.,  - A list of the Features in the  FeatureGroup . Each feature is defined by a  FeatureName and  FeatureType., 5 - A timestamp indicating when SageMaker created the  FeatureGroup.ҥ, / - A token to resume pagination of the list of Features (FeatureDefinitions).ڥamazonka-sagemaker-A free form description of the feature group.ۥamazonka-sagemakerThe reason that the  FeatureGroup! failed to be replicated in the  OfflineStore$. This is failure can occur because:The  FeatureGroup could not be created in the  OfflineStore.The  FeatureGroup could not be deleted from the  OfflineStore.ܥamazonka-sagemaker The status of the feature group.ݥamazonka-sagemaker?A timestamp indicating when the feature group was last updated.ޥamazonka-sagemakerA value indicating whether the update made to the feature group was successful.ߥamazonka-sagemakerThe configuration of the offline store. It includes the following configurations:(Amazon S3 location of the offline store.'Configuration of the Glue data catalog."Table format of the offline store.Option to disable the automatic creation of a Glue table for the offline store.Encryption configuration.amazonka-sagemakerThe status of the  OfflineStore-. Notifies you if replicating data into the  OfflineStore has failed. Returns either: Active or Blockedamazonka-sagemakerThe configuration for the  OnlineStore.amazonka-sagemakerThe size of the  OnlineStore in bytes.amazonka-sagemakerThe Amazon Resource Name (ARN) of the IAM execution role used to persist data into the OfflineStore if an OfflineStoreConfig is provided.amazonka-sagemaker The response's http status code.amazonka-sagemaker&The Amazon Resource Name (ARN) of the  FeatureGroup.amazonka-sagemakerhe name of the  FeatureGroup.amazonka-sagemakerThe name of the Feature used for RecordIdentifier, whose value uniquely identifies a record stored in the feature store.amazonka-sagemaker(The name of the feature that stores the  EventTime of a Record in a  FeatureGroup.An  EventTime is a point in time when a new event occurs that corresponds to the creation or update of a Record in a  FeatureGroup. All Records in the  FeatureGroup have a corresponding  EventTime.amazonka-sagemakerA list of the Features in the  FeatureGroup . Each feature is defined by a  FeatureName and  FeatureType.amazonka-sagemaker2A timestamp indicating when SageMaker created the  FeatureGroup.amazonka-sagemaker,A token to resume pagination of the list of Features (FeatureDefinitions).֥amazonka-sagemakerҥ٥amazonka-sagemakerʥamazonka-sagemakeramazonka-sagemakerҥamazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakerҥ.Хå˥̥ɥ¥ƥΥϥĥťǥͥʥѥȥҥӥեԥ֥ץإ٥ڥۥܥݥޥߥ.ҥӥեԥ֥ץإХå˥̥ɥ¥ƥΥϥĥťǥͥʥѥȥ٥ڥۥܥݥޥߥ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';$amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerWho created the experiment.amazonka-sagemaker When the experiment was created.amazonka-sagemaker"The description of the experiment.amazonka-sagemaker,The name of the experiment as displayed. If  DisplayName isn't specified, ExperimentName is displayed.amazonka-sagemaker1The Amazon Resource Name (ARN) of the experiment.amazonka-sagemakerThe name of the experiment.amazonka-sagemaker!Who last modified the experiment.amazonka-sagemaker&When the experiment was last modified.amazonka-sagemakerThe Amazon Resource Name (ARN) of the source and, optionally, the type.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker'The name of the experiment to describe.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, * - The name of the experiment to describe.amazonka-sagemaker'The name of the experiment to describe.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - Who created the experiment., # - When the experiment was created., % - The description of the experiment., / - The name of the experiment as displayed. If  DisplayName isn't specified, ExperimentName is displayed., 4 - The Amazon Resource Name (ARN) of the experiment.,  - The name of the experiment., $ - Who last modified the experiment., ) - When the experiment was last modified.,  - The Amazon Resource Name (ARN) of the source and, optionally, the type., # - The response's http status code.amazonka-sagemakerWho created the experiment.amazonka-sagemaker When the experiment was created.amazonka-sagemaker"The description of the experiment.amazonka-sagemaker,The name of the experiment as displayed. If  DisplayName isn't specified, ExperimentName is displayed.amazonka-sagemaker1The Amazon Resource Name (ARN) of the experiment.amazonka-sagemakerThe name of the experiment.amazonka-sagemaker!Who last modified the experiment.amazonka-sagemaker&When the experiment was last modified.amazonka-sagemakerThe Amazon Resource Name (ARN) of the source and, optionally, the type.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';$amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerReturns the description of an endpoint configuration created using the  https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateEndpointConfig.htmlCreateEndpointConfig API.amazonka-sagemaker.The configuration parameters for an explainer.amazonka-sagemakerAmazon Web Services KMS key ID Amazon SageMaker uses to encrypt data when storing it on the ML storage volume attached to the instance.amazonka-sagemaker An array of ProductionVariant objects, one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants.amazonka-sagemaker The response's http status code.amazonka-sagemaker-Name of the SageMaker endpoint configuration.amazonka-sagemaker=The Amazon Resource Name (ARN) of the endpoint configuration.amazonka-sagemaker An array of ProductionVariant objects, one for each model that you want to host at this endpoint.amazonka-sagemakerA timestamp that shows when the endpoint configuration was created.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker'The name of the endpoint configuration.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, * - The name of the endpoint configuration.amazonka-sagemaker'The name of the endpoint configuration.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - Returns the description of an endpoint configuration created using the  https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateEndpointConfig.htmlCreateEndpointConfig API.,  - Undocumented member., 1 - The configuration parameters for an explainer.,  - Amazon Web Services KMS key ID Amazon SageMaker uses to encrypt data when storing it on the ML storage volume attached to the instance.,  - An array of ProductionVariant objects, one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants., # - The response's http status code., 0 - Name of the SageMaker endpoint configuration.,  - The Amazon Resource Name (ARN) of the endpoint configuration., ¦ - An array of ProductionVariant objects, one for each model that you want to host at this endpoint., æ - A timestamp that shows when the endpoint configuration was created.amazonka-sagemakerReturns the description of an endpoint configuration created using the  https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateEndpointConfig.htmlCreateEndpointConfig API.amazonka-sagemakerUndocumented member.amazonka-sagemaker.The configuration parameters for an explainer.amazonka-sagemakerAmazon Web Services KMS key ID Amazon SageMaker uses to encrypt data when storing it on the ML storage volume attached to the instance.amazonka-sagemaker An array of ProductionVariant objects, one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants.amazonka-sagemaker The response's http status code.amazonka-sagemaker-Name of the SageMaker endpoint configuration.amazonka-sagemaker=The Amazon Resource Name (ARN) of the endpoint configuration.¦amazonka-sagemaker An array of ProductionVariant objects, one for each model that you want to host at this endpoint.æamazonka-sagemakerA timestamp that shows when the endpoint configuration was created.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker¦æ¦æ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';$Bm#Ԧamazonka-sagemakerSee:  smart constructor.֦amazonka-sagemakerReturns the description of an endpoint configuration created using the  https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateEndpointConfig.htmlCreateEndpointConfig API.ئamazonka-sagemaker.The configuration parameters for an explainer.٦amazonka-sagemaker!If the status of the endpoint is Failed, the reason why it failed.ڦamazonka-sagemaker:The most recent deployment configuration for the endpoint.ۦamazonka-sagemakerReturns the summary of an in-progress deployment. This field is only returned when the endpoint is creating or updating with a new endpoint configuration.ܦamazonka-sagemakerAn array of ProductionVariantSummary objects, one for each model hosted behind this endpoint.ݦamazonka-sagemakerAn array of ProductionVariantSummary objects, one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants.ަamazonka-sagemaker The response's http status code.ߦamazonka-sagemakerName of the endpoint.amazonka-sagemaker/The Amazon Resource Name (ARN) of the endpoint.amazonka-sagemakerThe name of the endpoint configuration associated with this endpoint.amazonka-sagemakerThe status of the endpoint. OutOfService6: Endpoint is not available to take incoming requests.Creating: CreateEndpoint is executing.Updating: UpdateEndpoint or UpdateEndpointWeightsAndCapacities is executing.SystemUpdating: Endpoint is undergoing maintenance and cannot be updated or deleted or re-scaled until it has completed. This maintenance operation does not change any customer-specified values such as VPC config, KMS encryption, model, instance type, or instance count. RollingBack: Endpoint fails to scale up or down or change its variant weight and is in the process of rolling back to its previous configuration. Once the rollback completes, endpoint returns to an  InService status. This transitional status only applies to an endpoint that has autoscaling enabled and is undergoing variant weight or capacity changes as part of an UpdateEndpointWeightsAndCapacities call or when the UpdateEndpointWeightsAndCapacities operation is called explicitly. InService5: Endpoint is available to process incoming requests.Deleting: DeleteEndpoint is executing.Failed: Endpoint could not be created, updated, or re-scaled. Use DescribeEndpointOutput$FailureReason for information about the failure. DeleteEndpoint is the only operation that can be performed on a failed endpoint.amazonka-sagemaker5A timestamp that shows when the endpoint was created.amazonka-sagemaker;A timestamp that shows when the endpoint was last modified.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe name of the endpoint.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The name of the endpoint.amazonka-sagemakerThe name of the endpoint.amazonka-sagemakerCreate a value of Ԧ" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:֦,  - Returns the description of an endpoint configuration created using the  https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateEndpointConfig.htmlCreateEndpointConfig API.Ԧ,  - Undocumented member.ئ, 1 - The configuration parameters for an explainer.Ԧ, $ - If the status of the endpoint is Failed, the reason why it failed.ڦ, = - The most recent deployment configuration for the endpoint.ۦ,  - Returns the summary of an in-progress deployment. This field is only returned when the endpoint is creating or updating with a new endpoint configuration.Ԧ,  - An array of ProductionVariantSummary objects, one for each model hosted behind this endpoint.Ԧ,  - An array of ProductionVariantSummary objects, one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants.ަ, # - The response's http status code.,  - Name of the endpoint.Ԧ, 2 - The Amazon Resource Name (ARN) of the endpoint.Ԧ,  - The name of the endpoint configuration associated with this endpoint.Ԧ,  - The status of the endpoint. OutOfService6: Endpoint is not available to take incoming requests.Creating: CreateEndpoint is executing.Updating: UpdateEndpoint or UpdateEndpointWeightsAndCapacities is executing.SystemUpdating: Endpoint is undergoing maintenance and cannot be updated or deleted or re-scaled until it has completed. This maintenance operation does not change any customer-specified values such as VPC config, KMS encryption, model, instance type, or instance count. RollingBack: Endpoint fails to scale up or down or change its variant weight and is in the process of rolling back to its previous configuration. Once the rollback completes, endpoint returns to an  InService status. This transitional status only applies to an endpoint that has autoscaling enabled and is undergoing variant weight or capacity changes as part of an UpdateEndpointWeightsAndCapacities call or when the UpdateEndpointWeightsAndCapacities operation is called explicitly. InService5: Endpoint is available to process incoming requests.Deleting: DeleteEndpoint is executing.Failed: Endpoint could not be created, updated, or re-scaled. Use DescribeEndpointOutput$FailureReason for information about the failure. DeleteEndpoint is the only operation that can be performed on a failed endpoint.Ԧ, 8 - A timestamp that shows when the endpoint was created.Ԧ, > - A timestamp that shows when the endpoint was last modified.amazonka-sagemakerReturns the description of an endpoint configuration created using the  https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateEndpointConfig.htmlCreateEndpointConfig API.amazonka-sagemakerUndocumented member.amazonka-sagemaker.The configuration parameters for an explainer.amazonka-sagemaker!If the status of the endpoint is Failed, the reason why it failed.amazonka-sagemaker:The most recent deployment configuration for the endpoint.amazonka-sagemakerReturns the summary of an in-progress deployment. This field is only returned when the endpoint is creating or updating with a new endpoint configuration.amazonka-sagemakerAn array of ProductionVariantSummary objects, one for each model hosted behind this endpoint.amazonka-sagemakerAn array of ProductionVariantSummary objects, one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants.amazonka-sagemaker The response's http status code.amazonka-sagemakerName of the endpoint.amazonka-sagemaker/The Amazon Resource Name (ARN) of the endpoint.amazonka-sagemakerThe name of the endpoint configuration associated with this endpoint.amazonka-sagemakerThe status of the endpoint. OutOfService6: Endpoint is not available to take incoming requests.Creating: CreateEndpoint is executing.Updating: UpdateEndpoint or UpdateEndpointWeightsAndCapacities is executing.SystemUpdating: Endpoint is undergoing maintenance and cannot be updated or deleted or re-scaled until it has completed. This maintenance operation does not change any customer-specified values such as VPC config, KMS encryption, model, instance type, or instance count. RollingBack: Endpoint fails to scale up or down or change its variant weight and is in the process of rolling back to its previous configuration. Once the rollback completes, endpoint returns to an  InService status. This transitional status only applies to an endpoint that has autoscaling enabled and is undergoing variant weight or capacity changes as part of an UpdateEndpointWeightsAndCapacities call or when the UpdateEndpointWeightsAndCapacities operation is called explicitly. InService5: Endpoint is available to process incoming requests.Deleting: DeleteEndpoint is executing.Failed: Endpoint could not be created, updated, or re-scaled. Use DescribeEndpointOutput$FailureReason for information about the failure. DeleteEndpoint is the only operation that can be performed on a failed endpoint.amazonka-sagemaker5A timestamp that shows when the endpoint was created.amazonka-sagemaker;A timestamp that shows when the endpoint was last modified.amazonka-sagemakeramazonka-sagemakerަamazonka-sagemakeramazonka-sagemakerԦamazonka-sagemakerԦamazonka-sagemakerԦamazonka-sagemakerԦamazonka-sagemakerԦ&Ԧզ٦ߦܦݦצަ֦ئڦۦ&Ԧզ٦ߦܦݦצަ֦ئڦۦ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';$X&amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe name of the SageMaker Neo compilation job that is used to locate model artifacts that are being packaged.amazonka-sagemaker4The timestamp of when the packaging job was created.amazonka-sagemaker?Returns a message describing the job status and error messages.amazonka-sagemaker/The timestamp of when the job was last updated.amazonka-sagemakerThe Amazon Simple Storage (S3) URI where model artifacts ares stored.amazonka-sagemakerThe name of the model.amazonka-sagemaker6The signature document of files in the model artifact.amazonka-sagemakerThe version of the model.amazonka-sagemaker4The output configuration for the edge packaging job.amazonka-sagemaker;The output of a SageMaker Edge Manager deployable resource.amazonka-sagemakerThe Amazon Web Services KMS key to use when encrypting the EBS volume the job run on.amazonka-sagemakerThe Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to download and upload the model, and to contact Neo.amazonka-sagemaker The response's http status code.amazonka-sagemaker9The Amazon Resource Name (ARN) of the edge packaging job.amazonka-sagemaker#The name of the edge packaging job.amazonka-sagemaker(The current status of the packaging job.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker#The name of the edge packaging job.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, & - The name of the edge packaging job.amazonka-sagemaker#The name of the edge packaging job.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The name of the SageMaker Neo compilation job that is used to locate model artifacts that are being packaged., 7 - The timestamp of when the packaging job was created.,  - Returns a message describing the job status and error messages., 2 - The timestamp of when the job was last updated.,  - The Amazon Simple Storage (S3) URI where model artifacts ares stored.,  - The name of the model., 9 - The signature document of files in the model artifact.,  - The version of the model., 7 - The output configuration for the edge packaging job., > - The output of a SageMaker Edge Manager deployable resource.,  - The Amazon Web Services KMS key to use when encrypting the EBS volume the job run on.,  - The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to download and upload the model, and to contact Neo., # - The response's http status code., < - The Amazon Resource Name (ARN) of the edge packaging job., & - The name of the edge packaging job., + - The current status of the packaging job.amazonka-sagemakerThe name of the SageMaker Neo compilation job that is used to locate model artifacts that are being packaged.amazonka-sagemaker4The timestamp of when the packaging job was created.amazonka-sagemaker?Returns a message describing the job status and error messages.amazonka-sagemaker/The timestamp of when the job was last updated.amazonka-sagemakerThe Amazon Simple Storage (S3) URI where model artifacts ares stored.amazonka-sagemakerThe name of the model.amazonka-sagemaker6The signature document of files in the model artifact.amazonka-sagemakerThe version of the model.amazonka-sagemaker4The output configuration for the edge packaging job.amazonka-sagemaker;The output of a SageMaker Edge Manager deployable resource.amazonka-sagemakerThe Amazon Web Services KMS key to use when encrypting the EBS volume the job run on.amazonka-sagemakerThe Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to download and upload the model, and to contact Neo.amazonka-sagemaker The response's http status code.amazonka-sagemaker9The Amazon Resource Name (ARN) of the edge packaging job.amazonka-sagemaker#The name of the edge packaging job.amazonka-sagemaker(The current status of the packaging job.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(((c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';$l"§amazonka-sagemakerSee: ٧ smart constructor.ħamazonka-sagemaker3The time when the edge deployment plan was created.ŧamazonka-sagemaker6The number of edge devices that failed the deployment.Ƨamazonka-sagemakerThe number of edge devices yet to pick up deployment, or in progress.ǧamazonka-sagemaker:The number of edge devices with the successful deployment.ȧamazonka-sagemaker8The time when the edge deployment plan was last updated.ɧamazonka-sagemakerToken to use when calling the next set of stages in the edge deployment plan.ʧamazonka-sagemaker The response's http status code.˧amazonka-sagemaker The ARN of edge deployment plan.̧amazonka-sagemaker%The name of the edge deployment plan.ͧamazonka-sagemaker8List of models associated with the edge deployment plan.Χamazonka-sagemaker4The device fleet used for this edge deployment plan.ϧamazonka-sagemaker+List of stages in the edge deployment plan.Чamazonka-sagemakerSee: է smart constructor.ҧamazonka-sagemaker8The maximum number of results to select (50 by default).ӧamazonka-sagemakerIf the edge deployment plan has enough stages to require tokening, then this is the response from the last list of stages returned.ԧamazonka-sagemaker,The name of the deployment plan to describe.էamazonka-sagemakerCreate a value of Ч" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:ҧ, ֧; - The maximum number of results to select (50 by default).Ч, ק - If the edge deployment plan has enough stages to require tokening, then this is the response from the last list of stages returned.Ч, ا/ - The name of the deployment plan to describe.֧amazonka-sagemaker8The maximum number of results to select (50 by default).קamazonka-sagemakerIf the edge deployment plan has enough stages to require tokening, then this is the response from the last list of stages returned.اamazonka-sagemaker,The name of the deployment plan to describe.٧amazonka-sagemakerCreate a value of §" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:§, ڧ6 - The time when the edge deployment plan was created.§, ۧ9 - The number of edge devices that failed the deployment.§, ܧ - The number of edge devices yet to pick up deployment, or in progress.§, ݧ= - The number of edge devices with the successful deployment.§, ާ; - The time when the edge deployment plan was last updated.Ч, ߧ - Token to use when calling the next set of stages in the edge deployment plan.ʧ, # - The response's http status code.§, # - The ARN of edge deployment plan.Ч, ( - The name of the edge deployment plan.ͧ, ; - List of models associated with the edge deployment plan.§, 7 - The device fleet used for this edge deployment plan.ϧ, . - List of stages in the edge deployment plan.ڧamazonka-sagemaker3The time when the edge deployment plan was created.ۧamazonka-sagemaker6The number of edge devices that failed the deployment.ܧamazonka-sagemakerThe number of edge devices yet to pick up deployment, or in progress.ݧamazonka-sagemaker:The number of edge devices with the successful deployment.ާamazonka-sagemaker8The time when the edge deployment plan was last updated.ߧamazonka-sagemakerToken to use when calling the next set of stages in the edge deployment plan.amazonka-sagemaker The response's http status code.amazonka-sagemaker The ARN of edge deployment plan.amazonka-sagemaker%The name of the edge deployment plan.amazonka-sagemaker8List of models associated with the edge deployment plan.amazonka-sagemaker4The device fleet used for this edge deployment plan.amazonka-sagemaker+List of stages in the edge deployment plan.էamazonka-sagemakerЧ٧amazonka-sagemakerʧamazonka-sagemaker§amazonka-sagemakerЧamazonka-sagemaker§$§çħȧΧ˧̧ǧƧŧʧɧͧϧЧѧԧҧӧէ֧קا٧ڧۧܧݧާߧ$Чѧԧҧӧէ֧קا§çħȧΧ˧̧ǧƧŧʧɧͧϧ٧ڧۧܧݧާߧ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';$72amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerSpecifies the VPC used for non-EFS traffic. The default value is PublicInternetOnly.PublicInternetOnly - Non-EFS traffic is through a VPC managed by Amazon SageMaker, which allows direct internet accessVpcOnly - All Studio traffic is through the specified VPC and subnetsamazonka-sagemakerThe entity that creates and manages the required security groups for inter-app communication in VPCOnly mode. Required when !CreateDomain.AppNetworkAccessType is VPCOnly and DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is provided.amazonka-sagemaker!The domain's authentication mode.amazonka-sagemakerThe creation time.amazonka-sagemaker,The default settings used to create a space.amazonka-sagemakerSettings which are applied to UserProfiles in this domain if settings are not explicitly specified in a given UserProfile.amazonka-sagemaker(The domain's Amazon Resource Name (ARN).amazonka-sagemakerThe domain ID.amazonka-sagemakerThe domain name.amazonka-sagemakerA collection of Domain settings.amazonka-sagemakerThe failure reason.amazonka-sagemakerThe ID of the Amazon Elastic File System (EFS) managed by this Domain.amazonka-sagemakerUse KmsKeyId.amazonka-sagemakerThe Amazon Web Services KMS customer managed key used to encrypt the EFS volume attached to the domain.amazonka-sagemakerThe last modified time.amazonka-sagemakerThe ID of the security group that authorizes traffic between the RSessionGateway apps and the RStudioServerPro app.amazonka-sagemaker8The IAM Identity Center managed application instance ID.amazonka-sagemaker The status.amazonka-sagemaker3The VPC subnets that Studio uses for communication.amazonka-sagemakerThe domain's URL.amazonka-sagemakerThe ID of the Amazon Virtual Private Cloud (VPC) that Studio uses for communication.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe domain ID.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The domain ID.amazonka-sagemakerThe domain ID.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - Specifies the VPC used for non-EFS traffic. The default value is PublicInternetOnly.PublicInternetOnly - Non-EFS traffic is through a VPC managed by Amazon SageMaker, which allows direct internet accessVpcOnly - All Studio traffic is through the specified VPC and subnets,  - The entity that creates and manages the required security groups for inter-app communication in VPCOnly mode. Required when !CreateDomain.AppNetworkAccessType is VPCOnly and DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is provided., $ - The domain's authentication mode.,  - The creation time., / - The default settings used to create a space.,  - Settings which are applied to UserProfiles in this domain if settings are not explicitly specified in a given UserProfile., + - The domain's Amazon Resource Name (ARN).,  - The domain ID.,  - The domain name.,  - A collection of Domain settings.,  - The failure reason.,  - The ID of the Amazon Elastic File System (EFS) managed by this Domain.,  - Use KmsKeyId.,  - The Amazon Web Services KMS customer managed key used to encrypt the EFS volume attached to the domain.,  - The last modified time.,  - The ID of the security group that authorizes traffic between the RSessionGateway apps and the RStudioServerPro app., ; - The IAM Identity Center managed application instance ID.,  - The status., 6 - The VPC subnets that Studio uses for communication.,  - The domain's URL.,  - The ID of the Amazon Virtual Private Cloud (VPC) that Studio uses for communication., # - The response's http status code.amazonka-sagemakerSpecifies the VPC used for non-EFS traffic. The default value is PublicInternetOnly.PublicInternetOnly - Non-EFS traffic is through a VPC managed by Amazon SageMaker, which allows direct internet accessVpcOnly - All Studio traffic is through the specified VPC and subnetsamazonka-sagemakerThe entity that creates and manages the required security groups for inter-app communication in VPCOnly mode. Required when !CreateDomain.AppNetworkAccessType is VPCOnly and DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is provided.amazonka-sagemaker!The domain's authentication mode.amazonka-sagemakerThe creation time.amazonka-sagemaker,The default settings used to create a space.amazonka-sagemakerSettings which are applied to UserProfiles in this domain if settings are not explicitly specified in a given UserProfile.amazonka-sagemaker(The domain's Amazon Resource Name (ARN).amazonka-sagemakerThe domain ID.amazonka-sagemakerThe domain name.amazonka-sagemakerA collection of Domain settings.amazonka-sagemakerThe failure reason.amazonka-sagemakerThe ID of the Amazon Elastic File System (EFS) managed by this Domain.amazonka-sagemakerUse KmsKeyId.amazonka-sagemakerThe Amazon Web Services KMS customer managed key used to encrypt the EFS volume attached to the domain.amazonka-sagemakerThe last modified time.amazonka-sagemakerThe ID of the security group that authorizes traffic between the RSessionGateway apps and the RStudioServerPro app.amazonka-sagemaker8The IAM Identity Center managed application instance ID.amazonka-sagemaker The status.amazonka-sagemaker3The VPC subnets that Studio uses for communication.amazonka-sagemakerThe domain's URL.amazonka-sagemakerThe ID of the Amazon Virtual Private Cloud (VPC) that Studio uses for communication.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemaker44(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';$"amazonka-sagemakerSee: ʨ smart constructor.amazonka-sagemakerA description of the fleet.amazonka-sagemakerThe Amazon Resource Name (ARN) alias created in Amazon Web Services Internet of Things (IoT).amazonka-sagemakerThe Amazon Resource Name (ARN) that has access to Amazon Web Services Internet of Things (IoT).amazonka-sagemaker The response's http status code.amazonka-sagemakerThe name of the fleet.amazonka-sagemaker0The The Amazon Resource Name (ARN) of the fleet.¨amazonka-sagemaker2The output configuration for storing sampled data.èamazonka-sagemaker/Timestamp of when the device fleet was created.Ĩamazonka-sagemaker4Timestamp of when the device fleet was last updated.Ũamazonka-sagemakerSee: Ȩ smart constructor.Ǩamazonka-sagemakerThe name of the fleet.Ȩamazonka-sagemakerCreate a value of Ũ" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:Ũ, ɨ - The name of the fleet.ɨamazonka-sagemakerThe name of the fleet.ʨamazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, ˨ - A description of the fleet., ̨ - The Amazon Resource Name (ARN) alias created in Amazon Web Services Internet of Things (IoT)., ͨ - The Amazon Resource Name (ARN) that has access to Amazon Web Services Internet of Things (IoT)., Ψ# - The response's http status code.Ũ, Ϩ - The name of the fleet., Ш3 - The The Amazon Resource Name (ARN) of the fleet., Ѩ5 - The output configuration for storing sampled data., Ҩ2 - Timestamp of when the device fleet was created., Ө7 - Timestamp of when the device fleet was last updated.˨amazonka-sagemakerA description of the fleet.̨amazonka-sagemakerThe Amazon Resource Name (ARN) alias created in Amazon Web Services Internet of Things (IoT).ͨamazonka-sagemakerThe Amazon Resource Name (ARN) that has access to Amazon Web Services Internet of Things (IoT).Ψamazonka-sagemaker The response's http status code.Ϩamazonka-sagemakerThe name of the fleet.Шamazonka-sagemaker0The The Amazon Resource Name (ARN) of the fleet.Ѩamazonka-sagemaker2The output configuration for storing sampled data.Ҩamazonka-sagemaker/Timestamp of when the device fleet was created.Өamazonka-sagemaker4Timestamp of when the device fleet was last updated.Ȩamazonka-sagemakerŨʨamazonka-sagemakeramazonka-sagemakerŨamazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakerèĨ¨ŨƨǨȨɨʨ˨̨ͨΨϨШѨҨӨŨƨǨȨɨèĨ¨ʨ˨̨ͨΨϨШѨҨӨ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';$"amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerEdge Manager agent version.amazonka-sagemakerA description of the device.amazonka-sagemaker-The Amazon Resource Name (ARN) of the device.amazonka-sagemakerThe Amazon Web Services Internet of Things (IoT) object thing name associated with the device.amazonka-sagemaker,The last heartbeat received from the device.amazonka-sagemakerThe maximum number of models.amazonka-sagemakerModels on the device.amazonka-sagemakerThe response from the last list when returning a list large enough to need tokening.amazonka-sagemaker The response's http status code.amazonka-sagemaker$The unique identifier of the device.amazonka-sagemaker,The name of the fleet the device belongs to.amazonka-sagemakerReturns the failure reason for an AutoML job, when applicable.amazonka-sagemakerIndicates whether the output for an AutoML job generates candidate definitions only.amazonka-sagemakerIndicates whether the model was deployed automatically to an endpoint and the name of that endpoint if deployed automatically.amazonka-sagemaker=Provides information about endpoint for the model deployment.amazonka-sagemakerReturns a list of reasons for partial failures within an AutoML job.amazonka-sagemakerReturns the job's problem type.amazonka-sagemakerThis contains  ProblemType, AutoMLJobObjective, and CompletionCriteria. If you do not provide these values, they are auto-inferred. If you do provide them, the values used are the ones you provide.amazonka-sagemaker The response's http status code.amazonka-sagemaker#Returns the name of the AutoML job.amazonka-sagemaker"Returns the ARN of the AutoML job.amazonka-sagemaker9Returns the input data configuration for the AutoML job..amazonka-sagemaker%Returns the job's output data config.amazonka-sagemakerThe Amazon Resource Name (ARN) of the Identity and Access Management (IAM) role that has read permission to the input data location and write permission to the output data location in Amazon S3.amazonka-sagemaker,Returns the creation time of the AutoML job.amazonka-sagemaker%Returns the job's last modified time.amazonka-sagemaker%Returns the status of the AutoML job.amazonka-sagemaker/Returns the secondary status of the AutoML job.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker?Requests information about an AutoML job using its unique name.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - Requests information about an AutoML job using its unique name.amazonka-sagemaker?Requests information about an AutoML job using its unique name.amazonka-sagemakerCreate a value of ت" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:ڪ, 8 - Returns information on the job's artifacts found in AutoMLJobArtifacts.۪, 0 - Returns the configuration for the AutoML job.ت,  - Returns the job's objective.ݪ,  - The best model candidate selected by SageMaker Autopilot using both the best objective metric and lowest  https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-metrics-validation.htmlInferenceLatency for an experiment.ت, * - Returns the end time of the AutoML job.ت,  - Returns the failure reason for an AutoML job, when applicable.,  - Indicates whether the output for an AutoML job generates candidate definitions only.,  - Indicates whether the model was deployed automatically to an endpoint and the name of that endpoint if deployed automatically.,  - Provides information about endpoint for the model deployment.ت,  - Returns a list of reasons for partial failures within an AutoML job.ت, " - Returns the job's problem type.,  - This contains  ProblemType, AutoMLJobObjective, and CompletionCriteria. If you do not provide these values, they are auto-inferred. If you do provide them, the values used are the ones you provide., # - The response's http status code., & - Returns the name of the AutoML job.ت, % - Returns the ARN of the AutoML job.ت, < - Returns the input data configuration for the AutoML job..ت, ( - Returns the job's output data config.ت,  - The Amazon Resource Name (ARN) of the Identity and Access Management (IAM) role that has read permission to the input data location and write permission to the output data location in Amazon S3.ت, / - Returns the creation time of the AutoML job.ت, ( - Returns the job's last modified time.ت, ( - Returns the status of the AutoML job.ت, 2 - Returns the secondary status of the AutoML job.amazonka-sagemaker5Returns information on the job's artifacts found in AutoMLJobArtifacts.amazonka-sagemaker-Returns the configuration for the AutoML job.amazonka-sagemakerReturns the job's objective.amazonka-sagemakerThe best model candidate selected by SageMaker Autopilot using both the best objective metric and lowest  https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-metrics-validation.htmlInferenceLatency for an experiment.amazonka-sagemaker'Returns the end time of the AutoML job.amazonka-sagemaker>Returns the failure reason for an AutoML job, when applicable.amazonka-sagemakerIndicates whether the output for an AutoML job generates candidate definitions only.amazonka-sagemakerIndicates whether the model was deployed automatically to an endpoint and the name of that endpoint if deployed automatically.amazonka-sagemaker=Provides information about endpoint for the model deployment.amazonka-sagemakerReturns a list of reasons for partial failures within an AutoML job.amazonka-sagemakerReturns the job's problem type.amazonka-sagemakerThis contains  ProblemType, AutoMLJobObjective, and CompletionCriteria. If you do not provide these values, they are auto-inferred. If you do provide them, the values used are the ones you provide.amazonka-sagemaker The response's http status code.amazonka-sagemaker#Returns the name of the AutoML job.amazonka-sagemaker"Returns the ARN of the AutoML job.amazonka-sagemaker9Returns the input data configuration for the AutoML job..amazonka-sagemaker%Returns the job's output data config.amazonka-sagemakerThe Amazon Resource Name (ARN) of the Identity and Access Management (IAM) role that has read permission to the input data location and write permission to the output data location in Amazon S3.amazonka-sagemaker,Returns the creation time of the AutoML job.amazonka-sagemaker%Returns the job's last modified time.amazonka-sagemaker%Returns the status of the AutoML job.amazonka-sagemaker/Returns the secondary status of the AutoML job.amazonka-sagemaker amazonka-sagemakeramazonka-sagemakeramazonka-sagemakerتamazonka-sagemakerتamazonka-sagemakerتamazonka-sagemakerتamazonka-sagemakerتamazonka-sagemakerتamazonka-sagemakerت amazonka-sagemakerت4ت٪ߪުܪڪ۪ݪ4ت٪ߪުܪڪ۪ݪ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';%1amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker/The Amazon Resource Name (ARN) of the artifact.amazonka-sagemakerThe name of the artifact.amazonka-sagemakerThe type of the artifact.amazonka-sagemakerWhen the artifact was created.amazonka-sagemaker$When the artifact was last modified.amazonka-sagemaker4The Amazon Resource Name (ARN) of the lineage group.amazonka-sagemaker$A list of the artifact's properties.amazonka-sagemakerThe source of the artifact.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker;The Amazon Resource Name (ARN) of the artifact to describe.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, > - The Amazon Resource Name (ARN) of the artifact to describe.amazonka-sagemaker;The Amazon Resource Name (ARN) of the artifact to describe.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 2 - The Amazon Resource Name (ARN) of the artifact.,  - The name of the artifact.,  - The type of the artifact.,  - Undocumented member., ! - When the artifact was created.,  - Undocumented member., ' - When the artifact was last modified., 7 - The Amazon Resource Name (ARN) of the lineage group.,  - Undocumented member., ' - A list of the artifact's properties.,  - The source of the artifact., # - The response's http status code.amazonka-sagemaker/The Amazon Resource Name (ARN) of the artifact.amazonka-sagemakerThe name of the artifact.amazonka-sagemakerThe type of the artifact.amazonka-sagemakerUndocumented member.amazonka-sagemakerWhen the artifact was created.amazonka-sagemakerUndocumented member.amazonka-sagemaker$When the artifact was last modified.amazonka-sagemaker4The Amazon Resource Name (ARN) of the lineage group.amazonka-sagemakerUndocumented member.amazonka-sagemaker$A list of the artifact's properties.amazonka-sagemakerThe source of the artifact.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemaker  (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';% - The name of the model group for which to delete the policy.amazonka-sagemaker;The name of the model group for which to delete the policy.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.amazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';%Lamazonka-sagemakerSee:  smart constructor.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker&The name of the model group to delete.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, ) - The name of the model group to delete.amazonka-sagemaker&The name of the model group to delete.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.amazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';%İamazonka-sagemakerSee: ˰ smart constructor.ưamazonka-sagemakerSee: ɰ smart constructor.Ȱamazonka-sagemakerThe name or Amazon Resource Name (ARN) of the model package to delete.When you specify a name, the name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).ɰamazonka-sagemakerCreate a value of ư" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:ư, ʰ - The name or Amazon Resource Name (ARN) of the model package to delete.When you specify a name, the name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).ʰamazonka-sagemakerThe name or Amazon Resource Name (ARN) of the model package to delete.When you specify a name, the name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).˰amazonka-sagemakerCreate a value of İ" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.ɰamazonka-sagemakerưİŰưǰȰɰʰ˰ưǰȰɰʰİŰ˰(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';%ܰamazonka-sagemakerSee:  smart constructor.ްamazonka-sagemakerSee:  smart constructor.amazonka-sagemaker>The name of the model explainability job definition to delete.amazonka-sagemakerCreate a value of ް" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The name of the model explainability job definition to delete.amazonka-sagemaker>The name of the model explainability job definition to delete.amazonka-sagemakerCreate a value of ܰ" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.amazonka-sagemakerܰݰް߰ް߰ܰݰ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';%yamazonka-sagemakerSee:  smart constructor.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker%The name of the model card to delete.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, ( - The name of the model card to delete.amazonka-sagemaker%The name of the model card to delete.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.amazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';%Vamazonka-sagemakerSee:  smart constructor.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker4The name of the model bias job definition to delete.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 7 - The name of the model bias job definition to delete.amazonka-sagemaker4The name of the model bias job definition to delete.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.amazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';%amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The name of the model to delete.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The name of the model to delete.amazonka-sagemaker The name of the model to delete.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.amazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';% amazonka-sagemakerSee: ű smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemaker,The ARN of the deleted inference experiment.amazonka-sagemakerSee: ñ smart constructor.±amazonka-sagemaker8The name of the inference experiment you want to delete.ñamazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, ı; - The name of the inference experiment you want to delete.ıamazonka-sagemaker8The name of the inference experiment you want to delete.űamazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, Ʊ# - The response's http status code., DZ/ - The ARN of the deleted inference experiment.Ʊamazonka-sagemaker The response's http status code.DZamazonka-sagemaker,The ARN of the deleted inference experiment.ñamazonka-sagemakerűamazonka-sagemakeramazonka-sagemaker ±ñıűƱDZ ±ñıűƱDZ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';%L رamazonka-sagemakerSee:  smart constructor.ڱamazonka-sagemaker The response's http status code.۱amazonka-sagemakerSee:  smart constructor.ݱamazonka-sagemaker!The alias of the image to delete.ޱamazonka-sagemakerThe version to delete.߱amazonka-sagemaker The name of the image to delete.amazonka-sagemakerCreate a value of ۱" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:ݱ, $ - The alias of the image to delete.۱,  - The version to delete.۱, # - The name of the image to delete.amazonka-sagemaker!The alias of the image to delete.amazonka-sagemakerThe version to delete.amazonka-sagemaker The name of the image to delete.amazonka-sagemakerCreate a value of ر" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:ڱ, # - The response's http status code.amazonka-sagemaker The response's http status code.amazonka-sagemaker۱amazonka-sagemakerڱرٱڱ۱ܱޱ߱ݱ۱ܱޱ߱ݱرٱڱ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';&Samazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The name of the image to delete.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The name of the image to delete.amazonka-sagemaker The name of the image to delete.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemaker  (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';&amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe name of the human task user interface (work task template) you want to delete.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The name of the human task user interface (work task template) you want to delete.amazonka-sagemakerThe name of the human task user interface (work task template) you want to delete.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemaker  (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';& amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker7The name of the hub that you want to delete content in.amazonka-sagemaker7The type of content that you want to delete from a hub.amazonka-sagemaker;The name of the content that you want to delete from a hub.amazonka-sagemaker>The version of the content that you want to delete from a hub.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, : - The name of the hub that you want to delete content in., : - The type of content that you want to delete from a hub., > - The name of the content that you want to delete from a hub.,  - The version of the content that you want to delete from a hub.amazonka-sagemaker7The name of the hub that you want to delete content in.amazonka-sagemaker7The type of content that you want to delete from a hub.amazonka-sagemaker;The name of the content that you want to delete from a hub.amazonka-sagemaker>The version of the content that you want to delete from a hub.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';&Ȳamazonka-sagemakerSee: ϲ smart constructor.ʲamazonka-sagemakerSee: Ͳ smart constructor.̲amazonka-sagemakerThe name of the hub to delete.Ͳamazonka-sagemakerCreate a value of ʲ" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:ʲ, β! - The name of the hub to delete.βamazonka-sagemakerThe name of the hub to delete.ϲamazonka-sagemakerCreate a value of Ȳ" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.Ͳamazonka-sagemakerʲȲɲʲ˲̲Ͳβϲʲ˲̲ͲβȲɲϲ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';&amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker1The name of the flow definition you are deleting.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 4 - The name of the flow definition you are deleting.amazonka-sagemaker1The name of the flow definition you are deleting.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemaker  (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';&"amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe name of the  FeatureGroup you want to delete. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The name of the  FeatureGroup you want to delete. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.amazonka-sagemakerThe name of the  FeatureGroup you want to delete. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.amazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';&)' amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe Amazon Resource Name (ARN) of the experiment that is being deleted.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker%The name of the experiment to delete.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, ( - The name of the experiment to delete.amazonka-sagemaker%The name of the experiment to delete.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The Amazon Resource Name (ARN) of the experiment that is being deleted., # - The response's http status code.amazonka-sagemakerThe Amazon Resource Name (ARN) of the experiment that is being deleted.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemaker  (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';&.>amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker?The name of the endpoint configuration that you want to delete.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The name of the endpoint configuration that you want to delete.amazonka-sagemaker?The name of the endpoint configuration that you want to delete.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.amazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';&3Ƴamazonka-sagemakerSee: ͳ smart constructor.ȳamazonka-sagemakerSee: ˳ smart constructor.ʳamazonka-sagemaker1The name of the endpoint that you want to delete.˳amazonka-sagemakerCreate a value of ȳ" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:ȳ, ̳4 - The name of the endpoint that you want to delete.̳amazonka-sagemaker1The name of the endpoint that you want to delete.ͳamazonka-sagemakerCreate a value of Ƴ" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.˳amazonka-sagemakerȳƳdzȳɳʳ˳̳ͳȳɳʳ˳̳Ƴdzͳ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';&8޳amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe name of the edge deployment plan from which the stage will be deleted.amazonka-sagemakerThe name of the stage.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The name of the edge deployment plan from which the stage will be deleted.,  - The name of the stage.amazonka-sagemakerThe name of the edge deployment plan from which the stage will be deleted.amazonka-sagemakerThe name of the stage.amazonka-sagemakerCreate a value of ޳" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.amazonka-sagemakeramazonka-sagemaker ޳߳ ޳߳(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';&=amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker/The name of the edge deployment plan to delete.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 2 - The name of the edge deployment plan to delete.amazonka-sagemaker/The name of the edge deployment plan to delete.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.amazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';&Damazonka-sagemakerSee:  smart constructor.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe retention policy for this domain, which specifies whether resources will be retained after the Domain is deleted. By default, all resources are retained (not automatically deleted).amazonka-sagemakerThe domain ID.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The retention policy for this domain, which specifies whether resources will be retained after the Domain is deleted. By default, all resources are retained (not automatically deleted).,  - The domain ID.amazonka-sagemakerThe retention policy for this domain, which specifies whether resources will be retained after the Domain is deleted. By default, all resources are retained (not automatically deleted).amazonka-sagemakerThe domain ID.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.amazonka-sagemaker  (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';&IWamazonka-sagemakerSee:  smart constructor.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The name of the fleet to delete.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The name of the fleet to delete.amazonka-sagemaker The name of the fleet to delete.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.amazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';&N^´amazonka-sagemakerSee: ɴ smart constructor.Ĵamazonka-sagemakerSee: Ǵ smart constructor.ƴamazonka-sagemakerThe name of the data quality monitoring job definition to delete.Ǵamazonka-sagemakerCreate a value of Ĵ" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:ƴ, ȴ - The name of the data quality monitoring job definition to delete.ȴamazonka-sagemakerThe name of the data quality monitoring job definition to delete.ɴamazonka-sagemakerCreate a value of ´" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.Ǵamazonka-sagemakerƴ´ôĴŴƴǴȴɴĴŴƴǴȴ´ôɴ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';&U ڴamazonka-sagemakerSee:  smart constructor.ܴamazonka-sagemaker.The Amazon Resource Name (ARN) of the context.ݴamazonka-sagemaker The response's http status code.޴amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker"The name of the context to delete.amazonka-sagemakerCreate a value of ޴" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:޴, % - The name of the context to delete.amazonka-sagemaker"The name of the context to delete.amazonka-sagemakerCreate a value of ڴ" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:ڴ, 1 - The Amazon Resource Name (ARN) of the context.ݴ, # - The response's http status code.amazonka-sagemaker.The Amazon Resource Name (ARN) of the context.amazonka-sagemaker The response's http status code.amazonka-sagemaker޴amazonka-sagemakerݴ ڴ۴ܴݴ޴ߴ ޴ߴڴ۴ܴݴ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';&Yamazonka-sagemakerSee:  smart constructor.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker)The name of the Git repository to delete.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, , - The name of the Git repository to delete.amazonka-sagemaker)The name of the Git repository to delete.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.amazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';&b,amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker2The Amazon Resource Name (ARN) of the destination.amazonka-sagemakerThe ARN of the source.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe ARN of the source.amazonka-sagemaker2The Amazon Resource Name (ARN) of the destination.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The ARN of the source., 5 - The Amazon Resource Name (ARN) of the destination.amazonka-sagemakerThe ARN of the source.amazonka-sagemaker2The Amazon Resource Name (ARN) of the destination.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 5 - The Amazon Resource Name (ARN) of the destination.,  - The ARN of the source., # - The response's http status code.amazonka-sagemaker2The Amazon Resource Name (ARN) of the destination.amazonka-sagemakerThe ARN of the source.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';&i amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker/The Amazon Resource Name (ARN) of the artifact.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker9The Amazon Resource Name (ARN) of the artifact to delete.amazonka-sagemakerThe URI of the source.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, < - The Amazon Resource Name (ARN) of the artifact to delete.,  - The URI of the source.amazonka-sagemaker9The Amazon Resource Name (ARN) of the artifact to delete.amazonka-sagemakerThe URI of the source.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 2 - The Amazon Resource Name (ARN) of the artifact., # - The response's http status code.amazonka-sagemaker/The Amazon Resource Name (ARN) of the artifact.amazonka-sagemaker The response's http status code.amazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';&n̵amazonka-sagemakerSee: ӵ smart constructor.εamazonka-sagemakerSee: ѵ smart constructor.еamazonka-sagemaker)The name of the AppImageConfig to delete.ѵamazonka-sagemakerCreate a value of ε" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:ε, ҵ, - The name of the AppImageConfig to delete.ҵamazonka-sagemaker)The name of the AppImageConfig to delete.ӵamazonka-sagemakerCreate a value of ̵" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.ѵamazonka-sagemakerε̵͵εϵеѵҵӵεϵеѵҵ̵͵ӵ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';&wamazonka-sagemakerSee:  smart constructor.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker6The name of the space. If this value is not set, then UserProfileName must be set.amazonka-sagemaker6The user profile name. If this value is not set, then  SpaceName must be set.amazonka-sagemakerThe domain ID.amazonka-sagemakerThe type of app.amazonka-sagemakerThe name of the app.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 9 - The name of the space. If this value is not set, then UserProfileName must be set., 9 - The user profile name. If this value is not set, then  SpaceName must be set.,  - The domain ID.,  - The type of app.,  - The name of the app.amazonka-sagemaker6The name of the space. If this value is not set, then UserProfileName must be set.amazonka-sagemaker6The user profile name. If this value is not set, then  SpaceName must be set.amazonka-sagemakerThe domain ID.amazonka-sagemakerThe type of app.amazonka-sagemakerThe name of the app.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.amazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';&{amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker$The name of the algorithm to delete.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, ' - The name of the algorithm to delete.amazonka-sagemaker$The name of the algorithm to delete.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.amazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';& amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker-The Amazon Resource Name (ARN) of the action.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker!The name of the action to delete.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, $ - The name of the action to delete.amazonka-sagemaker!The name of the action to delete.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 0 - The Amazon Resource Name (ARN) of the action., # - The response's http status code.amazonka-sagemaker-The Amazon Resource Name (ARN) of the action.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemaker  (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';&^amazonka-sagemakerSee: ˶ smart constructor.amazonka-sagemakerThe Amazon Resource Name (ARN) of the work team. You can use this ARN to identify the work team.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee: Ķ smart constructor.amazonka-sagemakerConfigures notification of workers regarding available or expiring work items.amazonka-sagemakerAn array of key-value pairs.For more information, see  https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-resource-tags.html Resource Tag and  https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatUsing Cost Allocation Tags in the :Amazon Web Services Billing and Cost Management User Guide.amazonka-sagemakerThe name of the workforce.amazonka-sagemakerThe name of the work team. Use this name to identify the work team.¶amazonka-sagemaker A list of MemberDefinition objects that contains objects that identify the workers that make up the work team.Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP). For private workforces created using Amazon Cognito use CognitoMemberDefinition. For workforces created using your own OIDC identity provider (IdP) use OidcMemberDefinition. Do not provide input for both of these parameters in a single request.For workforces created using Amazon Cognito, private work teams correspond to Amazon Cognito  user groups> within the user pool used to create a workforce. All of the CognitoMemberDefinition objects that make up the member definition must have the same ClientId and UserPool values. To add a Amazon Cognito user group to an existing worker pool, see  Addinggroups to a User Pool/. For more information about user pools, see  https://docs.aws.amazon.com/cognito/latest/developerguide/cognito-user-identity-pools.htmlAmazon Cognito User Pools.For workforces created using your own OIDC IdP, specify the user groups that you want to include in your private work team in OidcMemberDefinition by listing those groups in Groups.öamazonka-sagemakerA description of the work team.Ķamazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, Ŷ - Configures notification of workers regarding available or expiring work items., ƶ - An array of key-value pairs.For more information, see  https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-resource-tags.html Resource Tag and  https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatUsing Cost Allocation Tags in the :Amazon Web Services Billing and Cost Management User Guide., Ƕ - The name of the workforce., ȶ - The name of the work team. Use this name to identify the work team., ɶ - A list of MemberDefinition objects that contains objects that identify the workers that make up the work team.Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP). For private workforces created using Amazon Cognito use CognitoMemberDefinition. For workforces created using your own OIDC identity provider (IdP) use OidcMemberDefinition. Do not provide input for both of these parameters in a single request.For workforces created using Amazon Cognito, private work teams correspond to Amazon Cognito  user groups> within the user pool used to create a workforce. All of the CognitoMemberDefinition objects that make up the member definition must have the same ClientId and UserPool values. To add a Amazon Cognito user group to an existing worker pool, see  Addinggroups to a User Pool/. For more information about user pools, see  https://docs.aws.amazon.com/cognito/latest/developerguide/cognito-user-identity-pools.htmlAmazon Cognito User Pools.For workforces created using your own OIDC IdP, specify the user groups that you want to include in your private work team in OidcMemberDefinition by listing those groups in Groups., ʶ" - A description of the work team.Ŷamazonka-sagemakerConfigures notification of workers regarding available or expiring work items.ƶamazonka-sagemakerAn array of key-value pairs.For more information, see  https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-resource-tags.html Resource Tag and  https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatUsing Cost Allocation Tags in the :Amazon Web Services Billing and Cost Management User Guide.Ƕamazonka-sagemakerThe name of the workforce.ȶamazonka-sagemakerThe name of the work team. Use this name to identify the work team.ɶamazonka-sagemaker A list of MemberDefinition objects that contains objects that identify the workers that make up the work team.Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP). For private workforces created using Amazon Cognito use CognitoMemberDefinition. For workforces created using your own OIDC identity provider (IdP) use OidcMemberDefinition. Do not provide input for both of these parameters in a single request.For workforces created using Amazon Cognito, private work teams correspond to Amazon Cognito  user groups> within the user pool used to create a workforce. All of the CognitoMemberDefinition objects that make up the member definition must have the same ClientId and UserPool values. To add a Amazon Cognito user group to an existing worker pool, see  Addinggroups to a User Pool/. For more information about user pools, see  https://docs.aws.amazon.com/cognito/latest/developerguide/cognito-user-identity-pools.htmlAmazon Cognito User Pools.For workforces created using your own OIDC IdP, specify the user groups that you want to include in your private work team in OidcMemberDefinition by listing those groups in Groups.ʶamazonka-sagemakerA description of the work team.˶amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, ̶ - The Amazon Resource Name (ARN) of the work team. You can use this ARN to identify the work team., Ͷ# - The response's http status code.̶amazonka-sagemakerThe Amazon Resource Name (ARN) of the work team. You can use this ARN to identify the work team.Ͷamazonka-sagemaker The response's http status code.Ķamazonka-sagemakeramazonka-sagemakeramazonka-sagemaker˶amazonka-sagemakerö¶ĶŶƶǶȶɶʶ˶̶Ͷö¶ĶŶƶǶȶɶʶ˶̶Ͷ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';&޶amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemaker0The Amazon Resource Name (ARN) of the workforce.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerUse this parameter to configure an Amazon Cognito private workforce. A single Cognito workforce is created using and corresponds to a single  https://docs.aws.amazon.com/cognito/latest/developerguide/cognito-user-identity-pools.htmlAmazon Cognito user pool. Do not use  OidcConfig if you specify values for  CognitoConfig.amazonka-sagemakerUse this parameter to configure a private workforce using your own OIDC Identity Provider. Do not use  CognitoConfig if you specify values for  OidcConfig.amazonka-sagemakerAn array of key-value pairs that contain metadata to help you categorize and organize our workforce. Each tag consists of a key and a value, both of which you define.amazonka-sagemaker6Use this parameter to configure a workforce using VPC.amazonka-sagemaker"The name of the private workforce.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - Use this parameter to configure an Amazon Cognito private workforce. A single Cognito workforce is created using and corresponds to a single  https://docs.aws.amazon.com/cognito/latest/developerguide/cognito-user-identity-pools.htmlAmazon Cognito user pool. Do not use  OidcConfig if you specify values for  CognitoConfig.,  - Use this parameter to configure a private workforce using your own OIDC Identity Provider. Do not use  CognitoConfig if you specify values for  OidcConfig.,  - Undocumented member.,  - An array of key-value pairs that contain metadata to help you categorize and organize our workforce. Each tag consists of a key and a value, both of which you define., 9 - Use this parameter to configure a workforce using VPC., % - The name of the private workforce.amazonka-sagemakerUse this parameter to configure an Amazon Cognito private workforce. A single Cognito workforce is created using and corresponds to a single  https://docs.aws.amazon.com/cognito/latest/developerguide/cognito-user-identity-pools.htmlAmazon Cognito user pool. Do not use  OidcConfig if you specify values for  CognitoConfig.amazonka-sagemakerUse this parameter to configure a private workforce using your own OIDC Identity Provider. Do not use  CognitoConfig if you specify values for  OidcConfig.amazonka-sagemakerUndocumented member.amazonka-sagemakerAn array of key-value pairs that contain metadata to help you categorize and organize our workforce. Each tag consists of a key and a value, both of which you define.amazonka-sagemaker6Use this parameter to configure a workforce using VPC.amazonka-sagemaker"The name of the private workforce.amazonka-sagemakerCreate a value of ޶" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code.޶, 3 - The Amazon Resource Name (ARN) of the workforce.amazonka-sagemaker The response's http status code.amazonka-sagemaker0The Amazon Resource Name (ARN) of the workforce.amazonka-sagemakeramazonka-sagemakeramazonka-sagemaker޶޶߶޶߶(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';&amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker,The user profile Amazon Resource Name (ARN).amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerA specifier for the type of value specified in SingleSignOnUserValue. Currently, the only supported value is "UserName". If the Domain's AuthMode is IAM Identity Center, this field is required. If the Domain's AuthMode is not IAM Identity Center, this field cannot be specified.amazonka-sagemakerThe username of the associated Amazon Web Services Single Sign-On User for this UserProfile. If the Domain's AuthMode is IAM Identity Center, this field is required, and must match a valid username of a user in your directory. If the Domain's AuthMode is not IAM Identity Center, this field cannot be specified.amazonka-sagemakerEach tag consists of a key and an optional value. Tag keys must be unique per resource.Tags that you specify for the User Profile are also added to all Apps that the User Profile launches.amazonka-sagemakerA collection of settings.amazonka-sagemaker The ID of the associated Domain.amazonka-sagemaker=A name for the UserProfile. This value is not case sensitive.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - A specifier for the type of value specified in SingleSignOnUserValue. Currently, the only supported value is "UserName". If the Domain's AuthMode is IAM Identity Center, this field is required. If the Domain's AuthMode is not IAM Identity Center, this field cannot be specified.,  - The username of the associated Amazon Web Services Single Sign-On User for this UserProfile. If the Domain's AuthMode is IAM Identity Center, this field is required, and must match a valid username of a user in your directory. If the Domain's AuthMode is not IAM Identity Center, this field cannot be specified.,  - Each tag consists of a key and an optional value. Tag keys must be unique per resource.Tags that you specify for the User Profile are also added to all Apps that the User Profile launches.,  - A collection of settings., # - The ID of the associated Domain.,  - A name for the UserProfile. This value is not case sensitive.amazonka-sagemakerA specifier for the type of value specified in SingleSignOnUserValue. Currently, the only supported value is "UserName". If the Domain's AuthMode is IAM Identity Center, this field is required. If the Domain's AuthMode is not IAM Identity Center, this field cannot be specified.amazonka-sagemakerThe username of the associated Amazon Web Services Single Sign-On User for this UserProfile. If the Domain's AuthMode is IAM Identity Center, this field is required, and must match a valid username of a user in your directory. If the Domain's AuthMode is not IAM Identity Center, this field cannot be specified.amazonka-sagemakerEach tag consists of a key and an optional value. Tag keys must be unique per resource.Tags that you specify for the User Profile are also added to all Apps that the User Profile launches.amazonka-sagemakerA collection of settings.amazonka-sagemaker The ID of the associated Domain.amazonka-sagemaker=A name for the UserProfile. This value is not case sensitive.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, / - The user profile Amazon Resource Name (ARN)., # - The response's http status code.amazonka-sagemaker,The user profile Amazon Resource Name (ARN).amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';&ؿamazonka-sagemakerSee: ķ smart constructor.amazonka-sagemaker6The Amazon Resource Name (ARN) of the trial component.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe name of the component as displayed. The name doesn't need to be unique. If  DisplayName isn't specified, TrialComponentName is displayed.amazonka-sagemakerWhen the component ended.amazonka-sagemakerThe input artifacts for the component. Examples of input artifacts are datasets, algorithms, hyperparameters, source code, and instance types.amazonka-sagemakerThe output artifacts for the component. Examples of output artifacts are metrics, snapshots, logs, and images.amazonka-sagemaker&The hyperparameters for the component.amazonka-sagemakerWhen the component started.amazonka-sagemaker,The status of the component. States include: InProgress CompletedFailedamazonka-sagemakerA list of tags to associate with the component. You can use Search API to search on the tags.amazonka-sagemakerThe name of the component. The name must be unique in your Amazon Web Services account and is not case-sensitive.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The name of the component as displayed. The name doesn't need to be unique. If  DisplayName isn't specified, TrialComponentName is displayed.,  - When the component ended.,  - The input artifacts for the component. Examples of input artifacts are datasets, algorithms, hyperparameters, source code, and instance types.,  - Undocumented member.,  - The output artifacts for the component. Examples of output artifacts are metrics, snapshots, logs, and images., ) - The hyperparameters for the component.,  - When the component started., / - The status of the component. States include: InProgress CompletedFailed, · - A list of tags to associate with the component. You can use Search API to search on the tags., ÷ - The name of the component. The name must be unique in your Amazon Web Services account and is not case-sensitive.amazonka-sagemakerThe name of the component as displayed. The name doesn't need to be unique. If  DisplayName isn't specified, TrialComponentName is displayed.amazonka-sagemakerWhen the component ended.amazonka-sagemakerThe input artifacts for the component. Examples of input artifacts are datasets, algorithms, hyperparameters, source code, and instance types.amazonka-sagemakerUndocumented member.amazonka-sagemakerThe output artifacts for the component. Examples of output artifacts are metrics, snapshots, logs, and images.amazonka-sagemaker&The hyperparameters for the component.amazonka-sagemakerWhen the component started.amazonka-sagemaker,The status of the component. States include: InProgress CompletedFailed·amazonka-sagemakerA list of tags to associate with the component. You can use Search API to search on the tags.÷amazonka-sagemakerThe name of the component. The name must be unique in your Amazon Web Services account and is not case-sensitive.ķamazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, ŷ9 - The Amazon Resource Name (ARN) of the trial component., Ʒ# - The response's http status code.ŷamazonka-sagemaker6The Amazon Resource Name (ARN) of the trial component.Ʒamazonka-sagemaker The response's http status code.amazonka-sagemakerķamazonka-sagemaker·÷ķŷƷ·÷ķŷƷ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';&׷amazonka-sagemakerSee:  smart constructor.ٷamazonka-sagemaker,The Amazon Resource Name (ARN) of the trial.ڷamazonka-sagemaker The response's http status code.۷amazonka-sagemakerSee:  smart constructor.ݷamazonka-sagemakerThe name of the trial as displayed. The name doesn't need to be unique. If  DisplayName isn't specified,  TrialName is displayed.߷amazonka-sagemakerA list of tags to associate with the trial. You can use Search API to search on the tags.amazonka-sagemakerThe name of the trial. The name must be unique in your Amazon Web Services account and is not case-sensitive.amazonka-sagemaker7The name of the experiment to associate the trial with.amazonka-sagemakerCreate a value of ۷" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:۷,  - The name of the trial as displayed. The name doesn't need to be unique. If  DisplayName isn't specified,  TrialName is displayed.۷,  - Undocumented member.۷,  - A list of tags to associate with the trial. You can use Search API to search on the tags.۷,  - The name of the trial. The name must be unique in your Amazon Web Services account and is not case-sensitive.۷, : - The name of the experiment to associate the trial with.amazonka-sagemakerThe name of the trial as displayed. The name doesn't need to be unique. If  DisplayName isn't specified,  TrialName is displayed.amazonka-sagemakerUndocumented member.amazonka-sagemakerA list of tags to associate with the trial. You can use Search API to search on the tags.amazonka-sagemakerThe name of the trial. The name must be unique in your Amazon Web Services account and is not case-sensitive.amazonka-sagemaker7The name of the experiment to associate the trial with.amazonka-sagemakerCreate a value of ׷" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:׷, / - The Amazon Resource Name (ARN) of the trial.ڷ, # - The response's http status code.amazonka-sagemaker,The Amazon Resource Name (ARN) of the trial.amazonka-sagemaker The response's http status code.amazonka-sagemaker۷amazonka-sagemaker۷amazonka-sagemakerڷ׷طٷڷ۷ܷ߷ݷ޷۷ܷ߷ݷ޷׷طٷڷ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';' #amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemaker4The Amazon Resource Name (ARN) of the transform job.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerSpecifies the number of records to include in a mini-batch for an HTTP inference request. A record // is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record./To enable the batch strategy, you must set the  SplitType property to Line, RecordIO, or TFRecord.To use only one record when making an HTTP invocation request to a container, set  BatchStrategy to  SingleRecord and  SplitType to Line.>To fit as many records in a mini-batch as can fit within the MaxPayloadInMB limit, set  BatchStrategy to  MultiRecord and  SplitType to Line.amazonka-sagemaker?Configuration to control how SageMaker captures inference data.amazonka-sagemakerThe data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.htmlAssociate Prediction Results with their Corresponding Input Records.amazonka-sagemakerThe environment variables to set in the Docker container. We support up to 16 key and values entries in the map.amazonka-sagemakerThe maximum number of parallel requests that can be sent to each instance in a transform job. If MaxConcurrentTransforms is set to 0 or left unset, Amazon SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm. If the execution-parameters endpoint is not enabled, the default value is 16. For more information on execution-parameters, see  https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-batch-code.html#your-algorithms-batch-code-how-containe-serves-requestsHow Containers Serve Requests?. For built-in algorithms, you don't need to set a value for MaxConcurrentTransforms.amazonka-sagemaker2The maximum allowed size of the payload, in MB. A payload is the data portion of a record (without metadata). The value in MaxPayloadInMB must be greater than, or equal to, the size of a single record. To estimate the size of a record in MB, divide the size of your dataset by the number of records. To ensure that the records fit within the maximum payload size, we recommend using a slightly larger value. The default value is 6 MB. The value of MaxPayloadInMB4 cannot be greater than 100 MB. If you specify the MaxConcurrentTransforms parameter, the value of *(MaxConcurrentTransforms * MaxPayloadInMB) also cannot exceed 100 MB.For cases where the payload might be arbitrarily large and is transmitted using HTTP chunked encoding, set the value to 0. This feature works only in supported algorithms. Currently, Amazon SageMaker built-in algorithms do not support HTTP chunked encoding.amazonka-sagemakerConfigures the timeout and maximum number of retries for processing a transform job invocation.amazonka-sagemaker(Optional) An array of key-value pairs. For more information, see  https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatUsing Cost Allocation Tags in the :Amazon Web Services Billing and Cost Management User Guide.amazonka-sagemakerThe name of the transform job. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.amazonka-sagemakerThe name of the model that you want to use for the transform job.  ModelName must be the name of an existing Amazon SageMaker model within an Amazon Web Services Region in an Amazon Web Services account.amazonka-sagemakerDescribes the input source and the way the transform job consumes it.amazonka-sagemaker+Describes the results of the transform job.amazonka-sagemakerDescribes the resources, including ML instance types and ML instance count, to use for the transform job.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - Specifies the number of records to include in a mini-batch for an HTTP inference request. A record // is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record./To enable the batch strategy, you must set the  SplitType property to Line, RecordIO, or TFRecord.To use only one record when making an HTTP invocation request to a container, set  BatchStrategy to  SingleRecord and  SplitType to Line.>To fit as many records in a mini-batch as can fit within the MaxPayloadInMB limit, set  BatchStrategy to  MultiRecord and  SplitType to Line.,  - Configuration to control how SageMaker captures inference data.,  - The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.htmlAssociate Prediction Results with their Corresponding Input Records.,  - The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.,  - Undocumented member.,  - The maximum number of parallel requests that can be sent to each instance in a transform job. If MaxConcurrentTransforms is set to 0 or left unset, Amazon SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm. If the execution-parameters endpoint is not enabled, the default value is 16. For more information on execution-parameters, see  https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-batch-code.html#your-algorithms-batch-code-how-containe-serves-requestsHow Containers Serve Requests?. For built-in algorithms, you don't need to set a value for MaxConcurrentTransforms., 5 - The maximum allowed size of the payload, in MB. A payload is the data portion of a record (without metadata). The value in MaxPayloadInMB must be greater than, or equal to, the size of a single record. To estimate the size of a record in MB, divide the size of your dataset by the number of records. To ensure that the records fit within the maximum payload size, we recommend using a slightly larger value. The default value is 6 MB. The value of MaxPayloadInMB4 cannot be greater than 100 MB. If you specify the MaxConcurrentTransforms parameter, the value of *(MaxConcurrentTransforms * MaxPayloadInMB) also cannot exceed 100 MB.For cases where the payload might be arbitrarily large and is transmitted using HTTP chunked encoding, set the value to 0. This feature works only in supported algorithms. Currently, Amazon SageMaker built-in algorithms do not support HTTP chunked encoding.,  - Configures the timeout and maximum number of retries for processing a transform job invocation.,  - (Optional) An array of key-value pairs. For more information, see  https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatUsing Cost Allocation Tags in the :Amazon Web Services Billing and Cost Management User Guide.,  - The name of the transform job. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.,  - The name of the model that you want to use for the transform job.  ModelName must be the name of an existing Amazon SageMaker model within an Amazon Web Services Region in an Amazon Web Services account.,  - Describes the input source and the way the transform job consumes it., . - Describes the results of the transform job.,  - Describes the resources, including ML instance types and ML instance count, to use for the transform job.amazonka-sagemakerSpecifies the number of records to include in a mini-batch for an HTTP inference request. A record // is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record./To enable the batch strategy, you must set the  SplitType property to Line, RecordIO, or TFRecord.To use only one record when making an HTTP invocation request to a container, set  BatchStrategy to  SingleRecord and  SplitType to Line.>To fit as many records in a mini-batch as can fit within the MaxPayloadInMB limit, set  BatchStrategy to  MultiRecord and  SplitType to Line.amazonka-sagemaker?Configuration to control how SageMaker captures inference data.amazonka-sagemakerThe data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.htmlAssociate Prediction Results with their Corresponding Input Records.amazonka-sagemakerThe environment variables to set in the Docker container. We support up to 16 key and values entries in the map.amazonka-sagemakerUndocumented member.amazonka-sagemakerThe maximum number of parallel requests that can be sent to each instance in a transform job. If MaxConcurrentTransforms is set to 0 or left unset, Amazon SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm. If the execution-parameters endpoint is not enabled, the default value is 16. For more information on execution-parameters, see  https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-batch-code.html#your-algorithms-batch-code-how-containe-serves-requestsHow Containers Serve Requests?. For built-in algorithms, you don't need to set a value for MaxConcurrentTransforms.amazonka-sagemaker2The maximum allowed size of the payload, in MB. A payload is the data portion of a record (without metadata). The value in MaxPayloadInMB must be greater than, or equal to, the size of a single record. To estimate the size of a record in MB, divide the size of your dataset by the number of records. To ensure that the records fit within the maximum payload size, we recommend using a slightly larger value. The default value is 6 MB. The value of MaxPayloadInMB4 cannot be greater than 100 MB. If you specify the MaxConcurrentTransforms parameter, the value of *(MaxConcurrentTransforms * MaxPayloadInMB) also cannot exceed 100 MB.For cases where the payload might be arbitrarily large and is transmitted using HTTP chunked encoding, set the value to 0. This feature works only in supported algorithms. Currently, Amazon SageMaker built-in algorithms do not support HTTP chunked encoding.amazonka-sagemakerConfigures the timeout and maximum number of retries for processing a transform job invocation.amazonka-sagemaker(Optional) An array of key-value pairs. For more information, see  https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatUsing Cost Allocation Tags in the :Amazon Web Services Billing and Cost Management User Guide.amazonka-sagemakerThe name of the transform job. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.amazonka-sagemakerThe name of the model that you want to use for the transform job.  ModelName must be the name of an existing Amazon SageMaker model within an Amazon Web Services Region in an Amazon Web Services account.amazonka-sagemakerDescribes the input source and the way the transform job consumes it.amazonka-sagemaker+Describes the results of the transform job.amazonka-sagemakerDescribes the resources, including ML instance types and ML instance count, to use for the transform job.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code., 7 - The Amazon Resource Name (ARN) of the transform job.amazonka-sagemaker The response's http status code.amazonka-sagemaker4The Amazon Resource Name (ARN) of the transform job.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker&&(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';'}0amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemaker3The Amazon Resource Name (ARN) of the training job.amazonka-sagemakerSee: ͸ smart constructor.amazonka-sagemakerContains information about the output location for managed spot training checkpoint data.amazonka-sagemakerConfiguration information for Amazon SageMaker Debugger rules for debugging output tensors.amazonka-sagemakerTo encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/train-encrypt.htmlProtect Communications Between ML Compute Instances in a Distributed Training Job.amazonka-sagemaker4To train models using managed spot training, choose True. Managed spot training provides a fully managed and scalable infrastructure for training machine learning models. this option is useful when training jobs can be interrupted and when there is flexibility when the training job is run.The complete and intermediate results of jobs are stored in an Amazon S3 bucket, and can be used as a starting point to train models incrementally. Amazon SageMaker provides metrics and logs in CloudWatch. They can be used to see when managed spot training jobs are running, interrupted, resumed, or completed.amazonka-sagemakerIsolates the training container. No inbound or outbound network calls can be made, except for calls between peers within a training cluster for distributed training. If you enable network isolation for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.amazonka-sagemaker9The environment variables to set in the Docker container.amazonka-sagemakerAlgorithm-specific parameters that influence the quality of the model. You set hyperparameters before you start the learning process. For a list of hyperparameters for each training algorithm provided by SageMaker, see  :https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html Algorithms.You can specify a maximum of 100 hyperparameters. Each hyperparameter is a key-value pair. Each key and value is limited to 256 characters, as specified by the Length Constraint.Do not include any security-sensitive information including account access IDs, secrets or tokens in any hyperparameter field. If the use of security-sensitive credentials are detected, SageMaker will reject your training job request and return an exception error.amazonka-sagemaker An array of Channel1 objects. Each channel is a named input source. InputDataConfig+ describes the input data and its location.Algorithms can accept input data from one or more channels. For example, an algorithm might have two channels of input data,  training_data and validation_data. The configuration for each channel provides the S3, EFS, or FSx location where the input data is stored. It also provides information about the stored data: the MIME type, compression method, and whether the data is wrapped in RecordIO format.Depending on the input mode that the algorithm supports, SageMaker either copies input data files from an S3 bucket to a local directory in the Docker container, or makes it available as input streams. For example, if you specify an EFS location, input data files are available as input streams. They do not need to be downloaded.¸amazonka-sagemakerConfiguration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.øamazonka-sagemakerThe number of times to retry the job when the job fails due to an InternalServerError.ĸamazonka-sagemakerAn array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.Ƹamazonka-sagemakerA VpcConfig object that specifies the VPC that you want your training job to connect to. Control access to and from your training container by configuring the VPC. For more information, see  >https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html>Protect Training Jobs by Using an Amazon Virtual Private Cloud.Ǹamazonka-sagemakerThe name of the training job. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.ȸamazonka-sagemakerThe registry path of the Docker image that contains the training algorithm and algorithm-specific metadata, including the input mode. For more information about algorithms provided by SageMaker, see  :https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html Algorithms=. For information about providing your own algorithms, see  https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms.html/Using Your Own Algorithms with Amazon SageMaker.ɸamazonka-sagemakerThe Amazon Resource Name (ARN) of an IAM role that SageMaker can assume to perform tasks on your behalf.During model training, SageMaker needs your permission to read input data from an S3 bucket, download a Docker image that contains training code, write model artifacts to an S3 bucket, write logs to Amazon CloudWatch Logs, and publish metrics to Amazon CloudWatch. You grant permissions for all of these tasks to an IAM role. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-roles.htmlSageMaker Roles.To be able to pass this role to SageMaker, the caller of this API must have the  iam:PassRole permission.ʸamazonka-sagemakerSpecifies the path to the S3 location where you want to store model artifacts. SageMaker creates subfolders for the artifacts.˸amazonka-sagemakerThe resources, including the ML compute instances and ML storage volumes, to use for model training.ML storage volumes store model artifacts and incremental states. Training algorithms might also use ML storage volumes for scratch space. If you want SageMaker to use the ML storage volume to store the training data, choose File as the TrainingInputMode in the algorithm specification. For distributed training algorithms, specify an instance count greater than 1.̸amazonka-sagemakerSpecifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.1To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.͸amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, θ - Contains information about the output location for managed spot training checkpoint data., ϸ - Undocumented member., и - Configuration information for Amazon SageMaker Debugger rules for debugging output tensors., Ѹ - To encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/train-encrypt.htmlProtect Communications Between ML Compute Instances in a Distributed Training Job., Ҹ7 - To train models using managed spot training, choose True. Managed spot training provides a fully managed and scalable infrastructure for training machine learning models. this option is useful when training jobs can be interrupted and when there is flexibility when the training job is run.The complete and intermediate results of jobs are stored in an Amazon S3 bucket, and can be used as a starting point to train models incrementally. Amazon SageMaker provides metrics and logs in CloudWatch. They can be used to see when managed spot training jobs are running, interrupted, resumed, or completed., Ӹ - Isolates the training container. No inbound or outbound network calls can be made, except for calls between peers within a training cluster for distributed training. If you enable network isolation for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access., Ը< - The environment variables to set in the Docker container., ո - Undocumented member., ָ - Algorithm-specific parameters that influence the quality of the model. You set hyperparameters before you start the learning process. For a list of hyperparameters for each training algorithm provided by SageMaker, see  :https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html Algorithms.You can specify a maximum of 100 hyperparameters. Each hyperparameter is a key-value pair. Each key and value is limited to 256 characters, as specified by the Length Constraint.Do not include any security-sensitive information including account access IDs, secrets or tokens in any hyperparameter field. If the use of security-sensitive credentials are detected, SageMaker will reject your training job request and return an exception error., ׸ - An array of Channel1 objects. Each channel is a named input source. InputDataConfig+ describes the input data and its location.Algorithms can accept input data from one or more channels. For example, an algorithm might have two channels of input data,  training_data and validation_data. The configuration for each channel provides the S3, EFS, or FSx location where the input data is stored. It also provides information about the stored data: the MIME type, compression method, and whether the data is wrapped in RecordIO format.Depending on the input mode that the algorithm supports, SageMaker either copies input data files from an S3 bucket to a local directory in the Docker container, or makes it available as input streams. For example, if you specify an EFS location, input data files are available as input streams. They do not need to be downloaded., ظ - Undocumented member.¸, ٸ - Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics., ڸ - The number of times to retry the job when the job fails due to an InternalServerError., ۸ - An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources., ܸ - Undocumented member., ݸ - A VpcConfig object that specifies the VPC that you want your training job to connect to. Control access to and from your training container by configuring the VPC. For more information, see  >https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html>Protect Training Jobs by Using an Amazon Virtual Private Cloud., ޸ - The name of the training job. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account., ߸ - The registry path of the Docker image that contains the training algorithm and algorithm-specific metadata, including the input mode. For more information about algorithms provided by SageMaker, see  :https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html Algorithms=. For information about providing your own algorithms, see  https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms.html/Using Your Own Algorithms with Amazon SageMaker.,  - The Amazon Resource Name (ARN) of an IAM role that SageMaker can assume to perform tasks on your behalf.During model training, SageMaker needs your permission to read input data from an S3 bucket, download a Docker image that contains training code, write model artifacts to an S3 bucket, write logs to Amazon CloudWatch Logs, and publish metrics to Amazon CloudWatch. You grant permissions for all of these tasks to an IAM role. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-roles.htmlSageMaker Roles.To be able to pass this role to SageMaker, the caller of this API must have the  iam:PassRole permission.,  - Specifies the path to the S3 location where you want to store model artifacts. SageMaker creates subfolders for the artifacts.,  - The resources, including the ML compute instances and ML storage volumes, to use for model training.ML storage volumes store model artifacts and incremental states. Training algorithms might also use ML storage volumes for scratch space. If you want SageMaker to use the ML storage volume to store the training data, choose File as the TrainingInputMode in the algorithm specification. For distributed training algorithms, specify an instance count greater than 1.,  - Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.1To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.θamazonka-sagemakerContains information about the output location for managed spot training checkpoint data.ϸamazonka-sagemakerUndocumented member.иamazonka-sagemakerConfiguration information for Amazon SageMaker Debugger rules for debugging output tensors.Ѹamazonka-sagemakerTo encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/train-encrypt.htmlProtect Communications Between ML Compute Instances in a Distributed Training Job.Ҹamazonka-sagemaker4To train models using managed spot training, choose True. Managed spot training provides a fully managed and scalable infrastructure for training machine learning models. this option is useful when training jobs can be interrupted and when there is flexibility when the training job is run.The complete and intermediate results of jobs are stored in an Amazon S3 bucket, and can be used as a starting point to train models incrementally. Amazon SageMaker provides metrics and logs in CloudWatch. They can be used to see when managed spot training jobs are running, interrupted, resumed, or completed.Ӹamazonka-sagemakerIsolates the training container. No inbound or outbound network calls can be made, except for calls between peers within a training cluster for distributed training. If you enable network isolation for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.Ըamazonka-sagemaker9The environment variables to set in the Docker container.ոamazonka-sagemakerUndocumented member.ָamazonka-sagemakerAlgorithm-specific parameters that influence the quality of the model. You set hyperparameters before you start the learning process. For a list of hyperparameters for each training algorithm provided by SageMaker, see  :https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html Algorithms.You can specify a maximum of 100 hyperparameters. Each hyperparameter is a key-value pair. Each key and value is limited to 256 characters, as specified by the Length Constraint.Do not include any security-sensitive information including account access IDs, secrets or tokens in any hyperparameter field. If the use of security-sensitive credentials are detected, SageMaker will reject your training job request and return an exception error.׸amazonka-sagemaker An array of Channel1 objects. Each channel is a named input source. InputDataConfig+ describes the input data and its location.Algorithms can accept input data from one or more channels. For example, an algorithm might have two channels of input data,  training_data and validation_data. The configuration for each channel provides the S3, EFS, or FSx location where the input data is stored. It also provides information about the stored data: the MIME type, compression method, and whether the data is wrapped in RecordIO format.Depending on the input mode that the algorithm supports, SageMaker either copies input data files from an S3 bucket to a local directory in the Docker container, or makes it available as input streams. For example, if you specify an EFS location, input data files are available as input streams. They do not need to be downloaded.ظamazonka-sagemakerUndocumented member.ٸamazonka-sagemakerConfiguration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.ڸamazonka-sagemakerThe number of times to retry the job when the job fails due to an InternalServerError.۸amazonka-sagemakerAn array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.ܸamazonka-sagemakerUndocumented member.ݸamazonka-sagemakerA VpcConfig object that specifies the VPC that you want your training job to connect to. Control access to and from your training container by configuring the VPC. For more information, see  >https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html>Protect Training Jobs by Using an Amazon Virtual Private Cloud.޸amazonka-sagemakerThe name of the training job. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.߸amazonka-sagemakerThe registry path of the Docker image that contains the training algorithm and algorithm-specific metadata, including the input mode. For more information about algorithms provided by SageMaker, see  :https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html Algorithms=. For information about providing your own algorithms, see  https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms.html/Using Your Own Algorithms with Amazon SageMaker.amazonka-sagemakerThe Amazon Resource Name (ARN) of an IAM role that SageMaker can assume to perform tasks on your behalf.During model training, SageMaker needs your permission to read input data from an S3 bucket, download a Docker image that contains training code, write model artifacts to an S3 bucket, write logs to Amazon CloudWatch Logs, and publish metrics to Amazon CloudWatch. You grant permissions for all of these tasks to an IAM role. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-roles.htmlSageMaker Roles.To be able to pass this role to SageMaker, the caller of this API must have the  iam:PassRole permission.amazonka-sagemakerSpecifies the path to the S3 location where you want to store model artifacts. SageMaker creates subfolders for the artifacts.amazonka-sagemakerThe resources, including the ML compute instances and ML storage volumes, to use for model training.ML storage volumes store model artifacts and incremental states. Training algorithms might also use ML storage volumes for scratch space. If you want SageMaker to use the ML storage volume to store the training data, choose File as the TrainingInputMode in the algorithm specification. For distributed training algorithms, specify an instance count greater than 1.amazonka-sagemakerSpecifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.1To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code., 6 - The Amazon Resource Name (ARN) of the training job.amazonka-sagemaker The response's http status code.amazonka-sagemaker3The Amazon Resource Name (ARN) of the training job.͸amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker6ĸɸƸʸ˸̸ǸȸøŸ¸͸θϸиѸҸӸԸոָ׸ظٸڸ۸ܸݸ޸߸6ĸɸƸʸ˸̸ǸȸøŸ¸͸θϸиѸҸӸԸոָ׸ظٸڸ۸ܸݸ޸߸(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';'amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker0The ARN of your created Lifecycle Configuration.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerTags to be associated with the Lifecycle Configuration. Each tag consists of a key and an optional value. Tag keys must be unique per resource. Tags are searchable using the Search API.amazonka-sagemaker9The name of the Studio Lifecycle Configuration to create.amazonka-sagemakerThe content of your Studio Lifecycle Configuration script. This content must be base64 encoded.amazonka-sagemaker=The App type that the Lifecycle Configuration is attached to.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - Tags to be associated with the Lifecycle Configuration. Each tag consists of a key and an optional value. Tag keys must be unique per resource. Tags are searchable using the Search API., < - The name of the Studio Lifecycle Configuration to create.,  - The content of your Studio Lifecycle Configuration script. This content must be base64 encoded.,  - The App type that the Lifecycle Configuration is attached to.amazonka-sagemakerTags to be associated with the Lifecycle Configuration. Each tag consists of a key and an optional value. Tag keys must be unique per resource. Tags are searchable using the Search API.amazonka-sagemaker9The name of the Studio Lifecycle Configuration to create.amazonka-sagemakerThe content of your Studio Lifecycle Configuration script. This content must be base64 encoded.amazonka-sagemaker=The App type that the Lifecycle Configuration is attached to.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 3 - The ARN of your created Lifecycle Configuration., # - The response's http status code.amazonka-sagemaker0The ARN of your created Lifecycle Configuration.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';'amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker'The space's Amazon Resource Name (ARN).amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerA collection of space settings.amazonka-sagemakerTags to associated with the space. Each tag consists of a key and an optional value. Tag keys must be unique for each resource. Tags are searchable using the Search API.amazonka-sagemaker The ID of the associated Domain.amazonka-sagemakerThe name of the space.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, " - A collection of space settings.,  - Tags to associated with the space. Each tag consists of a key and an optional value. Tag keys must be unique for each resource. Tags are searchable using the Search API., # - The ID of the associated Domain.,  - The name of the space.amazonka-sagemakerA collection of space settings.amazonka-sagemakerTags to associated with the space. Each tag consists of a key and an optional value. Tag keys must be unique for each resource. Tags are searchable using the Search API.amazonka-sagemaker The ID of the associated Domain.amazonka-sagemakerThe name of the space.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, * - The space's Amazon Resource Name (ARN)., # - The response's http status code.amazonka-sagemaker'The space's Amazon Resource Name (ARN).amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';'amazonka-sagemakerSee: ˹ smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemaker.The Amazon Resource Name (ARN) of the project.amazonka-sagemakerThe ID of the new project.amazonka-sagemakerSee: ƹ smart constructor.¹amazonka-sagemakerA description for the project.ùamazonka-sagemakerAn array of key-value pairs that you want to use to organize and track your Amazon Web Services resource costs. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services resources in the +Amazon Web Services General Reference Guide.Ĺamazonka-sagemakerThe name of the project.Źamazonka-sagemakerThe product ID and provisioning artifact ID to provision a service catalog. The provisioning artifact ID will default to the latest provisioning artifact ID of the product, if you don't provide the provisioning artifact ID. For more information, see  https://docs.aws.amazon.com/servicecatalog/latest/adminguide/introduction.html+What is Amazon Web Services Service Catalog.ƹamazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, ǹ! - A description for the project., ȹ - An array of key-value pairs that you want to use to organize and track your Amazon Web Services resource costs. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services resources in the +Amazon Web Services General Reference Guide., ɹ - The name of the project., ʹ - The product ID and provisioning artifact ID to provision a service catalog. The provisioning artifact ID will default to the latest provisioning artifact ID of the product, if you don't provide the provisioning artifact ID. For more information, see  https://docs.aws.amazon.com/servicecatalog/latest/adminguide/introduction.html+What is Amazon Web Services Service Catalog.ǹamazonka-sagemakerA description for the project.ȹamazonka-sagemakerAn array of key-value pairs that you want to use to organize and track your Amazon Web Services resource costs. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services resources in the +Amazon Web Services General Reference Guide.ɹamazonka-sagemakerThe name of the project.ʹamazonka-sagemakerThe product ID and provisioning artifact ID to provision a service catalog. The provisioning artifact ID will default to the latest provisioning artifact ID of the product, if you don't provide the provisioning artifact ID. For more information, see  https://docs.aws.amazon.com/servicecatalog/latest/adminguide/introduction.html+What is Amazon Web Services Service Catalog.˹amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, ̹# - The response's http status code., ͹1 - The Amazon Resource Name (ARN) of the project., ι - The ID of the new project.̹amazonka-sagemaker The response's http status code.͹amazonka-sagemaker.The Amazon Resource Name (ARN) of the project.ιamazonka-sagemakerThe ID of the new project.ƹamazonka-sagemakeramazonka-sagemaker˹amazonka-sagemakeramazonka-sagemakeramazonka-sagemakerù¹ĹŹƹǹȹɹʹ˹̹͹ιù¹ĹŹƹǹȹɹʹ˹̹͹ι(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';'-߹amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemaker5The Amazon Resource Name (ARN) of the processing job.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe environment variables to set in the Docker container. Up to 100 key and values entries in the map are supported.amazonka-sagemakerNetworking options for a processing job, such as whether to allow inbound and outbound network calls to and from processing containers, and the VPC subnets and security groups to use for VPC-enabled processing jobs.amazonka-sagemakerAn array of inputs configuring the data to download into the processing container.amazonka-sagemaker,Output configuration for the processing job.amazonka-sagemakerThe time limit for how long the processing job is allowed to run.amazonka-sagemaker(Optional) An array of key-value pairs. For more information, see  https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURLUsing Cost Allocation Tags in the :Amazon Web Services Billing and Cost Management User Guide.amazonka-sagemakerThe name of the processing job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.amazonka-sagemakerIdentifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.amazonka-sagemakerConfigures the processing job to run a specified Docker container image.amazonka-sagemakerThe Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The environment variables to set in the Docker container. Up to 100 key and values entries in the map are supported.,  - Undocumented member.,  - Networking options for a processing job, such as whether to allow inbound and outbound network calls to and from processing containers, and the VPC subnets and security groups to use for VPC-enabled processing jobs.,  - An array of inputs configuring the data to download into the processing container., / - Output configuration for the processing job.,  - The time limit for how long the processing job is allowed to run.,  - (Optional) An array of key-value pairs. For more information, see  https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURLUsing Cost Allocation Tags in the :Amazon Web Services Billing and Cost Management User Guide.,  - The name of the processing job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.,  - Identifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.,  - Configures the processing job to run a specified Docker container image.,  - The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.amazonka-sagemakerThe environment variables to set in the Docker container. Up to 100 key and values entries in the map are supported.amazonka-sagemakerUndocumented member.amazonka-sagemakerNetworking options for a processing job, such as whether to allow inbound and outbound network calls to and from processing containers, and the VPC subnets and security groups to use for VPC-enabled processing jobs.amazonka-sagemakerAn array of inputs configuring the data to download into the processing container.amazonka-sagemaker,Output configuration for the processing job.amazonka-sagemakerThe time limit for how long the processing job is allowed to run.amazonka-sagemaker(Optional) An array of key-value pairs. For more information, see  https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURLUsing Cost Allocation Tags in the :Amazon Web Services Billing and Cost Management User Guide.amazonka-sagemakerThe name of the processing job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.amazonka-sagemakerIdentifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.amazonka-sagemakerConfigures the processing job to run a specified Docker container image.amazonka-sagemakerThe Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.amazonka-sagemakerCreate a value of ߹" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code.߹, 8 - The Amazon Resource Name (ARN) of the processing job.amazonka-sagemaker The response's http status code.amazonka-sagemaker5The Amazon Resource Name (ARN) of the processing job.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker߹ ߹ ߹(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';'ȉ amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker+A JSON object that contains the URL string.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe duration of the session, in seconds. The default is 12 hours.amazonka-sagemaker"The name of the notebook instance.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The duration of the session, in seconds. The default is 12 hours., % - The name of the notebook instance.amazonka-sagemakerThe duration of the session, in seconds. The default is 12 hours.amazonka-sagemaker"The name of the notebook instance.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, . - A JSON object that contains the URL string., # - The response's http status code.amazonka-sagemaker+A JSON object that contains the URL string.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';'amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe presigned URL.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe number of seconds until the pre-signed URL expires. This value defaults to 300.amazonka-sagemakerThe session expiration duration in seconds. This value defaults to 43200.amazonka-sagemakerThe name of the space.amazonka-sagemakerThe domain ID.amazonka-sagemaker*The name of the UserProfile to sign-in as.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The number of seconds until the pre-signed URL expires. This value defaults to 300.,  - The session expiration duration in seconds. This value defaults to 43200.,  - The name of the space.,  - The domain ID., - - The name of the UserProfile to sign-in as.amazonka-sagemakerThe number of seconds until the pre-signed URL expires. This value defaults to 300.amazonka-sagemakerThe session expiration duration in seconds. This value defaults to 43200.amazonka-sagemakerThe name of the space.amazonka-sagemakerThe domain ID.amazonka-sagemaker*The name of the UserProfile to sign-in as.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The presigned URL., # - The response's http status code.amazonka-sagemakerThe presigned URL.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';'Ѻamazonka-sagemakerSee:  smart constructor.Ӻamazonka-sagemaker7The Amazon Resource Name (ARN) of the created pipeline.Ժamazonka-sagemaker The response's http status code.պamazonka-sagemakerSee:  smart constructor.׺amazonka-sagemakerThis is the configuration that controls the parallelism of the pipeline. If specified, it applies to all runs of this pipeline by default.غamazonka-sagemaker-The JSON pipeline definition of the pipeline.ٺamazonka-sagemakerThe location of the pipeline definition stored in Amazon S3. If specified, SageMaker will retrieve the pipeline definition from this location.ںamazonka-sagemakerA description of the pipeline.ۺamazonka-sagemaker!The display name of the pipeline.ܺamazonka-sagemaker0A list of tags to apply to the created pipeline.ݺamazonka-sagemakerThe name of the pipeline.޺amazonka-sagemakerA unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.ߺamazonka-sagemakerThe Amazon Resource Name (ARN) of the role used by the pipeline to access and create resources.amazonka-sagemakerCreate a value of պ" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:պ,  - This is the configuration that controls the parallelism of the pipeline. If specified, it applies to all runs of this pipeline by default.غ, 0 - The JSON pipeline definition of the pipeline.ٺ,  - The location of the pipeline definition stored in Amazon S3. If specified, SageMaker will retrieve the pipeline definition from this location.պ, ! - A description of the pipeline.պ, $ - The display name of the pipeline.պ, 3 - A list of tags to apply to the created pipeline.պ,  - The name of the pipeline.޺,  - A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.պ,  - The Amazon Resource Name (ARN) of the role used by the pipeline to access and create resources.amazonka-sagemakerThis is the configuration that controls the parallelism of the pipeline. If specified, it applies to all runs of this pipeline by default.amazonka-sagemaker-The JSON pipeline definition of the pipeline.amazonka-sagemakerThe location of the pipeline definition stored in Amazon S3. If specified, SageMaker will retrieve the pipeline definition from this location.amazonka-sagemakerA description of the pipeline.amazonka-sagemaker!The display name of the pipeline.amazonka-sagemaker0A list of tags to apply to the created pipeline.amazonka-sagemakerThe name of the pipeline.amazonka-sagemakerA unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.amazonka-sagemakerThe Amazon Resource Name (ARN) of the role used by the pipeline to access and create resources.amazonka-sagemakerCreate a value of Ѻ" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:Ѻ, : - The Amazon Resource Name (ARN) of the created pipeline.Ժ, # - The response's http status code.amazonka-sagemaker7The Amazon Resource Name (ARN) of the created pipeline.amazonka-sagemaker The response's http status code.amazonka-sagemakerպamazonka-sagemaker޺amazonka-sagemakerպamazonka-sagemakerԺѺҺӺԺպֺܺߺںۺݺ׺޺غٺպֺܺߺںۺݺ׺޺غٺѺҺӺԺ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';')amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker>The Amazon Resource Name (ARN) of the lifecycle configuration.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerA shell script that runs only once, when you create a notebook instance. The shell script must be a base64-encoded string.amazonka-sagemakerA shell script that runs every time you start a notebook instance, including when you create the notebook instance. The shell script must be a base64-encoded string.amazonka-sagemaker(The name of the lifecycle configuration.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - A shell script that runs only once, when you create a notebook instance. The shell script must be a base64-encoded string.,  - A shell script that runs every time you start a notebook instance, including when you create the notebook instance. The shell script must be a base64-encoded string., + - The name of the lifecycle configuration.amazonka-sagemakerA shell script that runs only once, when you create a notebook instance. The shell script must be a base64-encoded string.amazonka-sagemakerA shell script that runs every time you start a notebook instance, including when you create the notebook instance. The shell script must be a base64-encoded string.amazonka-sagemaker(The name of the lifecycle configuration.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The Amazon Resource Name (ARN) of the lifecycle configuration., # - The response's http status code.amazonka-sagemaker>The Amazon Resource Name (ARN) of the lifecycle configuration.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';(2(amazonka-sagemakerSee: Ļ smart constructor.amazonka-sagemaker8The Amazon Resource Name (ARN) of the notebook instance.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerA list of Elastic Inference (EI) instance types to associate with this notebook instance. Currently, only one instance type can be associated with a notebook instance. For more information, see  7https://docs.aws.amazon.com/sagemaker/latest/dg/ei.html+Using Elastic Inference in Amazon SageMaker.amazonka-sagemakerAn array of up to three Git repositories to associate with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in  https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.htmlAmazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html>Associating Git Repositories with SageMaker Notebook Instances.amazonka-sagemakerA Git repository to associate with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in  https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.htmlAmazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html>Associating Git Repositories with SageMaker Notebook Instances.amazonka-sagemakerSets whether SageMaker provides internet access to the notebook instance. If you set this to Disabled this notebook instance is able to access resources only in your VPC, and is not be able to connect to SageMaker training and endpoint services unless you configure a NAT Gateway in your VPC.For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/appendix-additional-considerations.html#appendix-notebook-and-internet-access2Notebook Instances Are Internet-Enabled by Default.. You can set the value of this parameter to Disabled" only if you set a value for the SubnetId parameter.amazonka-sagemaker>Information on the IMDS configuration of the notebook instanceamazonka-sagemakerThe Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker uses to encrypt data on the storage volume attached to your notebook instance. The KMS key you provide must be enabled. For information, see  https://docs.aws.amazon.com/kms/latest/developerguide/enabling-keys.htmlEnabling and Disabling Keys in the :Amazon Web Services Key Management Service Developer Guide.amazonka-sagemakerThe name of a lifecycle configuration to associate with the notebook instance. For information about lifestyle configurations, see  https://docs.aws.amazon.com/sagemaker/latest/dg/notebook-lifecycle-config.html2Step 2.1: (Optional) Customize a Notebook Instance.amazonka-sagemakerThe platform identifier of the notebook instance runtime environment.amazonka-sagemakerWhether root access is enabled or disabled for users of the notebook instance. The default value is Enabled.Lifecycle configurations need root access to be able to set up a notebook instance. Because of this, lifecycle configurations associated with a notebook instance always run with root access even if you disable root access for users.amazonka-sagemakerThe VPC security group IDs, in the form sg-xxxxxxxx. The security groups must be for the same VPC as specified in the subnet.amazonka-sagemakerThe ID of the subnet in a VPC to which you would like to have a connectivity from your ML compute instance.amazonka-sagemakerAn array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.amazonka-sagemakerThe size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB.amazonka-sagemaker&The name of the new notebook instance.amazonka-sagemakerThe type of ML compute instance to launch for the notebook instance.amazonka-sagemakerWhen you send any requests to Amazon Web Services resources from the notebook instance, SageMaker assumes this role to perform tasks on your behalf. You must grant this role necessary permissions so SageMaker can perform these tasks. The policy must allow the SageMaker service principal (sagemaker.amazonaws.com) permissions to assume this role. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-roles.htmlSageMaker Roles.To be able to pass this role to SageMaker, the caller of this API must have the  iam:PassRole permission.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - A list of Elastic Inference (EI) instance types to associate with this notebook instance. Currently, only one instance type can be associated with a notebook instance. For more information, see  7https://docs.aws.amazon.com/sagemaker/latest/dg/ei.html+Using Elastic Inference in Amazon SageMaker.,  - An array of up to three Git repositories to associate with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in  https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.htmlAmazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html>Associating Git Repositories with SageMaker Notebook Instances.,  - A Git repository to associate with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in  https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.htmlAmazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html>Associating Git Repositories with SageMaker Notebook Instances.,  - Sets whether SageMaker provides internet access to the notebook instance. If you set this to Disabled this notebook instance is able to access resources only in your VPC, and is not be able to connect to SageMaker training and endpoint services unless you configure a NAT Gateway in your VPC.For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/appendix-additional-considerations.html#appendix-notebook-and-internet-access2Notebook Instances Are Internet-Enabled by Default.. You can set the value of this parameter to Disabled" only if you set a value for the SubnetId parameter.,  - Information on the IMDS configuration of the notebook instance,  - The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker uses to encrypt data on the storage volume attached to your notebook instance. The KMS key you provide must be enabled. For information, see  https://docs.aws.amazon.com/kms/latest/developerguide/enabling-keys.htmlEnabling and Disabling Keys in the :Amazon Web Services Key Management Service Developer Guide.,  - The name of a lifecycle configuration to associate with the notebook instance. For information about lifestyle configurations, see  https://docs.aws.amazon.com/sagemaker/latest/dg/notebook-lifecycle-config.html2Step 2.1: (Optional) Customize a Notebook Instance.,  - The platform identifier of the notebook instance runtime environment.,  - Whether root access is enabled or disabled for users of the notebook instance. The default value is Enabled.Lifecycle configurations need root access to be able to set up a notebook instance. Because of this, lifecycle configurations associated with a notebook instance always run with root access even if you disable root access for users.,  - The VPC security group IDs, in the form sg-xxxxxxxx. The security groups must be for the same VPC as specified in the subnet.,  - The ID of the subnet in a VPC to which you would like to have a connectivity from your ML compute instance.,  - An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.,  - The size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB., ) - The name of the new notebook instance., » - The type of ML compute instance to launch for the notebook instance., û - When you send any requests to Amazon Web Services resources from the notebook instance, SageMaker assumes this role to perform tasks on your behalf. You must grant this role necessary permissions so SageMaker can perform these tasks. The policy must allow the SageMaker service principal (sagemaker.amazonaws.com) permissions to assume this role. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-roles.htmlSageMaker Roles.To be able to pass this role to SageMaker, the caller of this API must have the  iam:PassRole permission.amazonka-sagemakerA list of Elastic Inference (EI) instance types to associate with this notebook instance. Currently, only one instance type can be associated with a notebook instance. For more information, see  7https://docs.aws.amazon.com/sagemaker/latest/dg/ei.html+Using Elastic Inference in Amazon SageMaker.amazonka-sagemakerAn array of up to three Git repositories to associate with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in  https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.htmlAmazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html>Associating Git Repositories with SageMaker Notebook Instances.amazonka-sagemakerA Git repository to associate with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in  https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.htmlAmazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html>Associating Git Repositories with SageMaker Notebook Instances.amazonka-sagemakerSets whether SageMaker provides internet access to the notebook instance. If you set this to Disabled this notebook instance is able to access resources only in your VPC, and is not be able to connect to SageMaker training and endpoint services unless you configure a NAT Gateway in your VPC.For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/appendix-additional-considerations.html#appendix-notebook-and-internet-access2Notebook Instances Are Internet-Enabled by Default.. You can set the value of this parameter to Disabled" only if you set a value for the SubnetId parameter.amazonka-sagemaker>Information on the IMDS configuration of the notebook instanceamazonka-sagemakerThe Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker uses to encrypt data on the storage volume attached to your notebook instance. The KMS key you provide must be enabled. For information, see  https://docs.aws.amazon.com/kms/latest/developerguide/enabling-keys.htmlEnabling and Disabling Keys in the :Amazon Web Services Key Management Service Developer Guide.amazonka-sagemakerThe name of a lifecycle configuration to associate with the notebook instance. For information about lifestyle configurations, see  https://docs.aws.amazon.com/sagemaker/latest/dg/notebook-lifecycle-config.html2Step 2.1: (Optional) Customize a Notebook Instance.amazonka-sagemakerThe platform identifier of the notebook instance runtime environment.amazonka-sagemakerWhether root access is enabled or disabled for users of the notebook instance. The default value is Enabled.Lifecycle configurations need root access to be able to set up a notebook instance. Because of this, lifecycle configurations associated with a notebook instance always run with root access even if you disable root access for users.amazonka-sagemakerThe VPC security group IDs, in the form sg-xxxxxxxx. The security groups must be for the same VPC as specified in the subnet.amazonka-sagemakerThe ID of the subnet in a VPC to which you would like to have a connectivity from your ML compute instance.amazonka-sagemakerAn array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.amazonka-sagemakerThe size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB.amazonka-sagemaker&The name of the new notebook instance.»amazonka-sagemakerThe type of ML compute instance to launch for the notebook instance.ûamazonka-sagemakerWhen you send any requests to Amazon Web Services resources from the notebook instance, SageMaker assumes this role to perform tasks on your behalf. You must grant this role necessary permissions so SageMaker can perform these tasks. The policy must allow the SageMaker service principal (sagemaker.amazonaws.com) permissions to assume this role. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-roles.htmlSageMaker Roles.To be able to pass this role to SageMaker, the caller of this API must have the  iam:PassRole permission.Ļamazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, Ż; - The Amazon Resource Name (ARN) of the notebook instance., ƻ# - The response's http status code.Żamazonka-sagemaker8The Amazon Resource Name (ARN) of the notebook instance.ƻamazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakerĻamazonka-sagemaker*»ûĻŻƻ*»ûĻŻƻ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';(A׻amazonka-sagemakerSee:  smart constructor.ٻamazonka-sagemaker The response's http status code.ڻamazonka-sagemaker:The Amazon Resource Name (ARN) of the monitoring schedule.ۻamazonka-sagemakerSee:  smart constructor.ݻamazonka-sagemaker(Optional) An array of key-value pairs. For more information, see  %20https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURLUsing Cost Allocation Tags in the :Amazon Web Services Billing and Cost Management User Guide.޻amazonka-sagemakerThe name of the monitoring schedule. The name must be unique within an Amazon Web Services Region within an Amazon Web Services account.߻amazonka-sagemakerThe configuration object that specifies the monitoring schedule and defines the monitoring job.amazonka-sagemakerCreate a value of ۻ" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:ۻ,  - (Optional) An array of key-value pairs. For more information, see  %20https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURLUsing Cost Allocation Tags in the :Amazon Web Services Billing and Cost Management User Guide.ۻ,  - The name of the monitoring schedule. The name must be unique within an Amazon Web Services Region within an Amazon Web Services account.ۻ,  - The configuration object that specifies the monitoring schedule and defines the monitoring job.amazonka-sagemaker(Optional) An array of key-value pairs. For more information, see  %20https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURLUsing Cost Allocation Tags in the :Amazon Web Services Billing and Cost Management User Guide.amazonka-sagemakerThe name of the monitoring schedule. The name must be unique within an Amazon Web Services Region within an Amazon Web Services account.amazonka-sagemakerThe configuration object that specifies the monitoring schedule and defines the monitoring job.amazonka-sagemakerCreate a value of ׻" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:ٻ, # - The response's http status code.׻, = - The Amazon Resource Name (ARN) of the monitoring schedule.amazonka-sagemaker The response's http status code.amazonka-sagemaker:The Amazon Resource Name (ARN) of the monitoring schedule.amazonka-sagemakerۻamazonka-sagemakerۻamazonka-sagemakerٻamazonka-sagemaker׻׻ػڻٻۻܻݻ޻߻ۻܻݻ޻߻׻ػڻٻ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';(SJamazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemakerThe Amazon Resource Name (ARN) of the model quality monitoring job.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker?Specifies the constraints and baselines for the monitoring job.amazonka-sagemaker;Specifies the network configuration for the monitoring job.amazonka-sagemaker(Optional) An array of key-value pairs. For more information, see  https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURLUsing Cost Allocation Tags in the :Amazon Web Services Billing and Cost Management User Guide.amazonka-sagemaker*The name of the monitoring job definition.amazonka-sagemaker+The container that runs the monitoring job.amazonka-sagemakerA list of the inputs that are monitored. Currently endpoints are supported.amazonka-sagemakerThe Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - Specifies the constraints and baselines for the monitoring job., > - Specifies the network configuration for the monitoring job.,  - Undocumented member.,  - (Optional) An array of key-value pairs. For more information, see  https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURLUsing Cost Allocation Tags in the :Amazon Web Services Billing and Cost Management User Guide., - - The name of the monitoring job definition., . - The container that runs the monitoring job.,  - A list of the inputs that are monitored. Currently endpoints are supported.,  - Undocumented member.,  - Undocumented member.,  - The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.amazonka-sagemaker?Specifies the constraints and baselines for the monitoring job.amazonka-sagemaker;Specifies the network configuration for the monitoring job.amazonka-sagemakerUndocumented member.amazonka-sagemaker(Optional) An array of key-value pairs. For more information, see  https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURLUsing Cost Allocation Tags in the :Amazon Web Services Billing and Cost Management User Guide.amazonka-sagemaker*The name of the monitoring job definition.amazonka-sagemaker+The container that runs the monitoring job.amazonka-sagemakerA list of the inputs that are monitored. Currently endpoints are supported.amazonka-sagemakerUndocumented member.amazonka-sagemakerUndocumented member.amazonka-sagemakerThe Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code.,  - The Amazon Resource Name (ARN) of the model quality monitoring job.amazonka-sagemaker The response's http status code.amazonka-sagemakerThe Amazon Resource Name (ARN) of the model quality monitoring job.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';(^amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemaker2The Amazon Resource Name (ARN) of the model group.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker"A description for the model group.amazonka-sagemakerA list of key value pairs associated with the model group. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services resources in the +Amazon Web Services General Reference Guide.amazonka-sagemakerThe name of the model group.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, % - A description for the model group.,  - A list of key value pairs associated with the model group. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services resources in the +Amazon Web Services General Reference Guide.,  - The name of the model group.amazonka-sagemaker"A description for the model group.amazonka-sagemakerA list of key value pairs associated with the model group. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services resources in the +Amazon Web Services General Reference Guide.amazonka-sagemakerThe name of the model group.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code., 5 - The Amazon Resource Name (ARN) of the model group.amazonka-sagemaker The response's http status code.amazonka-sagemaker2The Amazon Resource Name (ARN) of the model group.amazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';(+żamazonka-sagemakerSee:  smart constructor.Ǽamazonka-sagemaker The response's http status code.ȼamazonka-sagemaker8The Amazon Resource Name (ARN) of the new model package.ɼamazonka-sagemakerSee: ݼ smart constructor.˼amazonka-sagemakerAn array of additional Inference Specification objects. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.̼amazonka-sagemakerWhether to certify the model package for listing on Amazon Web Services Marketplace.This parameter is optional for unversioned models, and does not apply to versioned models.ͼamazonka-sagemakerA unique token that guarantees that the call to this API is idempotent.μamazonka-sagemakerThe metadata properties associated with the model package versions.ϼamazonka-sagemakerThe machine learning domain of your model package and its components. Common machine learning domains include computer vision and natural language processing.мamazonka-sagemakerRepresents the drift check baselines that can be used when the model monitor is set using the model package. For more information, see the topic on  https://docs.aws.amazon.com/sagemaker/latest/dg/pipelines-quality-clarify-baseline-lifecycle.html#pipelines-quality-clarify-baseline-drift-detectionDrift Detection against Previous Baselines in SageMaker Pipelines in the  Amazon SageMaker Developer Guide.Ѽamazonka-sagemakerSpecifies details about inference jobs that can be run with models based on this model package, including the following:The Amazon ECR paths of containers that contain the inference code and model artifacts.The instance types that the model package supports for transform jobs and real-time endpoints used for inference.The input and output content formats that the model package supports for inference.Ӽamazonka-sagemaker-Whether the model is approved for deployment.This parameter is optional for versioned models, and does not apply to unversioned models.For versioned models, the value of this parameter must be set to Approved to deploy the model.Լamazonka-sagemaker0A structure that contains model metrics reports.ռamazonka-sagemaker#A description of the model package.ּamazonka-sagemakerThe name or Amazon Resource Name (ARN) of the model package group that this model version belongs to.This parameter is required for versioned models, and does not apply to unversioned models.׼amazonka-sagemakerThe name of the model package. The name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).This parameter is required for unversioned models. It is not applicable to versioned models.ؼamazonka-sagemakerThe Amazon Simple Storage Service (Amazon S3) path where the sample payload are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).ټamazonka-sagemakerDetails about the algorithm that was used to create the model package.ڼamazonka-sagemakerA list of key value pairs associated with the model. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services resources in the +Amazon Web Services General Reference Guide.ۼamazonka-sagemakerThe machine learning task your model package accomplishes. Common machine learning tasks include object detection and image classification. The following tasks are supported by Inference Recommender: "IMAGE_CLASSIFICATION" | "OBJECT_DETECTION" | "TEXT_GENERATION" |"IMAGE_SEGMENTATION" |  "FILL_MASK" | "CLASSIFICATION" |  "REGRESSION" | "OTHER".>Specify "OTHER" if none of the tasks listed fit your use case.ܼamazonka-sagemakerSpecifies configurations for one or more transform jobs that SageMaker runs to test the model package.ݼamazonka-sagemakerCreate a value of ɼ" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:ɼ, ޼ - An array of additional Inference Specification objects. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.ɼ, ߼ - Whether to certify the model package for listing on Amazon Web Services Marketplace.This parameter is optional for unversioned models, and does not apply to versioned models.ͼ,  - A unique token that guarantees that the call to this API is idempotent.ɼ,  - The metadata properties associated with the model package versions.ɼ,  - The machine learning domain of your model package and its components. Common machine learning domains include computer vision and natural language processing.ɼ,  - Represents the drift check baselines that can be used when the model monitor is set using the model package. For more information, see the topic on  https://docs.aws.amazon.com/sagemaker/latest/dg/pipelines-quality-clarify-baseline-lifecycle.html#pipelines-quality-clarify-baseline-drift-detectionDrift Detection against Previous Baselines in SageMaker Pipelines in the  Amazon SageMaker Developer Guide.ɼ,  - Specifies details about inference jobs that can be run with models based on this model package, including the following:The Amazon ECR paths of containers that contain the inference code and model artifacts.The instance types that the model package supports for transform jobs and real-time endpoints used for inference.The input and output content formats that the model package supports for inference.ɼ,  - Undocumented member.ɼ, 0 - Whether the model is approved for deployment.This parameter is optional for versioned models, and does not apply to unversioned models.For versioned models, the value of this parameter must be set to Approved to deploy the model.ɼ, 3 - A structure that contains model metrics reports.ɼ, & - A description of the model package.ɼ,  - The name or Amazon Resource Name (ARN) of the model package group that this model version belongs to.This parameter is required for versioned models, and does not apply to unversioned models.ɼ,  - The name of the model package. The name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).This parameter is required for unversioned models. It is not applicable to versioned models.ɼ,  - The Amazon Simple Storage Service (Amazon S3) path where the sample payload are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).ɼ,  - Details about the algorithm that was used to create the model package.ɼ,  - A list of key value pairs associated with the model. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services resources in the +Amazon Web Services General Reference Guide.ɼ,  - The machine learning task your model package accomplishes. Common machine learning tasks include object detection and image classification. The following tasks are supported by Inference Recommender: "IMAGE_CLASSIFICATION" | "OBJECT_DETECTION" | "TEXT_GENERATION" |"IMAGE_SEGMENTATION" |  "FILL_MASK" | "CLASSIFICATION" |  "REGRESSION" | "OTHER".>Specify "OTHER" if none of the tasks listed fit your use case.ɼ,  - Specifies configurations for one or more transform jobs that SageMaker runs to test the model package.޼amazonka-sagemakerAn array of additional Inference Specification objects. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.߼amazonka-sagemakerWhether to certify the model package for listing on Amazon Web Services Marketplace.This parameter is optional for unversioned models, and does not apply to versioned models.amazonka-sagemakerA unique token that guarantees that the call to this API is idempotent.amazonka-sagemakerThe metadata properties associated with the model package versions.amazonka-sagemakerThe machine learning domain of your model package and its components. Common machine learning domains include computer vision and natural language processing.amazonka-sagemakerRepresents the drift check baselines that can be used when the model monitor is set using the model package. For more information, see the topic on  https://docs.aws.amazon.com/sagemaker/latest/dg/pipelines-quality-clarify-baseline-lifecycle.html#pipelines-quality-clarify-baseline-drift-detectionDrift Detection against Previous Baselines in SageMaker Pipelines in the  Amazon SageMaker Developer Guide.amazonka-sagemakerSpecifies details about inference jobs that can be run with models based on this model package, including the following:The Amazon ECR paths of containers that contain the inference code and model artifacts.The instance types that the model package supports for transform jobs and real-time endpoints used for inference.The input and output content formats that the model package supports for inference.amazonka-sagemakerUndocumented member.amazonka-sagemaker-Whether the model is approved for deployment.This parameter is optional for versioned models, and does not apply to unversioned models.For versioned models, the value of this parameter must be set to Approved to deploy the model.amazonka-sagemaker0A structure that contains model metrics reports.amazonka-sagemaker#A description of the model package.amazonka-sagemakerThe name or Amazon Resource Name (ARN) of the model package group that this model version belongs to.This parameter is required for versioned models, and does not apply to unversioned models.amazonka-sagemakerThe name of the model package. The name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).This parameter is required for unversioned models. It is not applicable to versioned models.amazonka-sagemakerThe Amazon Simple Storage Service (Amazon S3) path where the sample payload are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).amazonka-sagemakerDetails about the algorithm that was used to create the model package.amazonka-sagemakerA list of key value pairs associated with the model. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services resources in the +Amazon Web Services General Reference Guide.amazonka-sagemakerThe machine learning task your model package accomplishes. Common machine learning tasks include object detection and image classification. The following tasks are supported by Inference Recommender: "IMAGE_CLASSIFICATION" | "OBJECT_DETECTION" | "TEXT_GENERATION" |"IMAGE_SEGMENTATION" |  "FILL_MASK" | "CLASSIFICATION" |  "REGRESSION" | "OTHER".>Specify "OTHER" if none of the tasks listed fit your use case.amazonka-sagemakerSpecifies configurations for one or more transform jobs that SageMaker runs to test the model package.amazonka-sagemakerCreate a value of ż" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:Ǽ, # - The response's http status code.ż, ; - The Amazon Resource Name (ARN) of the new model package.amazonka-sagemaker The response's http status code.amazonka-sagemaker8The Amazon Resource Name (ARN) of the new model package.amazonka-sagemakerǼamazonka-sagemakerż.żƼȼǼɼʼڼּϼۼӼռ׼ؼѼҼ˼̼μмԼټܼͼݼ޼߼.ɼʼڼּϼۼӼռ׼ؼѼҼ˼̼μмԼټܼͼݼ޼߼żƼȼǼ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';(amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemaker?The Amazon Resource Name (ARN) of the model explainability job.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker:The baseline configuration for a model explainability job.amazonka-sagemaker2Networking options for a model explainability job.amazonka-sagemaker(Optional) An array of key-value pairs. For more information, see  https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURLUsing Cost Allocation Tags in the :Amazon Web Services Billing and Cost Management User Guide.amazonka-sagemakerThe name of the model explainability job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.amazonka-sagemakerConfigures the model explainability job to run a specified Docker container image.amazonka-sagemaker(Inputs for the model explainability job.amazonka-sagemakerThe Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, = - The baseline configuration for a model explainability job., 5 - Networking options for a model explainability job.,  - Undocumented member.,  - (Optional) An array of key-value pairs. For more information, see  https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURLUsing Cost Allocation Tags in the :Amazon Web Services Billing and Cost Management User Guide.,  - The name of the model explainability job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.,  - Configures the model explainability job to run a specified Docker container image., + - Inputs for the model explainability job.,  - Undocumented member.,  - Undocumented member.,  - The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.amazonka-sagemaker:The baseline configuration for a model explainability job.amazonka-sagemaker2Networking options for a model explainability job.amazonka-sagemakerUndocumented member.amazonka-sagemaker(Optional) An array of key-value pairs. For more information, see  https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURLUsing Cost Allocation Tags in the :Amazon Web Services Billing and Cost Management User Guide.amazonka-sagemakerThe name of the model explainability job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.amazonka-sagemakerConfigures the model explainability job to run a specified Docker container image.amazonka-sagemaker(Inputs for the model explainability job.amazonka-sagemakerUndocumented member.amazonka-sagemakerUndocumented member.amazonka-sagemakerThe Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code.,  - The Amazon Resource Name (ARN) of the model explainability job.amazonka-sagemaker The response's http status code.amazonka-sagemaker?The Amazon Resource Name (ARN) of the model explainability job.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';(Kamazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemakerhttps://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.amazonka-sagemakerA VpcConfig object that specifies the VPC that you want your model to connect to. Control access to and from your model container by configuring the VPC.  VpcConfig is used in hosting services and in batch transform. For more information, see  =https://docs.aws.amazon.com/sagemaker/latest/dg/host-vpc.html:Protect Endpoints by Using an Amazon Virtual Private Cloud and  >https://docs.aws.amazon.com/sagemaker/latest/dg/batch-vpc.htmlProtect Data in Batch Transform Jobs by Using an Amazon Virtual Private Cloud.amazonka-sagemakerThe name of the new model.amazonka-sagemakerThe Amazon Resource Name (ARN) of the IAM role that SageMaker can assume to access model artifacts and docker image for deployment on ML compute instances or for batch transform jobs. Deploying on ML compute instances is part of model hosting. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-roles.htmlSageMaker Roles.To be able to pass this role to SageMaker, the caller of this API must have the  iam:PassRole permission.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 6 - Specifies the containers in the inference pipeline.,  - Isolates the model container. No inbound or outbound network calls can be made to or from the model container.,  - Specifies details of how containers in a multi-container endpoint are called.,  - The location of the primary docker image containing inference code, associated artifacts, and custom environment map that the inference code uses when the model is deployed for predictions.,  - An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.,  - A VpcConfig object that specifies the VPC that you want your model to connect to. Control access to and from your model container by configuring the VPC.  VpcConfig is used in hosting services and in batch transform. For more information, see  =https://docs.aws.amazon.com/sagemaker/latest/dg/host-vpc.html:Protect Endpoints by Using an Amazon Virtual Private Cloud and  >https://docs.aws.amazon.com/sagemaker/latest/dg/batch-vpc.htmlProtect Data in Batch Transform Jobs by Using an Amazon Virtual Private Cloud.,  - The name of the new model.,  - The Amazon Resource Name (ARN) of the IAM role that SageMaker can assume to access model artifacts and docker image for deployment on ML compute instances or for batch transform jobs. Deploying on ML compute instances is part of model hosting. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-roles.htmlSageMaker Roles.To be able to pass this role to SageMaker, the caller of this API must have the  iam:PassRole permission.amazonka-sagemaker3Specifies the containers in the inference pipeline.amazonka-sagemakerIsolates the model container. No inbound or outbound network calls can be made to or from the model container.amazonka-sagemakerSpecifies details of how containers in a multi-container endpoint are called.amazonka-sagemakerThe location of the primary docker image containing inference code, associated artifacts, and custom environment map that the inference code uses when the model is deployed for predictions.amazonka-sagemakerAn array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.amazonka-sagemakerA VpcConfig object that specifies the VPC that you want your model to connect to. Control access to and from your model container by configuring the VPC.  VpcConfig is used in hosting services and in batch transform. For more information, see  =https://docs.aws.amazon.com/sagemaker/latest/dg/host-vpc.html:Protect Endpoints by Using an Amazon Virtual Private Cloud and  >https://docs.aws.amazon.com/sagemaker/latest/dg/batch-vpc.htmlProtect Data in Batch Transform Jobs by Using an Amazon Virtual Private Cloud.amazonka-sagemakerThe name of the new model.amazonka-sagemakerThe Amazon Resource Name (ARN) of the IAM role that SageMaker can assume to access model artifacts and docker image for deployment on ML compute instances or for batch transform jobs. Deploying on ML compute instances is part of model hosting. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-roles.htmlSageMaker Roles.To be able to pass this role to SageMaker, the caller of this API must have the  iam:PassRole permission.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code., - - The ARN of the model created in SageMaker.amazonka-sagemaker The response's http status code.amazonka-sagemaker*The ARN of the model created in SageMaker.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';)Qξamazonka-sagemakerSee:  smart constructor.оamazonka-sagemaker The response's http status code.Ѿamazonka-sagemakerThe Amazon Resource Name (ARN) of the labeling job. You use this ARN to identify the labeling job.Ҿamazonka-sagemakerSee: ޾ smart constructor.Ծamazonka-sagemakerThe S3 URI of the file, referred to as a /label category configuration file/, that defines the categories used to label the data objects.For 3D point cloud and video frame task types, you can add label category attributes and frame attributes to your label category configuration file. To learn how, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-point-cloud-label-category-config.htmlCreate a Labeling Category Configuration File for 3D Point Cloud Labeling Jobs.2For named entity recognition jobs, in addition to "labels", you must provide worker instructions in the label category configuration file using the "instructions" parameter: "instructions": {"shortInstruction":"

Add header

Add Instructions

", "fullInstruction":"

Add additional instructions.

"}$. For details and an example, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-named-entity-recg.html#sms-creating-ner-api4Create a Named Entity Recognition Labeling Job (API) .For all other  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-task-types.htmlbuilt-in task types and  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-custom-templates.html custom tasks, your label category configuration file must be a JSON file in the following format. Identify the labels you want to use by replacing label_1, label_2,...,label_n with your label categories. { !"document-version": "2018-11-28", "labels": [{"label": "label_1"},{"label": "label_2"},...{"label": "label_n"}] }?Note the following about the label category configuration file:For image classification and text classification (single and multi-label) you must specify at least two label categories. For all other task types, the minimum number of label categories required is one.Each label category must be unique, you cannot specify duplicate label categories.If you create a 3D point cloud or video frame adjustment or verification labeling job, you must include auditLabelAttributeName in the label category configuration. Use this parameter to enter the  https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateLabelingJob.html#sagemaker-CreateLabelingJob-request-LabelAttributeNameLabelAttributeName of the labeling job you want to adjust or verify annotations of.վamazonka-sagemakerConfigures the information required to perform automated data labeling.־amazonka-sagemakerA set of conditions for stopping the labeling job. If any of the conditions are met, the job is automatically stopped. You can use these conditions to control the cost of data labeling.׾amazonka-sagemaker8An array of key/value pairs. For more information, see  https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatUsing Cost Allocation Tags in the :Amazon Web Services Billing and Cost Management User Guide.ؾamazonka-sagemakerThe name of the labeling job. This name is used to identify the job in a list of labeling jobs. Labeling job names must be unique within an Amazon Web Services account and region. LabelingJobName is not case sensitive. For example, Example-job and example-job are considered the same labeling job name by Ground Truth.پamazonka-sagemakerThe attribute name to use for the label in the output manifest file. This is the key for the key/value pair formed with the label that a worker assigns to the object. The LabelAttributeName' must meet the following requirements.$The name can't end with "-metadata".+If you are using one of the following  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-task-types.htmlbuilt-in task types, the attribute name must end with "-ref". If the task type you are using is not listed below, the attribute name must not end with "-ref".Image semantic segmentation (SemanticSegmentation), and adjustment (AdjustmentSemanticSegmentation) and verification ( VerificationSemanticSegmentation') labeling jobs for this task type.Video frame object detection (VideoObjectDetection(), and adjustment and verification (AdjustmentVideoObjectDetection') labeling jobs for this task type.Video frame object tracking (VideoObjectTracking(), and adjustment and verification (AdjustmentVideoObjectTracking') labeling jobs for this task type.*3D point cloud semantic segmentation ( 3DPointCloudSemanticSegmentation(), and adjustment and verification (*Adjustment3DPointCloudSemanticSegmentation') labeling jobs for this task type. 3D point cloud object tracking (3DPointCloudObjectTracking,), and adjustment and verification ($Adjustment3DPointCloudObjectTracking') labeling jobs for this task type.If you are creating an adjustment or verification labeling job, you must use a  different LabelAttributeName than the one used in the original labeling job. The original labeling job is the Ground Truth labeling job that produced the labels that you want verified or adjusted. To learn more about adjustment and verification labeling jobs, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-verification-data.htmlVerify and Adjust Labels.ھamazonka-sagemakerInput data for the labeling job, such as the Amazon S3 location of the data objects and the location of the manifest file that describes the data objects.0You must specify at least one of the following:  S3DataSource or  SnsDataSource.Use  SnsDataSource to specify an SNS input topic for a streaming labeling job. If you do not specify and SNS input topic ARN, Ground Truth will create a one-time labeling job that stops after all data objects in the input manifest file have been labeled.Use  S3DataSource to specify an input manifest file for both streaming and one-time labeling jobs. Adding an  S3DataSource is optional if you use  SnsDataSource) to create a streaming labeling job.If you use the Amazon Mechanical Turk workforce, your input data should not include confidential information, personal information or protected health information. Use ContentClassifiers to specify that your data is free of personally identifiable information and adult content.۾amazonka-sagemakerThe location of the output data and the Amazon Web Services Key Management Service key ID for the key used to encrypt the output data, if any.ܾamazonka-sagemakerThe Amazon Resource Number (ARN) that Amazon SageMaker assumes to perform tasks on your behalf during data labeling. You must grant this role the necessary permissions so that Amazon SageMaker can successfully complete data labeling.ݾamazonka-sagemakerConfigures the labeling task and how it is presented to workers; including, but not limited to price, keywords, and batch size (task count).޾amazonka-sagemakerCreate a value of Ҿ" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:Ծ, ߾ - The S3 URI of the file, referred to as a /label category configuration file/, that defines the categories used to label the data objects.For 3D point cloud and video frame task types, you can add label category attributes and frame attributes to your label category configuration file. To learn how, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-point-cloud-label-category-config.htmlCreate a Labeling Category Configuration File for 3D Point Cloud Labeling Jobs.2For named entity recognition jobs, in addition to "labels", you must provide worker instructions in the label category configuration file using the "instructions" parameter: "instructions": {"shortInstruction":"

Add header

Add Instructions

", "fullInstruction":"

Add additional instructions.

"}$. For details and an example, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-named-entity-recg.html#sms-creating-ner-api4Create a Named Entity Recognition Labeling Job (API) .For all other  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-task-types.htmlbuilt-in task types and  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-custom-templates.html custom tasks, your label category configuration file must be a JSON file in the following format. Identify the labels you want to use by replacing label_1, label_2,...,label_n with your label categories. { !"document-version": "2018-11-28", "labels": [{"label": "label_1"},{"label": "label_2"},...{"label": "label_n"}] }?Note the following about the label category configuration file:For image classification and text classification (single and multi-label) you must specify at least two label categories. For all other task types, the minimum number of label categories required is one.Each label category must be unique, you cannot specify duplicate label categories.If you create a 3D point cloud or video frame adjustment or verification labeling job, you must include auditLabelAttributeName in the label category configuration. Use this parameter to enter the  https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateLabelingJob.html#sagemaker-CreateLabelingJob-request-LabelAttributeNameLabelAttributeName of the labeling job you want to adjust or verify annotations of.վ,  - Configures the information required to perform automated data labeling.־,  - A set of conditions for stopping the labeling job. If any of the conditions are met, the job is automatically stopped. You can use these conditions to control the cost of data labeling.Ҿ, ; - An array of key/value pairs. For more information, see  https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatUsing Cost Allocation Tags in the :Amazon Web Services Billing and Cost Management User Guide.Ҿ,  - The name of the labeling job. This name is used to identify the job in a list of labeling jobs. Labeling job names must be unique within an Amazon Web Services account and region. LabelingJobName is not case sensitive. For example, Example-job and example-job are considered the same labeling job name by Ground Truth.پ,  - The attribute name to use for the label in the output manifest file. This is the key for the key/value pair formed with the label that a worker assigns to the object. The LabelAttributeName' must meet the following requirements.$The name can't end with "-metadata".+If you are using one of the following  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-task-types.htmlbuilt-in task types, the attribute name must end with "-ref". If the task type you are using is not listed below, the attribute name must not end with "-ref".Image semantic segmentation (SemanticSegmentation), and adjustment (AdjustmentSemanticSegmentation) and verification ( VerificationSemanticSegmentation') labeling jobs for this task type.Video frame object detection (VideoObjectDetection(), and adjustment and verification (AdjustmentVideoObjectDetection') labeling jobs for this task type.Video frame object tracking (VideoObjectTracking(), and adjustment and verification (AdjustmentVideoObjectTracking') labeling jobs for this task type.*3D point cloud semantic segmentation ( 3DPointCloudSemanticSegmentation(), and adjustment and verification (*Adjustment3DPointCloudSemanticSegmentation') labeling jobs for this task type. 3D point cloud object tracking (3DPointCloudObjectTracking,), and adjustment and verification ($Adjustment3DPointCloudObjectTracking') labeling jobs for this task type.If you are creating an adjustment or verification labeling job, you must use a  different LabelAttributeName than the one used in the original labeling job. The original labeling job is the Ground Truth labeling job that produced the labels that you want verified or adjusted. To learn more about adjustment and verification labeling jobs, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-verification-data.htmlVerify and Adjust Labels.Ҿ,  - Input data for the labeling job, such as the Amazon S3 location of the data objects and the location of the manifest file that describes the data objects.0You must specify at least one of the following:  S3DataSource or  SnsDataSource.Use  SnsDataSource to specify an SNS input topic for a streaming labeling job. If you do not specify and SNS input topic ARN, Ground Truth will create a one-time labeling job that stops after all data objects in the input manifest file have been labeled.Use  S3DataSource to specify an input manifest file for both streaming and one-time labeling jobs. Adding an  S3DataSource is optional if you use  SnsDataSource) to create a streaming labeling job.If you use the Amazon Mechanical Turk workforce, your input data should not include confidential information, personal information or protected health information. Use ContentClassifiers to specify that your data is free of personally identifiable information and adult content.Ҿ,  - The location of the output data and the Amazon Web Services Key Management Service key ID for the key used to encrypt the output data, if any.Ҿ,  - The Amazon Resource Number (ARN) that Amazon SageMaker assumes to perform tasks on your behalf during data labeling. You must grant this role the necessary permissions so that Amazon SageMaker can successfully complete data labeling.ݾ,  - Configures the labeling task and how it is presented to workers; including, but not limited to price, keywords, and batch size (task count).߾amazonka-sagemakerThe S3 URI of the file, referred to as a /label category configuration file/, that defines the categories used to label the data objects.For 3D point cloud and video frame task types, you can add label category attributes and frame attributes to your label category configuration file. To learn how, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-point-cloud-label-category-config.htmlCreate a Labeling Category Configuration File for 3D Point Cloud Labeling Jobs.2For named entity recognition jobs, in addition to "labels", you must provide worker instructions in the label category configuration file using the "instructions" parameter: "instructions": {"shortInstruction":"

Add header

Add Instructions

", "fullInstruction":"

Add additional instructions.

"}$. For details and an example, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-named-entity-recg.html#sms-creating-ner-api4Create a Named Entity Recognition Labeling Job (API) .For all other  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-task-types.htmlbuilt-in task types and  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-custom-templates.html custom tasks, your label category configuration file must be a JSON file in the following format. Identify the labels you want to use by replacing label_1, label_2,...,label_n with your label categories. { !"document-version": "2018-11-28", "labels": [{"label": "label_1"},{"label": "label_2"},...{"label": "label_n"}] }?Note the following about the label category configuration file:For image classification and text classification (single and multi-label) you must specify at least two label categories. For all other task types, the minimum number of label categories required is one.Each label category must be unique, you cannot specify duplicate label categories.If you create a 3D point cloud or video frame adjustment or verification labeling job, you must include auditLabelAttributeName in the label category configuration. Use this parameter to enter the  https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateLabelingJob.html#sagemaker-CreateLabelingJob-request-LabelAttributeNameLabelAttributeName of the labeling job you want to adjust or verify annotations of.amazonka-sagemakerConfigures the information required to perform automated data labeling.amazonka-sagemakerA set of conditions for stopping the labeling job. If any of the conditions are met, the job is automatically stopped. You can use these conditions to control the cost of data labeling.amazonka-sagemaker8An array of key/value pairs. For more information, see  https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatUsing Cost Allocation Tags in the :Amazon Web Services Billing and Cost Management User Guide.amazonka-sagemakerThe name of the labeling job. This name is used to identify the job in a list of labeling jobs. Labeling job names must be unique within an Amazon Web Services account and region. LabelingJobName is not case sensitive. For example, Example-job and example-job are considered the same labeling job name by Ground Truth.amazonka-sagemakerThe attribute name to use for the label in the output manifest file. This is the key for the key/value pair formed with the label that a worker assigns to the object. The LabelAttributeName' must meet the following requirements.$The name can't end with "-metadata".+If you are using one of the following  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-task-types.htmlbuilt-in task types, the attribute name must end with "-ref". If the task type you are using is not listed below, the attribute name must not end with "-ref".Image semantic segmentation (SemanticSegmentation), and adjustment (AdjustmentSemanticSegmentation) and verification ( VerificationSemanticSegmentation') labeling jobs for this task type.Video frame object detection (VideoObjectDetection(), and adjustment and verification (AdjustmentVideoObjectDetection') labeling jobs for this task type.Video frame object tracking (VideoObjectTracking(), and adjustment and verification (AdjustmentVideoObjectTracking') labeling jobs for this task type.*3D point cloud semantic segmentation ( 3DPointCloudSemanticSegmentation(), and adjustment and verification (*Adjustment3DPointCloudSemanticSegmentation') labeling jobs for this task type. 3D point cloud object tracking (3DPointCloudObjectTracking,), and adjustment and verification ($Adjustment3DPointCloudObjectTracking') labeling jobs for this task type.If you are creating an adjustment or verification labeling job, you must use a  different LabelAttributeName than the one used in the original labeling job. The original labeling job is the Ground Truth labeling job that produced the labels that you want verified or adjusted. To learn more about adjustment and verification labeling jobs, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-verification-data.htmlVerify and Adjust Labels.amazonka-sagemakerInput data for the labeling job, such as the Amazon S3 location of the data objects and the location of the manifest file that describes the data objects.0You must specify at least one of the following:  S3DataSource or  SnsDataSource.Use  SnsDataSource to specify an SNS input topic for a streaming labeling job. If you do not specify and SNS input topic ARN, Ground Truth will create a one-time labeling job that stops after all data objects in the input manifest file have been labeled.Use  S3DataSource to specify an input manifest file for both streaming and one-time labeling jobs. Adding an  S3DataSource is optional if you use  SnsDataSource) to create a streaming labeling job.If you use the Amazon Mechanical Turk workforce, your input data should not include confidential information, personal information or protected health information. Use ContentClassifiers to specify that your data is free of personally identifiable information and adult content.amazonka-sagemakerThe location of the output data and the Amazon Web Services Key Management Service key ID for the key used to encrypt the output data, if any.amazonka-sagemakerThe Amazon Resource Number (ARN) that Amazon SageMaker assumes to perform tasks on your behalf during data labeling. You must grant this role the necessary permissions so that Amazon SageMaker can successfully complete data labeling.amazonka-sagemakerConfigures the labeling task and how it is presented to workers; including, but not limited to price, keywords, and batch size (task count).amazonka-sagemakerCreate a value of ξ" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:о, # - The response's http status code.ξ,  - The Amazon Resource Name (ARN) of the labeling job. You use this ARN to identify the labeling job.amazonka-sagemaker The response's http status code.amazonka-sagemakerThe Amazon Resource Name (ARN) of the labeling job. You use this ARN to identify the labeling job.޾amazonka-sagemakerҾamazonka-sagemakerپamazonka-sagemakerҾamazonka-sagemakerҾamazonka-sagemakerҾamazonka-sagemakerݾamazonka-sagemakerоamazonka-sagemakerξξϾѾоҾӾ׾۾ܾؾھپԾվ־ݾ޾߾ҾӾ׾۾ܾؾھپԾվ־ݾ޾߾ξϾѾо(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';)jjamazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemaker9The Amazon Resource Name (ARN) of the recommendation job.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker&Description of the recommendation job.amazonka-sagemakerProvides information about the output artifacts and the KMS key to use for Amazon S3 server-side encryption.amazonka-sagemakerA set of conditions for stopping a recommendation job. If any of the conditions are met, the job is automatically stopped.amazonka-sagemakerThe metadata that you apply to Amazon Web Services resources to help you categorize and organize them. Each tag consists of a key and a value, both of which you define. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources/ in the Amazon Web Services General Reference.amazonka-sagemakerA name for the recommendation job. The name must be unique within the Amazon Web Services Region and within your Amazon Web Services account.amazonka-sagemaker0Defines the type of recommendation job. Specify Default- to initiate an instance recommendation and Advanced to initiate a load test. If left unspecified, Amazon SageMaker Inference Recommender will run an instance recommendation (DEFAULT) job.amazonka-sagemakerThe Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to perform tasks on your behalf.amazonka-sagemakerProvides information about the versioned model package Amazon Resource Name (ARN), the traffic pattern, and endpoint configurations.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, ) - Description of the recommendation job.,  - Provides information about the output artifacts and the KMS key to use for Amazon S3 server-side encryption.,  - A set of conditions for stopping a recommendation job. If any of the conditions are met, the job is automatically stopped.,  - The metadata that you apply to Amazon Web Services resources to help you categorize and organize them. Each tag consists of a key and a value, both of which you define. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources/ in the Amazon Web Services General Reference.,  - A name for the recommendation job. The name must be unique within the Amazon Web Services Region and within your Amazon Web Services account., 3 - Defines the type of recommendation job. Specify Default- to initiate an instance recommendation and Advanced to initiate a load test. If left unspecified, Amazon SageMaker Inference Recommender will run an instance recommendation (DEFAULT) job.,  - The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to perform tasks on your behalf.,  - Provides information about the versioned model package Amazon Resource Name (ARN), the traffic pattern, and endpoint configurations.amazonka-sagemaker&Description of the recommendation job.amazonka-sagemakerProvides information about the output artifacts and the KMS key to use for Amazon S3 server-side encryption.amazonka-sagemakerA set of conditions for stopping a recommendation job. If any of the conditions are met, the job is automatically stopped.amazonka-sagemakerThe metadata that you apply to Amazon Web Services resources to help you categorize and organize them. Each tag consists of a key and a value, both of which you define. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources/ in the Amazon Web Services General Reference.amazonka-sagemakerA name for the recommendation job. The name must be unique within the Amazon Web Services Region and within your Amazon Web Services account.amazonka-sagemaker0Defines the type of recommendation job. Specify Default- to initiate an instance recommendation and Advanced to initiate a load test. If left unspecified, Amazon SageMaker Inference Recommender will run an instance recommendation (DEFAULT) job.amazonka-sagemakerThe Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to perform tasks on your behalf.amazonka-sagemakerProvides information about the versioned model package Amazon Resource Name (ARN), the traffic pattern, and endpoint configurations.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code., < - The Amazon Resource Name (ARN) of the recommendation job.amazonka-sagemaker The response's http status code.amazonka-sagemaker9The Amazon Resource Name (ARN) of the recommendation job.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';)amazonka-sagemakerSee: ÿ smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemaker&The ARN for your inference experiment.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe Amazon S3 location and configuration for storing inference request and response data.This is an optional parameter that you can use for data capture. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor-data-capture.html Capture data.amazonka-sagemaker+A description for the inference experiment.amazonka-sagemakerThe Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint. The KmsKey% can be any of the following formats: KMS key ID &"1234abcd-12ab-34cd-56ef-1234567890ab"'Amazon Resource Name (ARN) of a KMS key "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab" KMS key Alias "alias/ExampleAlias"-Amazon Resource Name (ARN) of a KMS key Alias 7"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"If you use a KMS key ID or an alias of your KMS key, the Amazon SageMaker execution role must include permissions to call  kms:Encrypt. If you don't provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role's account. Amazon SageMaker uses server-side encryption with KMS managed keys for OutputDataConfig&. If you use a bucket policy with an  s3:PutObject permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption to  "aws:kms". For more information, see  https://docs.aws.amazon.com/AmazonS3/latest/dev/UsingKMSEncryption.htmlKMS managed Encryption Keys in the .Amazon Simple Storage Service Developer Guide.The KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint and UpdateEndpoint' requests. For more information, see  https://docs.aws.amazon.com/kms/latest/developerguide/key-policies.html-Using Key Policies in Amazon Web Services KMS in the :Amazon Web Services Key Management Service Developer Guide.amazonka-sagemakerThe duration for which you want the inference experiment to run. If you don't specify this field, the experiment automatically starts immediately upon creation and concludes after 7 days.amazonka-sagemakerArray of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see  =https://docs.aws.amazon.com/ARG/latest/userguide/tagging.html*Tagging your Amazon Web Services Resources.amazonka-sagemaker&The name for the inference experiment.amazonka-sagemakerThe type of the inference experiment that you want to run. The following types of experiments are possible: ShadowMode: You can use this type to validate a shadow variant. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/shadow-tests.html Shadow tests.amazonka-sagemakerThe ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.amazonka-sagemakerThe name of the Amazon SageMaker endpoint on which you want to run the inference experiment.amazonka-sagemaker An array of ModelVariantConfig objects. There is one for each variant in the inference experiment. Each ModelVariantConfig object in the array describes the infrastructure configuration for the corresponding variant.amazonka-sagemakerThe configuration of  ShadowMode inference experiment type. Use this field to specify a production variant which takes all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant also specify the percentage of requests that Amazon SageMaker replicates.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The Amazon S3 location and configuration for storing inference request and response data.This is an optional parameter that you can use for data capture. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor-data-capture.html Capture data., . - A description for the inference experiment.,  - The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint. The KmsKey% can be any of the following formats: KMS key ID &"1234abcd-12ab-34cd-56ef-1234567890ab"'Amazon Resource Name (ARN) of a KMS key "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab" KMS key Alias "alias/ExampleAlias"-Amazon Resource Name (ARN) of a KMS key Alias 7"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"If you use a KMS key ID or an alias of your KMS key, the Amazon SageMaker execution role must include permissions to call  kms:Encrypt. If you don't provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role's account. Amazon SageMaker uses server-side encryption with KMS managed keys for OutputDataConfig&. If you use a bucket policy with an  s3:PutObject permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption to  "aws:kms". For more information, see  https://docs.aws.amazon.com/AmazonS3/latest/dev/UsingKMSEncryption.htmlKMS managed Encryption Keys in the .Amazon Simple Storage Service Developer Guide.The KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint and UpdateEndpoint' requests. For more information, see  https://docs.aws.amazon.com/kms/latest/developerguide/key-policies.html-Using Key Policies in Amazon Web Services KMS in the :Amazon Web Services Key Management Service Developer Guide.,  - The duration for which you want the inference experiment to run. If you don't specify this field, the experiment automatically starts immediately upon creation and concludes after 7 days.,  - Array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see  =https://docs.aws.amazon.com/ARG/latest/userguide/tagging.html*Tagging your Amazon Web Services Resources., ) - The name for the inference experiment.,  - The type of the inference experiment that you want to run. The following types of experiments are possible: ShadowMode: You can use this type to validate a shadow variant. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/shadow-tests.html Shadow tests.,  - The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.,  - The name of the Amazon SageMaker endpoint on which you want to run the inference experiment.,  - An array of ModelVariantConfig objects. There is one for each variant in the inference experiment. Each ModelVariantConfig object in the array describes the infrastructure configuration for the corresponding variant., ¿ - The configuration of  ShadowMode inference experiment type. Use this field to specify a production variant which takes all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant also specify the percentage of requests that Amazon SageMaker replicates.amazonka-sagemakerThe Amazon S3 location and configuration for storing inference request and response data.This is an optional parameter that you can use for data capture. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor-data-capture.html Capture data.amazonka-sagemaker+A description for the inference experiment.amazonka-sagemakerThe Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint. The KmsKey% can be any of the following formats: KMS key ID &"1234abcd-12ab-34cd-56ef-1234567890ab"'Amazon Resource Name (ARN) of a KMS key "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab" KMS key Alias "alias/ExampleAlias"-Amazon Resource Name (ARN) of a KMS key Alias 7"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"If you use a KMS key ID or an alias of your KMS key, the Amazon SageMaker execution role must include permissions to call  kms:Encrypt. If you don't provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role's account. Amazon SageMaker uses server-side encryption with KMS managed keys for OutputDataConfig&. If you use a bucket policy with an  s3:PutObject permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption to  "aws:kms". For more information, see  https://docs.aws.amazon.com/AmazonS3/latest/dev/UsingKMSEncryption.htmlKMS managed Encryption Keys in the .Amazon Simple Storage Service Developer Guide.The KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint and UpdateEndpoint' requests. For more information, see  https://docs.aws.amazon.com/kms/latest/developerguide/key-policies.html-Using Key Policies in Amazon Web Services KMS in the :Amazon Web Services Key Management Service Developer Guide.amazonka-sagemakerThe duration for which you want the inference experiment to run. If you don't specify this field, the experiment automatically starts immediately upon creation and concludes after 7 days.amazonka-sagemakerArray of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see  =https://docs.aws.amazon.com/ARG/latest/userguide/tagging.html*Tagging your Amazon Web Services Resources.amazonka-sagemaker&The name for the inference experiment.amazonka-sagemakerThe type of the inference experiment that you want to run. The following types of experiments are possible: ShadowMode: You can use this type to validate a shadow variant. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/shadow-tests.html Shadow tests.amazonka-sagemakerThe ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.amazonka-sagemakerThe name of the Amazon SageMaker endpoint on which you want to run the inference experiment.amazonka-sagemaker An array of ModelVariantConfig objects. There is one for each variant in the inference experiment. Each ModelVariantConfig object in the array describes the infrastructure configuration for the corresponding variant.¿amazonka-sagemakerThe configuration of  ShadowMode inference experiment type. Use this field to specify a production variant which takes all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant also specify the percentage of requests that Amazon SageMaker replicates.ÿamazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, Ŀ# - The response's http status code., ſ) - The ARN for your inference experiment.Ŀamazonka-sagemaker The response's http status code.ſamazonka-sagemaker&The ARN for your inference experiment.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakerÿamazonka-sagemakeramazonka-sagemaker ¿ÿĿſ ¿ÿĿſ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';)ֿamazonka-sagemakerSee:  smart constructor.ؿamazonka-sagemakerThe ARN of the image version.ٿamazonka-sagemaker The response's http status code.ڿamazonka-sagemakerSee:  smart constructor.ܿamazonka-sagemaker1A list of aliases created with the image version.ݿamazonka-sagemaker Indicates Horovod compatibility.޿amazonka-sagemaker+Indicates SageMaker job type compatibility.TRAINING: The image version is compatible with SageMaker training jobs. INFERENCE: The image version is compatible with SageMaker inference jobs.NOTEBOOK_KERNEL: The image version is compatible with SageMaker notebook kernels.߿amazonka-sagemaker;The machine learning framework vended in the image version.amazonka-sagemaker#Indicates CPU or GPU compatibility.CPU+: The image version is compatible with CPU.GPU+: The image version is compatible with GPU.amazonka-sagemaker3The supported programming language and its version.amazonka-sagemaker0The maintainer description of the image version.amazonka-sagemakerThe stability of the image version, specified by the maintainer. NOT_PROVIDED: The maintainers did not provide a status for image version stability.STABLE: The image version is stable.TO_BE_ARCHIVED: The image version is set to be archived. Custom image versions that are set to be archived are automatically archived after three months.ARCHIVED: The image version is archived. Archived image versions are not searchable and are no longer actively supported.amazonka-sagemakerThe registry path of the container image to use as the starting point for this version. The path is an Amazon Elastic Container Registry (ECR) URI in the following format: .dkr.ecr..amazonaws.com/amazonka-sagemakerA unique ID. If not specified, the Amazon Web Services CLI and Amazon Web Services SDKs, such as the SDK for Python (Boto3), add a unique value to the call.amazonka-sagemakerThe  ImageName of the Image to create a version of.amazonka-sagemakerCreate a value of ڿ" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:ܿ, 4 - A list of aliases created with the image version.ݿ, # - Indicates Horovod compatibility.ڿ, . - Indicates SageMaker job type compatibility.TRAINING: The image version is compatible with SageMaker training jobs. INFERENCE: The image version is compatible with SageMaker inference jobs.NOTEBOOK_KERNEL: The image version is compatible with SageMaker notebook kernels.߿, > - The machine learning framework vended in the image version., & - Indicates CPU or GPU compatibility.CPU+: The image version is compatible with CPU.GPU+: The image version is compatible with GPU., 6 - The supported programming language and its version., 3 - The maintainer description of the image version.,  - The stability of the image version, specified by the maintainer. NOT_PROVIDED: The maintainers did not provide a status for image version stability.STABLE: The image version is stable.TO_BE_ARCHIVED: The image version is set to be archived. Custom image versions that are set to be archived are automatically archived after three months.ARCHIVED: The image version is archived. Archived image versions are not searchable and are no longer actively supported.,  - The registry path of the container image to use as the starting point for this version. The path is an Amazon Elastic Container Registry (ECR) URI in the following format: .dkr.ecr..amazonaws.com/,  - A unique ID. If not specified, the Amazon Web Services CLI and Amazon Web Services SDKs, such as the SDK for Python (Boto3), add a unique value to the call.ڿ,  - The  ImageName of the Image to create a version of.amazonka-sagemaker1A list of aliases created with the image version.amazonka-sagemaker Indicates Horovod compatibility.amazonka-sagemaker+Indicates SageMaker job type compatibility.TRAINING: The image version is compatible with SageMaker training jobs. INFERENCE: The image version is compatible with SageMaker inference jobs.NOTEBOOK_KERNEL: The image version is compatible with SageMaker notebook kernels.amazonka-sagemaker;The machine learning framework vended in the image version.amazonka-sagemaker#Indicates CPU or GPU compatibility.CPU+: The image version is compatible with CPU.GPU+: The image version is compatible with GPU.amazonka-sagemaker3The supported programming language and its version.amazonka-sagemaker0The maintainer description of the image version.amazonka-sagemakerThe stability of the image version, specified by the maintainer. NOT_PROVIDED: The maintainers did not provide a status for image version stability.STABLE: The image version is stable.TO_BE_ARCHIVED: The image version is set to be archived. Custom image versions that are set to be archived are automatically archived after three months.ARCHIVED: The image version is archived. Archived image versions are not searchable and are no longer actively supported.amazonka-sagemakerThe registry path of the container image to use as the starting point for this version. The path is an Amazon Elastic Container Registry (ECR) URI in the following format: .dkr.ecr..amazonaws.com/amazonka-sagemakerA unique ID. If not specified, the Amazon Web Services CLI and Amazon Web Services SDKs, such as the SDK for Python (Boto3), add a unique value to the call.amazonka-sagemakerThe  ImageName of the Image to create a version of.amazonka-sagemakerCreate a value of ֿ" with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:ֿ,  - The ARN of the image version.ٿ, # - The response's http status code.amazonka-sagemakerThe ARN of the image version.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakerڿamazonka-sagemakerٿ ֿ׿ؿٿڿۿ޿ݿ߿ܿ ڿۿ޿ݿ߿ֿܿ׿ؿٿ(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';)amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe ARN of the image.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe description of the image.amazonka-sagemaker0The display name of the image. If not provided,  ImageName is displayed.amazonka-sagemaker%A list of tags to apply to the image.amazonka-sagemaker6The name of the image. Must be unique to your account.amazonka-sagemakerThe ARN of an IAM role that enables Amazon SageMaker to perform tasks on your behalf.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The description of the image., 3 - The display name of the image. If not provided,  ImageName is displayed., ( - A list of tags to apply to the image., 9 - The name of the image. Must be unique to your account.,  - The ARN of an IAM role that enables Amazon SageMaker to perform tasks on your behalf.amazonka-sagemakerThe description of the image.amazonka-sagemaker0The display name of the image. If not provided,  ImageName is displayed.amazonka-sagemaker%A list of tags to apply to the image.amazonka-sagemaker6The name of the image. Must be unique to your account.amazonka-sagemakerThe ARN of an IAM role that enables Amazon SageMaker to perform tasks on your behalf.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The ARN of the image., # - The response's http status code.amazonka-sagemakerThe ARN of the image.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';)amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemakerThe Amazon Resource Name (ARN) of the tuning job. SageMaker assigns an ARN to a hyperparameter tuning job when you create it.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerAn array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.Tags that you specify for the tuning job are also added to all training jobs that the tuning job launches.amazonka-sagemakerThe HyperParameterTrainingJobDefinition object that describes the training jobs that this tuning job launches, including static hyperparameters, input data configuration, output data configuration, resource configuration, and stopping condition.amazonka-sagemakerA list of the HyperParameterTrainingJobDefinition objects launched for this tuning job.amazonka-sagemakerSpecifies the configuration for starting the hyperparameter tuning job using one or more previous tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.All training jobs launched by the new hyperparameter tuning job are evaluated by using the objective metric. If you specify IDENTICAL_DATA_AND_ALGORITHM as the  WarmStartType value for the warm start configuration, the training job that performs the best in the new tuning job is compared to the best training jobs from the parent tuning jobs. From these, the training job that performs the best as measured by the objective metric is returned as the overall best training job.All training jobs launched by parent hyperparameter tuning jobs and the new hyperparameter tuning jobs count against the limit of training jobs for the tuning job.amazonka-sagemakerThe name of the tuning job. This name is the prefix for the names of all training jobs that this tuning job launches. The name must be unique within the same Amazon Web Services account and Amazon Web Services Region. The name must have 1 to 32 characters. Valid characters are a-z, A-Z, 0-9, and : + = @ _ % - (hyphen). The name is not case sensitive.amazonka-sagemakerThe HyperParameterTuningJobConfig object that describes the tuning job, including the search strategy, the objective metric used to evaluate training jobs, ranges of parameters to search, and resource limits for the tuning job. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-how-it-works.htmlHow Hyperparameter Tuning Works.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.Tags that you specify for the tuning job are also added to all training jobs that the tuning job launches.,  - The HyperParameterTrainingJobDefinition object that describes the training jobs that this tuning job launches, including static hyperparameters, input data configuration, output data configuration, resource configuration, and stopping condition.,  - A list of the HyperParameterTrainingJobDefinition objects launched for this tuning job.,  - Specifies the configuration for starting the hyperparameter tuning job using one or more previous tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.All training jobs launched by the new hyperparameter tuning job are evaluated by using the objective metric. If you specify IDENTICAL_DATA_AND_ALGORITHM as the  WarmStartType value for the warm start configuration, the training job that performs the best in the new tuning job is compared to the best training jobs from the parent tuning jobs. From these, the training job that performs the best as measured by the objective metric is returned as the overall best training job.All training jobs launched by parent hyperparameter tuning jobs and the new hyperparameter tuning jobs count against the limit of training jobs for the tuning job.,  - The name of the tuning job. This name is the prefix for the names of all training jobs that this tuning job launches. The name must be unique within the same Amazon Web Services account and Amazon Web Services Region. The name must have 1 to 32 characters. Valid characters are a-z, A-Z, 0-9, and : + = @ _ % - (hyphen). The name is not case sensitive.,  - The HyperParameterTuningJobConfig object that describes the tuning job, including the search strategy, the objective metric used to evaluate training jobs, ranges of parameters to search, and resource limits for the tuning job. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-how-it-works.htmlHow Hyperparameter Tuning Works.amazonka-sagemakerAn array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.Tags that you specify for the tuning job are also added to all training jobs that the tuning job launches.amazonka-sagemakerThe HyperParameterTrainingJobDefinition object that describes the training jobs that this tuning job launches, including static hyperparameters, input data configuration, output data configuration, resource configuration, and stopping condition.amazonka-sagemakerA list of the HyperParameterTrainingJobDefinition objects launched for this tuning job.amazonka-sagemakerSpecifies the configuration for starting the hyperparameter tuning job using one or more previous tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.All training jobs launched by the new hyperparameter tuning job are evaluated by using the objective metric. If you specify IDENTICAL_DATA_AND_ALGORITHM as the  WarmStartType value for the warm start configuration, the training job that performs the best in the new tuning job is compared to the best training jobs from the parent tuning jobs. From these, the training job that performs the best as measured by the objective metric is returned as the overall best training job.All training jobs launched by parent hyperparameter tuning jobs and the new hyperparameter tuning jobs count against the limit of training jobs for the tuning job.amazonka-sagemakerThe name of the tuning job. This name is the prefix for the names of all training jobs that this tuning job launches. The name must be unique within the same Amazon Web Services account and Amazon Web Services Region. The name must have 1 to 32 characters. Valid characters are a-z, A-Z, 0-9, and : + = @ _ % - (hyphen). The name is not case sensitive.amazonka-sagemakerThe HyperParameterTuningJobConfig object that describes the tuning job, including the search strategy, the objective metric used to evaluate training jobs, ranges of parameters to search, and resource limits for the tuning job. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-how-it-works.htmlHow Hyperparameter Tuning Works.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code.,  - The Amazon Resource Name (ARN) of the tuning job. SageMaker assigns an ARN to a hyperparameter tuning job when you create it.amazonka-sagemaker The response's http status code.amazonka-sagemakerThe Amazon Resource Name (ARN) of the tuning job. SageMaker assigns an ARN to a hyperparameter tuning job when you create it.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';) amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemakerThe Amazon Resource Name (ARN) of the human review workflow user interface you create.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerAn array of key-value pairs that contain metadata to help you categorize and organize a human review workflow user interface. Each tag consists of a key and a value, both of which you define.amazonka-sagemaker0The name of the user interface you are creating.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - An array of key-value pairs that contain metadata to help you categorize and organize a human review workflow user interface. Each tag consists of a key and a value, both of which you define., 3 - The name of the user interface you are creating.,  - Undocumented member.amazonka-sagemakerAn array of key-value pairs that contain metadata to help you categorize and organize a human review workflow user interface. Each tag consists of a key and a value, both of which you define.amazonka-sagemaker0The name of the user interface you are creating.amazonka-sagemakerUndocumented member.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code.,  - The Amazon Resource Name (ARN) of the human review workflow user interface you create.amazonka-sagemaker The response's http status code.amazonka-sagemakerThe Amazon Resource Name (ARN) of the human review workflow user interface you create.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';*3amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemaker*The Amazon Resource Name (ARN) of the hub.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe display name of the hub.amazonka-sagemaker$The searchable keywords for the hub.amazonka-sagemaker0The Amazon S3 storage configuration for the hub.amazonka-sagemaker#Any tags to associate with the hub.amazonka-sagemakerThe name of the hub to create.amazonka-sagemakerA description of the hub.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The display name of the hub., ' - The searchable keywords for the hub., 3 - The Amazon S3 storage configuration for the hub., & - Any tags to associate with the hub., ! - The name of the hub to create.,  - A description of the hub.amazonka-sagemakerThe display name of the hub.amazonka-sagemaker$The searchable keywords for the hub.amazonka-sagemaker0The Amazon S3 storage configuration for the hub.amazonka-sagemaker#Any tags to associate with the hub.amazonka-sagemakerThe name of the hub to create.amazonka-sagemakerA description of the hub.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code., - - The Amazon Resource Name (ARN) of the hub.amazonka-sagemaker The response's http status code.amazonka-sagemaker*The Amazon Resource Name (ARN) of the hub.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';*amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemakerThe Amazon Resource Name (ARN) of the flow definition you create.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerAn object containing information about the events that trigger a human workflow.amazonka-sagemakerContainer for configuring the source of human task requests. Use to specify if Amazon Rekognition or Amazon Textract is used as an integration source.amazonka-sagemakerAn array of key-value pairs that contain metadata to help you categorize and organize a flow definition. Each tag consists of a key and a value, both of which you define.amazonka-sagemaker!The name of your flow definition.amazonka-sagemakerAn object containing information about the tasks the human reviewers will perform.amazonka-sagemakerAn object containing information about where the human review results will be uploaded.amazonka-sagemakerThe Amazon Resource Name (ARN) of the role needed to call other services on your behalf. For example, arn:aws:iam::1234567890:role/service-role/AmazonSageMaker-ExecutionRole-20180111T151298.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - An object containing information about the events that trigger a human workflow.,  - Container for configuring the source of human task requests. Use to specify if Amazon Rekognition or Amazon Textract is used as an integration source.,  - An array of key-value pairs that contain metadata to help you categorize and organize a flow definition. Each tag consists of a key and a value, both of which you define., $ - The name of your flow definition.,  - An object containing information about the tasks the human reviewers will perform.,  - An object containing information about where the human review results will be uploaded.,  - The Amazon Resource Name (ARN) of the role needed to call other services on your behalf. For example, arn:aws:iam::1234567890:role/service-role/AmazonSageMaker-ExecutionRole-20180111T151298.amazonka-sagemakerAn object containing information about the events that trigger a human workflow.amazonka-sagemakerContainer for configuring the source of human task requests. Use to specify if Amazon Rekognition or Amazon Textract is used as an integration source.amazonka-sagemakerAn array of key-value pairs that contain metadata to help you categorize and organize a flow definition. Each tag consists of a key and a value, both of which you define.amazonka-sagemaker!The name of your flow definition.amazonka-sagemakerAn object containing information about the tasks the human reviewers will perform.amazonka-sagemakerAn object containing information about where the human review results will be uploaded.amazonka-sagemakerThe Amazon Resource Name (ARN) of the role needed to call other services on your behalf. For example, arn:aws:iam::1234567890:role/service-role/AmazonSageMaker-ExecutionRole-20180111T151298.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code.,  - The Amazon Resource Name (ARN) of the flow definition you create.amazonka-sagemaker The response's http status code.amazonka-sagemakerThe Amazon Resource Name (ARN) of the flow definition you create.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';*Mamazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemaker&The Amazon Resource Name (ARN) of the  FeatureGroup5. This is a unique identifier for the feature group.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerA free-form description of a  FeatureGroup.amazonka-sagemakerUse this to configure an OfflineFeatureStore(. This parameter allows you to specify:The Amazon Simple Storage Service (Amazon S3) location of an  OfflineStore.A configuration for an Amazon Web Services Glue or Amazon Web Services Hive data catalog.An KMS encryption key to encrypt the Amazon S3 location used for  OfflineStore. If KMS encryption key is not specified, by default we encrypt all data at rest using Amazon Web Services KMS key. By defining your  https://docs.aws.amazon.com/AmazonS3/latest/userguide/bucket-key.htmlbucket-level key for SSE, you can reduce Amazon Web Services KMS requests costs by up to 99 percent.Format for the offline store table. Supported formats are Glue (Default) and  https://iceberg.apache.org/Apache Iceberg.;To learn more about this parameter, see OfflineStoreConfig.amazonka-sagemakerYou can turn the  OnlineStore on or off by specifying True for the EnableOnlineStore flag in OnlineStoreConfig; the default value is False.8You can also include an Amazon Web Services KMS key ID (KMSKeyId!) for at-rest encryption of the  OnlineStore.amazonka-sagemakerThe Amazon Resource Name (ARN) of the IAM execution role used to persist data into the  OfflineStore if an OfflineStoreConfig is provided.amazonka-sagemakerTags used to identify Features in each  FeatureGroup.amazonka-sagemakerThe name of the  FeatureGroup. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account. The name:2Must start and end with an alphanumeric character.Can only contain alphanumeric character and hyphens. Spaces are not allowed.amazonka-sagemakerThe name of the Feature# whose value uniquely identifies a Record defined in the  FeatureStore. Only the latest record per identifier value will be stored in the  OnlineStore. RecordIdentifierFeatureName, must be one of feature definitions' names. You use the RecordIdentifierFeatureName to access data in a  FeatureStore. This name:2Must start and end with an alphanumeric character.Can only contains alphanumeric characters, hyphens, underscores. Spaces are not allowed.amazonka-sagemaker(The name of the feature that stores the  EventTime of a Record in a  FeatureGroup.An  EventTime is a point in time when a new event occurs that corresponds to the creation or update of a Record in a  FeatureGroup. All Records in the  FeatureGroup must have a corresponding  EventTime.An  EventTime can be a String or  Fractional. Fractional:  EventTime9 feature values must be a Unix timestamp in seconds.String:  EventTime feature values must be an ISO-8601 string in the format. The following formats are supported yyyy-MM-dd'T'HH:mm:ssZ and yyyy-MM-dd'T'HH:mm:ss.SSSZ where yyyy, MM, and dd: represent the year, month, and day respectively and HH, mm, ss, and if applicable, SSS represent the hour, month, second and milliseconds respsectively. 'T' and Z are constants.amazonka-sagemaker A list of Feature names and types. Name and Type is compulsory per Feature.Valid feature  FeatureTypes are Integral,  Fractional and String. FeatureName"s cannot be any of the following:  is_deleted,  write_time, api_invocation_timeYou can create up to 2,500 FeatureDefinitions per  FeatureGroup.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - A free-form description of a  FeatureGroup.,  - Use this to configure an OfflineFeatureStore(. This parameter allows you to specify:The Amazon Simple Storage Service (Amazon S3) location of an  OfflineStore.A configuration for an Amazon Web Services Glue or Amazon Web Services Hive data catalog.An KMS encryption key to encrypt the Amazon S3 location used for  OfflineStore. If KMS encryption key is not specified, by default we encrypt all data at rest using Amazon Web Services KMS key. By defining your  https://docs.aws.amazon.com/AmazonS3/latest/userguide/bucket-key.htmlbucket-level key for SSE, you can reduce Amazon Web Services KMS requests costs by up to 99 percent.Format for the offline store table. Supported formats are Glue (Default) and  https://iceberg.apache.org/Apache Iceberg.;To learn more about this parameter, see OfflineStoreConfig.,  - You can turn the  OnlineStore on or off by specifying True for the EnableOnlineStore flag in OnlineStoreConfig; the default value is False.8You can also include an Amazon Web Services KMS key ID (KMSKeyId!) for at-rest encryption of the  OnlineStore.,  - The Amazon Resource Name (ARN) of the IAM execution role used to persist data into the  OfflineStore if an OfflineStoreConfig is provided.,  - Tags used to identify Features in each  FeatureGroup.,  - The name of the  FeatureGroup. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account. The name:2Must start and end with an alphanumeric character.Can only contain alphanumeric character and hyphens. Spaces are not allowed.,  - The name of the Feature# whose value uniquely identifies a Record defined in the  FeatureStore. Only the latest record per identifier value will be stored in the  OnlineStore. RecordIdentifierFeatureName, must be one of feature definitions' names. You use the RecordIdentifierFeatureName to access data in a  FeatureStore. This name:2Must start and end with an alphanumeric character.Can only contains alphanumeric characters, hyphens, underscores. Spaces are not allowed., + - The name of the feature that stores the  EventTime of a Record in a  FeatureGroup.An  EventTime is a point in time when a new event occurs that corresponds to the creation or update of a Record in a  FeatureGroup. All Records in the  FeatureGroup must have a corresponding  EventTime.An  EventTime can be a String or  Fractional. Fractional:  EventTime9 feature values must be a Unix timestamp in seconds.String:  EventTime feature values must be an ISO-8601 string in the format. The following formats are supported yyyy-MM-dd'T'HH:mm:ssZ and yyyy-MM-dd'T'HH:mm:ss.SSSZ where yyyy, MM, and dd: represent the year, month, and day respectively and HH, mm, ss, and if applicable, SSS represent the hour, month, second and milliseconds respsectively. 'T' and Z are constants.,  - A list of Feature names and types. Name and Type is compulsory per Feature.Valid feature  FeatureTypes are Integral,  Fractional and String. FeatureName"s cannot be any of the following:  is_deleted,  write_time, api_invocation_timeYou can create up to 2,500 FeatureDefinitions per  FeatureGroup.amazonka-sagemakerA free-form description of a  FeatureGroup.amazonka-sagemakerUse this to configure an OfflineFeatureStore(. This parameter allows you to specify:The Amazon Simple Storage Service (Amazon S3) location of an  OfflineStore.A configuration for an Amazon Web Services Glue or Amazon Web Services Hive data catalog.An KMS encryption key to encrypt the Amazon S3 location used for  OfflineStore. If KMS encryption key is not specified, by default we encrypt all data at rest using Amazon Web Services KMS key. By defining your  https://docs.aws.amazon.com/AmazonS3/latest/userguide/bucket-key.htmlbucket-level key for SSE, you can reduce Amazon Web Services KMS requests costs by up to 99 percent.Format for the offline store table. Supported formats are Glue (Default) and  https://iceberg.apache.org/Apache Iceberg.;To learn more about this parameter, see OfflineStoreConfig.amazonka-sagemakerYou can turn the  OnlineStore on or off by specifying True for the EnableOnlineStore flag in OnlineStoreConfig; the default value is False.8You can also include an Amazon Web Services KMS key ID (KMSKeyId!) for at-rest encryption of the  OnlineStore.amazonka-sagemakerThe Amazon Resource Name (ARN) of the IAM execution role used to persist data into the  OfflineStore if an OfflineStoreConfig is provided.amazonka-sagemakerTags used to identify Features in each  FeatureGroup.amazonka-sagemakerThe name of the  FeatureGroup. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account. The name:2Must start and end with an alphanumeric character.Can only contain alphanumeric character and hyphens. Spaces are not allowed.amazonka-sagemakerThe name of the Feature# whose value uniquely identifies a Record defined in the  FeatureStore. Only the latest record per identifier value will be stored in the  OnlineStore. RecordIdentifierFeatureName, must be one of feature definitions' names. You use the RecordIdentifierFeatureName to access data in a  FeatureStore. This name:2Must start and end with an alphanumeric character.Can only contains alphanumeric characters, hyphens, underscores. Spaces are not allowed.amazonka-sagemaker(The name of the feature that stores the  EventTime of a Record in a  FeatureGroup.An  EventTime is a point in time when a new event occurs that corresponds to the creation or update of a Record in a  FeatureGroup. All Records in the  FeatureGroup must have a corresponding  EventTime.An  EventTime can be a String or  Fractional. Fractional:  EventTime9 feature values must be a Unix timestamp in seconds.String:  EventTime feature values must be an ISO-8601 string in the format. The following formats are supported yyyy-MM-dd'T'HH:mm:ssZ and yyyy-MM-dd'T'HH:mm:ss.SSSZ where yyyy, MM, and dd: represent the year, month, and day respectively and HH, mm, ss, and if applicable, SSS represent the hour, month, second and milliseconds respsectively. 'T' and Z are constants.amazonka-sagemaker A list of Feature names and types. Name and Type is compulsory per Feature.Valid feature  FeatureTypes are Integral,  Fractional and String. FeatureName"s cannot be any of the following:  is_deleted,  write_time, api_invocation_timeYou can create up to 2,500 FeatureDefinitions per  FeatureGroup.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code., ) - The Amazon Resource Name (ARN) of the  FeatureGroup5. This is a unique identifier for the feature group.amazonka-sagemaker The response's http status code.amazonka-sagemaker&The Amazon Resource Name (ARN) of the  FeatureGroup5. This is a unique identifier for the feature group.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';*Z[amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker1The Amazon Resource Name (ARN) of the experiment.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker"The description of the experiment.amazonka-sagemakerThe name of the experiment as displayed. The name doesn't need to be unique. If you don't specify  DisplayName, the value in ExperimentName is displayed.amazonka-sagemakerA list of tags to associate with the experiment. You can use Search API to search on the tags.amazonka-sagemakerThe name of the experiment. The name must be unique in your Amazon Web Services account and is not case-sensitive.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, % - The description of the experiment.,  - The name of the experiment as displayed. The name doesn't need to be unique. If you don't specify  DisplayName, the value in ExperimentName is displayed.,  - A list of tags to associate with the experiment. You can use Search API to search on the tags.,  - The name of the experiment. The name must be unique in your Amazon Web Services account and is not case-sensitive.amazonka-sagemaker"The description of the experiment.amazonka-sagemakerThe name of the experiment as displayed. The name doesn't need to be unique. If you don't specify  DisplayName, the value in ExperimentName is displayed.amazonka-sagemakerA list of tags to associate with the experiment. You can use Search API to search on the tags.amazonka-sagemakerThe name of the experiment. The name must be unique in your Amazon Web Services account and is not case-sensitive.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 4 - The Amazon Resource Name (ARN) of the experiment., # - The response's http status code.amazonka-sagemaker1The Amazon Resource Name (ARN) of the experiment.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';*Qamazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemaker=The Amazon Resource Name (ARN) of the endpoint configuration.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerSpecifies configuration for how an endpoint performs asynchronous inference. This is a required field in order for your Endpoint to be invoked using  https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_runtime_InvokeEndpointAsync.htmlInvokeEndpointAsync.amazonka-sagemaker A member of CreateEndpointConfig that enables explainers.amazonka-sagemakerThe Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint.1The KmsKeyId can be any of the following formats:Key ID: $1234abcd-12ab-34cd-56ef-1234567890abKey ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab Alias name: alias/ExampleAliasAlias name ARN: 5arn:aws:kms:us-west-2:111122223333:alias/ExampleAliasThe KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint, UpdateEndpoint requests. For more information, refer to the Amazon Web Services Key Management Service section https://docs.aws.amazon.com/kms/latest/developerguide/key-policies.html-Using Key Policies in Amazon Web Services KMSCertain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can't request a KmsKeyId when using an instance type with local storage. If any of the models that you specify in the ProductionVariants parameter use nitro-based instances with local storage, do not specify a value for the KmsKeyId( parameter. If you specify a value for KmsKeyId when using any nitro-based instances with local storage, the call to CreateEndpointConfig fails.For a list of instance types that support local instance storage, see  https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/InstanceStorage.html#instance-store-volumesInstance Store Volumes.For more information about local instance storage encryption, see  https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ssd-instance-store.htmlSSD Instance Store Volumes.amazonka-sagemaker An array of ProductionVariant objects, one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants?. If you use this field, you can only specify one variant for ProductionVariants and one variant for ShadowProductionVariants.amazonka-sagemakerAn array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.amazonka-sagemakerThe name of the endpoint configuration. You specify this name in a CreateEndpoint request.amazonka-sagemaker An array of ProductionVariant objects, one for each model that you want to host at this endpoint.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - Specifies configuration for how an endpoint performs asynchronous inference. This is a required field in order for your Endpoint to be invoked using  https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_runtime_InvokeEndpointAsync.htmlInvokeEndpointAsync.,  - Undocumented member.,  - A member of CreateEndpointConfig that enables explainers.,  - The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint.1The KmsKeyId can be any of the following formats:Key ID: $1234abcd-12ab-34cd-56ef-1234567890abKey ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab Alias name: alias/ExampleAliasAlias name ARN: 5arn:aws:kms:us-west-2:111122223333:alias/ExampleAliasThe KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint, UpdateEndpoint requests. For more information, refer to the Amazon Web Services Key Management Service section https://docs.aws.amazon.com/kms/latest/developerguide/key-policies.html-Using Key Policies in Amazon Web Services KMSCertain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can't request a KmsKeyId when using an instance type with local storage. If any of the models that you specify in the ProductionVariants parameter use nitro-based instances with local storage, do not specify a value for the KmsKeyId( parameter. If you specify a value for KmsKeyId when using any nitro-based instances with local storage, the call to CreateEndpointConfig fails.For a list of instance types that support local instance storage, see  https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/InstanceStorage.html#instance-store-volumesInstance Store Volumes.For more information about local instance storage encryption, see  https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ssd-instance-store.htmlSSD Instance Store Volumes.,  - An array of ProductionVariant objects, one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants?. If you use this field, you can only specify one variant for ProductionVariants and one variant for ShadowProductionVariants.,  - An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.,  - The name of the endpoint configuration. You specify this name in a CreateEndpoint request.,  - An array of ProductionVariant objects, one for each model that you want to host at this endpoint.amazonka-sagemakerSpecifies configuration for how an endpoint performs asynchronous inference. This is a required field in order for your Endpoint to be invoked using  https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_runtime_InvokeEndpointAsync.htmlInvokeEndpointAsync.amazonka-sagemakerUndocumented member.amazonka-sagemaker A member of CreateEndpointConfig that enables explainers.amazonka-sagemakerThe Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint.1The KmsKeyId can be any of the following formats:Key ID: $1234abcd-12ab-34cd-56ef-1234567890abKey ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab Alias name: alias/ExampleAliasAlias name ARN: 5arn:aws:kms:us-west-2:111122223333:alias/ExampleAliasThe KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint, UpdateEndpoint requests. For more information, refer to the Amazon Web Services Key Management Service section https://docs.aws.amazon.com/kms/latest/developerguide/key-policies.html-Using Key Policies in Amazon Web Services KMSCertain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can't request a KmsKeyId when using an instance type with local storage. If any of the models that you specify in the ProductionVariants parameter use nitro-based instances with local storage, do not specify a value for the KmsKeyId( parameter. If you specify a value for KmsKeyId when using any nitro-based instances with local storage, the call to CreateEndpointConfig fails.For a list of instance types that support local instance storage, see  https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/InstanceStorage.html#instance-store-volumesInstance Store Volumes.For more information about local instance storage encryption, see  https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ssd-instance-store.htmlSSD Instance Store Volumes.amazonka-sagemaker An array of ProductionVariant objects, one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants?. If you use this field, you can only specify one variant for ProductionVariants and one variant for ShadowProductionVariants.amazonka-sagemakerAn array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.amazonka-sagemakerThe name of the endpoint configuration. You specify this name in a CreateEndpoint request.amazonka-sagemaker An array of ProductionVariant objects, one for each model that you want to host at this endpoint.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code.,  - The Amazon Resource Name (ARN) of the endpoint configuration.amazonka-sagemaker The response's http status code.amazonka-sagemaker=The Amazon Resource Name (ARN) of the endpoint configuration.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';*amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemaker/The Amazon Resource Name (ARN) of the endpoint.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerAn array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.amazonka-sagemakerThe name of the endpoint.The name must be unique within an Amazon Web Services Region in your Amazon Web Services account. The name is case-insensitive in CreateEndpoint5, but the case is preserved and must be matched in .amazonka-sagemakerThe name of an endpoint configuration. For more information, see CreateEndpointConfig.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - Undocumented member.,  - An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.,  - The name of the endpoint.The name must be unique within an Amazon Web Services Region in your Amazon Web Services account. The name is case-insensitive in CreateEndpoint5, but the case is preserved and must be matched in .,  - The name of an endpoint configuration. For more information, see CreateEndpointConfig.amazonka-sagemakerUndocumented member.amazonka-sagemakerAn array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.amazonka-sagemakerThe name of the endpoint.The name must be unique within an Amazon Web Services Region in your Amazon Web Services account. The name is case-insensitive in CreateEndpoint5, but the case is preserved and must be matched in .amazonka-sagemakerThe name of an endpoint configuration. For more information, see CreateEndpointConfig.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code., 2 - The Amazon Resource Name (ARN) of the endpoint.amazonka-sagemaker The response's http status code.amazonka-sagemaker/The Amazon Resource Name (ARN) of the endpoint.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';* amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe Amazon Web Services KMS key to use when encrypting the EBS volume the edge packaging job runs on.amazonka-sagemaker#Creates tags for the packaging job.amazonka-sagemaker#The name of the edge packaging job.amazonka-sagemakerThe name of the SageMaker Neo compilation job that will be used to locate model artifacts for packaging.amazonka-sagemakerThe name of the model.amazonka-sagemakerThe version of the model.amazonka-sagemakerThe Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to download and upload the model, and to contact SageMaker Neo.amazonka-sagemakerProvides information about the output location for the packaged model.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The Amazon Web Services KMS key to use when encrypting the EBS volume the edge packaging job runs on., & - Creates tags for the packaging job., & - The name of the edge packaging job.,  - The name of the SageMaker Neo compilation job that will be used to locate model artifacts for packaging.,  - The name of the model.,  - The version of the model.,  - The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to download and upload the model, and to contact SageMaker Neo.,  - Provides information about the output location for the packaged model.amazonka-sagemakerThe Amazon Web Services KMS key to use when encrypting the EBS volume the edge packaging job runs on.amazonka-sagemaker#Creates tags for the packaging job.amazonka-sagemaker#The name of the edge packaging job.amazonka-sagemakerThe name of the SageMaker Neo compilation job that will be used to locate model artifacts for packaging.amazonka-sagemakerThe name of the model.amazonka-sagemakerThe version of the model.amazonka-sagemakerThe Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to download and upload the model, and to contact SageMaker Neo.amazonka-sagemakerProvides information about the output location for the packaged model.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';*amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker%The name of the edge deployment plan.amazonka-sagemaker7List of stages to be added to the edge deployment plan.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, ( - The name of the edge deployment plan., : - List of stages to be added to the edge deployment plan.amazonka-sagemaker%The name of the edge deployment plan.amazonka-sagemaker7List of stages to be added to the edge deployment plan.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.amazonka-sagemaker  (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';*Aamazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemaker$The ARN of the edge deployment plan.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerList of stages of the edge deployment plan. The number of stages is limited to 10 per deployment.amazonka-sagemaker8List of tags with which to tag the edge deployment plan.amazonka-sagemaker%The name of the edge deployment plan.amazonka-sagemaker8List of models associated with the edge deployment plan.amazonka-sagemaker4The device fleet used for this edge deployment plan.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - List of stages of the edge deployment plan. The number of stages is limited to 10 per deployment., ; - List of tags with which to tag the edge deployment plan., ( - The name of the edge deployment plan., ; - List of models associated with the edge deployment plan., 7 - The device fleet used for this edge deployment plan.amazonka-sagemakerList of stages of the edge deployment plan. The number of stages is limited to 10 per deployment.amazonka-sagemaker8List of tags with which to tag the edge deployment plan.amazonka-sagemaker%The name of the edge deployment plan.amazonka-sagemaker8List of models associated with the edge deployment plan.amazonka-sagemaker4The device fleet used for this edge deployment plan.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code., ' - The ARN of the edge deployment plan.amazonka-sagemaker The response's http status code.amazonka-sagemaker$The ARN of the edge deployment plan.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';*"amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker5The Amazon Resource Name (ARN) of the created domain.amazonka-sagemakerThe URL to the created domain.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerSpecifies the VPC used for non-EFS traffic. The default value is PublicInternetOnly.PublicInternetOnly - Non-EFS traffic is through a VPC managed by Amazon SageMaker, which allows direct internet accessVpcOnly - All Studio traffic is through the specified VPC and subnetsamazonka-sagemakerThe entity that creates and manages the required security groups for inter-app communication in VPCOnly mode. Required when !CreateDomain.AppNetworkAccessType is VPCOnly and DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is provided.amazonka-sagemaker,The default settings used to create a space.amazonka-sagemakerA collection of Domain settings.amazonka-sagemakerUse KmsKeyId.amazonka-sagemakerSageMaker uses Amazon Web Services KMS to encrypt the EFS volume attached to the domain with an Amazon Web Services managed key by default. For more control, specify a customer managed key.amazonka-sagemakerTags to associated with the Domain. Each tag consists of a key and an optional value. Tag keys must be unique per resource. Tags are searchable using the Search API.Tags that you specify for the Domain are also added to all Apps that the Domain launches.amazonka-sagemakerA name for the domain.amazonka-sagemakerThe mode of authentication that members use to access the domain.amazonka-sagemaker:The default settings to use to create a user profile when  UserSettings% isn't specified in the call to the CreateUserProfile API.SecurityGroups is aggregated when specified in both calls. For all other settings in  UserSettings, the values specified in CreateUserProfile* take precedence over those specified in  CreateDomain.amazonka-sagemaker3The VPC subnets that Studio uses for communication.amazonka-sagemakerThe ID of the Amazon Virtual Private Cloud (VPC) that Studio uses for communication.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - Specifies the VPC used for non-EFS traffic. The default value is PublicInternetOnly.PublicInternetOnly - Non-EFS traffic is through a VPC managed by Amazon SageMaker, which allows direct internet accessVpcOnly - All Studio traffic is through the specified VPC and subnets,  - The entity that creates and manages the required security groups for inter-app communication in VPCOnly mode. Required when !CreateDomain.AppNetworkAccessType is VPCOnly and DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is provided., / - The default settings used to create a space.,  - A collection of Domain settings.,  - Use KmsKeyId.,  - SageMaker uses Amazon Web Services KMS to encrypt the EFS volume attached to the domain with an Amazon Web Services managed key by default. For more control, specify a customer managed key.,  - Tags to associated with the Domain. Each tag consists of a key and an optional value. Tag keys must be unique per resource. Tags are searchable using the Search API.Tags that you specify for the Domain are also added to all Apps that the Domain launches.,  - A name for the domain.,  - The mode of authentication that members use to access the domain., = - The default settings to use to create a user profile when  UserSettings% isn't specified in the call to the CreateUserProfile API.SecurityGroups is aggregated when specified in both calls. For all other settings in  UserSettings, the values specified in CreateUserProfile* take precedence over those specified in  CreateDomain., 6 - The VPC subnets that Studio uses for communication.,  - The ID of the Amazon Virtual Private Cloud (VPC) that Studio uses for communication.amazonka-sagemakerSpecifies the VPC used for non-EFS traffic. The default value is PublicInternetOnly.PublicInternetOnly - Non-EFS traffic is through a VPC managed by Amazon SageMaker, which allows direct internet accessVpcOnly - All Studio traffic is through the specified VPC and subnetsamazonka-sagemakerThe entity that creates and manages the required security groups for inter-app communication in VPCOnly mode. Required when !CreateDomain.AppNetworkAccessType is VPCOnly and DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is provided.amazonka-sagemaker,The default settings used to create a space.amazonka-sagemakerA collection of Domain settings.amazonka-sagemakerUse KmsKeyId.amazonka-sagemakerSageMaker uses Amazon Web Services KMS to encrypt the EFS volume attached to the domain with an Amazon Web Services managed key by default. For more control, specify a customer managed key.amazonka-sagemakerTags to associated with the Domain. Each tag consists of a key and an optional value. Tag keys must be unique per resource. Tags are searchable using the Search API.Tags that you specify for the Domain are also added to all Apps that the Domain launches.amazonka-sagemakerA name for the domain.amazonka-sagemakerThe mode of authentication that members use to access the domain.amazonka-sagemaker:The default settings to use to create a user profile when  UserSettings% isn't specified in the call to the CreateUserProfile API.SecurityGroups is aggregated when specified in both calls. For all other settings in  UserSettings, the values specified in CreateUserProfile* take precedence over those specified in  CreateDomain.amazonka-sagemaker3The VPC subnets that Studio uses for communication.amazonka-sagemakerThe ID of the Amazon Virtual Private Cloud (VPC) that Studio uses for communication.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 8 - The Amazon Resource Name (ARN) of the created domain., ! - The URL to the created domain., # - The response's http status code.amazonka-sagemaker5The Amazon Resource Name (ARN) of the created domain.amazonka-sagemakerThe URL to the created domain.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker$$(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';*amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerA description of the fleet.amazonka-sagemakerWhether to create an Amazon Web Services IoT Role Alias during device fleet creation. The name of the role alias generated will match this pattern: "SageMakerEdge-{DeviceFleetName}".For example, if your device fleet is called "demo-fleet", the name of the role alias will be "SageMakerEdge-demo-fleet".amazonka-sagemakerThe Amazon Resource Name (ARN) that has access to Amazon Web Services Internet of Things (IoT).amazonka-sagemaker%Creates tags for the specified fleet.amazonka-sagemaker1The name of the fleet that the device belongs to.amazonka-sagemakerThe output configuration for storing sample data collected by the fleet.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - A description of the fleet.,  - Whether to create an Amazon Web Services IoT Role Alias during device fleet creation. The name of the role alias generated will match this pattern: "SageMakerEdge-{DeviceFleetName}".For example, if your device fleet is called "demo-fleet", the name of the role alias will be "SageMakerEdge-demo-fleet".,  - The Amazon Resource Name (ARN) that has access to Amazon Web Services Internet of Things (IoT)., ( - Creates tags for the specified fleet., 4 - The name of the fleet that the device belongs to.,  - The output configuration for storing sample data collected by the fleet.amazonka-sagemakerA description of the fleet.amazonka-sagemakerWhether to create an Amazon Web Services IoT Role Alias during device fleet creation. The name of the role alias generated will match this pattern: "SageMakerEdge-{DeviceFleetName}".For example, if your device fleet is called "demo-fleet", the name of the role alias will be "SageMakerEdge-demo-fleet".amazonka-sagemakerThe Amazon Resource Name (ARN) that has access to Amazon Web Services Internet of Things (IoT).amazonka-sagemaker%Creates tags for the specified fleet.amazonka-sagemaker1The name of the fleet that the device belongs to.amazonka-sagemakerThe output configuration for storing sample data collected by the fleet.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.amazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';* amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemaker5The Amazon Resource Name (ARN) of the job definition.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerConfigures the constraints and baselines for the monitoring job.amazonka-sagemaker:Specifies networking configuration for the monitoring job.amazonka-sagemaker(Optional) An array of key-value pairs. For more information, see  https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURLUsing Cost Allocation Tags in the :Amazon Web Services Billing and Cost Management User Guide.amazonka-sagemaker+The name for the monitoring job definition.amazonka-sagemaker5Specifies the container that runs the monitoring job.amazonka-sagemakerA list of inputs for the monitoring job. Currently endpoints are supported as monitoring inputs.amazonka-sagemakerThe Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - Configures the constraints and baselines for the monitoring job., = - Specifies networking configuration for the monitoring job.,  - Undocumented member.,  - (Optional) An array of key-value pairs. For more information, see  https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURLUsing Cost Allocation Tags in the :Amazon Web Services Billing and Cost Management User Guide., . - The name for the monitoring job definition., 8 - Specifies the container that runs the monitoring job.,  - A list of inputs for the monitoring job. Currently endpoints are supported as monitoring inputs.,  - Undocumented member.,  - Undocumented member.,  - The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.amazonka-sagemakerConfigures the constraints and baselines for the monitoring job.amazonka-sagemaker:Specifies networking configuration for the monitoring job.amazonka-sagemakerUndocumented member.amazonka-sagemaker(Optional) An array of key-value pairs. For more information, see  https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURLUsing Cost Allocation Tags in the :Amazon Web Services Billing and Cost Management User Guide.amazonka-sagemaker+The name for the monitoring job definition.amazonka-sagemaker5Specifies the container that runs the monitoring job.amazonka-sagemakerA list of inputs for the monitoring job. Currently endpoints are supported as monitoring inputs.amazonka-sagemakerUndocumented member.amazonka-sagemakerUndocumented member.amazonka-sagemakerThe Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code., 8 - The Amazon Resource Name (ARN) of the job definition.amazonka-sagemaker The response's http status code.amazonka-sagemaker5The Amazon Resource Name (ARN) of the job definition.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';+amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker.The Amazon Resource Name (ARN) of the context.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe description of the context.amazonka-sagemaker+A list of properties to add to the context.amazonka-sagemaker'A list of tags to apply to the context.amazonka-sagemakerThe name of the context. Must be unique to your account in an Amazon Web Services Region.amazonka-sagemakerThe source type, ID, and URI.amazonka-sagemakerThe context type.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, " - The description of the context., . - A list of properties to add to the context., * - A list of tags to apply to the context.,  - The name of the context. Must be unique to your account in an Amazon Web Services Region.,  - The source type, ID, and URI.,  - The context type.amazonka-sagemakerThe description of the context.amazonka-sagemaker+A list of properties to add to the context.amazonka-sagemaker'A list of tags to apply to the context.amazonka-sagemakerThe name of the context. Must be unique to your account in an Amazon Web Services Region.amazonka-sagemakerThe source type, ID, and URI.amazonka-sagemakerThe context type.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 1 - The Amazon Resource Name (ARN) of the context., # - The response's http status code.amazonka-sagemaker.The Amazon Resource Name (ARN) of the context.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';+$amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemakerIf the action is successful, the service sends back an HTTP 200 response. Amazon SageMaker returns the following data in JSON format:CompilationJobArn:: The Amazon Resource Name (ARN) of the compiled job.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerProvides information about the location of input model artifacts, the name and shape of the expected data inputs, and the framework in which the model was trained.amazonka-sagemakerThe Amazon Resource Name (ARN) of a versioned model package. Provide either a ModelPackageVersionArn or an  InputConfig object in the request syntax. The presence of both objects in the CreateCompilationJob" request will return an exception.amazonka-sagemakerAn array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.amazonka-sagemakerA VpcConfig object that specifies the VPC that you want your compilation job to connect to. Control access to your models by configuring the VPC. For more information, see  https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.,  - A VpcConfig object that specifies the VPC that you want your compilation job to connect to. Control access to your models by configuring the VPC. For more information, see  https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.amazonka-sagemakerA VpcConfig object that specifies the VPC that you want your compilation job to connect to. Control access to your models by configuring the VPC. For more information, see  https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.amazonka-sagemakerThe name of the Git repository. The name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).amazonka-sagemakerSpecifies details about the repository, including the URL where the repository is located, the default branch, and credentials to use to access the repository.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.,  - The name of the Git repository. The name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).,  - Specifies details about the repository, including the URL where the repository is located, the default branch, and credentials to use to access the repository.amazonka-sagemakerAn array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.amazonka-sagemakerThe name of the Git repository. The name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).amazonka-sagemakerSpecifies details about the repository, including the URL where the repository is located, the default branch, and credentials to use to access the repository.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code., 8 - The Amazon Resource Name (ARN) of the new repository.amazonka-sagemaker The response's http status code.amazonka-sagemaker5The Amazon Resource Name (ARN) of the new repository.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';+Namazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemaker=The unique ARN assigned to the AutoML job when it is created.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker9A collection of settings used to configure an AutoML job.amazonka-sagemakerDefines the objective metric used to measure the predictive quality of an AutoML job. You provide an AutoMLJobObjective$MetricName and Autopilot infers whether to minimize or maximize it.amazonka-sagemakerGenerates possible candidates without training the models. A candidate is a combination of data preprocessors, algorithms, and algorithm parameter settings.amazonka-sagemakerSpecifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.amazonka-sagemakerDefines the type of supervised learning available for the candidates. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development-problem-types.html>Amazon SageMaker Autopilot problem types and algorithm support.amazonka-sagemakerEach tag consists of a key and an optional value. Tag keys must be unique per resource.amazonka-sagemakerIdentifies an Autopilot job. The name must be unique to your account and is case-insensitive.amazonka-sagemakerAn array of channel objects that describes the input data and its location. Each channel is a named input source. Similar to InputDataConfig supported by . Format(s) supported: CSV, Parquet. A minimum of 500 rows is required for the training dataset. There is not a minimum number of rows required for the validation dataset.amazonka-sagemakerProvides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job. Format(s) supported: CSV.amazonka-sagemaker4The ARN of the role that is used to access the data.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, < - A collection of settings used to configure an AutoML job.,  - Defines the objective metric used to measure the predictive quality of an AutoML job. You provide an AutoMLJobObjective$MetricName and Autopilot infers whether to minimize or maximize it.,  - Generates possible candidates without training the models. A candidate is a combination of data preprocessors, algorithms, and algorithm parameter settings.,  - Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.,  - Defines the type of supervised learning available for the candidates. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development-problem-types.html>Amazon SageMaker Autopilot problem types and algorithm support.,  - Each tag consists of a key and an optional value. Tag keys must be unique per resource.,  - Identifies an Autopilot job. The name must be unique to your account and is case-insensitive.,  - An array of channel objects that describes the input data and its location. Each channel is a named input source. Similar to InputDataConfig supported by . Format(s) supported: CSV, Parquet. A minimum of 500 rows is required for the training dataset. There is not a minimum number of rows required for the validation dataset.,  - Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job. Format(s) supported: CSV., 7 - The ARN of the role that is used to access the data.amazonka-sagemaker9A collection of settings used to configure an AutoML job.amazonka-sagemakerDefines the objective metric used to measure the predictive quality of an AutoML job. You provide an AutoMLJobObjective$MetricName and Autopilot infers whether to minimize or maximize it.amazonka-sagemakerGenerates possible candidates without training the models. A candidate is a combination of data preprocessors, algorithms, and algorithm parameter settings.amazonka-sagemakerSpecifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.amazonka-sagemakerDefines the type of supervised learning available for the candidates. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development-problem-types.html>Amazon SageMaker Autopilot problem types and algorithm support.amazonka-sagemakerEach tag consists of a key and an optional value. Tag keys must be unique per resource.amazonka-sagemakerIdentifies an Autopilot job. The name must be unique to your account and is case-insensitive.amazonka-sagemakerAn array of channel objects that describes the input data and its location. Each channel is a named input source. Similar to InputDataConfig supported by . Format(s) supported: CSV, Parquet. A minimum of 500 rows is required for the training dataset. There is not a minimum number of rows required for the validation dataset.amazonka-sagemakerProvides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job. Format(s) supported: CSV.amazonka-sagemaker4The ARN of the role that is used to access the data.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code.,  - The unique ARN assigned to the AutoML job when it is created.amazonka-sagemaker The response's http status code.amazonka-sagemaker=The unique ARN assigned to the AutoML job when it is created.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';+Z#amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker/The Amazon Resource Name (ARN) of the artifact.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe name of the artifact. Must be unique to your account in an Amazon Web Services Region.amazonka-sagemaker,A list of properties to add to the artifact.amazonka-sagemaker(A list of tags to apply to the artifact.amazonka-sagemaker'The ID, ID type, and URI of the source.amazonka-sagemakerThe artifact type.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The name of the artifact. Must be unique to your account in an Amazon Web Services Region.,  - Undocumented member., / - A list of properties to add to the artifact., + - A list of tags to apply to the artifact., * - The ID, ID type, and URI of the source.,  - The artifact type.amazonka-sagemakerThe name of the artifact. Must be unique to your account in an Amazon Web Services Region.amazonka-sagemakerUndocumented member.amazonka-sagemaker,A list of properties to add to the artifact.amazonka-sagemaker(A list of tags to apply to the artifact.amazonka-sagemaker'The ID, ID type, and URI of the source.amazonka-sagemakerThe artifact type.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 2 - The Amazon Resource Name (ARN) of the artifact., # - The response's http status code.amazonka-sagemaker/The Amazon Resource Name (ARN) of the artifact.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';+eYamazonka-sagemakerSee:  smart constructor.amazonka-sagemaker5The Amazon Resource Name (ARN) of the AppImageConfig.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe KernelGatewayImageConfig. You can only specify one image kernel in the AppImageConfig API. This kernel will be shown to users before the image starts. Once the image runs, all kernels are visible in JupyterLab.amazonka-sagemaker.A list of tags to apply to the AppImageConfig.amazonka-sagemaker?The name of the AppImageConfig. Must be unique to your account.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The KernelGatewayImageConfig. You can only specify one image kernel in the AppImageConfig API. This kernel will be shown to users before the image starts. Once the image runs, all kernels are visible in JupyterLab., 1 - A list of tags to apply to the AppImageConfig.,  - The name of the AppImageConfig. Must be unique to your account.amazonka-sagemakerThe KernelGatewayImageConfig. You can only specify one image kernel in the AppImageConfig API. This kernel will be shown to users before the image starts. Once the image runs, all kernels are visible in JupyterLab.amazonka-sagemaker.A list of tags to apply to the AppImageConfig.amazonka-sagemaker?The name of the AppImageConfig. Must be unique to your account.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 8 - The Amazon Resource Name (ARN) of the AppImageConfig., # - The response's http status code.amazonka-sagemaker5The Amazon Resource Name (ARN) of the AppImageConfig.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';+wamazonka-sagemakerSee:  smart constructor.amazonka-sagemaker*The Amazon Resource Name (ARN) of the app.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe instance type and the Amazon Resource Name (ARN) of the SageMaker image created on the instance. The value of  InstanceType passed as part of the  ResourceSpec in the  CreateApp1 call overrides the value passed as part of the  ResourceSpec4 configured for the user profile or the domain. If  InstanceType( is not specified in any of those three  ResourceSpec values for a  KernelGateway app, the  CreateApp- call fails with a request validation error.amazonka-sagemaker6The name of the space. If this value is not set, then UserProfileName must be set.amazonka-sagemakerEach tag consists of a key and an optional value. Tag keys must be unique per resource.amazonka-sagemaker6The user profile name. If this value is not set, then  SpaceName must be set.amazonka-sagemakerThe domain ID.amazonka-sagemakerThe type of app.amazonka-sagemakerThe name of the app.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The instance type and the Amazon Resource Name (ARN) of the SageMaker image created on the instance. The value of  InstanceType passed as part of the  ResourceSpec in the  CreateApp1 call overrides the value passed as part of the  ResourceSpec4 configured for the user profile or the domain. If  InstanceType( is not specified in any of those three  ResourceSpec values for a  KernelGateway app, the  CreateApp- call fails with a request validation error., 9 - The name of the space. If this value is not set, then UserProfileName must be set.,  - Each tag consists of a key and an optional value. Tag keys must be unique per resource., 9 - The user profile name. If this value is not set, then  SpaceName must be set.,  - The domain ID.,  - The type of app.,  - The name of the app.amazonka-sagemakerThe instance type and the Amazon Resource Name (ARN) of the SageMaker image created on the instance. The value of  InstanceType passed as part of the  ResourceSpec in the  CreateApp1 call overrides the value passed as part of the  ResourceSpec4 configured for the user profile or the domain. If  InstanceType( is not specified in any of those three  ResourceSpec values for a  KernelGateway app, the  CreateApp- call fails with a request validation error.amazonka-sagemaker6The name of the space. If this value is not set, then UserProfileName must be set.amazonka-sagemakerEach tag consists of a key and an optional value. Tag keys must be unique per resource.amazonka-sagemaker6The user profile name. If this value is not set, then  SpaceName must be set.amazonka-sagemakerThe domain ID.amazonka-sagemakerThe type of app.amazonka-sagemakerThe name of the app.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, - - The Amazon Resource Name (ARN) of the app., # - The response's http status code.amazonka-sagemaker*The Amazon Resource Name (ARN) of the app.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';+2amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemaker4The Amazon Resource Name (ARN) of the new algorithm.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerA description of the algorithm.amazonka-sagemakerWhether to certify the algorithm so that it can be listed in Amazon Web Services Marketplace.amazonka-sagemakerSpecifies details about inference jobs that the algorithm runs, including the following:The Amazon ECR paths of containers that contain the inference code and model artifacts.The instance types that the algorithm supports for transform jobs and real-time endpoints used for inference.The input and output content formats that the algorithm supports for inference.amazonka-sagemakerAn array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.amazonka-sagemakerSpecifies configurations for one or more training jobs and that SageMaker runs to test the algorithm's training code and, optionally, one or more batch transform jobs that SageMaker runs to test the algorithm's inference code.amazonka-sagemakerThe name of the algorithm.amazonka-sagemakerSpecifies details about training jobs run by this algorithm, including the following:The Amazon ECR path of the container and the version digest of the algorithm.0The hyperparameters that the algorithm supports.https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.,  - Specifies configurations for one or more training jobs and that SageMaker runs to test the algorithm's training code and, optionally, one or more batch transform jobs that SageMaker runs to test the algorithm's inference code.,  - The name of the algorithm.,  - Specifies details about training jobs run by this algorithm, including the following:The Amazon ECR path of the container and the version digest of the algorithm.0The hyperparameters that the algorithm supports.https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.amazonka-sagemakerSpecifies configurations for one or more training jobs and that SageMaker runs to test the algorithm's training code and, optionally, one or more batch transform jobs that SageMaker runs to test the algorithm's inference code.amazonka-sagemakerThe name of the algorithm.amazonka-sagemakerSpecifies details about training jobs run by this algorithm, including the following:The Amazon ECR path of the container and the version digest of the algorithm.0The hyperparameters that the algorithm supports.https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The Amazon Resource Name (ARN) of the resource that you want to tag.,  - An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.amazonka-sagemakerThe Amazon Resource Name (ARN) of the resource that you want to tag.amazonka-sagemakerAn array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 9 - A list of tags associated with the SageMaker resource., # - The response's http status code.amazonka-sagemaker6A list of tags associated with the SageMaker resource.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';+amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker2The Amazon Resource Name (ARN) of the destination.amazonka-sagemakerThe ARN of the source.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe type of association. The following are suggested uses for each type. Amazon SageMaker places no restrictions on their use.ContributedTo - The source contributed to the destination or had a part in enabling the destination. For example, the training data contributed to the training job.AssociatedWith - The source is connected to the destination. For example, an approval workflow is associated with a model deployment.DerivedFrom - The destination is a modification of the source. For example, a digest output of a channel input for a processing job is derived from the original inputs.Produced - The source generated the destination. For example, a training job produced a model artifact.amazonka-sagemakerThe ARN of the source.amazonka-sagemaker2The Amazon Resource Name (ARN) of the destination.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The type of association. The following are suggested uses for each type. Amazon SageMaker places no restrictions on their use.ContributedTo - The source contributed to the destination or had a part in enabling the destination. For example, the training data contributed to the training job.AssociatedWith - The source is connected to the destination. For example, an approval workflow is associated with a model deployment.DerivedFrom - The destination is a modification of the source. For example, a digest output of a channel input for a processing job is derived from the original inputs.Produced - The source generated the destination. For example, a training job produced a model artifact.,  - The ARN of the source., 5 - The Amazon Resource Name (ARN) of the destination.amazonka-sagemakerThe type of association. The following are suggested uses for each type. Amazon SageMaker places no restrictions on their use.ContributedTo - The source contributed to the destination or had a part in enabling the destination. For example, the training data contributed to the training job.AssociatedWith - The source is connected to the destination. For example, an approval workflow is associated with a model deployment.DerivedFrom - The destination is a modification of the source. For example, a digest output of a channel input for a processing job is derived from the original inputs.Produced - The source generated the destination. For example, a training job produced a model artifact.amazonka-sagemakerThe ARN of the source.amazonka-sagemaker2The Amazon Resource Name (ARN) of the destination.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 5 - The Amazon Resource Name (ARN) of the destination.,  - The ARN of the source., # - The response's http status code.amazonka-sagemaker2The Amazon Resource Name (ARN) of the destination.amazonka-sagemakerThe ARN of the source.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';+ڔamazonka-sagemakerSee:  smart constructor.amazonka-sagemaker-The Amazon Resource Name (ARN) of the action.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker#The new description for the action.amazonka-sagemakerThe new list of properties. Overwrites the current property list.amazonka-sagemakerA list of properties to remove.amazonka-sagemakerThe new status for the action.amazonka-sagemaker!The name of the action to update.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, & - The new description for the action.,  - The new list of properties. Overwrites the current property list., " - A list of properties to remove., ! - The new status for the action., $ - The name of the action to update.amazonka-sagemaker#The new description for the action.amazonka-sagemakerThe new list of properties. Overwrites the current property list.amazonka-sagemakerA list of properties to remove.amazonka-sagemakerThe new status for the action.amazonka-sagemaker!The name of the action to update.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 0 - The Amazon Resource Name (ARN) of the action., # - The response's http status code.amazonka-sagemaker-The Amazon Resource Name (ARN) of the action.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';+ amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker6The Amazon Resource Name (ARN) for the AppImageConfig.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker.The new KernelGateway app to run on the image.amazonka-sagemaker)The name of the AppImageConfig to update.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 1 - The new KernelGateway app to run on the image., , - The name of the AppImageConfig to update.amazonka-sagemaker.The new KernelGateway app to run on the image.amazonka-sagemaker)The name of the AppImageConfig to update.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 9 - The Amazon Resource Name (ARN) for the AppImageConfig., # - The response's http status code.amazonka-sagemaker6The Amazon Resource Name (ARN) for the AppImageConfig.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';+6amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker/The Amazon Resource Name (ARN) of the artifact.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe new name for the artifact.amazonka-sagemakerThe new list of properties. Overwrites the current property list.amazonka-sagemakerA list of properties to remove.amazonka-sagemaker9The Amazon Resource Name (ARN) of the artifact to update.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, ! - The new name for the artifact.,  - The new list of properties. Overwrites the current property list., " - A list of properties to remove., < - The Amazon Resource Name (ARN) of the artifact to update.amazonka-sagemakerThe new name for the artifact.amazonka-sagemakerThe new list of properties. Overwrites the current property list.amazonka-sagemakerA list of properties to remove.amazonka-sagemaker9The Amazon Resource Name (ARN) of the artifact to update.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 2 - The Amazon Resource Name (ARN) of the artifact., # - The response's http status code.amazonka-sagemaker/The Amazon Resource Name (ARN) of the artifact.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';+ amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemakerThe ARN of the Git repository.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe configuration of the git repository, including the URL and the Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the repository. The secret must have a staging label of  AWSCURRENT& and must be in the following format: {"username": UserName, "password": Password}amazonka-sagemaker)The name of the Git repository to update.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The configuration of the git repository, including the URL and the Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the repository. The secret must have a staging label of  AWSCURRENT& and must be in the following format: {"username": UserName, "password": Password}, , - The name of the Git repository to update.amazonka-sagemakerThe configuration of the git repository, including the URL and the Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the repository. The secret must have a staging label of  AWSCURRENT& and must be in the following format: {"username": UserName, "password": Password}amazonka-sagemaker)The name of the Git repository to update.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code., ! - The ARN of the Git repository.amazonka-sagemaker The response's http status code.amazonka-sagemakerThe ARN of the Git repository.amazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';,9amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker.The Amazon Resource Name (ARN) of the context.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker$The new description for the context.amazonka-sagemakerThe new list of properties. Overwrites the current property list.amazonka-sagemakerA list of properties to remove.amazonka-sagemaker"The name of the context to update.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, ' - The new description for the context.,  - The new list of properties. Overwrites the current property list., " - A list of properties to remove., % - The name of the context to update.amazonka-sagemaker$The new description for the context.amazonka-sagemakerThe new list of properties. Overwrites the current property list.amazonka-sagemakerA list of properties to remove.amazonka-sagemaker"The name of the context to update.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 1 - The Amazon Resource Name (ARN) of the context., # - The response's http status code.amazonka-sagemaker.The Amazon Resource Name (ARN) of the context.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';, amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerDescription of the fleet.amazonka-sagemakerWhether to create an Amazon Web Services IoT Role Alias during device fleet creation. The name of the role alias generated will match this pattern: "SageMakerEdge-{DeviceFleetName}".For example, if your device fleet is called "demo-fleet", the name of the role alias will be "SageMakerEdge-demo-fleet".amazonka-sagemaker-The Amazon Resource Name (ARN) of the device.amazonka-sagemakerThe name of the fleet.amazonka-sagemakerOutput configuration for storing sample data collected by the fleet.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - Description of the fleet.,  - Whether to create an Amazon Web Services IoT Role Alias during device fleet creation. The name of the role alias generated will match this pattern: "SageMakerEdge-{DeviceFleetName}".For example, if your device fleet is called "demo-fleet", the name of the role alias will be "SageMakerEdge-demo-fleet"., 0 - The Amazon Resource Name (ARN) of the device.,  - The name of the fleet.,  - Output configuration for storing sample data collected by the fleet.amazonka-sagemakerDescription of the fleet.amazonka-sagemakerWhether to create an Amazon Web Services IoT Role Alias during device fleet creation. The name of the role alias generated will match this pattern: "SageMakerEdge-{DeviceFleetName}".For example, if your device fleet is called "demo-fleet", the name of the role alias will be "SageMakerEdge-demo-fleet".amazonka-sagemaker-The Amazon Resource Name (ARN) of the device.amazonka-sagemakerThe name of the fleet.amazonka-sagemakerOutput configuration for storing sample data collected by the fleet.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.amazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';,qamazonka-sagemakerSee:  smart constructor.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker,The name of the fleet the devices belong to.amazonka-sagemaker4List of devices to register with Edge Manager agent.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, / - The name of the fleet the devices belong to., 7 - List of devices to register with Edge Manager agent.amazonka-sagemaker,The name of the fleet the devices belong to.amazonka-sagemaker4List of devices to register with Edge Manager agent.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.amazonka-sagemaker  (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';,amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker-The Amazon Resource Name (ARN) of the domain.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe entity that creates and manages the required security groups for inter-app communication in VPCOnly mode. Required when !CreateDomain.AppNetworkAccessType is VPCOnly and DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is provided.amazonka-sagemaker>The default settings used to create a space within the Domain.amazonka-sagemakerA collection of settings.amazonka-sagemakerA collection of DomainSettings configuration values to update.amazonka-sagemaker#The ID of the domain to be updated.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The entity that creates and manages the required security groups for inter-app communication in VPCOnly mode. Required when !CreateDomain.AppNetworkAccessType is VPCOnly and DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is provided.,  - The default settings used to create a space within the Domain.,  - A collection of settings.,  - A collection of DomainSettings configuration values to update., & - The ID of the domain to be updated.amazonka-sagemakerThe entity that creates and manages the required security groups for inter-app communication in VPCOnly mode. Required when !CreateDomain.AppNetworkAccessType is VPCOnly and DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is provided.amazonka-sagemaker>The default settings used to create a space within the Domain.amazonka-sagemakerA collection of settings.amazonka-sagemakerA collection of DomainSettings configuration values to update.amazonka-sagemaker#The ID of the domain to be updated.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 0 - The Amazon Resource Name (ARN) of the domain., # - The response's http status code.amazonka-sagemaker-The Amazon Resource Name (ARN) of the domain.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';,70amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemaker/The Amazon Resource Name (ARN) of the endpoint.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe deployment configuration for an endpoint, which contains the desired deployment strategy and rollback configurations.amazonka-sagemakerWhen you are updating endpoint resources with UpdateEndpointInput$RetainAllVariantProperties, whose value is set to true,  ExcludeRetainedVariantProperties specifies the list of type VariantProperty to override with the values provided by EndpointConfig$. If you don't specify a value for ExcludeAllVariantProperties', no variant properties are overridden.amazonka-sagemakerWhen updating endpoint resources, enables or disables the retention of  https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_VariantProperty.htmlvariant properties, such as the instance count or the variant weight. To retain the variant properties of an endpoint when updating it, set RetainAllVariantProperties to true4. To use the variant properties specified in a new EndpointConfig& call when updating an endpoint, set RetainAllVariantProperties to false. The default is false.amazonka-sagemakerSpecifies whether to reuse the last deployment configuration. The default value is false (the configuration is not reused).amazonka-sagemakerThe name of the endpoint whose configuration you want to update.amazonka-sagemaker+The name of the new endpoint configuration.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The deployment configuration for an endpoint, which contains the desired deployment strategy and rollback configurations.,  - When you are updating endpoint resources with UpdateEndpointInput$RetainAllVariantProperties, whose value is set to true,  ExcludeRetainedVariantProperties specifies the list of type VariantProperty to override with the values provided by EndpointConfig$. If you don't specify a value for ExcludeAllVariantProperties', no variant properties are overridden.,  - When updating endpoint resources, enables or disables the retention of  https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_VariantProperty.htmlvariant properties, such as the instance count or the variant weight. To retain the variant properties of an endpoint when updating it, set RetainAllVariantProperties to true4. To use the variant properties specified in a new EndpointConfig& call when updating an endpoint, set RetainAllVariantProperties to false. The default is false.,  - Specifies whether to reuse the last deployment configuration. The default value is false (the configuration is not reused).,  - The name of the endpoint whose configuration you want to update., . - The name of the new endpoint configuration.amazonka-sagemakerThe deployment configuration for an endpoint, which contains the desired deployment strategy and rollback configurations.amazonka-sagemakerWhen you are updating endpoint resources with UpdateEndpointInput$RetainAllVariantProperties, whose value is set to true,  ExcludeRetainedVariantProperties specifies the list of type VariantProperty to override with the values provided by EndpointConfig$. If you don't specify a value for ExcludeAllVariantProperties', no variant properties are overridden.amazonka-sagemakerWhen updating endpoint resources, enables or disables the retention of  https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_VariantProperty.htmlvariant properties, such as the instance count or the variant weight. To retain the variant properties of an endpoint when updating it, set RetainAllVariantProperties to true4. To use the variant properties specified in a new EndpointConfig& call when updating an endpoint, set RetainAllVariantProperties to false. The default is false.amazonka-sagemakerSpecifies whether to reuse the last deployment configuration. The default value is false (the configuration is not reused).amazonka-sagemakerThe name of the endpoint whose configuration you want to update.amazonka-sagemaker+The name of the new endpoint configuration.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code., 2 - The Amazon Resource Name (ARN) of the endpoint.amazonka-sagemaker The response's http status code.amazonka-sagemaker/The Amazon Resource Name (ARN) of the endpoint.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';,? amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemaker7The Amazon Resource Name (ARN) of the updated endpoint.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker+The name of an existing SageMaker endpoint.amazonka-sagemakerAn object that provides new capacity and weight values for a variant.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, . - The name of an existing SageMaker endpoint.,  - An object that provides new capacity and weight values for a variant.amazonka-sagemaker+The name of an existing SageMaker endpoint.amazonka-sagemakerAn object that provides new capacity and weight values for a variant.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code., : - The Amazon Resource Name (ARN) of the updated endpoint.amazonka-sagemaker The response's http status code.amazonka-sagemaker7The Amazon Resource Name (ARN) of the updated endpoint.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';,Iamazonka-sagemakerSee:  smart constructor.amazonka-sagemaker1The Amazon Resource Name (ARN) of the experiment.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker"The description of the experiment.amazonka-sagemakerThe name of the experiment as displayed. The name doesn't need to be unique. If  DisplayName isn't specified, ExperimentName is displayed.amazonka-sagemaker%The name of the experiment to update.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, % - The description of the experiment.,  - The name of the experiment as displayed. The name doesn't need to be unique. If  DisplayName isn't specified, ExperimentName is displayed., ( - The name of the experiment to update.amazonka-sagemaker"The description of the experiment.amazonka-sagemakerThe name of the experiment as displayed. The name doesn't need to be unique. If  DisplayName isn't specified, ExperimentName is displayed.amazonka-sagemaker%The name of the experiment to update.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 4 - The Amazon Resource Name (ARN) of the experiment., # - The response's http status code.amazonka-sagemaker1The Amazon Resource Name (ARN) of the experiment.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';,Tp amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemakerThe Amazon Resource Number (ARN) of the feature group that you're updating.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerUpdates the feature group. Updating a feature group is an asynchronous operation. When you get an HTTP 200 response, you've made a valid request. It takes some time after you've made a valid request for Feature Store to update the feature group.amazonka-sagemaker3The name of the feature group that you're updating.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - Updates the feature group. Updating a feature group is an asynchronous operation. When you get an HTTP 200 response, you've made a valid request. It takes some time after you've made a valid request for Feature Store to update the feature group., 6 - The name of the feature group that you're updating.amazonka-sagemakerUpdates the feature group. Updating a feature group is an asynchronous operation. When you get an HTTP 200 response, you've made a valid request. It takes some time after you've made a valid request for Feature Store to update the feature group.amazonka-sagemaker3The name of the feature group that you're updating.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code.,  - The Amazon Resource Number (ARN) of the feature group that you're updating.amazonka-sagemaker The response's http status code.amazonka-sagemakerThe Amazon Resource Number (ARN) of the feature group that you're updating.amazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';,^[amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerA description that you can write to better describe the feature.amazonka-sagemakerA list of key-value pairs that you can add to better describe the feature.amazonka-sagemakerA list of parameter keys that you can specify to remove parameters that describe your feature.amazonka-sagemakerThe name of the feature group containing the feature that you're updating.amazonka-sagemaker-The name of the feature that you're updating.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - A description that you can write to better describe the feature.,  - A list of key-value pairs that you can add to better describe the feature.,  - A list of parameter keys that you can specify to remove parameters that describe your feature.,  - The name of the feature group containing the feature that you're updating., 0 - The name of the feature that you're updating.amazonka-sagemakerA description that you can write to better describe the feature.amazonka-sagemakerA list of key-value pairs that you can add to better describe the feature.amazonka-sagemakerA list of parameter keys that you can specify to remove parameters that describe your feature.amazonka-sagemakerThe name of the feature group containing the feature that you're updating.amazonka-sagemaker-The name of the feature that you're updating.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.amazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';,guamazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemaker2The Amazon Resource Name (ARN) of the updated hub.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker!A description of the updated hub.amazonka-sagemakerThe display name of the hub.amazonka-sagemaker$The searchable keywords for the hub.amazonka-sagemakerThe name of the hub to update.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, $ - A description of the updated hub.,  - The display name of the hub., ' - The searchable keywords for the hub., ! - The name of the hub to update.amazonka-sagemaker!A description of the updated hub.amazonka-sagemakerThe display name of the hub.amazonka-sagemaker$The searchable keywords for the hub.amazonka-sagemakerThe name of the hub to update.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code., 5 - The Amazon Resource Name (ARN) of the updated hub.amazonka-sagemaker The response's http status code.amazonka-sagemaker2The Amazon Resource Name (ARN) of the updated hub.amazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';,ramazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe ARN of the image.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker)A list of properties to delete. Only the  Description and  DisplayName properties can be deleted.amazonka-sagemaker"The new description for the image.amazonka-sagemaker#The new display name for the image.amazonka-sagemakerThe new ARN for the IAM role that enables Amazon SageMaker to perform tasks on your behalf.amazonka-sagemaker The name of the image to update.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, , - A list of properties to delete. Only the  Description and  DisplayName properties can be deleted., % - The new description for the image., & - The new display name for the image.,  - The new ARN for the IAM role that enables Amazon SageMaker to perform tasks on your behalf., # - The name of the image to update.amazonka-sagemaker)A list of properties to delete. Only the  Description and  DisplayName properties can be deleted.amazonka-sagemaker"The new description for the image.amazonka-sagemaker#The new display name for the image.amazonka-sagemakerThe new ARN for the IAM role that enables Amazon SageMaker to perform tasks on your behalf.amazonka-sagemaker The name of the image to update.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The ARN of the image., # - The response's http status code.amazonka-sagemakerThe ARN of the image.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';,n amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe ARN of the image version.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe alias of the image version.amazonka-sagemakerA list of aliases to add.amazonka-sagemakerA list of aliases to delete.amazonka-sagemaker Indicates Horovod compatibility.amazonka-sagemaker+Indicates SageMaker job type compatibility.TRAINING: The image version is compatible with SageMaker training jobs. INFERENCE: The image version is compatible with SageMaker inference jobs.NOTEBOOK_KERNEL: The image version is compatible with SageMaker notebook kernels.amazonka-sagemaker;The machine learning framework vended in the image version.amazonka-sagemaker#Indicates CPU or GPU compatibility.CPU+: The image version is compatible with CPU.GPU+: The image version is compatible with GPU.amazonka-sagemaker3The supported programming language and its version.amazonka-sagemaker0The maintainer description of the image version.amazonka-sagemakerThe availability of the image version specified by the maintainer. NOT_PROVIDED: The maintainers did not provide a status for image version stability.STABLE: The image version is stable.TO_BE_ARCHIVED: The image version is set to be archived. Custom image versions that are set to be archived are automatically archived after three months.ARCHIVED: The image version is archived. Archived image versions are not searchable and are no longer actively supported.amazonka-sagemakerThe version of the image.amazonka-sagemakerThe name of the image.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, " - The alias of the image version.,  - A list of aliases to add.,  - A list of aliases to delete., # - Indicates Horovod compatibility., . - Indicates SageMaker job type compatibility.TRAINING: The image version is compatible with SageMaker training jobs. INFERENCE: The image version is compatible with SageMaker inference jobs.NOTEBOOK_KERNEL: The image version is compatible with SageMaker notebook kernels., > - The machine learning framework vended in the image version., & - Indicates CPU or GPU compatibility.CPU+: The image version is compatible with CPU.GPU+: The image version is compatible with GPU., 6 - The supported programming language and its version., 3 - The maintainer description of the image version.,  - The availability of the image version specified by the maintainer. NOT_PROVIDED: The maintainers did not provide a status for image version stability.STABLE: The image version is stable.TO_BE_ARCHIVED: The image version is set to be archived. Custom image versions that are set to be archived are automatically archived after three months.ARCHIVED: The image version is archived. Archived image versions are not searchable and are no longer actively supported.,  - The version of the image.,  - The name of the image.amazonka-sagemakerThe alias of the image version.amazonka-sagemakerA list of aliases to add.amazonka-sagemakerA list of aliases to delete.amazonka-sagemaker Indicates Horovod compatibility.amazonka-sagemaker+Indicates SageMaker job type compatibility.TRAINING: The image version is compatible with SageMaker training jobs. INFERENCE: The image version is compatible with SageMaker inference jobs.NOTEBOOK_KERNEL: The image version is compatible with SageMaker notebook kernels.amazonka-sagemaker;The machine learning framework vended in the image version.amazonka-sagemaker#Indicates CPU or GPU compatibility.CPU+: The image version is compatible with CPU.GPU+: The image version is compatible with GPU.amazonka-sagemaker3The supported programming language and its version.amazonka-sagemaker0The maintainer description of the image version.amazonka-sagemakerThe availability of the image version specified by the maintainer. NOT_PROVIDED: The maintainers did not provide a status for image version stability.STABLE: The image version is stable.TO_BE_ARCHIVED: The image version is set to be archived. Custom image versions that are set to be archived are automatically archived after three months.ARCHIVED: The image version is archived. Archived image versions are not searchable and are no longer actively supported.amazonka-sagemakerThe version of the image.amazonka-sagemakerThe name of the image.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The ARN of the image version., # - The response's http status code.amazonka-sagemakerThe ARN of the image version.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemaker""(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';,amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemaker,The ARN of the updated inference experiment.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe Amazon S3 location and configuration for storing inference request and response data.amazonka-sagemaker,The description of the inference experiment.amazonka-sagemaker An array of ModelVariantConfig objects. There is one for each variant, whose infrastructure configuration you want to update.amazonka-sagemakerThe duration for which the inference experiment will run. If the status of the inference experiment is Created, then you can update both the start and end dates. If the status of the inference experiment is Running(, then you can update only the end date.amazonka-sagemakerThe configuration of  ShadowMode inference experiment type. Use this field to specify a production variant which takes all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant also specify the percentage of requests that Amazon SageMaker replicates.amazonka-sagemaker3The name of the inference experiment to be updated.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The Amazon S3 location and configuration for storing inference request and response data., / - The description of the inference experiment.,  - An array of ModelVariantConfig objects. There is one for each variant, whose infrastructure configuration you want to update.,  - The duration for which the inference experiment will run. If the status of the inference experiment is Created, then you can update both the start and end dates. If the status of the inference experiment is Running(, then you can update only the end date.,  - The configuration of  ShadowMode inference experiment type. Use this field to specify a production variant which takes all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant also specify the percentage of requests that Amazon SageMaker replicates., 6 - The name of the inference experiment to be updated.amazonka-sagemakerThe Amazon S3 location and configuration for storing inference request and response data.amazonka-sagemaker,The description of the inference experiment.amazonka-sagemaker An array of ModelVariantConfig objects. There is one for each variant, whose infrastructure configuration you want to update.amazonka-sagemakerThe duration for which the inference experiment will run. If the status of the inference experiment is Created, then you can update both the start and end dates. If the status of the inference experiment is Running(, then you can update only the end date.amazonka-sagemakerThe configuration of  ShadowMode inference experiment type. Use this field to specify a production variant which takes all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant also specify the percentage of requests that Amazon SageMaker replicates.amazonka-sagemaker3The name of the inference experiment to be updated.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code., / - The ARN of the updated inference experiment.amazonka-sagemaker The response's http status code.amazonka-sagemaker,The ARN of the updated inference experiment.amazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';,amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemaker9The Amazon Resource Name (ARN) of the updated model card.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker4The updated model card content. Content must be in  https://docs.aws.amazon.com/sagemaker/latest/dg/model-cards-api-json-schema.htmlmodel card JSON schema and provided as a string.When updating model card content, be sure to include the full content and not just updated content.amazonka-sagemakerThe approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.Draft': The model card is a work in progress. PendingReview#: The model card is pending review.Approved: The model card is approved.Archived: The model card is archived. No more updates should be made to the model card, but it can still be exported.amazonka-sagemaker%The name of the model card to update.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 7 - The updated model card content. Content must be in  https://docs.aws.amazon.com/sagemaker/latest/dg/model-cards-api-json-schema.htmlmodel card JSON schema and provided as a string.When updating model card content, be sure to include the full content and not just updated content.,  - The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.Draft': The model card is a work in progress. PendingReview#: The model card is pending review.Approved: The model card is approved.Archived: The model card is archived. No more updates should be made to the model card, but it can still be exported., ( - The name of the model card to update.amazonka-sagemaker4The updated model card content. Content must be in  https://docs.aws.amazon.com/sagemaker/latest/dg/model-cards-api-json-schema.htmlmodel card JSON schema and provided as a string.When updating model card content, be sure to include the full content and not just updated content.amazonka-sagemakerThe approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.Draft': The model card is a work in progress. PendingReview#: The model card is pending review.Approved: The model card is approved.Archived: The model card is archived. No more updates should be made to the model card, but it can still be exported.amazonka-sagemaker%The name of the model card to update.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code., < - The Amazon Resource Name (ARN) of the updated model card.amazonka-sagemaker The response's http status code.amazonka-sagemaker9The Amazon Resource Name (ARN) of the updated model card.amazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';,amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemaker,The Amazon Resource Name (ARN) of the model.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerAn array of additional Inference Specification objects to be added to the existing array additional Inference Specification. Total number of additional Inference Specifications can not exceed 15. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.amazonka-sagemaker3A description for the approval status of the model.amazonka-sagemakerThe metadata properties associated with the model package versions.amazonka-sagemakerThe metadata properties associated with the model package versions to remove.amazonka-sagemaker!The approval status of the model.amazonka-sagemaker4The Amazon Resource Name (ARN) of the model package.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - An array of additional Inference Specification objects to be added to the existing array additional Inference Specification. Total number of additional Inference Specifications can not exceed 15. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts., 6 - A description for the approval status of the model.,  - The metadata properties associated with the model package versions.,  - The metadata properties associated with the model package versions to remove., $ - The approval status of the model., 7 - The Amazon Resource Name (ARN) of the model package.amazonka-sagemakerAn array of additional Inference Specification objects to be added to the existing array additional Inference Specification. Total number of additional Inference Specifications can not exceed 15. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.amazonka-sagemaker3A description for the approval status of the model.amazonka-sagemakerThe metadata properties associated with the model package versions.amazonka-sagemakerThe metadata properties associated with the model package versions to remove.amazonka-sagemaker!The approval status of the model.amazonka-sagemaker4The Amazon Resource Name (ARN) of the model package.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code., / - The Amazon Resource Name (ARN) of the model.amazonka-sagemaker The response's http status code.amazonka-sagemaker,The Amazon Resource Name (ARN) of the model.amazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';,famazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe name of a monitoring alert.amazonka-sagemaker The response's http status code.amazonka-sagemaker:The Amazon Resource Name (ARN) of the monitoring schedule.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker"The name of a monitoring schedule.amazonka-sagemakerThe name of a monitoring alert.amazonka-sagemakerWithin EvaluationPeriod3, how many execution failures will raise an alert.amazonka-sagemakerThe number of most recent monitoring executions to consider when evaluating alert status.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, % - The name of a monitoring schedule., " - The name of a monitoring alert.,  - Within EvaluationPeriod3, how many execution failures will raise an alert.,  - The number of most recent monitoring executions to consider when evaluating alert status.amazonka-sagemaker"The name of a monitoring schedule.amazonka-sagemakerThe name of a monitoring alert.amazonka-sagemakerWithin EvaluationPeriod3, how many execution failures will raise an alert.amazonka-sagemakerThe number of most recent monitoring executions to consider when evaluating alert status.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, " - The name of a monitoring alert., # - The response's http status code., = - The Amazon Resource Name (ARN) of the monitoring schedule.amazonka-sagemakerThe name of a monitoring alert.amazonka-sagemaker The response's http status code.amazonka-sagemaker:The Amazon Resource Name (ARN) of the monitoring schedule.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';,t amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemaker:The Amazon Resource Name (ARN) of the monitoring schedule.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe name of the monitoring schedule. The name must be unique within an Amazon Web Services Region within an Amazon Web Services account.amazonka-sagemakerThe configuration object that specifies the monitoring schedule and defines the monitoring job.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The name of the monitoring schedule. The name must be unique within an Amazon Web Services Region within an Amazon Web Services account.,  - The configuration object that specifies the monitoring schedule and defines the monitoring job.amazonka-sagemakerThe name of the monitoring schedule. The name must be unique within an Amazon Web Services Region within an Amazon Web Services account.amazonka-sagemakerThe configuration object that specifies the monitoring schedule and defines the monitoring job.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code., = - The Amazon Resource Name (ARN) of the monitoring schedule.amazonka-sagemaker The response's http status code.amazonka-sagemaker:The Amazon Resource Name (ARN) of the monitoring schedule.amazonka-sagemakeramazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';-"amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerA list of the Elastic Inference (EI) instance types to associate with this notebook instance. Currently only one EI instance type can be associated with a notebook instance. For more information, see  7https://docs.aws.amazon.com/sagemaker/latest/dg/ei.html+Using Elastic Inference in Amazon SageMaker.amazonka-sagemakerAn array of up to three Git repositories to associate with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in  https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.htmlAmazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html>Associating Git Repositories with SageMaker Notebook Instances.amazonka-sagemakerThe Git repository to associate with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in  https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.htmlAmazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html>Associating Git Repositories with SageMaker Notebook Instances.amazonka-sagemakerA list of the Elastic Inference (EI) instance types to remove from this notebook instance. This operation is idempotent. If you specify an accelerator type that is not associated with the notebook instance when you call this method, it does not throw an error.amazonka-sagemakerA list of names or URLs of the default Git repositories to remove from this notebook instance. This operation is idempotent. If you specify a Git repository that is not associated with the notebook instance when you call this method, it does not throw an error.amazonka-sagemakerThe name or URL of the default Git repository to remove from this notebook instance. This operation is idempotent. If you specify a Git repository that is not associated with the notebook instance when you call this method, it does not throw an error.amazonka-sagemakerSet to true to remove the notebook instance lifecycle configuration currently associated with the notebook instance. This operation is idempotent. If you specify a lifecycle configuration that is not associated with the notebook instance when you call this method, it does not throw an error.amazonka-sagemaker>Information on the IMDS configuration of the notebook instanceamazonka-sagemaker$The Amazon ML compute instance type.amazonka-sagemakerThe name of a lifecycle configuration to associate with the notebook instance. For information about lifestyle configurations, see  https://docs.aws.amazon.com/sagemaker/latest/dg/notebook-lifecycle-config.html2Step 2.1: (Optional) Customize a Notebook Instance.amazonka-sagemakerThe Amazon Resource Name (ARN) of the IAM role that SageMaker can assume to access the notebook instance. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-roles.htmlSageMaker Roles.To be able to pass this role to SageMaker, the caller of this API must have the  iam:PassRole permission.amazonka-sagemakerWhether root access is enabled or disabled for users of the notebook instance. The default value is Enabled.If you set this to Disabled, users don't have root access on the notebook instance, but lifecycle configuration scripts still run with root permissions.amazonka-sagemakerThe size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB. ML storage volumes are encrypted, so SageMaker can't determine the amount of available free space on the volume. Because of this, you can increase the volume size when you update a notebook instance, but you can't decrease the volume size. If you want to decrease the size of the ML storage volume in use, create a new notebook instance with the desired size.amazonka-sagemaker,The name of the notebook instance to update.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - A list of the Elastic Inference (EI) instance types to associate with this notebook instance. Currently only one EI instance type can be associated with a notebook instance. For more information, see  7https://docs.aws.amazon.com/sagemaker/latest/dg/ei.html+Using Elastic Inference in Amazon SageMaker.,  - An array of up to three Git repositories to associate with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in  https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.htmlAmazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html>Associating Git Repositories with SageMaker Notebook Instances.,  - The Git repository to associate with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in  https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.htmlAmazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html>Associating Git Repositories with SageMaker Notebook Instances.,  - A list of the Elastic Inference (EI) instance types to remove from this notebook instance. This operation is idempotent. If you specify an accelerator type that is not associated with the notebook instance when you call this method, it does not throw an error.,  - A list of names or URLs of the default Git repositories to remove from this notebook instance. This operation is idempotent. If you specify a Git repository that is not associated with the notebook instance when you call this method, it does not throw an error.,  - The name or URL of the default Git repository to remove from this notebook instance. This operation is idempotent. If you specify a Git repository that is not associated with the notebook instance when you call this method, it does not throw an error.,  - Set to true to remove the notebook instance lifecycle configuration currently associated with the notebook instance. This operation is idempotent. If you specify a lifecycle configuration that is not associated with the notebook instance when you call this method, it does not throw an error.,  - Information on the IMDS configuration of the notebook instance, ' - The Amazon ML compute instance type.,  - The name of a lifecycle configuration to associate with the notebook instance. For information about lifestyle configurations, see  https://docs.aws.amazon.com/sagemaker/latest/dg/notebook-lifecycle-config.html2Step 2.1: (Optional) Customize a Notebook Instance.,  - The Amazon Resource Name (ARN) of the IAM role that SageMaker can assume to access the notebook instance. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-roles.htmlSageMaker Roles.To be able to pass this role to SageMaker, the caller of this API must have the  iam:PassRole permission.,  - Whether root access is enabled or disabled for users of the notebook instance. The default value is Enabled.If you set this to Disabled, users don't have root access on the notebook instance, but lifecycle configuration scripts still run with root permissions.,  - The size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB. ML storage volumes are encrypted, so SageMaker can't determine the amount of available free space on the volume. Because of this, you can increase the volume size when you update a notebook instance, but you can't decrease the volume size. If you want to decrease the size of the ML storage volume in use, create a new notebook instance with the desired size., / - The name of the notebook instance to update.amazonka-sagemakerA list of the Elastic Inference (EI) instance types to associate with this notebook instance. Currently only one EI instance type can be associated with a notebook instance. For more information, see  7https://docs.aws.amazon.com/sagemaker/latest/dg/ei.html+Using Elastic Inference in Amazon SageMaker.amazonka-sagemakerAn array of up to three Git repositories to associate with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in  https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.htmlAmazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html>Associating Git Repositories with SageMaker Notebook Instances.amazonka-sagemakerThe Git repository to associate with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in  https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.htmlAmazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html>Associating Git Repositories with SageMaker Notebook Instances.amazonka-sagemakerA list of the Elastic Inference (EI) instance types to remove from this notebook instance. This operation is idempotent. If you specify an accelerator type that is not associated with the notebook instance when you call this method, it does not throw an error.amazonka-sagemakerA list of names or URLs of the default Git repositories to remove from this notebook instance. This operation is idempotent. If you specify a Git repository that is not associated with the notebook instance when you call this method, it does not throw an error.amazonka-sagemakerThe name or URL of the default Git repository to remove from this notebook instance. This operation is idempotent. If you specify a Git repository that is not associated with the notebook instance when you call this method, it does not throw an error.amazonka-sagemakerSet to true to remove the notebook instance lifecycle configuration currently associated with the notebook instance. This operation is idempotent. If you specify a lifecycle configuration that is not associated with the notebook instance when you call this method, it does not throw an error.amazonka-sagemaker>Information on the IMDS configuration of the notebook instanceamazonka-sagemaker$The Amazon ML compute instance type.amazonka-sagemakerThe name of a lifecycle configuration to associate with the notebook instance. For information about lifestyle configurations, see  https://docs.aws.amazon.com/sagemaker/latest/dg/notebook-lifecycle-config.html2Step 2.1: (Optional) Customize a Notebook Instance.amazonka-sagemakerThe Amazon Resource Name (ARN) of the IAM role that SageMaker can assume to access the notebook instance. For more information, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-roles.htmlSageMaker Roles.To be able to pass this role to SageMaker, the caller of this API must have the  iam:PassRole permission.amazonka-sagemakerWhether root access is enabled or disabled for users of the notebook instance. The default value is Enabled.If you set this to Disabled, users don't have root access on the notebook instance, but lifecycle configuration scripts still run with root permissions.amazonka-sagemakerThe size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB. ML storage volumes are encrypted, so SageMaker can't determine the amount of available free space on the volume. Because of this, you can increase the volume size when you update a notebook instance, but you can't decrease the volume size. If you want to decrease the size of the ML storage volume in use, create a new notebook instance with the desired size.amazonka-sagemaker,The name of the notebook instance to update.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemaker$$(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';-k amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe shell script that runs only once, when you create a notebook instance. The shell script must be a base64-encoded string.amazonka-sagemakerThe shell script that runs every time you start a notebook instance, including when you create the notebook instance. The shell script must be a base64-encoded string.amazonka-sagemaker(The name of the lifecycle configuration.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The shell script that runs only once, when you create a notebook instance. The shell script must be a base64-encoded string.,  - The shell script that runs every time you start a notebook instance, including when you create the notebook instance. The shell script must be a base64-encoded string., + - The name of the lifecycle configuration.amazonka-sagemakerThe shell script that runs only once, when you create a notebook instance. The shell script must be a base64-encoded string.amazonka-sagemakerThe shell script that runs every time you start a notebook instance, including when you create the notebook instance. The shell script must be a base64-encoded string.amazonka-sagemaker(The name of the lifecycle configuration.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';-'amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker7The Amazon Resource Name (ARN) of the updated pipeline.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerIf specified, it applies to all executions of this pipeline by default.amazonka-sagemakerThe JSON pipeline definition.amazonka-sagemakerThe location of the pipeline definition stored in Amazon S3. If specified, SageMaker will retrieve the pipeline definition from this location.amazonka-sagemaker The description of the pipeline.amazonka-sagemaker!The display name of the pipeline.amazonka-sagemakerThe Amazon Resource Name (ARN) that the pipeline uses to execute.amazonka-sagemaker#The name of the pipeline to update.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - If specified, it applies to all executions of this pipeline by default.,  - The JSON pipeline definition.,  - The location of the pipeline definition stored in Amazon S3. If specified, SageMaker will retrieve the pipeline definition from this location., # - The description of the pipeline., $ - The display name of the pipeline.,  - The Amazon Resource Name (ARN) that the pipeline uses to execute., & - The name of the pipeline to update.amazonka-sagemakerIf specified, it applies to all executions of this pipeline by default.amazonka-sagemakerThe JSON pipeline definition.amazonka-sagemakerThe location of the pipeline definition stored in Amazon S3. If specified, SageMaker will retrieve the pipeline definition from this location.amazonka-sagemaker The description of the pipeline.amazonka-sagemaker!The display name of the pipeline.amazonka-sagemakerThe Amazon Resource Name (ARN) that the pipeline uses to execute.amazonka-sagemaker#The name of the pipeline to update.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, : - The Amazon Resource Name (ARN) of the updated pipeline., # - The response's http status code.amazonka-sagemaker7The Amazon Resource Name (ARN) of the updated pipeline.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';-2amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe Amazon Resource Name (ARN) of the updated pipeline execution.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThis configuration, if specified, overrides the parallelism configuration of the parent pipeline for this specific run.amazonka-sagemaker*The description of the pipeline execution.amazonka-sagemaker+The display name of the pipeline execution.amazonka-sagemaker9The Amazon Resource Name (ARN) of the pipeline execution.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - This configuration, if specified, overrides the parallelism configuration of the parent pipeline for this specific run., - - The description of the pipeline execution., . - The display name of the pipeline execution., < - The Amazon Resource Name (ARN) of the pipeline execution.amazonka-sagemakerThis configuration, if specified, overrides the parallelism configuration of the parent pipeline for this specific run.amazonka-sagemaker*The description of the pipeline execution.amazonka-sagemaker+The display name of the pipeline execution.amazonka-sagemaker9The Amazon Resource Name (ARN) of the pipeline execution.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The Amazon Resource Name (ARN) of the updated pipeline execution., # - The response's http status code.amazonka-sagemakerThe Amazon Resource Name (ARN) of the updated pipeline execution.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';-Famazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemaker.The Amazon Resource Name (ARN) of the project.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The description for the project.amazonka-sagemakerThe product ID and provisioning artifact ID to provision a service catalog. The provisioning artifact ID will default to the latest provisioning artifact ID of the product, if you don't provide the provisioning artifact ID. For more information, see  https://docs.aws.amazon.com/servicecatalog/latest/adminguide/introduction.html+What is Amazon Web Services Service Catalog.amazonka-sagemakerAn array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources. In addition, the project must have tag update constraints set in order to include this parameter in the request. For more information, see  https://docs.aws.amazon.com/servicecatalog/latest/adminguide/constraints-resourceupdate.html:Amazon Web Services Service Catalog Tag Update Constraints.amazonka-sagemakerThe name of the project.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The description for the project.,  - The product ID and provisioning artifact ID to provision a service catalog. The provisioning artifact ID will default to the latest provisioning artifact ID of the product, if you don't provide the provisioning artifact ID. For more information, see  https://docs.aws.amazon.com/servicecatalog/latest/adminguide/introduction.html+What is Amazon Web Services Service Catalog.,  - An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources. In addition, the project must have tag update constraints set in order to include this parameter in the request. For more information, see  https://docs.aws.amazon.com/servicecatalog/latest/adminguide/constraints-resourceupdate.html:Amazon Web Services Service Catalog Tag Update Constraints.,  - The name of the project.amazonka-sagemaker The description for the project.amazonka-sagemakerThe product ID and provisioning artifact ID to provision a service catalog. The provisioning artifact ID will default to the latest provisioning artifact ID of the product, if you don't provide the provisioning artifact ID. For more information, see  https://docs.aws.amazon.com/servicecatalog/latest/adminguide/introduction.html+What is Amazon Web Services Service Catalog.amazonka-sagemakerAn array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see  >https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html%Tagging Amazon Web Services Resources. In addition, the project must have tag update constraints set in order to include this parameter in the request. For more information, see  https://docs.aws.amazon.com/servicecatalog/latest/adminguide/constraints-resourceupdate.html:Amazon Web Services Service Catalog Tag Update Constraints.amazonka-sagemakerThe name of the project.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code., 1 - The Amazon Resource Name (ARN) of the project.amazonka-sagemaker The response's http status code.amazonka-sagemaker.The Amazon Resource Name (ARN) of the project.amazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';-Namazonka-sagemakerSee:  smart constructor.amazonka-sagemaker'The space's Amazon Resource Name (ARN).amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerA collection of space settings.amazonka-sagemaker The ID of the associated Domain.amazonka-sagemakerThe name of the space.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, " - A collection of space settings., # - The ID of the associated Domain.,  - The name of the space.amazonka-sagemakerA collection of space settings.amazonka-sagemaker The ID of the associated Domain.amazonka-sagemakerThe name of the space.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, * - The space's Amazon Resource Name (ARN)., # - The response's http status code.amazonka-sagemaker'The space's Amazon Resource Name (ARN).amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';-Zamazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemaker3The Amazon Resource Name (ARN) of the training job.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerConfiguration information for Amazon SageMaker Debugger system monitoring, framework profiling, and storage paths.amazonka-sagemakerConfiguration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.amazonka-sagemakerThe training job ResourceConfig& to update warm pool retention length.amazonka-sagemakerThe name of a training job to update the Debugger profiling configuration.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - Configuration information for Amazon SageMaker Debugger system monitoring, framework profiling, and storage paths.,  - Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.,  - The training job ResourceConfig& to update warm pool retention length.,  - The name of a training job to update the Debugger profiling configuration.amazonka-sagemakerConfiguration information for Amazon SageMaker Debugger system monitoring, framework profiling, and storage paths.amazonka-sagemakerConfiguration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.amazonka-sagemakerThe training job ResourceConfig& to update warm pool retention length.amazonka-sagemakerThe name of a training job to update the Debugger profiling configuration.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code., 6 - The Amazon Resource Name (ARN) of the training job.amazonka-sagemaker The response's http status code.amazonka-sagemaker3The Amazon Resource Name (ARN) of the training job.amazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';-c amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker,The Amazon Resource Name (ARN) of the trial.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe name of the trial as displayed. The name doesn't need to be unique. If  DisplayName isn't specified,  TrialName is displayed.amazonka-sagemaker The name of the trial to update.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The name of the trial as displayed. The name doesn't need to be unique. If  DisplayName isn't specified,  TrialName is displayed., # - The name of the trial to update.amazonka-sagemakerThe name of the trial as displayed. The name doesn't need to be unique. If  DisplayName isn't specified,  TrialName is displayed.amazonka-sagemaker The name of the trial to update.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, / - The Amazon Resource Name (ARN) of the trial., # - The response's http status code.amazonka-sagemaker,The Amazon Resource Name (ARN) of the trial.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';-u/amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker6The Amazon Resource Name (ARN) of the trial component.amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerThe name of the component as displayed. The name doesn't need to be unique. If  DisplayName isn't specified, TrialComponentName is displayed.amazonka-sagemakerWhen the component ended.amazonka-sagemakerReplaces all of the component's input artifacts with the specified artifacts.amazonka-sagemaker1The input artifacts to remove from the component.amazonka-sagemakerReplaces all of the component's output artifacts with the specified artifacts.amazonka-sagemaker2The output artifacts to remove from the component.amazonka-sagemakerReplaces all of the component's hyperparameters with the specified hyperparameters.amazonka-sagemaker1The hyperparameters to remove from the component.amazonka-sagemakerWhen the component started.amazonka-sagemaker The new status of the component.amazonka-sagemaker$The name of the component to update.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - The name of the component as displayed. The name doesn't need to be unique. If  DisplayName isn't specified, TrialComponentName is displayed.,  - When the component ended.,  - Replaces all of the component's input artifacts with the specified artifacts., 4 - The input artifacts to remove from the component.,  - Replaces all of the component's output artifacts with the specified artifacts., 5 - The output artifacts to remove from the component.,  - Replaces all of the component's hyperparameters with the specified hyperparameters., 4 - The hyperparameters to remove from the component.,  - When the component started., # - The new status of the component., ' - The name of the component to update.amazonka-sagemakerThe name of the component as displayed. The name doesn't need to be unique. If  DisplayName isn't specified, TrialComponentName is displayed.amazonka-sagemakerWhen the component ended.amazonka-sagemakerReplaces all of the component's input artifacts with the specified artifacts.amazonka-sagemaker1The input artifacts to remove from the component.amazonka-sagemakerReplaces all of the component's output artifacts with the specified artifacts.amazonka-sagemaker2The output artifacts to remove from the component.amazonka-sagemakerReplaces all of the component's hyperparameters with the specified hyperparameters.amazonka-sagemaker1The hyperparameters to remove from the component.amazonka-sagemakerWhen the component started.amazonka-sagemaker The new status of the component.amazonka-sagemaker$The name of the component to update.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, 9 - The Amazon Resource Name (ARN) of the trial component., # - The response's http status code.amazonka-sagemaker6The Amazon Resource Name (ARN) of the trial component.amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemaker  (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';-}amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker,The user profile Amazon Resource Name (ARN).amazonka-sagemaker The response's http status code.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerA collection of settings.amazonka-sagemakerThe domain ID.amazonka-sagemakerThe user profile name.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - A collection of settings.,  - The domain ID.,  - The user profile name.amazonka-sagemakerA collection of settings.amazonka-sagemakerThe domain ID.amazonka-sagemakerThe user profile name.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, / - The user profile Amazon Resource Name (ARN)., # - The response's http status code.amazonka-sagemaker,The user profile Amazon Resource Name (ARN).amazonka-sagemaker The response's http status code.amazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';-[amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemakerA single private workforce. You can create one private work force in each Amazon Web Services Region. By default, any workforce-related API operation used in a specific region will apply to the workforce created in that region. To learn how to create a private workforce, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-workforce-create-private.htmlCreate a Private Workforce.amazonka-sagemakerSee:  smart constructor.amazonka-sagemakerUse this parameter to update your OIDC Identity Provider (IdP) configuration for a workforce made using your own IdP.amazonka-sagemaker0A list of one to ten worker IP address ranges ( https://docs.aws.amazon.com/vpc/latest/userguide/VPC_Subnets.htmlCIDRs?) that can be used to access tasks assigned to this workforce.Maximum: Ten CIDR valuesamazonka-sagemakerUse this parameter to update your VPC configuration for a workforce.amazonka-sagemakerThe name of the private workforce that you want to update. You can find your workforce name by using the operation.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:,  - Use this parameter to update your OIDC Identity Provider (IdP) configuration for a workforce made using your own IdP., 3 - A list of one to ten worker IP address ranges ( https://docs.aws.amazon.com/vpc/latest/userguide/VPC_Subnets.htmlCIDRs?) that can be used to access tasks assigned to this workforce.Maximum: Ten CIDR values,  - Use this parameter to update your VPC configuration for a workforce.,  - The name of the private workforce that you want to update. You can find your workforce name by using the operation.amazonka-sagemakerUse this parameter to update your OIDC Identity Provider (IdP) configuration for a workforce made using your own IdP.amazonka-sagemaker0A list of one to ten worker IP address ranges ( https://docs.aws.amazon.com/vpc/latest/userguide/VPC_Subnets.htmlCIDRs?) that can be used to access tasks assigned to this workforce.Maximum: Ten CIDR valuesamazonka-sagemakerUse this parameter to update your VPC configuration for a workforce.amazonka-sagemakerThe name of the private workforce that you want to update. You can find your workforce name by using the operation.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code.,  - A single private workforce. You can create one private work force in each Amazon Web Services Region. By default, any workforce-related API operation used in a specific region will apply to the workforce created in that region. To learn how to create a private workforce, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-workforce-create-private.htmlCreate a Private Workforce.amazonka-sagemaker The response's http status code.amazonka-sagemakerA single private workforce. You can create one private work force in each Amazon Web Services Region. By default, any workforce-related API operation used in a specific region will apply to the workforce created in that region. To learn how to create a private workforce, see  https://docs.aws.amazon.com/sagemaker/latest/dg/sms-workforce-create-private.htmlCreate a Private Workforce.amazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred "%&';- amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker The response's http status code.amazonka-sagemakerA Workteam- object that describes the updated work team.amazonka-sagemakerSee:  smart constructor.amazonka-sagemaker)An updated description for the work team.amazonka-sagemaker A list of MemberDefinition objects that contains objects that identify the workers that make up the work team.Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP). For private workforces created using Amazon Cognito use CognitoMemberDefinition. For workforces created using your own OIDC identity provider (IdP) use OidcMemberDefinition. You should not provide input for both of these parameters in a single request.For workforces created using Amazon Cognito, private work teams correspond to Amazon Cognito  user groups> within the user pool used to create a workforce. All of the CognitoMemberDefinition objects that make up the member definition must have the same ClientId and UserPool values. To add a Amazon Cognito user group to an existing worker pool, see  Addinggroups to a User Pool/. For more information about user pools, see  https://docs.aws.amazon.com/cognito/latest/developerguide/cognito-user-identity-pools.htmlAmazon Cognito User Pools.For workforces created using your own OIDC IdP, specify the user groups that you want to include in your private work team in OidcMemberDefinition by listing those groups in Groups. Be aware that user groups that are already in the work team must also be listed in Groups when you make this request to remain on the work team. If you do not include these user groups, they will no longer be associated with the work team you update.amazonka-sagemakerConfigures SNS topic notifications for available or expiring work itemsamazonka-sagemaker$The name of the work team to update.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, , - An updated description for the work team.,  - A list of MemberDefinition objects that contains objects that identify the workers that make up the work team.Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP). For private workforces created using Amazon Cognito use CognitoMemberDefinition. For workforces created using your own OIDC identity provider (IdP) use OidcMemberDefinition. You should not provide input for both of these parameters in a single request.For workforces created using Amazon Cognito, private work teams correspond to Amazon Cognito  user groups> within the user pool used to create a workforce. All of the CognitoMemberDefinition objects that make up the member definition must have the same ClientId and UserPool values. To add a Amazon Cognito user group to an existing worker pool, see  Addinggroups to a User Pool/. For more information about user pools, see  https://docs.aws.amazon.com/cognito/latest/developerguide/cognito-user-identity-pools.htmlAmazon Cognito User Pools.For workforces created using your own OIDC IdP, specify the user groups that you want to include in your private work team in OidcMemberDefinition by listing those groups in Groups. Be aware that user groups that are already in the work team must also be listed in Groups when you make this request to remain on the work team. If you do not include these user groups, they will no longer be associated with the work team you update.,  - Configures SNS topic notifications for available or expiring work items, ' - The name of the work team to update.amazonka-sagemaker)An updated description for the work team.amazonka-sagemaker A list of MemberDefinition objects that contains objects that identify the workers that make up the work team.Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP). For private workforces created using Amazon Cognito use CognitoMemberDefinition. For workforces created using your own OIDC identity provider (IdP) use OidcMemberDefinition. You should not provide input for both of these parameters in a single request.For workforces created using Amazon Cognito, private work teams correspond to Amazon Cognito  user groups> within the user pool used to create a workforce. All of the CognitoMemberDefinition objects that make up the member definition must have the same ClientId and UserPool values. To add a Amazon Cognito user group to an existing worker pool, see  Addinggroups to a User Pool/. For more information about user pools, see  https://docs.aws.amazon.com/cognito/latest/developerguide/cognito-user-identity-pools.htmlAmazon Cognito User Pools.For workforces created using your own OIDC IdP, specify the user groups that you want to include in your private work team in OidcMemberDefinition by listing those groups in Groups. Be aware that user groups that are already in the work team must also be listed in Groups when you make this request to remain on the work team. If you do not include these user groups, they will no longer be associated with the work team you update.amazonka-sagemakerConfigures SNS topic notifications for available or expiring work itemsamazonka-sagemaker$The name of the work team to update.amazonka-sagemakerCreate a value of " with all optional fields omitted.Use  0https://hackage.haskell.org/package/generic-lens generic-lens or  *https://hackage.haskell.org/package/opticsoptics! to modify other optional fields.The following record fields are available, with the corresponding lenses provided for backwards compatibility:, # - The response's http status code.,  - A Workteam- object that describes the updated work team.amazonka-sagemaker The response's http status code.amazonka-sagemakerA Workteam- object that describes the updated work team.amazonka-sagemakeramazonka-sagemakeramazonka-sagemaker(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred-"789:;<=JKW  !!!""""""""###########$$$$$$$$$$$$$$%%%%%%%&&&&&&'''''''''''''''''''''''''''((((((((((((()))))))))))))))))))+++++++++,,,,,,,,,,,,,,,,--------------.........//////0000000000000000000011111111222222222222222222333333333333333333444444444455555555555566666666666666777777777788888888888889999999999999::::::::;;;;;;;;;;;;;;;;;;;;;;<<<<<<<<<<<<<<<<<<<<<<<<<==========>>>>>>>>>>>>>>>>??????????????????@@@@@@@@@@@@@@@@@AAAAAAAAABBBBBBBBBBBBBBBBBCCCCCCCCCCCCCCCCDDDDDDDDDDDDDDDDDDDDDDDEEEEEEEEEEEEEEEEFFGGGGGGGGGHHHHHHHHHHHHHHHHHHHHHHHHHHIIIIIIIIIIJJJJJJJJJJJJJJJJJJJKKKKKKKKKKKKKKKKKKKKKKKLLLLLLLLLLLLLLLLMMMMMMMMMMMMMMMNNNNNNNNNNNNNNNNNNNNOOOOOOOOOOOOOOOOOOPPPPPPPPPPPPPPPPPPPPPPPPPQQQQQQQQQRRRRRRRRRRSSSSSSSSSSSTTTTTTTTTTTTTTTTUUUUUUUUUUUUUUUUXXXXXXYYYYYYYYYYYYYYYZZZZZZZZZZZZ[[[[[[[[[[[[[[[[[[[[[[[]]]]]]]]]]]]]]]]]]]]]]]]]^^^^^^^^^^^^^^^^^^^^________________________````````````aaaaaaaaaaaabbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbccccccccccccccccccccddddddddddddddddddddddeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeefffffffffffffffffffffffgggggggggggggggggggggggggggggggghhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiijjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkllllllllllllllllllllllllllmmmmmmmmmmmmmmmmmmnnnnnnnnnnnnnnnnnnnnnnnnnnnnnooooooooooooooooooooooooooooooooooooooooppppppppppppppppppppppppppppppppppppppppppppppppppppppppqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrssssssssssssssssssssssssssssssssssssssstttttttttttttttttuuuuuuuuuuuuuuuuuuuuuuuuvvvvvvvvwwwwwwwwwwwwxxxxxxxxxxxyyyyyyyyyyyyyyyyyzzzzzzzzzzzzzzzzzzzzzz{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{|||||||||||||||||||||||||||||}}}}}}}}}}}}}}}}}}}}}}}}}~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ӀԀՀր׀؀ـۀ܀݀Ɂʁˁ́΁ρЁ݂ނ߂ŃƃǃɃʃ˃DŽȄɄʄ˄̄̈́΄Єф҄˅̅ͅυЅх͆ΆφІц҆ӆԆֆ׆؆ևׇ؇هڇۇ݇އ߇‰ÉĉƉljȉʊˊ̊͊ΊϊЊъҊӊՊ֊׊ЋыҋӋԋՋ֋׋؋ًۋ܋݋،ٌڌی܌݌ތߌߍŽÎĎŎƎǎȎɎˎ͎̎ÏďÐĐŐƐǐȐɐʐː͐ΐϐ͑ΑϑБёґӑԑՑّ֑ؑڑےܒݒޒߒܓݓޓߓ”ĔŔƔؕڕەܕݕޕߕ˖͖ΖƗȗɗʗ˗̗͗ΗϗЗїҗӗԗ՗֗חؗٗڗ˜ØĘŘƘǘȘɘʘ˘̘љәԙ˚͚ΚϚКњҚӚԚ՚֚ךؚ›ÛěśƛǛțɛʛ˛̛͛ΛœÜĜŜƜݝߝÞĞŞƞǞȞɞʞ˞̞͞ΞϞОўҞӞԞ՞֞מ؞ٞڞ۞ܞޟߟ àĠŠƠǠաסء١ڡۡܡݡޡߡɢʢˢ͢΢ϢТѢҢӢԢբ֢עآ٢ڢۢܢݢޣǤɤʤˤ̤ͤΤϤФѤҤӤץإڥۥܥݥޥߥ¦æ֧קاڧۧܧݧާߧɨ˨̨ͨΨϨШѨҨӨکܩݩީߩªêĪŪƪǪثګ۫ܫݫޫ߫¬ìĬŬƬǬȬɬ˭ͭҮүʰıƱDZβ̳ȴҵŶƶǶȶɶʶ̶Ͷ·÷ŷƷθϸиѸҸӸԸոָ׸ظٸڸ۸ܸݸ޸߸ǹȹɹʹ̹͹ι»ûŻƻ޼߼½߽߾¿Ŀſ"¿Ŀſ߾߽½޼߼»ûŻƻǹȹɹʹ̹͹ιθϸиѸҸӸԸոָ׸ظٸڸ۸ܸݸ޸߸·÷ŷƷŶƶǶȶɶʶ̶Ͷҵȴ̳βıƱDZʰүҮ˭ͭ¬ìĬŬƬǬȬɬثګ۫ܫݫޫ߫ªêĪŪƪǪکܩݩީߩɨ˨̨ͨΨϨШѨҨӨ֧קاڧۧܧݧާߧ¦æץإڥۥܥݥޥߥǤɤʤˤ̤ͤΤϤФѤҤӤޣɢʢˢ͢΢ϢТѢҢӢԢբ֢עآ٢ڢۢܢݢաסء١ڡۡܡݡޡߡ àĠŠƠǠޟߟÞĞŞƞǞȞɞʞ˞̞͞ΞϞОўҞӞԞ՞֞מ؞ٞڞ۞ܞݝߝœÜĜŜƜ›ÛěśƛǛțɛʛ˛̛͛Λ˚͚ΚϚКњҚӚԚ՚֚ךؚљәԙ˜ØĘŘƘǘȘɘʘ˘̘Ɨȗɗʗ˗̗͗ΗϗЗїҗӗԗ՗֗חؗٗڗ˖͖Ζؕڕەܕݕޕߕ”ĔŔƔܓݓޓߓےܒݒޒߒ͑ΑϑБёґӑԑՑّ֑ؑڑÐĐŐƐǐȐɐʐː͐ΐϐÏďŽÎĎŎƎǎȎɎˎ͎̎ߍ،ٌڌی܌݌ތߌЋыҋӋԋՋ֋׋؋ًۋ܋݋ʊˊ̊͊ΊϊЊъҊӊՊ֊׊‰ÉĉƉljȉևׇ؇هڇۇ݇އ߇͆ΆφІц҆ӆԆֆ׆؆˅̅ͅυЅхDŽȄɄʄ˄̄̈́΄Єф҄ŃƃǃɃʃ˃݂ނ߂Ɂʁˁ́΁ρЁӀԀՀր׀؀ـۀ܀݀~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~}}}}}}}}}}}}}}}}}}}}}}|||||||||}}}||||||||||||||||||||{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{zzzzzzzzzzzzzzzyyzzzzzzzyyyyyyyyyyyyyyyxxxxxxxxxxxwwwwwwwwwwwwvvvvvvvvuuu789:;<=cccccccJKW_______eeeee'''''lllllllll;;;;;;;;;;; ssssssss ccccccccDDDDDDDDDDD---^^^ >>> ,,] _____________  ]]]]]]]]]]]OOOOOOOOO '''888DDSSNNNNNBBBBBBBRRRRRQQQQ^^YYYYPPPPPP-------,,,,,,YYYYYYqqqqqqqqqqqqCCCCCCCCCCGGGGGGG%%llllllllll,[[[[[[[[[[[[[[[[<<<<<=== hhhhhhhhhhhhhhhhhhhhh____???????rrrrrrrrrrrrrrrrrbbbbbbbbbbbb```gggggggg ssssssssssssssss!bbbbbbbbbb??aaaaaa!!""""""""OO###########$$$$$$$$$$$$$$MMMLLLLLLLLLLMMMMccccc%%%%```%&&&&&&QQQPPP''''''''''''rrr'((''''''(((((((rr(((())))))))))))>>)))))))<<+++++++,,,,++,,,rrrrrrrrrr----66DDDkkkkkklllllll.........//////0000000000000000rrrrrkkkkkkkkkkkkqqqqqqqqqqq00001111166DDKK111222222224444kkkkkkkkkkkkkkkkkkkkkkkkkk2222222222jjjjkkk333333333333333333eeee44778888866DDD4444KKKKKKK55555555555566666888AAAA6677799999999996DDppppppppp77777qqqEEEAEEEqqqqqqqqqqqqqqqTTTTTTTT88999==ooo::::::::;;;;;;;;;;;[[[[<<<<<<<<<<<<<<<<<<===]]]]]==>>>>>>>>>>>???nnnnnnnnnnnnnnn???jjjjjjjjjjjjj???jjjjjjjjjjjjjhhhhhhhhhhgggggggggggggg@@@@@@@@@@@@@@@@AAAA@NNNNppppppppppppppppppppppBBBBBBBBBEEEEEEBCCCCCCEEEEHHHHHHHHHHHFFGGmmmnnnnnnnnnHHHHHHHHHHHHHHHRRRRRjjjjjjjjjjjjIIIIIIIIIIhJJJJJJJJJJJJJJJJJPPJJPPPPPPPPKKKKKKKKKKMMMM^^^^^^^^^KKKKLLLLLLMMMMNNNNNNNNNNNOOOOOO``````OPPPPPPQQSSSSSSSSSTTTTsssssssssssssssTTTTUUUUUUUUUUUUUUUUXXXXYYYYYXXZZZZZZZZZZZZ[[[]]]]]]]]^^^^^^oooooooooooooooooooooooooooooooooooooaaaaaabbbbbbtttttttbbbbbbbbdddddeeeeeeeeeeeeeeeffffffeeeeeeedddddddddddddddddiiiiiiiiiiijpppppppppppppppppppppfffffffffffffiiiiiffppppffiiiiiiiiiiigggggggggghhhhhiiiiiimmmmmmmmmmmmmmmnnnnntttuuuuuuuuuuutttttttuuuuuuuuuu(c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred"%. amazonka-sagemakerPolls  every 30 seconds until a successful state is reached. An error is returned after 60 failed checks.amazonka-sagemakerPolls  every 30 seconds until a successful state is reached. An error is returned after 120 failed checks.amazonka-sagemakerPolls  every 60 seconds until a successful state is reached. An error is returned after 60 failed checks.amazonka-sagemakerPolls  every 60 seconds until a successful state is reached. An error is returned after 60 failed checks.amazonka-sagemakerPolls  every 60 seconds until a successful state is reached. An error is returned after 60 failed checks.amazonka-sagemakerPolls  every 60 seconds until a successful state is reached. An error is returned after 60 failed checks.amazonka-sagemakerPolls  every 60 seconds until a successful state is reached. An error is returned after 60 failed checks.amazonka-sagemakerPolls  every 30 seconds until a successful state is reached. An error is returned after 60 failed checks.amazonka-sagemakerPolls  every 30 seconds until a successful state is reached. An error is returned after 60 failed checks.amazonka-sagemakerPolls  every 30 seconds until a successful state is reached. An error is returned after 60 failed checks.amazonka-sagemakerPolls  every 60 seconds until a successful state is reached. An error is returned after 60 failed checks.amazonka-sagemakerPolls  every 120 seconds until a successful state is reached. An error is returned after 180 failed checks.amazonka-sagemakerPolls  every 60 seconds until a successful state is reached. An error is returned after 60 failed checks.  (c) 2013-2023 Brendan HayMozilla Public License, v. 2.0. Brendan Hayauto-generatednon-portable (GHC extensions) Safe-Inferred. (-.6EFISTV`dcabx~}|{yz   !!!!!!!!!!!!!!!!!!!!!!!!!!!""!!!"""""""""""""""""""""""""##""########################$$$$$$$$$$$$$$$$$$$$$$$$$$$%%%%%%%%%%%%%%%&&&&&&&&&&&&&&&&&&&&%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&&&&&&&&&&&&&&&&&&&&'''''''''''''''''''''(((((((((((((((((((((((((((((()))))))))))))))))))))))***))****************************+**+++++++++++++++++++++++++,,,,,,,,,,,,,,,,,,,,,,,,-------------------------........................./.......////////////////////////000000000000000000000000111111111111111111111111111122222222222222222222222222333333333333333333333333444334444444444444444444444455555555555555555555555555566666666666666666666666666677777777777777777777777777888888888888888888888888888999999999999999999999999999::::::::::::::::::::::::::::::;;;;;;;;;;;;;;;;;;;;;<<;;;<<<<<<<<<<<<<<<<<<=================================>>>>>>>>>>>>>>>>>>>>>>>>>>>>??????????????????????????@@@@@@@@@@@@@@@@@@@@@@AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABBBBBBBBBBBBBBBBBBBBBBBBBBBBCCCCCCCCCCCCCCCCCCDDDDDDDDDDDDDDDDDDDDDDDEEEEEEEEEEEEEEEEEEEEEEEEFFFFFFFFFFFFFGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFGGGGGGGGGHHHHHHHHHHHHHHHHHHHHHHIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIJJJJJJJJJJJJJJJJJJJJJJKKKKKKKKKKKKKKKKKKKKKKKLLLLLLLLLLLLLLLLLLLLLLLLLLMMMMMMMMMMMMMMMMMMMMMMMMMMMNNNNNNNNNNNNNNNNNNNNOOOOOOOOOOOOOOOOOOOOOOOOOPPPPPPPPPPPPPPPPPPPPPPQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQRRQRRRRRRRRRRRRRRRRRRRRRRRRRRRSSSSSSSSSSSSSSSSSSSSSSSSSTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTUUUUUUUUUUUUUUUUUUUUUUUUVUVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVWWWWWWWWWWWWWWWWWWWWWWWWWXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXYYYYYYYYYYYYYYYYYYYYYYYYYYYZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ[[[[[[[[[[[[[[[[[[\\\\\\\\\\\\\\\\\\\\\\\\\\[[[[[[[[\\\\\\\\\\\\\\\\\\\\\\\]]]]]]]]]]]]]]]]]]]]]]]]^^^^^^^^^^^^^^^^^^^___________________````````````````````````````````````````````````___```````````aaaaaaaaaaaaaaaaaaaaaaaaaabbbbbbbbbbbbbbcccccccccccccccccccccbbbbbbbbbbbbbcccccccccccccccccdddddddddddddddddddddeeeeeeeeeeeeeeeeeeffffffffffffffffffffffffggggggggggggggggggghhhhhhhhhhhhhhhhiiiiiiiiiiiiiiiiiijjjjjjjjjjjjkkkkkkkkklllllllllllllllllllllllmmmmmmmmmmmmmmmmmmmmmmmmmmnnnnnnnnnnnnnnnnnnnnooooooooppppppppppqqqqqqqqqqqqqqqrrrrrrrrrrrrrrrsssssssssssssttttstttttttttttttttttttttttuuuuuuuuuuuuuuuuuuuuuuuuuuuvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwxxxxxxxxxxxxxxxxxxxxxxxxxxxxyyyyyyyyyyyyyyyyyyyyyyyyyzzzzzzzzzzzzzzzzzzzzzzz{{{{{{{{{{{{{{{{{{{{|||||||||||||||||}}}}}}}}}}}}}}}}}~~~~~~~~~~~~~~~~~~~ĀŀɀʀҀڀÁȁ́Ȃɂ͂΂܂ăȃ݃ރƄτŅƅʅ΅†Æ̆Նȇɇ͇·Շ܇ψЈԈՈʼnډۉ߉ɊԊËċϋڋnjȌ̌͌׌ЍэՍ֍ލʎߎ֏׏ۏ܏̐̑ב̒͒ђҒڒ͓ΓғӓۓÔהؔ۔ܔߔɕʕԕՕוٕÖĖǖȖʖ̖ߖ—×ŗǗݘޘəʙ͙ΙЙҙǚȚʚ̚ߛל؜˝̝ٝڝܝޝž˟̟ٟڟݟؠ٠ѡҡԡ֡âĢȢ̢ңӣڣۣݣߣäĤƤȤҥӥ֥٥Ԧզ§çЧѧէ٧ŨƨȨʨȩɩ֩ש٩۩ت٪̫ͫԫի׫٫ڬ۬ĭŭǭȭʭ̭ޭ̮߭ͮήϮѮӮ̯ͯίϯѯӯİŰưǰɰ˰ܰݰް߰ñűرٱ۱ܱȲɲʲ˲ͲϲƳdzȳɳ˳ͳ޳߳´ôĴŴǴɴڴ۴޴ߴ̵͵εϵѵӵĶ˶޶߶ķ׷ط۷ܷ͸ƹ˹߹ѺҺպֺĻ׻ػۻܻżƼɼʼݼӽԽ׽ؽ޽ξϾҾӾ޾ÿֿ׿ڿۿ2uuuuuڿۿֿ׿ÿҾӾ޾ξϾ׽ؽ޽ӽԽɼʼݼżƼۻܻ׻ػĻպֺѺҺ߹ƹ˹͸۷ܷ׷طķ޶߶Ķ˶εϵѵ̵͵ӵ޴ߴڴ۴ĴŴǴ´ôɴ޳߳ȳɳ˳Ƴdzͳʲ˲ͲȲɲϲ۱ܱرٱñűް߰ܰݰưǰɰİŰ˰ίϯѯ̯ͯӯήϮѮ̮ͮӮޭ߭ǭȭʭĭṷ̆ڬ۬ԫի׫̫ͫ٫ت٪֩ש٩ȩɩ۩ŨƨȨʨЧѧէ§ç٧Ԧզҥӥ֥٥äĤƤȤڣۣݣңӣߣâĢȢ̢ѡҡԡ֡ؠ٠ٟڟݟ˟̟žٝڝܝ˝̝ޝל؜ߛǚȚʚ͙̚ΙЙəʙҙݘޘ—×ŗǗߖǖȖʖÖĖ̖ԕՕוɕʕٕ۔ܔߔהؔÔғӓۓ͓ΓђҒڒ̒͒̑ב̐ۏ܏֏׏ߎʎՍ֍ލЍэ̌͌׌njȌËċϋڋɊԊ߉ډۉʼnԈՈψЈ͇·Շȇɇ܇†Æ̆ՆŅƅʅ΅Ƅτ݃ރăȃ͂΂܂ȂɂÁȁ́ɀʀҀĀŀڀ~~~~~~~~~~~~~~~~~}}~}}~}}}}}}}}}}}}|||||}||||||||||||{{{{{{{{{{{{{{{{{{zz{zz{zzzzzzzzzzzzzzzzzzyyyyyzyyyyyyyyyyyyyyyyyyxxyxxyxxxxxxxxxxxxxxxxxxxxxxxxwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvuuuuuuuuuuuuuuuuuu`dcabdcx~}|{yz~}|{    !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!""!!!""!""""""""""""""""""""""""""""""""""##""######################$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$%%%%%%%%&&&&&&&&&&&&&&&&&&&&%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&&&&&&&&&&&&&&&&&&&&%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&&&&&&&&&&&&&&&&((((((((((((((()))))))))))))))))))))***))**********************************************+**++++++++++++++++++++++++----------------........................../......./.....//////////////////////////0000111111111111111122222222222222222222223333333333333333333334443344444444444444444445555555555555555555555555556666666667777777777777777888888888888888888889999999999999999999999999999999:::::::::::::::::::::::::::::::::;;;;;;;;;;;;;;;;;<<;;;<<;==============================>>>>>>>>>>>?????????????@@@@@@@@@@@@@@AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABBBBBBBBBBBBBBBBBBBBBBBBBBBCCCCCCCCCCCCCCDDDDDDDEEEEEEEFFFFFFFFFFFFFFFFGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFHHHHHHHHHHHHHHIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIJJJJJJJJJJJJJJLLLLLLLLLLLLLLLLLLLLLLMMMMMMMMMMMMMMMMMMMMMMMMMNNNNNNNOOOOOOOQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQRRQRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRSSSSSSSSSSSSSSSSSSTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTUUUUUUUUVUVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ[[[[[[[[\\\\\\\\\\\\\\\\\\\\\\\\\\[[[[[[[[\\\\\\\\\\\\\\\\\\\\\\\\\\[[[[[[\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\]]]]]]]]]^^^^^__________````````````````````````````````````````````````___````````````````````````````````````````````````_aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabcccccccccccccccccccccbbbbbbbbbbbbbcccccccccccccccccccccbbbbbbbbbbbcccccccccccccfffffffffffffllllllllllllllllllllllllmmmmmmmmmmmmmmmmmmmmmmnnnnnnnnnnnsttttstttttttttttttttttt-.6cccEFISTV___eeeeee'''lll;;; ssssss cccCCD---^^^ >>> ,,,]]] ______  ]]]OOO &&&888DDDSSSNNNAABRRRQQQ^^^YYYPPPPPP---,,,,,,,,,,,,YYYqqqCCCGGGGGG%%%lll,,,[[[<<<=== hhhhhh___???rrraab```ggg sss!!!bbb???``a!!!"""OOO###########$$$$$$$MMMLLLMMMccc%%%```%%%&&&&&&QQQPPP''''''''''''rrr'''((('''(((((((((rrr((((((((()))>>>))))))<<<++++++,,,+++,,,rrr------666DDDkkk--.......//////000000000000000rrrkkkqqq000000111111111666DDDKKK111111112222222444kkk222jjj223333333333eeeeee444777666DDD444444KKKKKK555555555666888AAA666666777889666DDDppp777777qqqEEEEEE777AAAEEEqqqqqqSTT888888999999===ooo:::::::::;;;;;;[[[<<<<<<<<<<<<======]]]===>>>>>>>>>>>>>>>??????nnnnnn???jjj???jjjgghggg@@@@@@@@@AAA@@@NNNoopBBBBBBEEEEEEBBBCCCDDEEEEHHHFFFGGGmmmmmnHHHHHHHHHRRRjjjIIIIIIIIIIIIhhhJJJJJJPPPJJJPPPPPPJJJKKKKKKMMM^^^KKKKKKKKLLLLLLLLLMNNNNNNNNNOOOOOOOOO```OOOOOPPPPQQQQQQSSSSSSSSSTTTsssTTTTTTUUUUUUUUUUUUUUUUUUXXXXXXXXXYYYXXXZZZZZZZZZ[[[[[[\\\]]]]]]]]]^^^^^^oooaaabbbbbbtttbbbddddddeeeeeedddddddddddddddiiipppfffffffffiiifffpppfffiiifggggggggggghhhhhhiiiiiiiiillmmmmmmmnnnnnntttttuttttttuuu                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   ! ! ! ! ! ! ! ! ! ! ! ! ! " " " " " " " " " " " " " " " " " " " " " " " " # # # # # # # # # #######$$$$$$$$$$$$$%%%%%%%%%%%%%%&&&&&&&&&&&&&&&&&''''''''''''''''''''''''((((((((((((((((((((((((((((((((((((((()))))))))))))))))))))))))))************+++++++++++++++++++++++++++++++++++,,,,,,,,,,,,,-------------------------------------.........................///////////////000000000000111111111111111111111111111122222222222222222222222233333333333333344444444444445555555555555555555555555666666666666666666666666777777777777788888888888888888888888899999999999999999::::::::::::::;;;;;;;;;;;;;;;;;;;;;;;;<<<<<<<<<<<<<<<<<<<<<<<<============>>>>>>>>>>>>>>?????????????????????????@@@@@@@@@@@@@@@@@@@@@@@@@@@AAAAAAAAAAAAAAAAAAAAAAAAABBBBBBBBBBBBBBBBCCCCCCCCCCCCCCCCCCCCCCCCDDDDDDDDDDDDDDDEEEEEEEEEEEEEEEFFFFFFFFFFFFFFFFFFFFFFFFGGGGGGGGGGGGGHHHHHHHHHHHHHHHHHHHHHHHHIIIIIIIIIIIIIIIJJJJJJJJJJJJJJJKKKKKKKKKKKKKLLLLLLLLLLLLLLLMMMMMMMMMMMMMMMMMMMMMMMMMMNNNNNNNNNNNNNNNNNNNNNNNNNOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOPPPPPPPPPPPPPPPPPQQQQQQQQQQQQQQQQQQQQQQQQQRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRSSSSSSSSSSSSSSSTTTTTTTTTTTTTTTTTTTTTUUUUUUUUUUUUUUUUUVVVVVVVVVVVVVWWWWWWWWWWWWWWWWWWWWWWWWWXXXXXXXXXXXXXXXXXXXXXXXXYYYYYYYYYYYYYYYZZZZZZZZZZZZZZZZZ[[[[[[[[[[[[[[[\\\\\\\\\\\\\\\\\\\\\\\\\\\\]]]]]]]]]]]]]]]]]]]]]]]]^^^^^^^^^^^^^^^^^^^^^________________________````````````aaaaaaaaaaaaaaaaaaaaaaaabbbbbbbbbbbbbbbbbbbbbbbbcccccccccccccccccddddddddddddddddddddddeeeeeeeeeeeeeeefffffffffffffffffggggggggggggggggggggggghhhhhhhhhhhhhhhhhhhhiiiiiiiiiiiiiiiiijjjjjjjjjjjjjjjjjjjjjjjjkkkkkkkkkkkkkkkkkkkkkkklllllllllllllllllllmmmmmmmmmmmmmmmmnnnnnnnnnnnnnnnnooooooooooooooooooooooooooppppppppppppppppqqqqqqqqqqqqqqrrrrrrrrrrrrrrrrrrrrrrrrrrssssssssssssssssttttttttttttttttttttttttttttuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuvvvvvvvvvvvvvvvvvvwwwwwwwwwwwwwwxxxxxxxxxxxxxxxxxxxxxxxxxyyyyyyyyyyyyyyyyyyyzzzzzzzzzzzzzzzzzzzzzzzz{{{{{{{{{{{{{{{{{{{{{{{{{|||||||||||||||||||||||||||||}}}}}}}}}}}}}}}}}}}}}}}}~~~~~~~~~~~~~~~~~~                                                                                                                                !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""################################################################################################################################$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''(((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((())))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))********************************************************************************************************************************++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,--------------------------------------------------------------------------------------------------------------------------------................................................................................................................................////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////00000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111112222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222233333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444445555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555555566666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777778888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888899999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<================================================================================================================================>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJJKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^________________________________________________________________________________________________________________________________````````````````````````````````````````````````````````````````````````````````````````````````````````````````````````````````aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffgggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggggghhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiijjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzz{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{{||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~€ÀĀŀƀǀȀɀʀˀ̀̀΀πЀрҀӀԀՀր׀؀ـڀۀ܀݀ހ߀ÁāŁƁǁȁɁʁˁ́́΁ρЁсҁӁԁՁցׁ؁فځہ܁݁ށ߁‚ÂĂłƂǂȂɂʂ˂̂͂΂ςЂт҂ӂԂՂւׂ؂قڂۂ܂݂ނ߂ƒÃăŃƃǃȃɃʃ˃̃̓΃σЃу҃ӃԃՃփ׃؃كڃۃ܃݃ރ߃„ÄĄńƄDŽȄɄʄ˄̄̈́΄τЄф҄ӄԄՄքׄ؄لڄۄ܄݄ބ߄…ÅąŅƅDžȅɅʅ˅̅ͅ΅υЅх҅ӅԅՅօׅ؅مڅۅ܅݅ޅ߅†ÆĆņƆdžȆɆʆˆ̆͆ΆφІц҆ӆԆՆֆ׆؆نچۆ܆݆ކ߆‡ÇćŇƇLJȇɇʇˇ͇̇·χЇч҇ӇԇՇևׇ؇هڇۇ܇݇އ߇ˆÈĈňƈLjȈɈʈˈ͈̈ΈψЈш҈ӈԈՈֈ׈؈وڈۈ܈݈ވ߈‰ÉĉʼnƉljȉɉʉˉ͉̉ΉωЉщ҉ӉԉՉ։׉؉ىډۉ܉݉މ߉ŠÊĊŊƊNJȊɊʊˊ̊͊ΊϊЊъҊӊԊՊ֊׊؊يڊۊ܊݊ފߊ‹ËċŋƋNjȋɋʋˋ̋͋΋ϋЋыҋӋԋՋ֋׋؋ًڋۋ܋݋ދߋŒÌČŌƌnjȌɌʌˌ̌͌ΌόЌьҌӌԌՌ֌׌،ٌڌی܌݌ތߌÍčōƍǍȍɍʍˍ͍̍΍ύЍэҍӍԍՍ֍׍؍ٍڍۍ܍ݍލߍŽÎĎŎƎǎȎɎʎˎ͎̎ΎώЎюҎӎԎՎ֎׎؎َڎێ܎ݎގߎÏďŏƏǏȏɏʏˏ̏͏ΏϏЏяҏӏԏՏ֏׏؏ُڏۏ܏ݏޏߏÐĐŐƐǐȐɐʐː̐͐ΐϐАѐҐӐԐՐ֐אِؐڐېܐݐސߐ‘ÑđőƑǑȑɑʑˑ̑͑ΑϑБёґӑԑՑ֑בّؑڑۑܑݑޑߑ’ÒĒŒƒǒȒɒʒ˒̒͒ΒϒВђҒӒԒՒ֒גْؒڒےܒݒޒߒ“ÓēœƓǓȓɓʓ˓͓̓ΓϓГѓғӓԓՓ֓דؓٓړۓܓݓޓߓ”ÔĔŔƔǔȔɔʔ˔͔̔ΔϔДєҔӔԔՔ֔הؔٔڔ۔ܔݔޔߔ•ÕĕŕƕǕȕɕʕ˕͕̕ΕϕЕѕҕӕԕՕ֕וٕؕڕەܕݕޕߕ–ÖĖŖƖǖȖɖʖ˖̖͖ΖϖЖіҖӖԖՖ֖זٖؖږۖܖݖޖߖ—×ėŗƗǗȗɗʗ˗̗͗ΗϗЗїҗӗԗ՗֗חؗٗڗۗܗݗޗߗ˜ØĘŘƘǘȘɘʘ˘̘͘ΘϘИјҘӘԘ՘֘טؘ٘ژۘܘݘޘߘ™ÙęřƙǙșəʙ˙̙͙ΙϙЙљҙәԙՙ֙יؙٙڙۙܙݙޙߙšÚĚŚƚǚȚɚʚ˚͚̚ΚϚКњҚӚԚ՚֚ךؚٚښۚܚݚޚߚ›ÛěśƛǛțɛʛ˛̛͛ΛϛЛћқӛԛ՛֛כ؛ٛڛۛܛݛޛߛœÜĜŜƜǜȜɜʜ˜̜͜ΜϜМќҜӜԜ՜֜ל؜ٜڜۜܜݜޜߜÝĝŝƝǝȝɝʝ˝̝͝ΝϝНѝҝӝԝ՝֝ם؝ٝڝ۝ܝݝޝߝžÞĞŞƞǞȞɞʞ˞̞͞ΞϞОўҞӞԞ՞֞מ؞ٞڞ۞ܞݞޞߞŸßğşƟǟȟɟʟ˟̟͟ΟϟПџҟӟԟ՟֟ן؟ٟڟ۟ܟݟޟߟ àĠŠƠǠȠɠʠˠ̠͠ΠϠРѠҠӠԠՠ֠נؠ٠ڠ۠ܠݠޠߠ¡áġšơǡȡɡʡˡ̡͡ΡϡСѡҡӡԡա֡סء١ڡۡܡݡޡߡ¢âĢŢƢǢȢɢʢˢ̢͢΢ϢТѢҢӢԢբ֢עآ٢ڢۢܢݢޢߢ£ãģţƣǣȣɣʣˣ̣ͣΣϣУѣңӣԣգ֣ףأ٣ڣۣܣݣޣߣ¤äĤŤƤǤȤɤʤˤ̤ͤΤϤФѤҤӤԤդ֤פؤ٤ڤۤܤݤޤߤ¥åĥťƥǥȥɥʥ˥̥ͥΥϥХѥҥӥԥե֥ץإ٥ڥۥܥݥޥߥ¦æĦŦƦǦȦɦʦ˦̦ͦΦϦЦѦҦӦԦզ֦צئ٦ڦۦܦݦަߦ§çħŧƧǧȧɧʧ˧̧ͧΧϧЧѧҧӧԧէ֧קا٧ڧۧܧݧާߧ¨èĨŨƨǨȨɨʨ˨̨ͨΨϨШѨҨӨԨը֨רب٨ڨۨܨݨިߨ©éĩũƩǩȩɩʩ˩̩ͩΩϩЩѩҩөԩթ֩שة٩ک۩ܩݩީߩªêĪŪƪǪȪɪʪ˪̪ͪΪϪЪѪҪӪԪժ֪תت٪ڪ۪ܪݪުߪ«ëīūƫǫȫɫʫ˫̫ͫΫϫЫѫҫӫԫի֫׫ث٫ګ۫ܫݫޫ߫¬ìĬŬƬǬȬɬʬˬ̬ͬάϬЬѬҬӬԬլ֬׬ج٬ڬ۬ܬݬެ߬­íĭŭƭǭȭɭʭ˭̭ͭέϭЭѭҭӭԭխ֭׭ح٭ڭۭܭݭޭ߭®îĮŮƮǮȮɮʮˮ̮ͮήϮЮѮҮӮԮծ֮׮خٮڮۮܮݮޮ߮¯ïįůƯǯȯɯʯ˯̯ͯίϯЯѯүӯԯկ֯ׯدٯگۯܯݯޯ߯°ðİŰưǰȰɰʰ˰̰ͰΰϰаѰҰӰ԰հְװذٰڰ۰ܰݰް߰±ñıűƱDZȱɱʱ˱̱ͱαϱбѱұӱԱձֱױرٱڱ۱ܱݱޱ߱²òIJŲƲDzȲɲʲ˲̲ͲβϲвѲҲӲԲղֲײزٲڲ۲ܲݲ޲߲³óijųƳdzȳɳʳ˳̳ͳγϳгѳҳӳԳճֳ׳سٳڳ۳ܳݳ޳߳´ôĴŴƴǴȴɴʴ˴̴ʹδϴдѴҴӴԴմִ״شٴڴ۴ܴݴ޴ߴµõĵŵƵǵȵɵʵ˵̵͵εϵеѵҵӵԵյֵ׵صٵڵ۵ܵݵ޵ߵ¶öĶŶƶǶȶɶʶ˶̶Ͷζ϶жѶҶӶԶնֶ׶ضٶڶ۶ܶݶ޶߶·÷ķŷƷǷȷɷʷ˷̷ͷηϷзѷҷӷԷշַ׷طٷڷ۷ܷݷ޷߷¸øĸŸƸǸȸɸʸ˸̸͸θϸиѸҸӸԸոָ׸ظٸڸ۸ܸݸ޸߸¹ùĹŹƹǹȹɹʹ˹̹͹ιϹйѹҹӹԹչֹ׹عٹڹ۹ܹݹ޹߹ºúĺźƺǺȺɺʺ˺̺ͺκϺкѺҺӺԺպֺ׺غٺںۺܺݺ޺ߺ»ûĻŻƻǻȻɻʻ˻̻ͻλϻлѻһӻԻջֻ׻ػٻڻۻܻݻ޻߻¼üļżƼǼȼɼʼ˼̼ͼμϼмѼҼӼԼռּ׼ؼټڼۼܼݼ޼߼½ýĽŽƽǽȽɽʽ˽̽ͽνϽнѽҽӽԽսֽ׽ؽٽڽ۽ܽݽ޽߽¾þľžƾǾȾɾʾ˾̾;ξϾоѾҾӾԾվ־׾ؾپھ۾ܾݾ޾߾¿ÿĿſƿǿȿɿʿ˿̿ͿοϿпѿҿӿԿտֿ׿ؿٿڿۿܿݿ޿߿-amazonka-sagemaker-2.0-9SyrKZ4KqhsL1qX9u3ILA3%Amazonka.SageMaker.Types.ActionSource%Amazonka.SageMaker.Types.ActionStatus&Amazonka.SageMaker.Types.ActionSummary%Amazonka.SageMaker.Types.AgentVersionAmazonka.SageMaker.Types.Alarm(Amazonka.SageMaker.Types.AlgorithmSortBy(Amazonka.SageMaker.Types.AlgorithmStatus)Amazonka.SageMaker.Types.AlgorithmSummary6Amazonka.SageMaker.Types.AnnotationConsolidationConfig.Amazonka.SageMaker.Types.AppImageConfigSortKey(Amazonka.SageMaker.Types.AppInstanceType-Amazonka.SageMaker.Types.AppNetworkAccessType3Amazonka.SageMaker.Types.AppSecurityGroupManagement#Amazonka.SageMaker.Types.AppSortKey)Amazonka.SageMaker.Types.AppSpecification"Amazonka.SageMaker.Types.AppStatus Amazonka.SageMaker.Types.AppType#Amazonka.SageMaker.Types.AppDetails-Amazonka.SageMaker.Types.ArtifactSourceIdType+Amazonka.SageMaker.Types.ArtifactSourceType'Amazonka.SageMaker.Types.ArtifactSource(Amazonka.SageMaker.Types.ArtifactSummary%Amazonka.SageMaker.Types.AssemblyType,Amazonka.SageMaker.Types.AssociationEdgeType3Amazonka.SageMaker.Types.AsyncInferenceClientConfig9Amazonka.SageMaker.Types.AsyncInferenceNotificationConfig3Amazonka.SageMaker.Types.AsyncInferenceOutputConfig-Amazonka.SageMaker.Types.AsyncInferenceConfig4Amazonka.SageMaker.Types.AthenaResultCompressionType+Amazonka.SageMaker.Types.AthenaResultFormat0Amazonka.SageMaker.Types.AthenaDatasetDefinition!Amazonka.SageMaker.Types.AuthMode8Amazonka.SageMaker.Types.AutoMLCandidateGenerationConfig*Amazonka.SageMaker.Types.AutoMLChannelType2Amazonka.SageMaker.Types.AutoMLContainerDefinition.Amazonka.SageMaker.Types.AutoMLDataSplitConfig+Amazonka.SageMaker.Types.AutoMLJobArtifacts4Amazonka.SageMaker.Types.AutoMLJobCompletionCriteria/Amazonka.SageMaker.Types.AutoMLJobObjectiveType1Amazonka.SageMaker.Types.AutoMLJobSecondaryStatus(Amazonka.SageMaker.Types.AutoMLJobStatus.Amazonka.SageMaker.Types.AutoMLJobStepMetadata)Amazonka.SageMaker.Types.AutoMLMetricEnum+Amazonka.SageMaker.Types.AutoMLJobObjective1Amazonka.SageMaker.Types.AutoMLMetricExtendedEnum#Amazonka.SageMaker.Types.AutoMLMode/Amazonka.SageMaker.Types.AutoMLOutputDataConfig3Amazonka.SageMaker.Types.AutoMLPartialFailureReason)Amazonka.SageMaker.Types.AutoMLJobSummary)Amazonka.SageMaker.Types.AutoMLS3DataType+Amazonka.SageMaker.Types.AutoMLS3DataSource)Amazonka.SageMaker.Types.AutoMLDataSource%Amazonka.SageMaker.Types.AutoMLSortBy(Amazonka.SageMaker.Types.AutoMLSortOrder+Amazonka.SageMaker.Types.AutoRollbackConfig9Amazonka.SageMaker.Types.AwsManagedHumanLoopRequestSource/Amazonka.SageMaker.Types.BatchDataCaptureConfig7Amazonka.SageMaker.Types.BatchDescribeModelPackageError&Amazonka.SageMaker.Types.BatchStrategy(Amazonka.SageMaker.Types.BooleanOperator'Amazonka.SageMaker.Types.CacheHitResult3Amazonka.SageMaker.Types.CandidateArtifactLocations(Amazonka.SageMaker.Types.CandidateSortBy(Amazonka.SageMaker.Types.CandidateStatus*Amazonka.SageMaker.Types.CandidateStepType,Amazonka.SageMaker.Types.AutoMLCandidateStep)Amazonka.SageMaker.Types.CapacitySizeType%Amazonka.SageMaker.Types.CapacitySize1Amazonka.SageMaker.Types.CaptureContentTypeHeader$Amazonka.SageMaker.Types.CaptureMode&Amazonka.SageMaker.Types.CaptureOption&Amazonka.SageMaker.Types.CaptureStatus-Amazonka.SageMaker.Types.CategoricalParameter2Amazonka.SageMaker.Types.CategoricalParameterRange?Amazonka.SageMaker.Types.CategoricalParameterRangeSpecification)Amazonka.SageMaker.Types.CheckpointConfig1Amazonka.SageMaker.Types.ClarifyCheckStepMetadata+Amazonka.SageMaker.Types.ClarifyFeatureType/Amazonka.SageMaker.Types.ClarifyInferenceConfig2Amazonka.SageMaker.Types.ClarifyShapBaselineConfig/Amazonka.SageMaker.Types.ClarifyTextGranularity,Amazonka.SageMaker.Types.ClarifyTextLanguage*Amazonka.SageMaker.Types.ClarifyTextConfig*Amazonka.SageMaker.Types.ClarifyShapConfig/Amazonka.SageMaker.Types.ClarifyExplainerConfig'Amazonka.SageMaker.Types.CodeRepository-Amazonka.SageMaker.Types.CodeRepositorySortBy0Amazonka.SageMaker.Types.CodeRepositorySortOrder&Amazonka.SageMaker.Types.CognitoConfig0Amazonka.SageMaker.Types.CognitoMemberDefinition0Amazonka.SageMaker.Types.CollectionConfiguration-Amazonka.SageMaker.Types.CompilationJobStatus(Amazonka.SageMaker.Types.CompressionType&Amazonka.SageMaker.Types.AutoMLChannel)Amazonka.SageMaker.Types.ConditionOutcome.Amazonka.SageMaker.Types.ConditionStepMetadata&Amazonka.SageMaker.Types.ContainerMode*Amazonka.SageMaker.Types.ContentClassifier&Amazonka.SageMaker.Types.ContextSource'Amazonka.SageMaker.Types.ContextSummary>Amazonka.SageMaker.Types.ContinuousParameterRangeSpecification$Amazonka.SageMaker.Types.CustomImage*Amazonka.SageMaker.Types.DataCaptureConfig1Amazonka.SageMaker.Types.DataCaptureConfigSummary*Amazonka.SageMaker.Types.DataCatalogConfig-Amazonka.SageMaker.Types.DataDistributionType4Amazonka.SageMaker.Types.DataQualityAppSpecification(Amazonka.SageMaker.Types.DebugHookConfig&Amazonka.SageMaker.Types.DeployedImage1Amazonka.SageMaker.Types.DesiredWeightAndCapacity0Amazonka.SageMaker.Types.DetailedAlgorithmStatus,Amazonka.SageMaker.Types.AlgorithmStatusItem/Amazonka.SageMaker.Types.AlgorithmStatusDetails3Amazonka.SageMaker.Types.DetailedModelPackageStatusAmazonka.SageMaker.Types.Device/Amazonka.SageMaker.Types.DeviceDeploymentStatus0Amazonka.SageMaker.Types.DeviceDeploymentSummary+Amazonka.SageMaker.Types.DeviceFleetSummary$Amazonka.SageMaker.Types.DeviceStats)Amazonka.SageMaker.Types.DeviceSubsetType.Amazonka.SageMaker.Types.DeviceSelectionConfig-Amazonka.SageMaker.Types.DirectInternetAccess"Amazonka.SageMaker.Types.Direction%Amazonka.SageMaker.Types.DomainStatus&Amazonka.SageMaker.Types.DomainDetails(Amazonka.SageMaker.Types.EMRStepMetadataAmazonka.SageMaker.Types.Edge2Amazonka.SageMaker.Types.EdgeDeploymentModelConfig2Amazonka.SageMaker.Types.EdgeDeploymentPlanSummary"Amazonka.SageMaker.Types.EdgeModel&Amazonka.SageMaker.Types.EdgeModelStat)Amazonka.SageMaker.Types.EdgeModelSummary&Amazonka.SageMaker.Types.DeviceSummary/Amazonka.SageMaker.Types.EdgePackagingJobStatus0Amazonka.SageMaker.Types.EdgePackagingJobSummary3Amazonka.SageMaker.Types.EdgePresetDeploymentStatus1Amazonka.SageMaker.Types.EdgePresetDeploymentType3Amazonka.SageMaker.Types.EdgePresetDeploymentOutput)Amazonka.SageMaker.Types.EdgeOutputConfig.Amazonka.SageMaker.Types.EndpointConfigSortKey.Amazonka.SageMaker.Types.EndpointConfigSummary%Amazonka.SageMaker.Types.EndpointInfo(Amazonka.SageMaker.Types.EndpointSortKey'Amazonka.SageMaker.Types.EndpointStatus)Amazonka.SageMaker.Types.EndpointMetadata(Amazonka.SageMaker.Types.EndpointSummary-Amazonka.SageMaker.Types.EnvironmentParameter3Amazonka.SageMaker.Types.EnvironmentParameterRanges4Amazonka.SageMaker.Types.ExecutionRoleIdentityConfig(Amazonka.SageMaker.Types.ExecutionStatus)Amazonka.SageMaker.Types.ExperimentConfig)Amazonka.SageMaker.Types.ExperimentSource*Amazonka.SageMaker.Types.ExperimentSummary(Amazonka.SageMaker.Types.ExplainerConfig)Amazonka.SageMaker.Types.FailStepMetadata.Amazonka.SageMaker.Types.FailureHandlingPolicy-Amazonka.SageMaker.Types.EdgeDeploymentConfig(Amazonka.SageMaker.Types.DeploymentStage+Amazonka.SageMaker.Types.FeatureGroupSortBy.Amazonka.SageMaker.Types.FeatureGroupSortOrder+Amazonka.SageMaker.Types.FeatureGroupStatus)Amazonka.SageMaker.Types.FeatureParameter&Amazonka.SageMaker.Types.FeatureStatus$Amazonka.SageMaker.Types.FeatureType(Amazonka.SageMaker.Types.FeatureMetadata*Amazonka.SageMaker.Types.FeatureDefinition#Amazonka.SageMaker.Types.FileSource-Amazonka.SageMaker.Types.FileSystemAccessMode)Amazonka.SageMaker.Types.FileSystemConfig'Amazonka.SageMaker.Types.FileSystemType-Amazonka.SageMaker.Types.FileSystemDataSource6Amazonka.SageMaker.Types.FinalAutoMLJobObjectiveMetric3Amazonka.SageMaker.Types.FlowDefinitionOutputConfig-Amazonka.SageMaker.Types.FlowDefinitionStatus.Amazonka.SageMaker.Types.FlowDefinitionSummary"Amazonka.SageMaker.Types.Framework"Amazonka.SageMaker.Types.GitConfig.Amazonka.SageMaker.Types.CodeRepositorySummary+Amazonka.SageMaker.Types.GitConfigForUpdate-Amazonka.SageMaker.Types.HubContentDependency)Amazonka.SageMaker.Types.HubContentSortBy)Amazonka.SageMaker.Types.HubContentStatus'Amazonka.SageMaker.Types.HubContentType'Amazonka.SageMaker.Types.HubContentInfo+Amazonka.SageMaker.Types.HubS3StorageConfig"Amazonka.SageMaker.Types.HubSortBy"Amazonka.SageMaker.Types.HubStatus Amazonka.SageMaker.Types.HubInfoAmazonka.SageMaker.Types.HyperParameterTuningJobStrategyConfig$Amazonka.SageMaker.Types.ImageSortBy'Amazonka.SageMaker.Types.ImageSortOrder$Amazonka.SageMaker.Types.ImageStatusAmazonka.SageMaker.Types.Image+Amazonka.SageMaker.Types.ImageVersionSortBy.Amazonka.SageMaker.Types.ImageVersionSortOrder+Amazonka.SageMaker.Types.ImageVersionStatus%Amazonka.SageMaker.Types.ImageVersion/Amazonka.SageMaker.Types.InferenceExecutionMode1Amazonka.SageMaker.Types.InferenceExecutionConfig=Amazonka.SageMaker.Types.InferenceExperimentDataStorageConfig4Amazonka.SageMaker.Types.InferenceExperimentSchedule2Amazonka.SageMaker.Types.InferenceExperimentStatusAmazonka.SageMaker.Types.RecommendationJobCompiledOutputConfig6Amazonka.SageMaker.Types.RecommendationJobOutputConfig7Amazonka.SageMaker.Types.RecommendationJobPayloadConfig9Amazonka.SageMaker.Types.RecommendationJobContainerConfig7Amazonka.SageMaker.Types.RecommendationJobResourceLimit0Amazonka.SageMaker.Types.RecommendationJobStatusannotationConsolidationConfig_annotationConsolidationLambdaArn%$fToJSONAnnotationConsolidationConfig%$fNFDataAnnotationConsolidationConfig'$fHashableAnnotationConsolidationConfig'$fFromJSONAnnotationConsolidationConfig!$fEqAnnotationConsolidationConfig#$fReadAnnotationConsolidationConfig#$fShowAnnotationConsolidationConfig&$fGenericAnnotationConsolidationConfigAppImageConfigSortKeyAppImageConfigSortKey'fromAppImageConfigSortKeyAppImageConfigSortKey_Name&AppImageConfigSortKey_LastModifiedTime"AppImageConfigSortKey_CreationTime$fShowAppImageConfigSortKey$fReadAppImageConfigSortKey$fEqAppImageConfigSortKey$fOrdAppImageConfigSortKey$fGenericAppImageConfigSortKey$fHashableAppImageConfigSortKey$fNFDataAppImageConfigSortKey$fFromTextAppImageConfigSortKey$fToTextAppImageConfigSortKey#$fToByteStringAppImageConfigSortKey$fToLogAppImageConfigSortKey$fToHeaderAppImageConfigSortKey$fToQueryAppImageConfigSortKey$fFromJSONAppImageConfigSortKey"$fFromJSONKeyAppImageConfigSortKey$fToJSONAppImageConfigSortKey $fToJSONKeyAppImageConfigSortKey$fFromXMLAppImageConfigSortKey$fToXMLAppImageConfigSortKeyAppInstanceTypeAppInstanceType'fromAppInstanceTypeAppInstanceType_SystemAppInstanceType_Ml_t3_xlargeAppInstanceType_Ml_t3_smallAppInstanceType_Ml_t3_microAppInstanceType_Ml_t3_mediumAppInstanceType_Ml_t3_largeAppInstanceType_Ml_t3_2xlargeAppInstanceType_Ml_r5_xlargeAppInstanceType_Ml_r5_largeAppInstanceType_Ml_r5_8xlargeAppInstanceType_Ml_r5_4xlargeAppInstanceType_Ml_r5_2xlargeAppInstanceType_Ml_r5_24xlargeAppInstanceType_Ml_r5_16xlargeAppInstanceType_Ml_r5_12xlarge AppInstanceType_Ml_p3dn_24xlargeAppInstanceType_Ml_p3_8xlargeAppInstanceType_Ml_p3_2xlargeAppInstanceType_Ml_p3_16xlargeAppInstanceType_Ml_m5d_xlargeAppInstanceType_Ml_m5d_largeAppInstanceType_Ml_m5d_8xlargeAppInstanceType_Ml_m5d_4xlargeAppInstanceType_Ml_m5d_2xlargeAppInstanceType_Ml_m5d_24xlargeAppInstanceType_Ml_m5d_16xlargeAppInstanceType_Ml_m5d_12xlargeAppInstanceType_Ml_m5_xlargeAppInstanceType_Ml_m5_largeAppInstanceType_Ml_m5_8xlargeAppInstanceType_Ml_m5_4xlargeAppInstanceType_Ml_m5_2xlargeAppInstanceType_Ml_m5_24xlargeAppInstanceType_Ml_m5_16xlargeAppInstanceType_Ml_m5_12xlargeAppInstanceType_Ml_g5_xlargeAppInstanceType_Ml_g5_8xlargeAppInstanceType_Ml_g5_4xlargeAppInstanceType_Ml_g5_48xlargeAppInstanceType_Ml_g5_2xlargeAppInstanceType_Ml_g5_24xlargeAppInstanceType_Ml_g5_16xlargeAppInstanceType_Ml_g5_12xlargeAppInstanceType_Ml_g4dn_xlargeAppInstanceType_Ml_g4dn_8xlargeAppInstanceType_Ml_g4dn_4xlargeAppInstanceType_Ml_g4dn_2xlarge AppInstanceType_Ml_g4dn_16xlarge AppInstanceType_Ml_g4dn_12xlargeAppInstanceType_Ml_c5_xlargeAppInstanceType_Ml_c5_largeAppInstanceType_Ml_c5_9xlargeAppInstanceType_Ml_c5_4xlargeAppInstanceType_Ml_c5_2xlargeAppInstanceType_Ml_c5_24xlargeAppInstanceType_Ml_c5_18xlargeAppInstanceType_Ml_c5_12xlarge$fShowAppInstanceType$fReadAppInstanceType$fEqAppInstanceType$fOrdAppInstanceType$fGenericAppInstanceType$fHashableAppInstanceType$fNFDataAppInstanceType$fFromTextAppInstanceType$fToTextAppInstanceType$fToByteStringAppInstanceType$fToLogAppInstanceType$fToHeaderAppInstanceType$fToQueryAppInstanceType$fFromJSONAppInstanceType$fFromJSONKeyAppInstanceType$fToJSONAppInstanceType$fToJSONKeyAppInstanceType$fFromXMLAppInstanceType$fToXMLAppInstanceTypeAppNetworkAccessTypeAppNetworkAccessType'fromAppNetworkAccessTypeAppNetworkAccessType_VpcOnly'AppNetworkAccessType_PublicInternetOnly$fShowAppNetworkAccessType$fReadAppNetworkAccessType$fEqAppNetworkAccessType$fOrdAppNetworkAccessType$fGenericAppNetworkAccessType$fHashableAppNetworkAccessType$fNFDataAppNetworkAccessType$fFromTextAppNetworkAccessType$fToTextAppNetworkAccessType"$fToByteStringAppNetworkAccessType$fToLogAppNetworkAccessType$fToHeaderAppNetworkAccessType$fToQueryAppNetworkAccessType$fFromJSONAppNetworkAccessType!$fFromJSONKeyAppNetworkAccessType$fToJSONAppNetworkAccessType$fToJSONKeyAppNetworkAccessType$fFromXMLAppNetworkAccessType$fToXMLAppNetworkAccessTypeAppSecurityGroupManagementAppSecurityGroupManagement'fromAppSecurityGroupManagement"AppSecurityGroupManagement_Service#AppSecurityGroupManagement_Customer $fShowAppSecurityGroupManagement $fReadAppSecurityGroupManagement$fEqAppSecurityGroupManagement$fOrdAppSecurityGroupManagement#$fGenericAppSecurityGroupManagement$$fHashableAppSecurityGroupManagement"$fNFDataAppSecurityGroupManagement$$fFromTextAppSecurityGroupManagement"$fToTextAppSecurityGroupManagement($fToByteStringAppSecurityGroupManagement!$fToLogAppSecurityGroupManagement$$fToHeaderAppSecurityGroupManagement#$fToQueryAppSecurityGroupManagement$$fFromJSONAppSecurityGroupManagement'$fFromJSONKeyAppSecurityGroupManagement"$fToJSONAppSecurityGroupManagement%$fToJSONKeyAppSecurityGroupManagement#$fFromXMLAppSecurityGroupManagement!$fToXMLAppSecurityGroupManagement AppSortKey AppSortKey'fromAppSortKeyAppSortKey_CreationTime$fShowAppSortKey$fReadAppSortKey$fEqAppSortKey$fOrdAppSortKey$fGenericAppSortKey$fHashableAppSortKey$fNFDataAppSortKey$fFromTextAppSortKey$fToTextAppSortKey$fToByteStringAppSortKey$fToLogAppSortKey$fToHeaderAppSortKey$fToQueryAppSortKey$fFromJSONAppSortKey$fFromJSONKeyAppSortKey$fToJSONAppSortKey$fToJSONKeyAppSortKey$fFromXMLAppSortKey$fToXMLAppSortKeyAppSpecificationAppSpecification')$sel:containerArguments:AppSpecification'*$sel:containerEntrypoint:AppSpecification'$sel:imageUri:AppSpecification'newAppSpecification#appSpecification_containerArguments$appSpecification_containerEntrypointappSpecification_imageUri$fToJSONAppSpecification$fNFDataAppSpecification$fHashableAppSpecification$fFromJSONAppSpecification$fEqAppSpecification$fReadAppSpecification$fShowAppSpecification$fGenericAppSpecification AppStatus AppStatus' fromAppStatusAppStatus_PendingAppStatus_InServiceAppStatus_FailedAppStatus_DeletingAppStatus_Deleted$fShowAppStatus$fReadAppStatus $fEqAppStatus$fOrdAppStatus$fGenericAppStatus$fHashableAppStatus$fNFDataAppStatus$fFromTextAppStatus$fToTextAppStatus$fToByteStringAppStatus$fToLogAppStatus$fToHeaderAppStatus$fToQueryAppStatus$fFromJSONAppStatus$fFromJSONKeyAppStatus$fToJSONAppStatus$fToJSONKeyAppStatus$fFromXMLAppStatus$fToXMLAppStatusAppTypeAppType' fromAppTypeAppType_TensorBoardAppType_RStudioServerProAppType_RSessionGatewayAppType_KernelGatewayAppType_JupyterServer $fShowAppType $fReadAppType $fEqAppType $fOrdAppType$fGenericAppType$fHashableAppType$fNFDataAppType$fFromTextAppType$fToTextAppType$fToByteStringAppType$fToLogAppType$fToHeaderAppType$fToQueryAppType$fFromJSONAppType$fFromJSONKeyAppType$fToJSONAppType$fToJSONKeyAppType$fFromXMLAppType$fToXMLAppType AppDetails AppDetails'$sel:appName:AppDetails'$sel:appType:AppDetails'$sel:creationTime:AppDetails'$sel:domainId:AppDetails'$sel:spaceName:AppDetails'$sel:status:AppDetails' $sel:userProfileName:AppDetails' newAppDetailsappDetails_appNameappDetails_appTypeappDetails_creationTimeappDetails_domainIdappDetails_spaceNameappDetails_statusappDetails_userProfileName$fNFDataAppDetails$fHashableAppDetails$fFromJSONAppDetails$fEqAppDetails$fReadAppDetails$fShowAppDetails$fGenericAppDetailsArtifactSourceIdTypeArtifactSourceIdType'fromArtifactSourceIdTypeArtifactSourceIdType_S3VersionArtifactSourceIdType_S3ETagArtifactSourceIdType_MD5HashArtifactSourceIdType_Custom$fShowArtifactSourceIdType$fReadArtifactSourceIdType$fEqArtifactSourceIdType$fOrdArtifactSourceIdType$fGenericArtifactSourceIdType$fHashableArtifactSourceIdType$fNFDataArtifactSourceIdType$fFromTextArtifactSourceIdType$fToTextArtifactSourceIdType"$fToByteStringArtifactSourceIdType$fToLogArtifactSourceIdType$fToHeaderArtifactSourceIdType$fToQueryArtifactSourceIdType$fFromJSONArtifactSourceIdType!$fFromJSONKeyArtifactSourceIdType$fToJSONArtifactSourceIdType$fToJSONKeyArtifactSourceIdType$fFromXMLArtifactSourceIdType$fToXMLArtifactSourceIdTypeArtifactSourceTypeArtifactSourceType'%$sel:sourceIdType:ArtifactSourceType'$sel:value:ArtifactSourceType'newArtifactSourceTypeartifactSourceType_sourceIdTypeartifactSourceType_value$fToJSONArtifactSourceType$fNFDataArtifactSourceType$fHashableArtifactSourceType$fFromJSONArtifactSourceType$fEqArtifactSourceType$fReadArtifactSourceType$fShowArtifactSourceType$fGenericArtifactSourceTypeArtifactSourceArtifactSource' $sel:sourceTypes:ArtifactSource'$sel:sourceUri:ArtifactSource'newArtifactSourceartifactSource_sourceTypesartifactSource_sourceUri$fToJSONArtifactSource$fNFDataArtifactSource$fHashableArtifactSource$fFromJSONArtifactSource$fEqArtifactSource$fReadArtifactSource$fShowArtifactSource$fGenericArtifactSourceArtifactSummaryArtifactSummary'!$sel:artifactArn:ArtifactSummary'"$sel:artifactName:ArtifactSummary'"$sel:artifactType:ArtifactSummary'"$sel:creationTime:ArtifactSummary'&$sel:lastModifiedTime:ArtifactSummary'$sel:source:ArtifactSummary'newArtifactSummaryartifactSummary_artifactArnartifactSummary_artifactNameartifactSummary_artifactTypeartifactSummary_creationTime artifactSummary_lastModifiedTimeartifactSummary_source$fNFDataArtifactSummary$fHashableArtifactSummary$fFromJSONArtifactSummary$fEqArtifactSummary$fReadArtifactSummary$fShowArtifactSummary$fGenericArtifactSummary AssemblyType AssemblyType'fromAssemblyTypeAssemblyType_NoneAssemblyType_Line$fShowAssemblyType$fReadAssemblyType$fEqAssemblyType$fOrdAssemblyType$fGenericAssemblyType$fHashableAssemblyType$fNFDataAssemblyType$fFromTextAssemblyType$fToTextAssemblyType$fToByteStringAssemblyType$fToLogAssemblyType$fToHeaderAssemblyType$fToQueryAssemblyType$fFromJSONAssemblyType$fFromJSONKeyAssemblyType$fToJSONAssemblyType$fToJSONKeyAssemblyType$fFromXMLAssemblyType$fToXMLAssemblyTypeAssociationEdgeTypeAssociationEdgeType'fromAssociationEdgeTypeAssociationEdgeType_ProducedAssociationEdgeType_DerivedFrom!AssociationEdgeType_ContributedTo"AssociationEdgeType_AssociatedWith$fShowAssociationEdgeType$fReadAssociationEdgeType$fEqAssociationEdgeType$fOrdAssociationEdgeType$fGenericAssociationEdgeType$fHashableAssociationEdgeType$fNFDataAssociationEdgeType$fFromTextAssociationEdgeType$fToTextAssociationEdgeType!$fToByteStringAssociationEdgeType$fToLogAssociationEdgeType$fToHeaderAssociationEdgeType$fToQueryAssociationEdgeType$fFromJSONAssociationEdgeType $fFromJSONKeyAssociationEdgeType$fToJSONAssociationEdgeType$fToJSONKeyAssociationEdgeType$fFromXMLAssociationEdgeType$fToXMLAssociationEdgeTypeAsyncInferenceClientConfigAsyncInferenceClientConfig'$sel:maxConcurrentInvocationsPerInstance:AsyncInferenceClientConfig'newAsyncInferenceClientConfig>asyncInferenceClientConfig_maxConcurrentInvocationsPerInstance"$fToJSONAsyncInferenceClientConfig"$fNFDataAsyncInferenceClientConfig$$fHashableAsyncInferenceClientConfig$$fFromJSONAsyncInferenceClientConfig$fEqAsyncInferenceClientConfig $fReadAsyncInferenceClientConfig $fShowAsyncInferenceClientConfig#$fGenericAsyncInferenceClientConfig AsyncInferenceNotificationConfig!AsyncInferenceNotificationConfig'1$sel:errorTopic:AsyncInferenceNotificationConfig'3$sel:successTopic:AsyncInferenceNotificationConfig'#newAsyncInferenceNotificationConfig+asyncInferenceNotificationConfig_errorTopic-asyncInferenceNotificationConfig_successTopic($fToJSONAsyncInferenceNotificationConfig($fNFDataAsyncInferenceNotificationConfig*$fHashableAsyncInferenceNotificationConfig*$fFromJSONAsyncInferenceNotificationConfig$$fEqAsyncInferenceNotificationConfig&$fReadAsyncInferenceNotificationConfig&$fShowAsyncInferenceNotificationConfig)$fGenericAsyncInferenceNotificationConfigAsyncInferenceOutputConfigAsyncInferenceOutputConfig')$sel:kmsKeyId:AsyncInferenceOutputConfig'3$sel:notificationConfig:AsyncInferenceOutputConfig'-$sel:s3OutputPath:AsyncInferenceOutputConfig'newAsyncInferenceOutputConfig#asyncInferenceOutputConfig_kmsKeyId-asyncInferenceOutputConfig_notificationConfig'asyncInferenceOutputConfig_s3OutputPath"$fToJSONAsyncInferenceOutputConfig"$fNFDataAsyncInferenceOutputConfig$$fHashableAsyncInferenceOutputConfig$$fFromJSONAsyncInferenceOutputConfig$fEqAsyncInferenceOutputConfig $fReadAsyncInferenceOutputConfig $fShowAsyncInferenceOutputConfig#$fGenericAsyncInferenceOutputConfigAsyncInferenceConfigAsyncInferenceConfig''$sel:clientConfig:AsyncInferenceConfig''$sel:outputConfig:AsyncInferenceConfig'newAsyncInferenceConfig!asyncInferenceConfig_clientConfig!asyncInferenceConfig_outputConfig$fToJSONAsyncInferenceConfig$fNFDataAsyncInferenceConfig$fHashableAsyncInferenceConfig$fFromJSONAsyncInferenceConfig$fEqAsyncInferenceConfig$fReadAsyncInferenceConfig$fShowAsyncInferenceConfig$fGenericAsyncInferenceConfigAthenaResultCompressionTypeAthenaResultCompressionType'fromAthenaResultCompressionType AthenaResultCompressionType_ZLIB"AthenaResultCompressionType_SNAPPY AthenaResultCompressionType_GZIP!$fShowAthenaResultCompressionType!$fReadAthenaResultCompressionType$fEqAthenaResultCompressionType $fOrdAthenaResultCompressionType$$fGenericAthenaResultCompressionType%$fHashableAthenaResultCompressionType#$fNFDataAthenaResultCompressionType%$fFromTextAthenaResultCompressionType#$fToTextAthenaResultCompressionType)$fToByteStringAthenaResultCompressionType"$fToLogAthenaResultCompressionType%$fToHeaderAthenaResultCompressionType$$fToQueryAthenaResultCompressionType%$fFromJSONAthenaResultCompressionType($fFromJSONKeyAthenaResultCompressionType#$fToJSONAthenaResultCompressionType&$fToJSONKeyAthenaResultCompressionType$$fFromXMLAthenaResultCompressionType"$fToXMLAthenaResultCompressionTypeAthenaResultFormatAthenaResultFormat'fromAthenaResultFormatAthenaResultFormat_TEXTFILEAthenaResultFormat_PARQUETAthenaResultFormat_ORCAthenaResultFormat_JSONAthenaResultFormat_AVRO$fShowAthenaResultFormat$fReadAthenaResultFormat$fEqAthenaResultFormat$fOrdAthenaResultFormat$fGenericAthenaResultFormat$fHashableAthenaResultFormat$fNFDataAthenaResultFormat$fFromTextAthenaResultFormat$fToTextAthenaResultFormat $fToByteStringAthenaResultFormat$fToLogAthenaResultFormat$fToHeaderAthenaResultFormat$fToQueryAthenaResultFormat$fFromJSONAthenaResultFormat$fFromJSONKeyAthenaResultFormat$fToJSONAthenaResultFormat$fToJSONKeyAthenaResultFormat$fFromXMLAthenaResultFormat$fToXMLAthenaResultFormatAthenaDatasetDefinitionAthenaDatasetDefinition'&$sel:kmsKeyId:AthenaDatasetDefinition'/$sel:outputCompression:AthenaDatasetDefinition''$sel:workGroup:AthenaDatasetDefinition'%$sel:catalog:AthenaDatasetDefinition'&$sel:database:AthenaDatasetDefinition')$sel:queryString:AthenaDatasetDefinition')$sel:outputS3Uri:AthenaDatasetDefinition'*$sel:outputFormat:AthenaDatasetDefinition'newAthenaDatasetDefinition athenaDatasetDefinition_kmsKeyId)athenaDatasetDefinition_outputCompression!athenaDatasetDefinition_workGroupathenaDatasetDefinition_catalog athenaDatasetDefinition_database#athenaDatasetDefinition_queryString#athenaDatasetDefinition_outputS3Uri$athenaDatasetDefinition_outputFormat$fToJSONAthenaDatasetDefinition$fNFDataAthenaDatasetDefinition!$fHashableAthenaDatasetDefinition!$fFromJSONAthenaDatasetDefinition$fEqAthenaDatasetDefinition$fReadAthenaDatasetDefinition$fShowAthenaDatasetDefinition $fGenericAthenaDatasetDefinitionAuthMode AuthMode' fromAuthMode AuthMode_SSO AuthMode_IAM$fShowAuthMode$fReadAuthMode $fEqAuthMode $fOrdAuthMode$fGenericAuthMode$fHashableAuthMode$fNFDataAuthMode$fFromTextAuthMode$fToTextAuthMode$fToByteStringAuthMode$fToLogAuthMode$fToHeaderAuthMode$fToQueryAuthMode$fFromJSONAuthMode$fFromJSONKeyAuthMode$fToJSONAuthMode$fToJSONKeyAuthMode$fFromXMLAuthMode$fToXMLAuthModeAutoMLCandidateGenerationConfig AutoMLCandidateGenerationConfig'?$sel:featureSpecificationS3Uri:AutoMLCandidateGenerationConfig'"newAutoMLCandidateGenerationConfig9autoMLCandidateGenerationConfig_featureSpecificationS3Uri'$fToJSONAutoMLCandidateGenerationConfig'$fNFDataAutoMLCandidateGenerationConfig)$fHashableAutoMLCandidateGenerationConfig)$fFromJSONAutoMLCandidateGenerationConfig#$fEqAutoMLCandidateGenerationConfig%$fReadAutoMLCandidateGenerationConfig%$fShowAutoMLCandidateGenerationConfig($fGenericAutoMLCandidateGenerationConfigAutoMLChannelTypeAutoMLChannelType'fromAutoMLChannelTypeAutoMLChannelType_ValidationAutoMLChannelType_Training$fShowAutoMLChannelType$fReadAutoMLChannelType$fEqAutoMLChannelType$fOrdAutoMLChannelType$fGenericAutoMLChannelType$fHashableAutoMLChannelType$fNFDataAutoMLChannelType$fFromTextAutoMLChannelType$fToTextAutoMLChannelType$fToByteStringAutoMLChannelType$fToLogAutoMLChannelType$fToHeaderAutoMLChannelType$fToQueryAutoMLChannelType$fFromJSONAutoMLChannelType$fFromJSONKeyAutoMLChannelType$fToJSONAutoMLChannelType$fToJSONKeyAutoMLChannelType$fFromXMLAutoMLChannelType$fToXMLAutoMLChannelTypeAutoMLContainerDefinitionAutoMLContainerDefinition'+$sel:environment:AutoMLContainerDefinition'%$sel:image:AutoMLContainerDefinition',$sel:modelDataUrl:AutoMLContainerDefinition'newAutoMLContainerDefinition%autoMLContainerDefinition_environmentautoMLContainerDefinition_image&autoMLContainerDefinition_modelDataUrl!$fNFDataAutoMLContainerDefinition#$fHashableAutoMLContainerDefinition#$fFromJSONAutoMLContainerDefinition$fEqAutoMLContainerDefinition$fReadAutoMLContainerDefinition$fShowAutoMLContainerDefinition"$fGenericAutoMLContainerDefinitionAutoMLDataSplitConfigAutoMLDataSplitConfig'.$sel:validationFraction:AutoMLDataSplitConfig'newAutoMLDataSplitConfig(autoMLDataSplitConfig_validationFraction$fToJSONAutoMLDataSplitConfig$fNFDataAutoMLDataSplitConfig$fHashableAutoMLDataSplitConfig$fFromJSONAutoMLDataSplitConfig$fEqAutoMLDataSplitConfig$fReadAutoMLDataSplitConfig$fShowAutoMLDataSplitConfig$fGenericAutoMLDataSplitConfigAutoMLJobArtifactsAutoMLJobArtifacts'<$sel:candidateDefinitionNotebookLocation:AutoMLJobArtifacts'8$sel:dataExplorationNotebookLocation:AutoMLJobArtifacts'newAutoMLJobArtifacts6autoMLJobArtifacts_candidateDefinitionNotebookLocation2autoMLJobArtifacts_dataExplorationNotebookLocation$fNFDataAutoMLJobArtifacts$fHashableAutoMLJobArtifacts$fFromJSONAutoMLJobArtifacts$fEqAutoMLJobArtifacts$fReadAutoMLJobArtifacts$fShowAutoMLJobArtifacts$fGenericAutoMLJobArtifactsAutoMLJobCompletionCriteriaAutoMLJobCompletionCriteria'>$sel:maxAutoMLJobRuntimeInSeconds:AutoMLJobCompletionCriteria'/$sel:maxCandidates:AutoMLJobCompletionCriteria'$sel:maxRuntimePerTrainingJobInSeconds:AutoMLJobCompletionCriteria'newAutoMLJobCompletionCriteria8autoMLJobCompletionCriteria_maxAutoMLJobRuntimeInSeconds)autoMLJobCompletionCriteria_maxCandidates=autoMLJobCompletionCriteria_maxRuntimePerTrainingJobInSeconds#$fToJSONAutoMLJobCompletionCriteria#$fNFDataAutoMLJobCompletionCriteria%$fHashableAutoMLJobCompletionCriteria%$fFromJSONAutoMLJobCompletionCriteria$fEqAutoMLJobCompletionCriteria!$fReadAutoMLJobCompletionCriteria!$fShowAutoMLJobCompletionCriteria$$fGenericAutoMLJobCompletionCriteriaAutoMLJobObjectiveTypeAutoMLJobObjectiveType'fromAutoMLJobObjectiveTypeAutoMLJobObjectiveType_MinimizeAutoMLJobObjectiveType_Maximize$fShowAutoMLJobObjectiveType$fReadAutoMLJobObjectiveType$fEqAutoMLJobObjectiveType$fOrdAutoMLJobObjectiveType$fGenericAutoMLJobObjectiveType $fHashableAutoMLJobObjectiveType$fNFDataAutoMLJobObjectiveType $fFromTextAutoMLJobObjectiveType$fToTextAutoMLJobObjectiveType$$fToByteStringAutoMLJobObjectiveType$fToLogAutoMLJobObjectiveType $fToHeaderAutoMLJobObjectiveType$fToQueryAutoMLJobObjectiveType $fFromJSONAutoMLJobObjectiveType#$fFromJSONKeyAutoMLJobObjectiveType$fToJSONAutoMLJobObjectiveType!$fToJSONKeyAutoMLJobObjectiveType$fFromXMLAutoMLJobObjectiveType$fToXMLAutoMLJobObjectiveTypeAutoMLJobSecondaryStatusAutoMLJobSecondaryStatus'fromAutoMLJobSecondaryStatus!AutoMLJobSecondaryStatus_Stopping AutoMLJobSecondaryStatus_Stopped!AutoMLJobSecondaryStatus_Starting$AutoMLJobSecondaryStatus_ModelTuning+AutoMLJobSecondaryStatus_ModelInsightsError-AutoMLJobSecondaryStatus_ModelDeploymentError-AutoMLJobSecondaryStatus_MaxCandidatesReached3AutoMLJobSecondaryStatus_MaxAutoMLJobRuntimeReached6AutoMLJobSecondaryStatus_GeneratingModelInsightsReport7AutoMLJobSecondaryStatus_GeneratingExplainabilityReport+AutoMLJobSecondaryStatus_FeatureEngineeringAutoMLJobSecondaryStatus_Failed,AutoMLJobSecondaryStatus_ExplainabilityError'AutoMLJobSecondaryStatus_DeployingModel"AutoMLJobSecondaryStatus_Completed6AutoMLJobSecondaryStatus_CandidateDefinitionsGenerated&AutoMLJobSecondaryStatus_AnalyzingData$fShowAutoMLJobSecondaryStatus$fReadAutoMLJobSecondaryStatus$fEqAutoMLJobSecondaryStatus$fOrdAutoMLJobSecondaryStatus!$fGenericAutoMLJobSecondaryStatus"$fHashableAutoMLJobSecondaryStatus $fNFDataAutoMLJobSecondaryStatus"$fFromTextAutoMLJobSecondaryStatus $fToTextAutoMLJobSecondaryStatus&$fToByteStringAutoMLJobSecondaryStatus$fToLogAutoMLJobSecondaryStatus"$fToHeaderAutoMLJobSecondaryStatus!$fToQueryAutoMLJobSecondaryStatus"$fFromJSONAutoMLJobSecondaryStatus%$fFromJSONKeyAutoMLJobSecondaryStatus $fToJSONAutoMLJobSecondaryStatus#$fToJSONKeyAutoMLJobSecondaryStatus!$fFromXMLAutoMLJobSecondaryStatus$fToXMLAutoMLJobSecondaryStatusAutoMLJobStatusAutoMLJobStatus'fromAutoMLJobStatusAutoMLJobStatus_StoppingAutoMLJobStatus_StoppedAutoMLJobStatus_InProgressAutoMLJobStatus_FailedAutoMLJobStatus_Completed$fShowAutoMLJobStatus$fReadAutoMLJobStatus$fEqAutoMLJobStatus$fOrdAutoMLJobStatus$fGenericAutoMLJobStatus$fHashableAutoMLJobStatus$fNFDataAutoMLJobStatus$fFromTextAutoMLJobStatus$fToTextAutoMLJobStatus$fToByteStringAutoMLJobStatus$fToLogAutoMLJobStatus$fToHeaderAutoMLJobStatus$fToQueryAutoMLJobStatus$fFromJSONAutoMLJobStatus$fFromJSONKeyAutoMLJobStatus$fToJSONAutoMLJobStatus$fToJSONKeyAutoMLJobStatus$fFromXMLAutoMLJobStatus$fToXMLAutoMLJobStatusAutoMLJobStepMetadataAutoMLJobStepMetadata'$sel:arn:AutoMLJobStepMetadata'newAutoMLJobStepMetadataautoMLJobStepMetadata_arn$fNFDataAutoMLJobStepMetadata$fHashableAutoMLJobStepMetadata$fFromJSONAutoMLJobStepMetadata$fEqAutoMLJobStepMetadata$fReadAutoMLJobStepMetadata$fShowAutoMLJobStepMetadata$fGenericAutoMLJobStepMetadataAutoMLMetricEnumAutoMLMetricEnum'fromAutoMLMetricEnumAutoMLMetricEnum_RecallMacroAutoMLMetricEnum_RecallAutoMLMetricEnum_RMSEAutoMLMetricEnum_R2AutoMLMetricEnum_PrecisionMacroAutoMLMetricEnum_PrecisionAutoMLMetricEnum_MSEAutoMLMetricEnum_MAEAutoMLMetricEnum_F1macroAutoMLMetricEnum_F1!AutoMLMetricEnum_BalancedAccuracyAutoMLMetricEnum_AccuracyAutoMLMetricEnum_AUC$fShowAutoMLMetricEnum$fReadAutoMLMetricEnum$fEqAutoMLMetricEnum$fOrdAutoMLMetricEnum$fGenericAutoMLMetricEnum$fHashableAutoMLMetricEnum$fNFDataAutoMLMetricEnum$fFromTextAutoMLMetricEnum$fToTextAutoMLMetricEnum$fToByteStringAutoMLMetricEnum$fToLogAutoMLMetricEnum$fToHeaderAutoMLMetricEnum$fToQueryAutoMLMetricEnum$fFromJSONAutoMLMetricEnum$fFromJSONKeyAutoMLMetricEnum$fToJSONAutoMLMetricEnum$fToJSONKeyAutoMLMetricEnum$fFromXMLAutoMLMetricEnum$fToXMLAutoMLMetricEnumAutoMLJobObjectiveAutoMLJobObjective'#$sel:metricName:AutoMLJobObjective'newAutoMLJobObjectiveautoMLJobObjective_metricName$fToJSONAutoMLJobObjective$fNFDataAutoMLJobObjective$fHashableAutoMLJobObjective$fFromJSONAutoMLJobObjective$fEqAutoMLJobObjective$fReadAutoMLJobObjective$fShowAutoMLJobObjective$fGenericAutoMLJobObjectiveAutoMLMetricExtendedEnumAutoMLMetricExtendedEnum'fromAutoMLMetricExtendedEnum$AutoMLMetricExtendedEnum_RecallMacroAutoMLMetricExtendedEnum_RecallAutoMLMetricExtendedEnum_RMSEAutoMLMetricExtendedEnum_R2'AutoMLMetricExtendedEnum_PrecisionMacro"AutoMLMetricExtendedEnum_PrecisionAutoMLMetricExtendedEnum_MSEAutoMLMetricExtendedEnum_MAE AutoMLMetricExtendedEnum_LogLoss)AutoMLMetricExtendedEnum_InferenceLatency AutoMLMetricExtendedEnum_F1macroAutoMLMetricExtendedEnum_F1)AutoMLMetricExtendedEnum_BalancedAccuracy!AutoMLMetricExtendedEnum_AccuracyAutoMLMetricExtendedEnum_AUC$fShowAutoMLMetricExtendedEnum$fReadAutoMLMetricExtendedEnum$fEqAutoMLMetricExtendedEnum$fOrdAutoMLMetricExtendedEnum!$fGenericAutoMLMetricExtendedEnum"$fHashableAutoMLMetricExtendedEnum $fNFDataAutoMLMetricExtendedEnum"$fFromTextAutoMLMetricExtendedEnum $fToTextAutoMLMetricExtendedEnum&$fToByteStringAutoMLMetricExtendedEnum$fToLogAutoMLMetricExtendedEnum"$fToHeaderAutoMLMetricExtendedEnum!$fToQueryAutoMLMetricExtendedEnum"$fFromJSONAutoMLMetricExtendedEnum%$fFromJSONKeyAutoMLMetricExtendedEnum $fToJSONAutoMLMetricExtendedEnum#$fToJSONKeyAutoMLMetricExtendedEnum!$fFromXMLAutoMLMetricExtendedEnum$fToXMLAutoMLMetricExtendedEnum AutoMLMode AutoMLMode'fromAutoMLMode AutoMLMode_HYPERPARAMETER_TUNINGAutoMLMode_ENSEMBLINGAutoMLMode_AUTO$fShowAutoMLMode$fReadAutoMLMode$fEqAutoMLMode$fOrdAutoMLMode$fGenericAutoMLMode$fHashableAutoMLMode$fNFDataAutoMLMode$fFromTextAutoMLMode$fToTextAutoMLMode$fToByteStringAutoMLMode$fToLogAutoMLMode$fToHeaderAutoMLMode$fToQueryAutoMLMode$fFromJSONAutoMLMode$fFromJSONKeyAutoMLMode$fToJSONAutoMLMode$fToJSONKeyAutoMLMode$fFromXMLAutoMLMode$fToXMLAutoMLModeAutoMLOutputDataConfigAutoMLOutputDataConfig'%$sel:kmsKeyId:AutoMLOutputDataConfig')$sel:s3OutputPath:AutoMLOutputDataConfig'newAutoMLOutputDataConfigautoMLOutputDataConfig_kmsKeyId#autoMLOutputDataConfig_s3OutputPath$fToJSONAutoMLOutputDataConfig$fNFDataAutoMLOutputDataConfig $fHashableAutoMLOutputDataConfig $fFromJSONAutoMLOutputDataConfig$fEqAutoMLOutputDataConfig$fReadAutoMLOutputDataConfig$fShowAutoMLOutputDataConfig$fGenericAutoMLOutputDataConfigAutoMLPartialFailureReasonAutoMLPartialFailureReason'6$sel:partialFailureMessage:AutoMLPartialFailureReason'newAutoMLPartialFailureReason0autoMLPartialFailureReason_partialFailureMessage"$fNFDataAutoMLPartialFailureReason$$fHashableAutoMLPartialFailureReason$$fFromJSONAutoMLPartialFailureReason$fEqAutoMLPartialFailureReason $fReadAutoMLPartialFailureReason $fShowAutoMLPartialFailureReason#$fGenericAutoMLPartialFailureReasonAutoMLJobSummaryAutoMLJobSummary'$sel:endTime:AutoMLJobSummary'$$sel:failureReason:AutoMLJobSummary',$sel:partialFailureReasons:AutoMLJobSummary'$$sel:autoMLJobName:AutoMLJobSummary'#$sel:autoMLJobArn:AutoMLJobSummary'&$sel:autoMLJobStatus:AutoMLJobSummary'/$sel:autoMLJobSecondaryStatus:AutoMLJobSummary'#$sel:creationTime:AutoMLJobSummary''$sel:lastModifiedTime:AutoMLJobSummary'newAutoMLJobSummaryautoMLJobSummary_endTimeautoMLJobSummary_failureReason&autoMLJobSummary_partialFailureReasonsautoMLJobSummary_autoMLJobNameautoMLJobSummary_autoMLJobArn autoMLJobSummary_autoMLJobStatus)autoMLJobSummary_autoMLJobSecondaryStatusautoMLJobSummary_creationTime!autoMLJobSummary_lastModifiedTime$fNFDataAutoMLJobSummary$fHashableAutoMLJobSummary$fFromJSONAutoMLJobSummary$fEqAutoMLJobSummary$fReadAutoMLJobSummary$fShowAutoMLJobSummary$fGenericAutoMLJobSummaryAutoMLS3DataTypeAutoMLS3DataType'fromAutoMLS3DataTypeAutoMLS3DataType_S3PrefixAutoMLS3DataType_ManifestFile$fShowAutoMLS3DataType$fReadAutoMLS3DataType$fEqAutoMLS3DataType$fOrdAutoMLS3DataType$fGenericAutoMLS3DataType$fHashableAutoMLS3DataType$fNFDataAutoMLS3DataType$fFromTextAutoMLS3DataType$fToTextAutoMLS3DataType$fToByteStringAutoMLS3DataType$fToLogAutoMLS3DataType$fToHeaderAutoMLS3DataType$fToQueryAutoMLS3DataType$fFromJSONAutoMLS3DataType$fFromJSONKeyAutoMLS3DataType$fToJSONAutoMLS3DataType$fToJSONKeyAutoMLS3DataType$fFromXMLAutoMLS3DataType$fToXMLAutoMLS3DataTypeAutoMLS3DataSourceAutoMLS3DataSource'#$sel:s3DataType:AutoMLS3DataSource'$sel:s3Uri:AutoMLS3DataSource'newAutoMLS3DataSourceautoMLS3DataSource_s3DataTypeautoMLS3DataSource_s3Uri$fToJSONAutoMLS3DataSource$fNFDataAutoMLS3DataSource$fHashableAutoMLS3DataSource$fFromJSONAutoMLS3DataSource$fEqAutoMLS3DataSource$fReadAutoMLS3DataSource$fShowAutoMLS3DataSource$fGenericAutoMLS3DataSourceAutoMLDataSourceAutoMLDataSource'#$sel:s3DataSource:AutoMLDataSource'newAutoMLDataSourceautoMLDataSource_s3DataSource$fToJSONAutoMLDataSource$fNFDataAutoMLDataSource$fHashableAutoMLDataSource$fFromJSONAutoMLDataSource$fEqAutoMLDataSource$fReadAutoMLDataSource$fShowAutoMLDataSource$fGenericAutoMLDataSource AutoMLSortBy AutoMLSortBy'fromAutoMLSortByAutoMLSortBy_StatusAutoMLSortBy_NameAutoMLSortBy_CreationTime$fShowAutoMLSortBy$fReadAutoMLSortBy$fEqAutoMLSortBy$fOrdAutoMLSortBy$fGenericAutoMLSortBy$fHashableAutoMLSortBy$fNFDataAutoMLSortBy$fFromTextAutoMLSortBy$fToTextAutoMLSortBy$fToByteStringAutoMLSortBy$fToLogAutoMLSortBy$fToHeaderAutoMLSortBy$fToQueryAutoMLSortBy$fFromJSONAutoMLSortBy$fFromJSONKeyAutoMLSortBy$fToJSONAutoMLSortBy$fToJSONKeyAutoMLSortBy$fFromXMLAutoMLSortBy$fToXMLAutoMLSortByAutoMLSortOrderAutoMLSortOrder'fromAutoMLSortOrderAutoMLSortOrder_DescendingAutoMLSortOrder_Ascending$fShowAutoMLSortOrder$fReadAutoMLSortOrder$fEqAutoMLSortOrder$fOrdAutoMLSortOrder$fGenericAutoMLSortOrder$fHashableAutoMLSortOrder$fNFDataAutoMLSortOrder$fFromTextAutoMLSortOrder$fToTextAutoMLSortOrder$fToByteStringAutoMLSortOrder$fToLogAutoMLSortOrder$fToHeaderAutoMLSortOrder$fToQueryAutoMLSortOrder$fFromJSONAutoMLSortOrder$fFromJSONKeyAutoMLSortOrder$fToJSONAutoMLSortOrder$fToJSONKeyAutoMLSortOrder$fFromXMLAutoMLSortOrder$fToXMLAutoMLSortOrderAutoRollbackConfigAutoRollbackConfig'$sel:alarms:AutoRollbackConfig'newAutoRollbackConfigautoRollbackConfig_alarms$fToJSONAutoRollbackConfig$fNFDataAutoRollbackConfig$fHashableAutoRollbackConfig$fFromJSONAutoRollbackConfig$fEqAutoRollbackConfig$fReadAutoRollbackConfig$fShowAutoRollbackConfig$fGenericAutoRollbackConfig AwsManagedHumanLoopRequestSource!AwsManagedHumanLoopRequestSource'$fromAwsManagedHumanLoopRequestSourceAwsManagedHumanLoopRequestSource_AWS_Textract_AnalyzeDocument_Forms_V1AwsManagedHumanLoopRequestSource_AWS_Rekognition_DetectModerationLabels_Image_V3&$fShowAwsManagedHumanLoopRequestSource&$fReadAwsManagedHumanLoopRequestSource$$fEqAwsManagedHumanLoopRequestSource%$fOrdAwsManagedHumanLoopRequestSource)$fGenericAwsManagedHumanLoopRequestSource*$fHashableAwsManagedHumanLoopRequestSource($fNFDataAwsManagedHumanLoopRequestSource*$fFromTextAwsManagedHumanLoopRequestSource($fToTextAwsManagedHumanLoopRequestSource.$fToByteStringAwsManagedHumanLoopRequestSource'$fToLogAwsManagedHumanLoopRequestSource*$fToHeaderAwsManagedHumanLoopRequestSource)$fToQueryAwsManagedHumanLoopRequestSource*$fFromJSONAwsManagedHumanLoopRequestSource-$fFromJSONKeyAwsManagedHumanLoopRequestSource($fToJSONAwsManagedHumanLoopRequestSource+$fToJSONKeyAwsManagedHumanLoopRequestSource)$fFromXMLAwsManagedHumanLoopRequestSource'$fToXMLAwsManagedHumanLoopRequestSourceBatchDataCaptureConfigBatchDataCaptureConfig'0$sel:generateInferenceId:BatchDataCaptureConfig'%$sel:kmsKeyId:BatchDataCaptureConfig'-$sel:destinationS3Uri:BatchDataCaptureConfig'newBatchDataCaptureConfig*batchDataCaptureConfig_generateInferenceIdbatchDataCaptureConfig_kmsKeyId'batchDataCaptureConfig_destinationS3Uri$fToJSONBatchDataCaptureConfig$fNFDataBatchDataCaptureConfig $fHashableBatchDataCaptureConfig $fFromJSONBatchDataCaptureConfig$fEqBatchDataCaptureConfig$fReadBatchDataCaptureConfig$fShowBatchDataCaptureConfig$fGenericBatchDataCaptureConfigBatchDescribeModelPackageErrorBatchDescribeModelPackageError'.$sel:errorCode:BatchDescribeModelPackageError'2$sel:errorResponse:BatchDescribeModelPackageError'!newBatchDescribeModelPackageError(batchDescribeModelPackageError_errorCode,batchDescribeModelPackageError_errorResponse&$fNFDataBatchDescribeModelPackageError($fHashableBatchDescribeModelPackageError($fFromJSONBatchDescribeModelPackageError"$fEqBatchDescribeModelPackageError$$fReadBatchDescribeModelPackageError$$fShowBatchDescribeModelPackageError'$fGenericBatchDescribeModelPackageError BatchStrategyBatchStrategy'fromBatchStrategyBatchStrategy_SingleRecordBatchStrategy_MultiRecord$fShowBatchStrategy$fReadBatchStrategy$fEqBatchStrategy$fOrdBatchStrategy$fGenericBatchStrategy$fHashableBatchStrategy$fNFDataBatchStrategy$fFromTextBatchStrategy$fToTextBatchStrategy$fToByteStringBatchStrategy$fToLogBatchStrategy$fToHeaderBatchStrategy$fToQueryBatchStrategy$fFromJSONBatchStrategy$fFromJSONKeyBatchStrategy$fToJSONBatchStrategy$fToJSONKeyBatchStrategy$fFromXMLBatchStrategy$fToXMLBatchStrategyBooleanOperatorBooleanOperator'fromBooleanOperatorBooleanOperator_OrBooleanOperator_And$fShowBooleanOperator$fReadBooleanOperator$fEqBooleanOperator$fOrdBooleanOperator$fGenericBooleanOperator$fHashableBooleanOperator$fNFDataBooleanOperator$fFromTextBooleanOperator$fToTextBooleanOperator$fToByteStringBooleanOperator$fToLogBooleanOperator$fToHeaderBooleanOperator$fToQueryBooleanOperator$fFromJSONBooleanOperator$fFromJSONKeyBooleanOperator$fToJSONBooleanOperator$fToJSONKeyBooleanOperator$fFromXMLBooleanOperator$fToXMLBooleanOperatorCacheHitResultCacheHitResult'/$sel:sourcePipelineExecutionArn:CacheHitResult'newCacheHitResult)cacheHitResult_sourcePipelineExecutionArn$fNFDataCacheHitResult$fHashableCacheHitResult$fFromJSONCacheHitResult$fEqCacheHitResult$fReadCacheHitResult$fShowCacheHitResult$fGenericCacheHitResultCandidateArtifactLocationsCandidateArtifactLocations'.$sel:modelInsights:CandidateArtifactLocations'/$sel:explainability:CandidateArtifactLocations'newCandidateArtifactLocations(candidateArtifactLocations_modelInsights)candidateArtifactLocations_explainability"$fNFDataCandidateArtifactLocations$$fHashableCandidateArtifactLocations$$fFromJSONCandidateArtifactLocations$fEqCandidateArtifactLocations $fReadCandidateArtifactLocations $fShowCandidateArtifactLocations#$fGenericCandidateArtifactLocationsCandidateSortByCandidateSortBy'fromCandidateSortByCandidateSortBy_Status)CandidateSortBy_FinalObjectiveMetricValueCandidateSortBy_CreationTime$fShowCandidateSortBy$fReadCandidateSortBy$fEqCandidateSortBy$fOrdCandidateSortBy$fGenericCandidateSortBy$fHashableCandidateSortBy$fNFDataCandidateSortBy$fFromTextCandidateSortBy$fToTextCandidateSortBy$fToByteStringCandidateSortBy$fToLogCandidateSortBy$fToHeaderCandidateSortBy$fToQueryCandidateSortBy$fFromJSONCandidateSortBy$fFromJSONKeyCandidateSortBy$fToJSONCandidateSortBy$fToJSONKeyCandidateSortBy$fFromXMLCandidateSortBy$fToXMLCandidateSortByCandidateStatusCandidateStatus'fromCandidateStatusCandidateStatus_StoppingCandidateStatus_StoppedCandidateStatus_InProgressCandidateStatus_FailedCandidateStatus_Completed$fShowCandidateStatus$fReadCandidateStatus$fEqCandidateStatus$fOrdCandidateStatus$fGenericCandidateStatus$fHashableCandidateStatus$fNFDataCandidateStatus$fFromTextCandidateStatus$fToTextCandidateStatus$fToByteStringCandidateStatus$fToLogCandidateStatus$fToHeaderCandidateStatus$fToQueryCandidateStatus$fFromJSONCandidateStatus$fFromJSONKeyCandidateStatus$fToJSONCandidateStatus$fToJSONKeyCandidateStatus$fFromXMLCandidateStatus$fToXMLCandidateStatusCandidateStepTypeCandidateStepType'fromCandidateStepType.CandidateStepType_AWS__SageMaker__TransformJob-CandidateStepType_AWS__SageMaker__TrainingJob/CandidateStepType_AWS__SageMaker__ProcessingJob$fShowCandidateStepType$fReadCandidateStepType$fEqCandidateStepType$fOrdCandidateStepType$fGenericCandidateStepType$fHashableCandidateStepType$fNFDataCandidateStepType$fFromTextCandidateStepType$fToTextCandidateStepType$fToByteStringCandidateStepType$fToLogCandidateStepType$fToHeaderCandidateStepType$fToQueryCandidateStepType$fFromJSONCandidateStepType$fFromJSONKeyCandidateStepType$fToJSONCandidateStepType$fToJSONKeyCandidateStepType$fFromXMLCandidateStepType$fToXMLCandidateStepTypeAutoMLCandidateStepAutoMLCandidateStep'+$sel:candidateStepType:AutoMLCandidateStep'*$sel:candidateStepArn:AutoMLCandidateStep'+$sel:candidateStepName:AutoMLCandidateStep'newAutoMLCandidateStep%autoMLCandidateStep_candidateStepType$autoMLCandidateStep_candidateStepArn%autoMLCandidateStep_candidateStepName$fNFDataAutoMLCandidateStep$fHashableAutoMLCandidateStep$fFromJSONAutoMLCandidateStep$fEqAutoMLCandidateStep$fReadAutoMLCandidateStep$fShowAutoMLCandidateStep$fGenericAutoMLCandidateStepCapacitySizeTypeCapacitySizeType'fromCapacitySizeTypeCapacitySizeType_INSTANCE_COUNT!CapacitySizeType_CAPACITY_PERCENT$fShowCapacitySizeType$fReadCapacitySizeType$fEqCapacitySizeType$fOrdCapacitySizeType$fGenericCapacitySizeType$fHashableCapacitySizeType$fNFDataCapacitySizeType$fFromTextCapacitySizeType$fToTextCapacitySizeType$fToByteStringCapacitySizeType$fToLogCapacitySizeType$fToHeaderCapacitySizeType$fToQueryCapacitySizeType$fFromJSONCapacitySizeType$fFromJSONKeyCapacitySizeType$fToJSONCapacitySizeType$fToJSONKeyCapacitySizeType$fFromXMLCapacitySizeType$fToXMLCapacitySizeType CapacitySize CapacitySize'$sel:type':CapacitySize'$sel:value:CapacitySize'newCapacitySizecapacitySize_typecapacitySize_value$fToJSONCapacitySize$fNFDataCapacitySize$fHashableCapacitySize$fFromJSONCapacitySize$fEqCapacitySize$fReadCapacitySize$fShowCapacitySize$fGenericCapacitySizeCaptureContentTypeHeaderCaptureContentTypeHeader'.$sel:csvContentTypes:CaptureContentTypeHeader'/$sel:jsonContentTypes:CaptureContentTypeHeader'newCaptureContentTypeHeader(captureContentTypeHeader_csvContentTypes)captureContentTypeHeader_jsonContentTypes $fToJSONCaptureContentTypeHeader $fNFDataCaptureContentTypeHeader"$fHashableCaptureContentTypeHeader"$fFromJSONCaptureContentTypeHeader$fEqCaptureContentTypeHeader$fReadCaptureContentTypeHeader$fShowCaptureContentTypeHeader!$fGenericCaptureContentTypeHeader CaptureMode CaptureMode'fromCaptureModeCaptureMode_OutputCaptureMode_Input$fShowCaptureMode$fReadCaptureMode$fEqCaptureMode$fOrdCaptureMode$fGenericCaptureMode$fHashableCaptureMode$fNFDataCaptureMode$fFromTextCaptureMode$fToTextCaptureMode$fToByteStringCaptureMode$fToLogCaptureMode$fToHeaderCaptureMode$fToQueryCaptureMode$fFromJSONCaptureMode$fFromJSONKeyCaptureMode$fToJSONCaptureMode$fToJSONKeyCaptureMode$fFromXMLCaptureMode$fToXMLCaptureMode CaptureOptionCaptureOption'$sel:captureMode:CaptureOption'newCaptureOptioncaptureOption_captureMode$fToJSONCaptureOption$fNFDataCaptureOption$fHashableCaptureOption$fFromJSONCaptureOption$fEqCaptureOption$fReadCaptureOption$fShowCaptureOption$fGenericCaptureOption CaptureStatusCaptureStatus'fromCaptureStatusCaptureStatus_StoppedCaptureStatus_Started$fShowCaptureStatus$fReadCaptureStatus$fEqCaptureStatus$fOrdCaptureStatus$fGenericCaptureStatus$fHashableCaptureStatus$fNFDataCaptureStatus$fFromTextCaptureStatus$fToTextCaptureStatus$fToByteStringCaptureStatus$fToLogCaptureStatus$fToHeaderCaptureStatus$fToQueryCaptureStatus$fFromJSONCaptureStatus$fFromJSONKeyCaptureStatus$fToJSONCaptureStatus$fToJSONKeyCaptureStatus$fFromXMLCaptureStatus$fToXMLCaptureStatusCategoricalParameterCategoricalParameter'$sel:name:CategoricalParameter' $sel:value:CategoricalParameter'newCategoricalParametercategoricalParameter_namecategoricalParameter_value$fToJSONCategoricalParameter$fNFDataCategoricalParameter$fHashableCategoricalParameter$fFromJSONCategoricalParameter$fEqCategoricalParameter$fReadCategoricalParameter$fShowCategoricalParameter$fGenericCategoricalParameterCategoricalParameterRangeCategoricalParameterRange'$$sel:name:CategoricalParameterRange'&$sel:values:CategoricalParameterRange'newCategoricalParameterRangecategoricalParameterRange_name categoricalParameterRange_values!$fToJSONCategoricalParameterRange!$fNFDataCategoricalParameterRange#$fHashableCategoricalParameterRange#$fFromJSONCategoricalParameterRange$fEqCategoricalParameterRange$fReadCategoricalParameterRange$fShowCategoricalParameterRange"$fGenericCategoricalParameterRange&CategoricalParameterRangeSpecification'CategoricalParameterRangeSpecification'3$sel:values:CategoricalParameterRangeSpecification')newCategoricalParameterRangeSpecification-categoricalParameterRangeSpecification_values.$fToJSONCategoricalParameterRangeSpecification.$fNFDataCategoricalParameterRangeSpecification0$fHashableCategoricalParameterRangeSpecification0$fFromJSONCategoricalParameterRangeSpecification*$fEqCategoricalParameterRangeSpecification,$fReadCategoricalParameterRangeSpecification,$fShowCategoricalParameterRangeSpecification/$fGenericCategoricalParameterRangeSpecificationCheckpointConfigCheckpointConfig' $sel:localPath:CheckpointConfig'$sel:s3Uri:CheckpointConfig'newCheckpointConfigcheckpointConfig_localPathcheckpointConfig_s3Uri$fToJSONCheckpointConfig$fNFDataCheckpointConfig$fHashableCheckpointConfig$fFromJSONCheckpointConfig$fEqCheckpointConfig$fReadCheckpointConfig$fShowCheckpointConfig$fGenericCheckpointConfigClarifyCheckStepMetadataClarifyCheckStepMetadata'$sel:baselineUsedForDriftCheckConstraints:ClarifyCheckStepMetadata'<$sel:calculatedBaselineConstraints:ClarifyCheckStepMetadata'*$sel:checkJobArn:ClarifyCheckStepMetadata'($sel:checkType:ClarifyCheckStepMetadata'4$sel:modelPackageGroupName:ClarifyCheckStepMetadata'2$sel:registerNewBaseline:ClarifyCheckStepMetadata'($sel:skipCheck:ClarifyCheckStepMetadata'.$sel:violationReport:ClarifyCheckStepMetadata'newClarifyCheckStepMetadata=clarifyCheckStepMetadata_baselineUsedForDriftCheckConstraints6clarifyCheckStepMetadata_calculatedBaselineConstraints$clarifyCheckStepMetadata_checkJobArn"clarifyCheckStepMetadata_checkType.clarifyCheckStepMetadata_modelPackageGroupName,clarifyCheckStepMetadata_registerNewBaseline"clarifyCheckStepMetadata_skipCheck(clarifyCheckStepMetadata_violationReport $fNFDataClarifyCheckStepMetadata"$fHashableClarifyCheckStepMetadata"$fFromJSONClarifyCheckStepMetadata$fEqClarifyCheckStepMetadata$fReadClarifyCheckStepMetadata$fShowClarifyCheckStepMetadata!$fGenericClarifyCheckStepMetadataClarifyFeatureTypeClarifyFeatureType'fromClarifyFeatureTypeClarifyFeatureType_TextClarifyFeatureType_NumericalClarifyFeatureType_Categorical$fShowClarifyFeatureType$fReadClarifyFeatureType$fEqClarifyFeatureType$fOrdClarifyFeatureType$fGenericClarifyFeatureType$fHashableClarifyFeatureType$fNFDataClarifyFeatureType$fFromTextClarifyFeatureType$fToTextClarifyFeatureType $fToByteStringClarifyFeatureType$fToLogClarifyFeatureType$fToHeaderClarifyFeatureType$fToQueryClarifyFeatureType$fFromJSONClarifyFeatureType$fFromJSONKeyClarifyFeatureType$fToJSONClarifyFeatureType$fToJSONKeyClarifyFeatureType$fFromXMLClarifyFeatureType$fToXMLClarifyFeatureTypeClarifyInferenceConfigClarifyInferenceConfig',$sel:contentTemplate:ClarifyInferenceConfig'+$sel:featureHeaders:ClarifyInferenceConfig')$sel:featureTypes:ClarifyInferenceConfig'.$sel:featuresAttribute:ClarifyInferenceConfig'+$sel:labelAttribute:ClarifyInferenceConfig')$sel:labelHeaders:ClarifyInferenceConfig''$sel:labelIndex:ClarifyInferenceConfig'+$sel:maxPayloadInMB:ClarifyInferenceConfig'+$sel:maxRecordCount:ClarifyInferenceConfig'1$sel:probabilityAttribute:ClarifyInferenceConfig'-$sel:probabilityIndex:ClarifyInferenceConfig'newClarifyInferenceConfig&clarifyInferenceConfig_contentTemplate%clarifyInferenceConfig_featureHeaders#clarifyInferenceConfig_featureTypes(clarifyInferenceConfig_featuresAttribute%clarifyInferenceConfig_labelAttribute#clarifyInferenceConfig_labelHeaders!clarifyInferenceConfig_labelIndex%clarifyInferenceConfig_maxPayloadInMB%clarifyInferenceConfig_maxRecordCount+clarifyInferenceConfig_probabilityAttribute'clarifyInferenceConfig_probabilityIndex$fToJSONClarifyInferenceConfig$fNFDataClarifyInferenceConfig $fHashableClarifyInferenceConfig $fFromJSONClarifyInferenceConfig$fEqClarifyInferenceConfig$fReadClarifyInferenceConfig$fShowClarifyInferenceConfig$fGenericClarifyInferenceConfigClarifyShapBaselineConfigClarifyShapBaselineConfig'($sel:mimeType:ClarifyShapBaselineConfig',$sel:shapBaseline:ClarifyShapBaselineConfig'/$sel:shapBaselineUri:ClarifyShapBaselineConfig'newClarifyShapBaselineConfig"clarifyShapBaselineConfig_mimeType&clarifyShapBaselineConfig_shapBaseline)clarifyShapBaselineConfig_shapBaselineUri!$fToJSONClarifyShapBaselineConfig!$fNFDataClarifyShapBaselineConfig#$fHashableClarifyShapBaselineConfig#$fFromJSONClarifyShapBaselineConfig$fEqClarifyShapBaselineConfig$fReadClarifyShapBaselineConfig$fShowClarifyShapBaselineConfig"$fGenericClarifyShapBaselineConfigClarifyTextGranularityClarifyTextGranularity'fromClarifyTextGranularityClarifyTextGranularity_TokenClarifyTextGranularity_Sentence ClarifyTextGranularity_Paragraph$fShowClarifyTextGranularity$fReadClarifyTextGranularity$fEqClarifyTextGranularity$fOrdClarifyTextGranularity$fGenericClarifyTextGranularity $fHashableClarifyTextGranularity$fNFDataClarifyTextGranularity $fFromTextClarifyTextGranularity$fToTextClarifyTextGranularity$$fToByteStringClarifyTextGranularity$fToLogClarifyTextGranularity $fToHeaderClarifyTextGranularity$fToQueryClarifyTextGranularity $fFromJSONClarifyTextGranularity#$fFromJSONKeyClarifyTextGranularity$fToJSONClarifyTextGranularity!$fToJSONKeyClarifyTextGranularity$fFromXMLClarifyTextGranularity$fToXMLClarifyTextGranularityClarifyTextLanguageClarifyTextLanguage'fromClarifyTextLanguageClarifyTextLanguage_ZhClarifyTextLanguage_YoClarifyTextLanguage_XxClarifyTextLanguage_UrClarifyTextLanguage_UkClarifyTextLanguage_TtClarifyTextLanguage_TrClarifyTextLanguage_TnClarifyTextLanguage_TlClarifyTextLanguage_TeClarifyTextLanguage_TaClarifyTextLanguage_SvClarifyTextLanguage_SrClarifyTextLanguage_SqClarifyTextLanguage_SlClarifyTextLanguage_SkClarifyTextLanguage_SiClarifyTextLanguage_SaClarifyTextLanguage_RuClarifyTextLanguage_RoClarifyTextLanguage_PtClarifyTextLanguage_PlClarifyTextLanguage_NlClarifyTextLanguage_NeClarifyTextLanguage_NbClarifyTextLanguage_MrClarifyTextLanguage_MlClarifyTextLanguage_MkClarifyTextLanguage_LvClarifyTextLanguage_LtClarifyTextLanguage_LijClarifyTextLanguage_LbClarifyTextLanguage_KyClarifyTextLanguage_KnClarifyTextLanguage_ItClarifyTextLanguage_IsClarifyTextLanguage_IdClarifyTextLanguage_HyClarifyTextLanguage_HuClarifyTextLanguage_HrClarifyTextLanguage_HiClarifyTextLanguage_HeClarifyTextLanguage_GuClarifyTextLanguage_GaClarifyTextLanguage_FrClarifyTextLanguage_FiClarifyTextLanguage_FaClarifyTextLanguage_EuClarifyTextLanguage_EtClarifyTextLanguage_EsClarifyTextLanguage_EnClarifyTextLanguage_ElClarifyTextLanguage_DeClarifyTextLanguage_DaClarifyTextLanguage_CsClarifyTextLanguage_CaClarifyTextLanguage_BnClarifyTextLanguage_BgClarifyTextLanguage_ArClarifyTextLanguage_Af$fShowClarifyTextLanguage$fReadClarifyTextLanguage$fEqClarifyTextLanguage$fOrdClarifyTextLanguage$fGenericClarifyTextLanguage$fHashableClarifyTextLanguage$fNFDataClarifyTextLanguage$fFromTextClarifyTextLanguage$fToTextClarifyTextLanguage!$fToByteStringClarifyTextLanguage$fToLogClarifyTextLanguage$fToHeaderClarifyTextLanguage$fToQueryClarifyTextLanguage$fFromJSONClarifyTextLanguage $fFromJSONKeyClarifyTextLanguage$fToJSONClarifyTextLanguage$fToJSONKeyClarifyTextLanguage$fFromXMLClarifyTextLanguage$fToXMLClarifyTextLanguageClarifyTextConfigClarifyTextConfig' $sel:language:ClarifyTextConfig'#$sel:granularity:ClarifyTextConfig'newClarifyTextConfigclarifyTextConfig_languageclarifyTextConfig_granularity$fToJSONClarifyTextConfig$fNFDataClarifyTextConfig$fHashableClarifyTextConfig$fFromJSONClarifyTextConfig$fEqClarifyTextConfig$fReadClarifyTextConfig$fShowClarifyTextConfig$fGenericClarifyTextConfigClarifyShapConfigClarifyShapConfig''$sel:numberOfSamples:ClarifyShapConfig'$sel:seed:ClarifyShapConfig'"$sel:textConfig:ClarifyShapConfig' $sel:useLogit:ClarifyShapConfig'*$sel:shapBaselineConfig:ClarifyShapConfig'newClarifyShapConfig!clarifyShapConfig_numberOfSamplesclarifyShapConfig_seedclarifyShapConfig_textConfigclarifyShapConfig_useLogit$clarifyShapConfig_shapBaselineConfig$fToJSONClarifyShapConfig$fNFDataClarifyShapConfig$fHashableClarifyShapConfig$fFromJSONClarifyShapConfig$fEqClarifyShapConfig$fReadClarifyShapConfig$fShowClarifyShapConfig$fGenericClarifyShapConfigClarifyExplainerConfigClarifyExplainerConfig'/$sel:enableExplanations:ClarifyExplainerConfig',$sel:inferenceConfig:ClarifyExplainerConfig''$sel:shapConfig:ClarifyExplainerConfig'newClarifyExplainerConfig)clarifyExplainerConfig_enableExplanations&clarifyExplainerConfig_inferenceConfig!clarifyExplainerConfig_shapConfig$fToJSONClarifyExplainerConfig$fNFDataClarifyExplainerConfig $fHashableClarifyExplainerConfig $fFromJSONClarifyExplainerConfig$fEqClarifyExplainerConfig$fReadClarifyExplainerConfig$fShowClarifyExplainerConfig$fGenericClarifyExplainerConfigCodeRepositoryCodeRepository'"$sel:repositoryUrl:CodeRepository'newCodeRepositorycodeRepository_repositoryUrl$fToJSONCodeRepository$fNFDataCodeRepository$fHashableCodeRepository$fFromJSONCodeRepository$fEqCodeRepository$fReadCodeRepository$fShowCodeRepository$fGenericCodeRepositoryCodeRepositorySortByCodeRepositorySortBy'fromCodeRepositorySortByCodeRepositorySortBy_Name%CodeRepositorySortBy_LastModifiedTime!CodeRepositorySortBy_CreationTime$fShowCodeRepositorySortBy$fReadCodeRepositorySortBy$fEqCodeRepositorySortBy$fOrdCodeRepositorySortBy$fGenericCodeRepositorySortBy$fHashableCodeRepositorySortBy$fNFDataCodeRepositorySortBy$fFromTextCodeRepositorySortBy$fToTextCodeRepositorySortBy"$fToByteStringCodeRepositorySortBy$fToLogCodeRepositorySortBy$fToHeaderCodeRepositorySortBy$fToQueryCodeRepositorySortBy$fFromJSONCodeRepositorySortBy!$fFromJSONKeyCodeRepositorySortBy$fToJSONCodeRepositorySortBy$fToJSONKeyCodeRepositorySortBy$fFromXMLCodeRepositorySortBy$fToXMLCodeRepositorySortByCodeRepositorySortOrderCodeRepositorySortOrder'fromCodeRepositorySortOrder"CodeRepositorySortOrder_Descending!CodeRepositorySortOrder_Ascending$fShowCodeRepositorySortOrder$fReadCodeRepositorySortOrder$fEqCodeRepositorySortOrder$fOrdCodeRepositorySortOrder $fGenericCodeRepositorySortOrder!$fHashableCodeRepositorySortOrder$fNFDataCodeRepositorySortOrder!$fFromTextCodeRepositorySortOrder$fToTextCodeRepositorySortOrder%$fToByteStringCodeRepositorySortOrder$fToLogCodeRepositorySortOrder!$fToHeaderCodeRepositorySortOrder $fToQueryCodeRepositorySortOrder!$fFromJSONCodeRepositorySortOrder$$fFromJSONKeyCodeRepositorySortOrder$fToJSONCodeRepositorySortOrder"$fToJSONKeyCodeRepositorySortOrder $fFromXMLCodeRepositorySortOrder$fToXMLCodeRepositorySortOrder CognitoConfigCognitoConfig'$sel:userPool:CognitoConfig'$sel:clientId:CognitoConfig'newCognitoConfigcognitoConfig_userPoolcognitoConfig_clientId$fToJSONCognitoConfig$fNFDataCognitoConfig$fHashableCognitoConfig$fFromJSONCognitoConfig$fEqCognitoConfig$fReadCognitoConfig$fShowCognitoConfig$fGenericCognitoConfigCognitoMemberDefinitionCognitoMemberDefinition'&$sel:userPool:CognitoMemberDefinition''$sel:userGroup:CognitoMemberDefinition'&$sel:clientId:CognitoMemberDefinition'newCognitoMemberDefinition cognitoMemberDefinition_userPool!cognitoMemberDefinition_userGroup cognitoMemberDefinition_clientId$fToJSONCognitoMemberDefinition$fNFDataCognitoMemberDefinition!$fHashableCognitoMemberDefinition!$fFromJSONCognitoMemberDefinition$fEqCognitoMemberDefinition$fReadCognitoMemberDefinition$fShowCognitoMemberDefinition $fGenericCognitoMemberDefinitionCollectionConfigurationCollectionConfiguration',$sel:collectionName:CollectionConfiguration'2$sel:collectionParameters:CollectionConfiguration'newCollectionConfiguration&collectionConfiguration_collectionName,collectionConfiguration_collectionParameters$fToJSONCollectionConfiguration$fNFDataCollectionConfiguration!$fHashableCollectionConfiguration!$fFromJSONCollectionConfiguration$fEqCollectionConfiguration$fReadCollectionConfiguration$fShowCollectionConfiguration $fGenericCollectionConfigurationCompilationJobStatusCompilationJobStatus'fromCompilationJobStatusCompilationJobStatus_STOPPINGCompilationJobStatus_STOPPEDCompilationJobStatus_STARTINGCompilationJobStatus_INPROGRESSCompilationJobStatus_FAILEDCompilationJobStatus_COMPLETED$fShowCompilationJobStatus$fReadCompilationJobStatus$fEqCompilationJobStatus$fOrdCompilationJobStatus$fGenericCompilationJobStatus$fHashableCompilationJobStatus$fNFDataCompilationJobStatus$fFromTextCompilationJobStatus$fToTextCompilationJobStatus"$fToByteStringCompilationJobStatus$fToLogCompilationJobStatus$fToHeaderCompilationJobStatus$fToQueryCompilationJobStatus$fFromJSONCompilationJobStatus!$fFromJSONKeyCompilationJobStatus$fToJSONCompilationJobStatus$fToJSONKeyCompilationJobStatus$fFromXMLCompilationJobStatus$fToXMLCompilationJobStatusCompressionTypeCompressionType'fromCompressionTypeCompressionType_NoneCompressionType_Gzip$fShowCompressionType$fReadCompressionType$fEqCompressionType$fOrdCompressionType$fGenericCompressionType$fHashableCompressionType$fNFDataCompressionType$fFromTextCompressionType$fToTextCompressionType$fToByteStringCompressionType$fToLogCompressionType$fToHeaderCompressionType$fToQueryCompressionType$fFromJSONCompressionType$fFromJSONKeyCompressionType$fToJSONCompressionType$fToJSONKeyCompressionType$fFromXMLCompressionType$fToXMLCompressionType AutoMLChannelAutoMLChannel'$sel:channelType:AutoMLChannel'#$sel:compressionType:AutoMLChannel'$sel:contentType:AutoMLChannel'$sel:dataSource:AutoMLChannel''$sel:targetAttributeName:AutoMLChannel'newAutoMLChannelautoMLChannel_channelTypeautoMLChannel_compressionTypeautoMLChannel_contentTypeautoMLChannel_dataSource!autoMLChannel_targetAttributeName$fToJSONAutoMLChannel$fNFDataAutoMLChannel$fHashableAutoMLChannel$fFromJSONAutoMLChannel$fEqAutoMLChannel$fReadAutoMLChannel$fShowAutoMLChannel$fGenericAutoMLChannelConditionOutcomeConditionOutcome'fromConditionOutcomeConditionOutcome_TrueConditionOutcome_False$fShowConditionOutcome$fReadConditionOutcome$fEqConditionOutcome$fOrdConditionOutcome$fGenericConditionOutcome$fHashableConditionOutcome$fNFDataConditionOutcome$fFromTextConditionOutcome$fToTextConditionOutcome$fToByteStringConditionOutcome$fToLogConditionOutcome$fToHeaderConditionOutcome$fToQueryConditionOutcome$fFromJSONConditionOutcome$fFromJSONKeyConditionOutcome$fToJSONConditionOutcome$fToJSONKeyConditionOutcome$fFromXMLConditionOutcome$fToXMLConditionOutcomeConditionStepMetadataConditionStepMetadata'#$sel:outcome:ConditionStepMetadata'newConditionStepMetadataconditionStepMetadata_outcome$fNFDataConditionStepMetadata$fHashableConditionStepMetadata$fFromJSONConditionStepMetadata$fEqConditionStepMetadata$fReadConditionStepMetadata$fShowConditionStepMetadata$fGenericConditionStepMetadata ContainerModeContainerMode'fromContainerModeContainerMode_SingleModelContainerMode_MultiModel$fShowContainerMode$fReadContainerMode$fEqContainerMode$fOrdContainerMode$fGenericContainerMode$fHashableContainerMode$fNFDataContainerMode$fFromTextContainerMode$fToTextContainerMode$fToByteStringContainerMode$fToLogContainerMode$fToHeaderContainerMode$fToQueryContainerMode$fFromJSONContainerMode$fFromJSONKeyContainerMode$fToJSONContainerMode$fToJSONKeyContainerMode$fFromXMLContainerMode$fToXMLContainerModeContentClassifierContentClassifier'fromContentClassifier9ContentClassifier_FreeOfPersonallyIdentifiableInformation$ContentClassifier_FreeOfAdultContent$fShowContentClassifier$fReadContentClassifier$fEqContentClassifier$fOrdContentClassifier$fGenericContentClassifier$fHashableContentClassifier$fNFDataContentClassifier$fFromTextContentClassifier$fToTextContentClassifier$fToByteStringContentClassifier$fToLogContentClassifier$fToHeaderContentClassifier$fToQueryContentClassifier$fFromJSONContentClassifier$fFromJSONKeyContentClassifier$fToJSONContentClassifier$fToJSONKeyContentClassifier$fFromXMLContentClassifier$fToXMLContentClassifier ContextSourceContextSource'$sel:sourceId:ContextSource'$sel:sourceType:ContextSource'$sel:sourceUri:ContextSource'newContextSourcecontextSource_sourceIdcontextSource_sourceTypecontextSource_sourceUri$fToJSONContextSource$fNFDataContextSource$fHashableContextSource$fFromJSONContextSource$fEqContextSource$fReadContextSource$fShowContextSource$fGenericContextSourceContextSummaryContextSummary'$sel:contextArn:ContextSummary' $sel:contextName:ContextSummary' $sel:contextType:ContextSummary'!$sel:creationTime:ContextSummary'%$sel:lastModifiedTime:ContextSummary'$sel:source:ContextSummary'newContextSummarycontextSummary_contextArncontextSummary_contextNamecontextSummary_contextTypecontextSummary_creationTimecontextSummary_lastModifiedTimecontextSummary_source$fNFDataContextSummary$fHashableContextSummary$fFromJSONContextSummary$fEqContextSummary$fReadContextSummary$fShowContextSummary$fGenericContextSummary%ContinuousParameterRangeSpecification&ContinuousParameterRangeSpecification'4$sel:minValue:ContinuousParameterRangeSpecification'4$sel:maxValue:ContinuousParameterRangeSpecification'(newContinuousParameterRangeSpecification.continuousParameterRangeSpecification_minValue.continuousParameterRangeSpecification_maxValue-$fToJSONContinuousParameterRangeSpecification-$fNFDataContinuousParameterRangeSpecification/$fHashableContinuousParameterRangeSpecification/$fFromJSONContinuousParameterRangeSpecification)$fEqContinuousParameterRangeSpecification+$fReadContinuousParameterRangeSpecification+$fShowContinuousParameterRangeSpecification.$fGenericContinuousParameterRangeSpecification CustomImage CustomImage'$$sel:imageVersionNumber:CustomImage'$sel:imageName:CustomImage'$$sel:appImageConfigName:CustomImage'newCustomImagecustomImage_imageVersionNumbercustomImage_imageNamecustomImage_appImageConfigName$fToJSONCustomImage$fNFDataCustomImage$fHashableCustomImage$fFromJSONCustomImage$fEqCustomImage$fReadCustomImage$fShowCustomImage$fGenericCustomImageDataCaptureConfigDataCaptureConfig'0$sel:captureContentTypeHeader:DataCaptureConfig'%$sel:enableCapture:DataCaptureConfig' $sel:kmsKeyId:DataCaptureConfig'1$sel:initialSamplingPercentage:DataCaptureConfig'($sel:destinationS3Uri:DataCaptureConfig'&$sel:captureOptions:DataCaptureConfig'newDataCaptureConfig*dataCaptureConfig_captureContentTypeHeaderdataCaptureConfig_enableCapturedataCaptureConfig_kmsKeyId+dataCaptureConfig_initialSamplingPercentage"dataCaptureConfig_destinationS3Uri dataCaptureConfig_captureOptions$fToJSONDataCaptureConfig$fNFDataDataCaptureConfig$fHashableDataCaptureConfig$fFromJSONDataCaptureConfig$fEqDataCaptureConfig$fReadDataCaptureConfig$fShowDataCaptureConfig$fGenericDataCaptureConfigDataCaptureConfigSummaryDataCaptureConfigSummary',$sel:enableCapture:DataCaptureConfigSummary',$sel:captureStatus:DataCaptureConfigSummary'8$sel:currentSamplingPercentage:DataCaptureConfigSummary'/$sel:destinationS3Uri:DataCaptureConfigSummary''$sel:kmsKeyId:DataCaptureConfigSummary'newDataCaptureConfigSummary&dataCaptureConfigSummary_enableCapture&dataCaptureConfigSummary_captureStatus2dataCaptureConfigSummary_currentSamplingPercentage)dataCaptureConfigSummary_destinationS3Uri!dataCaptureConfigSummary_kmsKeyId $fNFDataDataCaptureConfigSummary"$fHashableDataCaptureConfigSummary"$fFromJSONDataCaptureConfigSummary$fEqDataCaptureConfigSummary$fReadDataCaptureConfigSummary$fShowDataCaptureConfigSummary!$fGenericDataCaptureConfigSummaryDataCatalogConfigDataCatalogConfig'!$sel:tableName:DataCatalogConfig'$sel:catalog:DataCatalogConfig' $sel:database:DataCatalogConfig'newDataCatalogConfigdataCatalogConfig_tableNamedataCatalogConfig_catalogdataCatalogConfig_database$fToJSONDataCatalogConfig$fNFDataDataCatalogConfig$fHashableDataCatalogConfig$fFromJSONDataCatalogConfig$fEqDataCatalogConfig$fReadDataCatalogConfig$fShowDataCatalogConfig$fGenericDataCatalogConfigDataDistributionTypeDataDistributionType'fromDataDistributionType#DataDistributionType_ShardedByS3Key$DataDistributionType_FullyReplicated$fShowDataDistributionType$fReadDataDistributionType$fEqDataDistributionType$fOrdDataDistributionType$fGenericDataDistributionType$fHashableDataDistributionType$fNFDataDataDistributionType$fFromTextDataDistributionType$fToTextDataDistributionType"$fToByteStringDataDistributionType$fToLogDataDistributionType$fToHeaderDataDistributionType$fToQueryDataDistributionType$fFromJSONDataDistributionType!$fFromJSONKeyDataDistributionType$fToJSONDataDistributionType$fToJSONKeyDataDistributionType$fFromXMLDataDistributionType$fToXMLDataDistributionTypeDataQualityAppSpecificationDataQualityAppSpecification'4$sel:containerArguments:DataQualityAppSpecification'5$sel:containerEntrypoint:DataQualityAppSpecification'-$sel:environment:DataQualityAppSpecification'$sel:postAnalyticsProcessorSourceUri:DataQualityAppSpecification'=$sel:recordPreprocessorSourceUri:DataQualityAppSpecification'*$sel:imageUri:DataQualityAppSpecification'newDataQualityAppSpecification.dataQualityAppSpecification_containerArguments/dataQualityAppSpecification_containerEntrypoint'dataQualityAppSpecification_environment;dataQualityAppSpecification_postAnalyticsProcessorSourceUri7dataQualityAppSpecification_recordPreprocessorSourceUri$dataQualityAppSpecification_imageUri#$fToJSONDataQualityAppSpecification#$fNFDataDataQualityAppSpecification%$fHashableDataQualityAppSpecification%$fFromJSONDataQualityAppSpecification$fEqDataQualityAppSpecification!$fReadDataQualityAppSpecification!$fShowDataQualityAppSpecification$$fGenericDataQualityAppSpecificationDebugHookConfigDebugHookConfig'.$sel:collectionConfigurations:DebugHookConfig'$$sel:hookParameters:DebugHookConfig'$sel:localPath:DebugHookConfig'"$sel:s3OutputPath:DebugHookConfig'newDebugHookConfig(debugHookConfig_collectionConfigurationsdebugHookConfig_hookParametersdebugHookConfig_localPathdebugHookConfig_s3OutputPath$fToJSONDebugHookConfig$fNFDataDebugHookConfig$fHashableDebugHookConfig$fFromJSONDebugHookConfig$fEqDebugHookConfig$fReadDebugHookConfig$fShowDebugHookConfig$fGenericDebugHookConfig DeployedImageDeployedImage'"$sel:resolutionTime:DeployedImage'!$sel:resolvedImage:DeployedImage'"$sel:specifiedImage:DeployedImage'newDeployedImagedeployedImage_resolutionTimedeployedImage_resolvedImagedeployedImage_specifiedImage$fNFDataDeployedImage$fHashableDeployedImage$fFromJSONDeployedImage$fEqDeployedImage$fReadDeployedImage$fShowDeployedImage$fGenericDeployedImageDesiredWeightAndCapacityDesiredWeightAndCapacity'3$sel:desiredInstanceCount:DesiredWeightAndCapacity',$sel:desiredWeight:DesiredWeightAndCapacity'*$sel:variantName:DesiredWeightAndCapacity'newDesiredWeightAndCapacity-desiredWeightAndCapacity_desiredInstanceCount&desiredWeightAndCapacity_desiredWeight$desiredWeightAndCapacity_variantName $fToJSONDesiredWeightAndCapacity $fNFDataDesiredWeightAndCapacity"$fHashableDesiredWeightAndCapacity$fEqDesiredWeightAndCapacity$fReadDesiredWeightAndCapacity$fShowDesiredWeightAndCapacity!$fGenericDesiredWeightAndCapacityDetailedAlgorithmStatusDetailedAlgorithmStatus'fromDetailedAlgorithmStatus"DetailedAlgorithmStatus_NotStarted"DetailedAlgorithmStatus_InProgressDetailedAlgorithmStatus_Failed!DetailedAlgorithmStatus_Completed$fShowDetailedAlgorithmStatus$fReadDetailedAlgorithmStatus$fEqDetailedAlgorithmStatus$fOrdDetailedAlgorithmStatus $fGenericDetailedAlgorithmStatus!$fHashableDetailedAlgorithmStatus$fNFDataDetailedAlgorithmStatus!$fFromTextDetailedAlgorithmStatus$fToTextDetailedAlgorithmStatus%$fToByteStringDetailedAlgorithmStatus$fToLogDetailedAlgorithmStatus!$fToHeaderDetailedAlgorithmStatus $fToQueryDetailedAlgorithmStatus!$fFromJSONDetailedAlgorithmStatus$$fFromJSONKeyDetailedAlgorithmStatus$fToJSONDetailedAlgorithmStatus"$fToJSONKeyDetailedAlgorithmStatus $fFromXMLDetailedAlgorithmStatus$fToXMLDetailedAlgorithmStatusAlgorithmStatusItemAlgorithmStatusItem''$sel:failureReason:AlgorithmStatusItem'$sel:name:AlgorithmStatusItem' $sel:status:AlgorithmStatusItem'newAlgorithmStatusItem!algorithmStatusItem_failureReasonalgorithmStatusItem_namealgorithmStatusItem_status$fNFDataAlgorithmStatusItem$fHashableAlgorithmStatusItem$fFromJSONAlgorithmStatusItem$fEqAlgorithmStatusItem$fReadAlgorithmStatusItem$fShowAlgorithmStatusItem$fGenericAlgorithmStatusItemAlgorithmStatusDetailsAlgorithmStatusDetails'.$sel:imageScanStatuses:AlgorithmStatusDetails'/$sel:validationStatuses:AlgorithmStatusDetails'newAlgorithmStatusDetails(algorithmStatusDetails_imageScanStatuses)algorithmStatusDetails_validationStatuses$fNFDataAlgorithmStatusDetails $fHashableAlgorithmStatusDetails $fFromJSONAlgorithmStatusDetails$fEqAlgorithmStatusDetails$fReadAlgorithmStatusDetails$fShowAlgorithmStatusDetails$fGenericAlgorithmStatusDetailsDetailedModelPackageStatusDetailedModelPackageStatus'fromDetailedModelPackageStatus%DetailedModelPackageStatus_NotStarted%DetailedModelPackageStatus_InProgress!DetailedModelPackageStatus_Failed$DetailedModelPackageStatus_Completed $fShowDetailedModelPackageStatus $fReadDetailedModelPackageStatus$fEqDetailedModelPackageStatus$fOrdDetailedModelPackageStatus#$fGenericDetailedModelPackageStatus$$fHashableDetailedModelPackageStatus"$fNFDataDetailedModelPackageStatus$$fFromTextDetailedModelPackageStatus"$fToTextDetailedModelPackageStatus($fToByteStringDetailedModelPackageStatus!$fToLogDetailedModelPackageStatus$$fToHeaderDetailedModelPackageStatus#$fToQueryDetailedModelPackageStatus$$fFromJSONDetailedModelPackageStatus'$fFromJSONKeyDetailedModelPackageStatus"$fToJSONDetailedModelPackageStatus%$fToJSONKeyDetailedModelPackageStatus#$fFromXMLDetailedModelPackageStatus!$fToXMLDetailedModelPackageStatusDeviceDevice'$sel:description:Device'$sel:iotThingName:Device'$sel:deviceName:Device' newDevicedevice_descriptiondevice_iotThingNamedevice_deviceName$fToJSONDevice$fNFDataDevice$fHashableDevice $fEqDevice $fReadDevice $fShowDevice$fGenericDeviceDeviceDeploymentStatusDeviceDeploymentStatus'fromDeviceDeploymentStatusDeviceDeploymentStatus_STOPPINGDeviceDeploymentStatus_STOPPED$DeviceDeploymentStatus_READYTODEPLOY!DeviceDeploymentStatus_INPROGRESSDeviceDeploymentStatus_FAILEDDeviceDeploymentStatus_DEPLOYED$fShowDeviceDeploymentStatus$fReadDeviceDeploymentStatus$fEqDeviceDeploymentStatus$fOrdDeviceDeploymentStatus$fGenericDeviceDeploymentStatus $fHashableDeviceDeploymentStatus$fNFDataDeviceDeploymentStatus $fFromTextDeviceDeploymentStatus$fToTextDeviceDeploymentStatus$$fToByteStringDeviceDeploymentStatus$fToLogDeviceDeploymentStatus $fToHeaderDeviceDeploymentStatus$fToQueryDeviceDeploymentStatus $fFromJSONDeviceDeploymentStatus#$fFromJSONKeyDeviceDeploymentStatus$fToJSONDeviceDeploymentStatus!$fToJSONKeyDeviceDeploymentStatus$fFromXMLDeviceDeploymentStatus$fToXMLDeviceDeploymentStatusDeviceDeploymentSummaryDeviceDeploymentSummary'/$sel:deployedStageName:DeviceDeploymentSummary'1$sel:deploymentStartTime:DeviceDeploymentSummary')$sel:description:DeviceDeploymentSummary'4$sel:deviceDeploymentStatus:DeviceDeploymentSummary';$sel:deviceDeploymentStatusMessage:DeviceDeploymentSummary'-$sel:deviceFleetName:DeviceDeploymentSummary'3$sel:edgeDeploymentPlanArn:DeviceDeploymentSummary'4$sel:edgeDeploymentPlanName:DeviceDeploymentSummary''$sel:stageName:DeviceDeploymentSummary'($sel:deviceName:DeviceDeploymentSummary''$sel:deviceArn:DeviceDeploymentSummary'newDeviceDeploymentSummary)deviceDeploymentSummary_deployedStageName+deviceDeploymentSummary_deploymentStartTime#deviceDeploymentSummary_description.deviceDeploymentSummary_deviceDeploymentStatus5deviceDeploymentSummary_deviceDeploymentStatusMessage'deviceDeploymentSummary_deviceFleetName-deviceDeploymentSummary_edgeDeploymentPlanArn.deviceDeploymentSummary_edgeDeploymentPlanName!deviceDeploymentSummary_stageName"deviceDeploymentSummary_deviceName!deviceDeploymentSummary_deviceArn$fNFDataDeviceDeploymentSummary!$fHashableDeviceDeploymentSummary!$fFromJSONDeviceDeploymentSummary$fEqDeviceDeploymentSummary$fReadDeviceDeploymentSummary$fShowDeviceDeploymentSummary $fGenericDeviceDeploymentSummaryDeviceFleetSummaryDeviceFleetSummary'%$sel:creationTime:DeviceFleetSummary')$sel:lastModifiedTime:DeviceFleetSummary''$sel:deviceFleetArn:DeviceFleetSummary'($sel:deviceFleetName:DeviceFleetSummary'newDeviceFleetSummarydeviceFleetSummary_creationTime#deviceFleetSummary_lastModifiedTime!deviceFleetSummary_deviceFleetArn"deviceFleetSummary_deviceFleetName$fNFDataDeviceFleetSummary$fHashableDeviceFleetSummary$fFromJSONDeviceFleetSummary$fEqDeviceFleetSummary$fReadDeviceFleetSummary$fShowDeviceFleetSummary$fGenericDeviceFleetSummary DeviceStats DeviceStats'&$sel:connectedDeviceCount:DeviceStats''$sel:registeredDeviceCount:DeviceStats'newDeviceStats deviceStats_connectedDeviceCount!deviceStats_registeredDeviceCount$fNFDataDeviceStats$fHashableDeviceStats$fFromJSONDeviceStats$fEqDeviceStats$fReadDeviceStats$fShowDeviceStats$fGenericDeviceStatsDeviceSubsetTypeDeviceSubsetType'fromDeviceSubsetTypeDeviceSubsetType_SELECTIONDeviceSubsetType_PERCENTAGEDeviceSubsetType_NAMECONTAINS$fShowDeviceSubsetType$fReadDeviceSubsetType$fEqDeviceSubsetType$fOrdDeviceSubsetType$fGenericDeviceSubsetType$fHashableDeviceSubsetType$fNFDataDeviceSubsetType$fFromTextDeviceSubsetType$fToTextDeviceSubsetType$fToByteStringDeviceSubsetType$fToLogDeviceSubsetType$fToHeaderDeviceSubsetType$fToQueryDeviceSubsetType$fFromJSONDeviceSubsetType$fFromJSONKeyDeviceSubsetType$fToJSONDeviceSubsetType$fToJSONKeyDeviceSubsetType$fFromXMLDeviceSubsetType$fToXMLDeviceSubsetTypeDeviceSelectionConfigDeviceSelectionConfig'.$sel:deviceNameContains:DeviceSelectionConfig''$sel:deviceNames:DeviceSelectionConfig'&$sel:percentage:DeviceSelectionConfig',$sel:deviceSubsetType:DeviceSelectionConfig'newDeviceSelectionConfig(deviceSelectionConfig_deviceNameContains!deviceSelectionConfig_deviceNames deviceSelectionConfig_percentage&deviceSelectionConfig_deviceSubsetType$fToJSONDeviceSelectionConfig$fNFDataDeviceSelectionConfig$fHashableDeviceSelectionConfig$fFromJSONDeviceSelectionConfig$fEqDeviceSelectionConfig$fReadDeviceSelectionConfig$fShowDeviceSelectionConfig$fGenericDeviceSelectionConfigDirectInternetAccessDirectInternetAccess'fromDirectInternetAccessDirectInternetAccess_EnabledDirectInternetAccess_Disabled$fShowDirectInternetAccess$fReadDirectInternetAccess$fEqDirectInternetAccess$fOrdDirectInternetAccess$fGenericDirectInternetAccess$fHashableDirectInternetAccess$fNFDataDirectInternetAccess$fFromTextDirectInternetAccess$fToTextDirectInternetAccess"$fToByteStringDirectInternetAccess$fToLogDirectInternetAccess$fToHeaderDirectInternetAccess$fToQueryDirectInternetAccess$fFromJSONDirectInternetAccess!$fFromJSONKeyDirectInternetAccess$fToJSONDirectInternetAccess$fToJSONKeyDirectInternetAccess$fFromXMLDirectInternetAccess$fToXMLDirectInternetAccess Direction Direction' fromDirectionDirection_DescendantsDirection_BothDirection_Ascendants$fShowDirection$fReadDirection $fEqDirection$fOrdDirection$fGenericDirection$fHashableDirection$fNFDataDirection$fFromTextDirection$fToTextDirection$fToByteStringDirection$fToLogDirection$fToHeaderDirection$fToQueryDirection$fFromJSONDirection$fFromJSONKeyDirection$fToJSONDirection$fToJSONKeyDirection$fFromXMLDirection$fToXMLDirection DomainStatus DomainStatus'fromDomainStatusDomainStatus_UpdatingDomainStatus_Update_FailedDomainStatus_PendingDomainStatus_InServiceDomainStatus_FailedDomainStatus_DeletingDomainStatus_Delete_Failed$fShowDomainStatus$fReadDomainStatus$fEqDomainStatus$fOrdDomainStatus$fGenericDomainStatus$fHashableDomainStatus$fNFDataDomainStatus$fFromTextDomainStatus$fToTextDomainStatus$fToByteStringDomainStatus$fToLogDomainStatus$fToHeaderDomainStatus$fToQueryDomainStatus$fFromJSONDomainStatus$fFromJSONKeyDomainStatus$fToJSONDomainStatus$fToJSONKeyDomainStatus$fFromXMLDomainStatus$fToXMLDomainStatus DomainDetailsDomainDetails' $sel:creationTime:DomainDetails'$sel:domainArn:DomainDetails'$sel:domainId:DomainDetails'$sel:domainName:DomainDetails'$$sel:lastModifiedTime:DomainDetails'$sel:status:DomainDetails'$sel:url:DomainDetails'newDomainDetailsdomainDetails_creationTimedomainDetails_domainArndomainDetails_domainIddomainDetails_domainNamedomainDetails_lastModifiedTimedomainDetails_statusdomainDetails_url$fNFDataDomainDetails$fHashableDomainDetails$fFromJSONDomainDetails$fEqDomainDetails$fReadDomainDetails$fShowDomainDetails$fGenericDomainDetailsEMRStepMetadataEMRStepMetadata'$sel:clusterId:EMRStepMetadata'!$sel:logFilePath:EMRStepMetadata'$sel:stepId:EMRStepMetadata'$sel:stepName:EMRStepMetadata'newEMRStepMetadataeMRStepMetadata_clusterIdeMRStepMetadata_logFilePatheMRStepMetadata_stepIdeMRStepMetadata_stepName$fNFDataEMRStepMetadata$fHashableEMRStepMetadata$fFromJSONEMRStepMetadata$fEqEMRStepMetadata$fReadEMRStepMetadata$fShowEMRStepMetadata$fGenericEMRStepMetadataEdgeEdge'$sel:associationType:Edge'$sel:destinationArn:Edge'$sel:sourceArn:Edge'newEdgeedge_associationTypeedge_destinationArnedge_sourceArn $fNFDataEdge$fHashableEdge$fFromJSONEdge$fEqEdge $fReadEdge $fShowEdge $fGenericEdgeEdgeDeploymentModelConfigEdgeDeploymentModelConfig'+$sel:modelHandle:EdgeDeploymentModelConfig'4$sel:edgePackagingJobName:EdgeDeploymentModelConfig'newEdgeDeploymentModelConfig%edgeDeploymentModelConfig_modelHandle.edgeDeploymentModelConfig_edgePackagingJobName!$fToJSONEdgeDeploymentModelConfig!$fNFDataEdgeDeploymentModelConfig#$fHashableEdgeDeploymentModelConfig#$fFromJSONEdgeDeploymentModelConfig$fEqEdgeDeploymentModelConfig$fReadEdgeDeploymentModelConfig$fShowEdgeDeploymentModelConfig"$fGenericEdgeDeploymentModelConfigEdgeDeploymentPlanSummaryEdgeDeploymentPlanSummary',$sel:creationTime:EdgeDeploymentPlanSummary'0$sel:lastModifiedTime:EdgeDeploymentPlanSummary'5$sel:edgeDeploymentPlanArn:EdgeDeploymentPlanSummary'6$sel:edgeDeploymentPlanName:EdgeDeploymentPlanSummary'/$sel:deviceFleetName:EdgeDeploymentPlanSummary'5$sel:edgeDeploymentSuccess:EdgeDeploymentPlanSummary'5$sel:edgeDeploymentPending:EdgeDeploymentPlanSummary'4$sel:edgeDeploymentFailed:EdgeDeploymentPlanSummary'newEdgeDeploymentPlanSummary&edgeDeploymentPlanSummary_creationTime*edgeDeploymentPlanSummary_lastModifiedTime/edgeDeploymentPlanSummary_edgeDeploymentPlanArn0edgeDeploymentPlanSummary_edgeDeploymentPlanName)edgeDeploymentPlanSummary_deviceFleetName/edgeDeploymentPlanSummary_edgeDeploymentSuccess/edgeDeploymentPlanSummary_edgeDeploymentPending.edgeDeploymentPlanSummary_edgeDeploymentFailed!$fNFDataEdgeDeploymentPlanSummary#$fHashableEdgeDeploymentPlanSummary#$fFromJSONEdgeDeploymentPlanSummary$fEqEdgeDeploymentPlanSummary$fReadEdgeDeploymentPlanSummary$fShowEdgeDeploymentPlanSummary"$fGenericEdgeDeploymentPlanSummary EdgeModel EdgeModel'$sel:latestInference:EdgeModel' $sel:latestSampleTime:EdgeModel'$sel:modelName:EdgeModel'$sel:modelVersion:EdgeModel' newEdgeModeledgeModel_latestInferenceedgeModel_latestSampleTimeedgeModel_modelNameedgeModel_modelVersion$fNFDataEdgeModel$fHashableEdgeModel$fFromJSONEdgeModel $fEqEdgeModel$fReadEdgeModel$fShowEdgeModel$fGenericEdgeModel EdgeModelStatEdgeModelStat'$sel:modelName:EdgeModelStat' $sel:modelVersion:EdgeModelStat'&$sel:offlineDeviceCount:EdgeModelStat'($sel:connectedDeviceCount:EdgeModelStat'%$sel:activeDeviceCount:EdgeModelStat''$sel:samplingDeviceCount:EdgeModelStat'newEdgeModelStatedgeModelStat_modelNameedgeModelStat_modelVersion edgeModelStat_offlineDeviceCount"edgeModelStat_connectedDeviceCountedgeModelStat_activeDeviceCount!edgeModelStat_samplingDeviceCount$fNFDataEdgeModelStat$fHashableEdgeModelStat$fFromJSONEdgeModelStat$fEqEdgeModelStat$fReadEdgeModelStat$fShowEdgeModelStat$fGenericEdgeModelStatEdgeModelSummaryEdgeModelSummary' $sel:modelName:EdgeModelSummary'#$sel:modelVersion:EdgeModelSummary'newEdgeModelSummaryedgeModelSummary_modelNameedgeModelSummary_modelVersion$fNFDataEdgeModelSummary$fHashableEdgeModelSummary$fFromJSONEdgeModelSummary$fEqEdgeModelSummary$fReadEdgeModelSummary$fShowEdgeModelSummary$fGenericEdgeModelSummary DeviceSummaryDeviceSummary' $sel:agentVersion:DeviceSummary'$sel:description:DeviceSummary'#$sel:deviceFleetName:DeviceSummary' $sel:iotThingName:DeviceSummary'#$sel:latestHeartbeat:DeviceSummary'$sel:models:DeviceSummary'$$sel:registrationTime:DeviceSummary'$sel:deviceName:DeviceSummary'$sel:deviceArn:DeviceSummary'newDeviceSummarydeviceSummary_agentVersiondeviceSummary_descriptiondeviceSummary_deviceFleetNamedeviceSummary_iotThingNamedeviceSummary_latestHeartbeatdeviceSummary_modelsdeviceSummary_registrationTimedeviceSummary_deviceNamedeviceSummary_deviceArn$fNFDataDeviceSummary$fHashableDeviceSummary$fFromJSONDeviceSummary$fEqDeviceSummary$fReadDeviceSummary$fShowDeviceSummary$fGenericDeviceSummaryEdgePackagingJobStatusEdgePackagingJobStatus'fromEdgePackagingJobStatusEdgePackagingJobStatus_STOPPINGEdgePackagingJobStatus_STOPPEDEdgePackagingJobStatus_STARTING!EdgePackagingJobStatus_INPROGRESSEdgePackagingJobStatus_FAILED EdgePackagingJobStatus_COMPLETED$fShowEdgePackagingJobStatus$fReadEdgePackagingJobStatus$fEqEdgePackagingJobStatus$fOrdEdgePackagingJobStatus$fGenericEdgePackagingJobStatus $fHashableEdgePackagingJobStatus$fNFDataEdgePackagingJobStatus $fFromTextEdgePackagingJobStatus$fToTextEdgePackagingJobStatus$$fToByteStringEdgePackagingJobStatus$fToLogEdgePackagingJobStatus $fToHeaderEdgePackagingJobStatus$fToQueryEdgePackagingJobStatus $fFromJSONEdgePackagingJobStatus#$fFromJSONKeyEdgePackagingJobStatus$fToJSONEdgePackagingJobStatus!$fToJSONKeyEdgePackagingJobStatus$fFromXMLEdgePackagingJobStatus$fToXMLEdgePackagingJobStatusEdgePackagingJobSummaryEdgePackagingJobSummary'0$sel:compilationJobName:EdgePackagingJobSummary'*$sel:creationTime:EdgePackagingJobSummary'.$sel:lastModifiedTime:EdgePackagingJobSummary''$sel:modelName:EdgePackagingJobSummary'*$sel:modelVersion:EdgePackagingJobSummary'1$sel:edgePackagingJobArn:EdgePackagingJobSummary'2$sel:edgePackagingJobName:EdgePackagingJobSummary'4$sel:edgePackagingJobStatus:EdgePackagingJobSummary'newEdgePackagingJobSummary*edgePackagingJobSummary_compilationJobName$edgePackagingJobSummary_creationTime(edgePackagingJobSummary_lastModifiedTime!edgePackagingJobSummary_modelName$edgePackagingJobSummary_modelVersion+edgePackagingJobSummary_edgePackagingJobArn,edgePackagingJobSummary_edgePackagingJobName.edgePackagingJobSummary_edgePackagingJobStatus$fNFDataEdgePackagingJobSummary!$fHashableEdgePackagingJobSummary!$fFromJSONEdgePackagingJobSummary$fEqEdgePackagingJobSummary$fReadEdgePackagingJobSummary$fShowEdgePackagingJobSummary $fGenericEdgePackagingJobSummaryEdgePresetDeploymentStatusEdgePresetDeploymentStatus'fromEdgePresetDeploymentStatus!EdgePresetDeploymentStatus_FAILED$EdgePresetDeploymentStatus_COMPLETED $fShowEdgePresetDeploymentStatus $fReadEdgePresetDeploymentStatus$fEqEdgePresetDeploymentStatus$fOrdEdgePresetDeploymentStatus#$fGenericEdgePresetDeploymentStatus$$fHashableEdgePresetDeploymentStatus"$fNFDataEdgePresetDeploymentStatus$$fFromTextEdgePresetDeploymentStatus"$fToTextEdgePresetDeploymentStatus($fToByteStringEdgePresetDeploymentStatus!$fToLogEdgePresetDeploymentStatus$$fToHeaderEdgePresetDeploymentStatus#$fToQueryEdgePresetDeploymentStatus$$fFromJSONEdgePresetDeploymentStatus'$fFromJSONKeyEdgePresetDeploymentStatus"$fToJSONEdgePresetDeploymentStatus%$fToJSONKeyEdgePresetDeploymentStatus#$fFromXMLEdgePresetDeploymentStatus!$fToXMLEdgePresetDeploymentStatusEdgePresetDeploymentTypeEdgePresetDeploymentType'fromEdgePresetDeploymentType.EdgePresetDeploymentType_GreengrassV2Component$fShowEdgePresetDeploymentType$fReadEdgePresetDeploymentType$fEqEdgePresetDeploymentType$fOrdEdgePresetDeploymentType!$fGenericEdgePresetDeploymentType"$fHashableEdgePresetDeploymentType $fNFDataEdgePresetDeploymentType"$fFromTextEdgePresetDeploymentType $fToTextEdgePresetDeploymentType&$fToByteStringEdgePresetDeploymentType$fToLogEdgePresetDeploymentType"$fToHeaderEdgePresetDeploymentType!$fToQueryEdgePresetDeploymentType"$fFromJSONEdgePresetDeploymentType%$fFromJSONKeyEdgePresetDeploymentType $fToJSONEdgePresetDeploymentType#$fToJSONKeyEdgePresetDeploymentType!$fFromXMLEdgePresetDeploymentType$fToXMLEdgePresetDeploymentTypeEdgePresetDeploymentOutputEdgePresetDeploymentOutput')$sel:artifact:EdgePresetDeploymentOutput''$sel:status:EdgePresetDeploymentOutput'.$sel:statusMessage:EdgePresetDeploymentOutput'&$sel:type':EdgePresetDeploymentOutput'newEdgePresetDeploymentOutput#edgePresetDeploymentOutput_artifact!edgePresetDeploymentOutput_status(edgePresetDeploymentOutput_statusMessageedgePresetDeploymentOutput_type"$fNFDataEdgePresetDeploymentOutput$$fHashableEdgePresetDeploymentOutput$$fFromJSONEdgePresetDeploymentOutput$fEqEdgePresetDeploymentOutput $fReadEdgePresetDeploymentOutput $fShowEdgePresetDeploymentOutput#$fGenericEdgePresetDeploymentOutputEdgeOutputConfigEdgeOutputConfig'$sel:kmsKeyId:EdgeOutputConfig'-$sel:presetDeploymentConfig:EdgeOutputConfig'+$sel:presetDeploymentType:EdgeOutputConfig''$sel:s3OutputLocation:EdgeOutputConfig'newEdgeOutputConfigedgeOutputConfig_kmsKeyId'edgeOutputConfig_presetDeploymentConfig%edgeOutputConfig_presetDeploymentType!edgeOutputConfig_s3OutputLocation$fToJSONEdgeOutputConfig$fNFDataEdgeOutputConfig$fHashableEdgeOutputConfig$fFromJSONEdgeOutputConfig$fEqEdgeOutputConfig$fReadEdgeOutputConfig$fShowEdgeOutputConfig$fGenericEdgeOutputConfigEndpointConfigSortKeyEndpointConfigSortKey'fromEndpointConfigSortKeyEndpointConfigSortKey_Name"EndpointConfigSortKey_CreationTime$fShowEndpointConfigSortKey$fReadEndpointConfigSortKey$fEqEndpointConfigSortKey$fOrdEndpointConfigSortKey$fGenericEndpointConfigSortKey$fHashableEndpointConfigSortKey$fNFDataEndpointConfigSortKey$fFromTextEndpointConfigSortKey$fToTextEndpointConfigSortKey#$fToByteStringEndpointConfigSortKey$fToLogEndpointConfigSortKey$fToHeaderEndpointConfigSortKey$fToQueryEndpointConfigSortKey$fFromJSONEndpointConfigSortKey"$fFromJSONKeyEndpointConfigSortKey$fToJSONEndpointConfigSortKey $fToJSONKeyEndpointConfigSortKey$fFromXMLEndpointConfigSortKey$fToXMLEndpointConfigSortKeyEndpointConfigSummaryEndpointConfigSummary'.$sel:endpointConfigName:EndpointConfigSummary'-$sel:endpointConfigArn:EndpointConfigSummary'($sel:creationTime:EndpointConfigSummary'newEndpointConfigSummary(endpointConfigSummary_endpointConfigName'endpointConfigSummary_endpointConfigArn"endpointConfigSummary_creationTime$fNFDataEndpointConfigSummary$fHashableEndpointConfigSummary$fFromJSONEndpointConfigSummary$fEqEndpointConfigSummary$fReadEndpointConfigSummary$fShowEndpointConfigSummary$fGenericEndpointConfigSummary EndpointInfo EndpointInfo'$sel:endpointName:EndpointInfo'newEndpointInfoendpointInfo_endpointName$fToJSONEndpointInfo$fNFDataEndpointInfo$fHashableEndpointInfo$fFromJSONEndpointInfo$fEqEndpointInfo$fReadEndpointInfo$fShowEndpointInfo$fGenericEndpointInfoEndpointSortKeyEndpointSortKey'fromEndpointSortKeyEndpointSortKey_StatusEndpointSortKey_NameEndpointSortKey_CreationTime$fShowEndpointSortKey$fReadEndpointSortKey$fEqEndpointSortKey$fOrdEndpointSortKey$fGenericEndpointSortKey$fHashableEndpointSortKey$fNFDataEndpointSortKey$fFromTextEndpointSortKey$fToTextEndpointSortKey$fToByteStringEndpointSortKey$fToLogEndpointSortKey$fToHeaderEndpointSortKey$fToQueryEndpointSortKey$fFromJSONEndpointSortKey$fFromJSONKeyEndpointSortKey$fToJSONEndpointSortKey$fToJSONKeyEndpointSortKey$fFromXMLEndpointSortKey$fToXMLEndpointSortKeyEndpointStatusEndpointStatus'fromEndpointStatusEndpointStatus_UpdatingEndpointStatus_SystemUpdatingEndpointStatus_RollingBackEndpointStatus_OutOfServiceEndpointStatus_InServiceEndpointStatus_FailedEndpointStatus_DeletingEndpointStatus_Creating$fShowEndpointStatus$fReadEndpointStatus$fEqEndpointStatus$fOrdEndpointStatus$fGenericEndpointStatus$fHashableEndpointStatus$fNFDataEndpointStatus$fFromTextEndpointStatus$fToTextEndpointStatus$fToByteStringEndpointStatus$fToLogEndpointStatus$fToHeaderEndpointStatus$fToQueryEndpointStatus$fFromJSONEndpointStatus$fFromJSONKeyEndpointStatus$fToJSONEndpointStatus$fToJSONKeyEndpointStatus$fFromXMLEndpointStatus$fToXMLEndpointStatusEndpointMetadataEndpointMetadata')$sel:endpointConfigName:EndpointMetadata'%$sel:endpointStatus:EndpointMetadata'$$sel:failureReason:EndpointMetadata'#$sel:endpointName:EndpointMetadata'newEndpointMetadata#endpointMetadata_endpointConfigNameendpointMetadata_endpointStatusendpointMetadata_failureReasonendpointMetadata_endpointName$fNFDataEndpointMetadata$fHashableEndpointMetadata$fFromJSONEndpointMetadata$fEqEndpointMetadata$fReadEndpointMetadata$fShowEndpointMetadata$fGenericEndpointMetadataEndpointSummaryEndpointSummary'"$sel:endpointName:EndpointSummary'!$sel:endpointArn:EndpointSummary'"$sel:creationTime:EndpointSummary'&$sel:lastModifiedTime:EndpointSummary'$$sel:endpointStatus:EndpointSummary'newEndpointSummaryendpointSummary_endpointNameendpointSummary_endpointArnendpointSummary_creationTime endpointSummary_lastModifiedTimeendpointSummary_endpointStatus$fNFDataEndpointSummary$fHashableEndpointSummary$fFromJSONEndpointSummary$fEqEndpointSummary$fReadEndpointSummary$fShowEndpointSummary$fGenericEndpointSummaryEnvironmentParameterEnvironmentParameter'$sel:key:EnvironmentParameter'$$sel:valueType:EnvironmentParameter' $sel:value:EnvironmentParameter'newEnvironmentParameterenvironmentParameter_keyenvironmentParameter_valueTypeenvironmentParameter_value$fNFDataEnvironmentParameter$fHashableEnvironmentParameter$fFromJSONEnvironmentParameter$fEqEnvironmentParameter$fReadEnvironmentParameter$fShowEnvironmentParameter$fGenericEnvironmentParameterEnvironmentParameterRangesEnvironmentParameterRanges';$sel:categoricalParameterRanges:EnvironmentParameterRanges'newEnvironmentParameterRanges5environmentParameterRanges_categoricalParameterRanges"$fToJSONEnvironmentParameterRanges"$fNFDataEnvironmentParameterRanges$$fHashableEnvironmentParameterRanges$$fFromJSONEnvironmentParameterRanges$fEqEnvironmentParameterRanges $fReadEnvironmentParameterRanges $fShowEnvironmentParameterRanges#$fGenericEnvironmentParameterRangesExecutionRoleIdentityConfigExecutionRoleIdentityConfig'fromExecutionRoleIdentityConfig-ExecutionRoleIdentityConfig_USER_PROFILE_NAME$ExecutionRoleIdentityConfig_DISABLED!$fShowExecutionRoleIdentityConfig!$fReadExecutionRoleIdentityConfig$fEqExecutionRoleIdentityConfig $fOrdExecutionRoleIdentityConfig$$fGenericExecutionRoleIdentityConfig%$fHashableExecutionRoleIdentityConfig#$fNFDataExecutionRoleIdentityConfig%$fFromTextExecutionRoleIdentityConfig#$fToTextExecutionRoleIdentityConfig)$fToByteStringExecutionRoleIdentityConfig"$fToLogExecutionRoleIdentityConfig%$fToHeaderExecutionRoleIdentityConfig$$fToQueryExecutionRoleIdentityConfig%$fFromJSONExecutionRoleIdentityConfig($fFromJSONKeyExecutionRoleIdentityConfig#$fToJSONExecutionRoleIdentityConfig&$fToJSONKeyExecutionRoleIdentityConfig$$fFromXMLExecutionRoleIdentityConfig"$fToXMLExecutionRoleIdentityConfigExecutionStatusExecutionStatus'fromExecutionStatusExecutionStatus_StoppingExecutionStatus_StoppedExecutionStatus_PendingExecutionStatus_InProgressExecutionStatus_Failed'ExecutionStatus_CompletedWithViolationsExecutionStatus_Completed$fShowExecutionStatus$fReadExecutionStatus$fEqExecutionStatus$fOrdExecutionStatus$fGenericExecutionStatus$fHashableExecutionStatus$fNFDataExecutionStatus$fFromTextExecutionStatus$fToTextExecutionStatus$fToByteStringExecutionStatus$fToLogExecutionStatus$fToHeaderExecutionStatus$fToQueryExecutionStatus$fFromJSONExecutionStatus$fFromJSONKeyExecutionStatus$fToJSONExecutionStatus$fToJSONKeyExecutionStatus$fFromXMLExecutionStatus$fToXMLExecutionStatusExperimentConfigExperimentConfig'%$sel:experimentName:ExperimentConfig'$sel:runName:ExperimentConfig'0$sel:trialComponentDisplayName:ExperimentConfig' $sel:trialName:ExperimentConfig'newExperimentConfigexperimentConfig_experimentNameexperimentConfig_runName*experimentConfig_trialComponentDisplayNameexperimentConfig_trialName$fToJSONExperimentConfig$fNFDataExperimentConfig$fHashableExperimentConfig$fFromJSONExperimentConfig$fEqExperimentConfig$fReadExperimentConfig$fShowExperimentConfig$fGenericExperimentConfigExperimentSourceExperimentSource'!$sel:sourceType:ExperimentSource' $sel:sourceArn:ExperimentSource'newExperimentSourceexperimentSource_sourceTypeexperimentSource_sourceArn$fNFDataExperimentSource$fHashableExperimentSource$fFromJSONExperimentSource$fEqExperimentSource$fReadExperimentSource$fShowExperimentSource$fGenericExperimentSourceExperimentSummaryExperimentSummary'$$sel:creationTime:ExperimentSummary'#$sel:displayName:ExperimentSummary'%$sel:experimentArn:ExperimentSummary'&$sel:experimentName:ExperimentSummary'($sel:experimentSource:ExperimentSummary'($sel:lastModifiedTime:ExperimentSummary'newExperimentSummaryexperimentSummary_creationTimeexperimentSummary_displayNameexperimentSummary_experimentArn experimentSummary_experimentName"experimentSummary_experimentSource"experimentSummary_lastModifiedTime$fNFDataExperimentSummary$fHashableExperimentSummary$fFromJSONExperimentSummary$fEqExperimentSummary$fReadExperimentSummary$fShowExperimentSummary$fGenericExperimentSummaryExplainerConfigExplainerConfig',$sel:clarifyExplainerConfig:ExplainerConfig'newExplainerConfig&explainerConfig_clarifyExplainerConfig$fToJSONExplainerConfig$fNFDataExplainerConfig$fHashableExplainerConfig$fFromJSONExplainerConfig$fEqExplainerConfig$fReadExplainerConfig$fShowExplainerConfig$fGenericExplainerConfigFailStepMetadataFailStepMetadata'#$sel:errorMessage:FailStepMetadata'newFailStepMetadatafailStepMetadata_errorMessage$fNFDataFailStepMetadata$fHashableFailStepMetadata$fFromJSONFailStepMetadata$fEqFailStepMetadata$fReadFailStepMetadata$fShowFailStepMetadata$fGenericFailStepMetadataFailureHandlingPolicyFailureHandlingPolicy'fromFailureHandlingPolicy)FailureHandlingPolicy_ROLLBACK_ON_FAILURE FailureHandlingPolicy_DO_NOTHING$fShowFailureHandlingPolicy$fReadFailureHandlingPolicy$fEqFailureHandlingPolicy$fOrdFailureHandlingPolicy$fGenericFailureHandlingPolicy$fHashableFailureHandlingPolicy$fNFDataFailureHandlingPolicy$fFromTextFailureHandlingPolicy$fToTextFailureHandlingPolicy#$fToByteStringFailureHandlingPolicy$fToLogFailureHandlingPolicy$fToHeaderFailureHandlingPolicy$fToQueryFailureHandlingPolicy$fFromJSONFailureHandlingPolicy"$fFromJSONKeyFailureHandlingPolicy$fToJSONFailureHandlingPolicy $fToJSONKeyFailureHandlingPolicy$fFromXMLFailureHandlingPolicy$fToXMLFailureHandlingPolicyEdgeDeploymentConfigEdgeDeploymentConfig'0$sel:failureHandlingPolicy:EdgeDeploymentConfig'newEdgeDeploymentConfig*edgeDeploymentConfig_failureHandlingPolicy$fToJSONEdgeDeploymentConfig$fNFDataEdgeDeploymentConfig$fHashableEdgeDeploymentConfig$fFromJSONEdgeDeploymentConfig$fEqEdgeDeploymentConfig$fReadEdgeDeploymentConfig$fShowEdgeDeploymentConfig$fGenericEdgeDeploymentConfigDeploymentStageDeploymentStage'&$sel:deploymentConfig:DeploymentStage'$sel:stageName:DeploymentStage'+$sel:deviceSelectionConfig:DeploymentStage'newDeploymentStage deploymentStage_deploymentConfigdeploymentStage_stageName%deploymentStage_deviceSelectionConfig$fToJSONDeploymentStage$fNFDataDeploymentStage$fHashableDeploymentStage$fEqDeploymentStage$fReadDeploymentStage$fShowDeploymentStage$fGenericDeploymentStageFeatureGroupSortByFeatureGroupSortBy'fromFeatureGroupSortBy%FeatureGroupSortBy_OfflineStoreStatusFeatureGroupSortBy_Name%FeatureGroupSortBy_FeatureGroupStatusFeatureGroupSortBy_CreationTime$fShowFeatureGroupSortBy$fReadFeatureGroupSortBy$fEqFeatureGroupSortBy$fOrdFeatureGroupSortBy$fGenericFeatureGroupSortBy$fHashableFeatureGroupSortBy$fNFDataFeatureGroupSortBy$fFromTextFeatureGroupSortBy$fToTextFeatureGroupSortBy $fToByteStringFeatureGroupSortBy$fToLogFeatureGroupSortBy$fToHeaderFeatureGroupSortBy$fToQueryFeatureGroupSortBy$fFromJSONFeatureGroupSortBy$fFromJSONKeyFeatureGroupSortBy$fToJSONFeatureGroupSortBy$fToJSONKeyFeatureGroupSortBy$fFromXMLFeatureGroupSortBy$fToXMLFeatureGroupSortByFeatureGroupSortOrderFeatureGroupSortOrder'fromFeatureGroupSortOrder FeatureGroupSortOrder_DescendingFeatureGroupSortOrder_Ascending$fShowFeatureGroupSortOrder$fReadFeatureGroupSortOrder$fEqFeatureGroupSortOrder$fOrdFeatureGroupSortOrder$fGenericFeatureGroupSortOrder$fHashableFeatureGroupSortOrder$fNFDataFeatureGroupSortOrder$fFromTextFeatureGroupSortOrder$fToTextFeatureGroupSortOrder#$fToByteStringFeatureGroupSortOrder$fToLogFeatureGroupSortOrder$fToHeaderFeatureGroupSortOrder$fToQueryFeatureGroupSortOrder$fFromJSONFeatureGroupSortOrder"$fFromJSONKeyFeatureGroupSortOrder$fToJSONFeatureGroupSortOrder $fToJSONKeyFeatureGroupSortOrder$fFromXMLFeatureGroupSortOrder$fToXMLFeatureGroupSortOrderFeatureGroupStatusFeatureGroupStatus'fromFeatureGroupStatusFeatureGroupStatus_DeletingFeatureGroupStatus_DeleteFailedFeatureGroupStatus_CreatingFeatureGroupStatus_CreatedFeatureGroupStatus_CreateFailed$fShowFeatureGroupStatus$fReadFeatureGroupStatus$fEqFeatureGroupStatus$fOrdFeatureGroupStatus$fGenericFeatureGroupStatus$fHashableFeatureGroupStatus$fNFDataFeatureGroupStatus$fFromTextFeatureGroupStatus$fToTextFeatureGroupStatus $fToByteStringFeatureGroupStatus$fToLogFeatureGroupStatus$fToHeaderFeatureGroupStatus$fToQueryFeatureGroupStatus$fFromJSONFeatureGroupStatus$fFromJSONKeyFeatureGroupStatus$fToJSONFeatureGroupStatus$fToJSONKeyFeatureGroupStatus$fFromXMLFeatureGroupStatus$fToXMLFeatureGroupStatusFeatureParameterFeatureParameter'$sel:key:FeatureParameter'$sel:value:FeatureParameter'newFeatureParameterfeatureParameter_keyfeatureParameter_value$fToJSONFeatureParameter$fNFDataFeatureParameter$fHashableFeatureParameter$fFromJSONFeatureParameter$fEqFeatureParameter$fReadFeatureParameter$fShowFeatureParameter$fGenericFeatureParameter FeatureStatusFeatureStatus'fromFeatureStatusFeatureStatus_ENABLEDFeatureStatus_DISABLED$fShowFeatureStatus$fReadFeatureStatus$fEqFeatureStatus$fOrdFeatureStatus$fGenericFeatureStatus$fHashableFeatureStatus$fNFDataFeatureStatus$fFromTextFeatureStatus$fToTextFeatureStatus$fToByteStringFeatureStatus$fToLogFeatureStatus$fToHeaderFeatureStatus$fToQueryFeatureStatus$fFromJSONFeatureStatus$fFromJSONKeyFeatureStatus$fToJSONFeatureStatus$fToJSONKeyFeatureStatus$fFromXMLFeatureStatus$fToXMLFeatureStatus FeatureType FeatureType'fromFeatureTypeFeatureType_StringFeatureType_IntegralFeatureType_Fractional$fShowFeatureType$fReadFeatureType$fEqFeatureType$fOrdFeatureType$fGenericFeatureType$fHashableFeatureType$fNFDataFeatureType$fFromTextFeatureType$fToTextFeatureType$fToByteStringFeatureType$fToLogFeatureType$fToHeaderFeatureType$fToQueryFeatureType$fFromJSONFeatureType$fFromJSONKeyFeatureType$fToJSONFeatureType$fToJSONKeyFeatureType$fFromXMLFeatureType$fToXMLFeatureTypeFeatureMetadataFeatureMetadata'"$sel:creationTime:FeatureMetadata'!$sel:description:FeatureMetadata'%$sel:featureGroupArn:FeatureMetadata'&$sel:featureGroupName:FeatureMetadata'!$sel:featureName:FeatureMetadata'!$sel:featureType:FeatureMetadata'&$sel:lastModifiedTime:FeatureMetadata' $sel:parameters:FeatureMetadata'newFeatureMetadatafeatureMetadata_creationTimefeatureMetadata_descriptionfeatureMetadata_featureGroupArn featureMetadata_featureGroupNamefeatureMetadata_featureNamefeatureMetadata_featureType featureMetadata_lastModifiedTimefeatureMetadata_parameters$fNFDataFeatureMetadata$fHashableFeatureMetadata$fFromJSONFeatureMetadata$fEqFeatureMetadata$fReadFeatureMetadata$fShowFeatureMetadata$fGenericFeatureMetadataFeatureDefinitionFeatureDefinition'#$sel:featureName:FeatureDefinition'#$sel:featureType:FeatureDefinition'newFeatureDefinitionfeatureDefinition_featureNamefeatureDefinition_featureType$fToJSONFeatureDefinition$fNFDataFeatureDefinition$fHashableFeatureDefinition$fFromJSONFeatureDefinition$fEqFeatureDefinition$fReadFeatureDefinition$fShowFeatureDefinition$fGenericFeatureDefinition FileSource FileSource'$sel:contentDigest:FileSource'$sel:contentType:FileSource'$sel:s3Uri:FileSource' newFileSourcefileSource_contentDigestfileSource_contentTypefileSource_s3Uri$fToJSONFileSource$fNFDataFileSource$fHashableFileSource$fFromJSONFileSource$fEqFileSource$fReadFileSource$fShowFileSource$fGenericFileSourceFileSystemAccessModeFileSystemAccessMode'fromFileSystemAccessModeFileSystemAccessMode_RwFileSystemAccessMode_Ro$fShowFileSystemAccessMode$fReadFileSystemAccessMode$fEqFileSystemAccessMode$fOrdFileSystemAccessMode$fGenericFileSystemAccessMode$fHashableFileSystemAccessMode$fNFDataFileSystemAccessMode$fFromTextFileSystemAccessMode$fToTextFileSystemAccessMode"$fToByteStringFileSystemAccessMode$fToLogFileSystemAccessMode$fToHeaderFileSystemAccessMode$fToQueryFileSystemAccessMode$fFromJSONFileSystemAccessMode!$fFromJSONKeyFileSystemAccessMode$fToJSONFileSystemAccessMode$fToJSONKeyFileSystemAccessMode$fFromXMLFileSystemAccessMode$fToXMLFileSystemAccessModeFileSystemConfigFileSystemConfig'!$sel:defaultGid:FileSystemConfig'!$sel:defaultUid:FileSystemConfig' $sel:mountPath:FileSystemConfig'newFileSystemConfigfileSystemConfig_defaultGidfileSystemConfig_defaultUidfileSystemConfig_mountPath$fToJSONFileSystemConfig$fNFDataFileSystemConfig$fHashableFileSystemConfig$fFromJSONFileSystemConfig$fEqFileSystemConfig$fReadFileSystemConfig$fShowFileSystemConfig$fGenericFileSystemConfigFileSystemTypeFileSystemType'fromFileSystemTypeFileSystemType_FSxLustreFileSystemType_EFS$fShowFileSystemType$fReadFileSystemType$fEqFileSystemType$fOrdFileSystemType$fGenericFileSystemType$fHashableFileSystemType$fNFDataFileSystemType$fFromTextFileSystemType$fToTextFileSystemType$fToByteStringFileSystemType$fToLogFileSystemType$fToHeaderFileSystemType$fToQueryFileSystemType$fFromJSONFileSystemType$fFromJSONKeyFileSystemType$fToJSONFileSystemType$fToJSONKeyFileSystemType$fFromXMLFileSystemType$fToXMLFileSystemTypeFileSystemDataSourceFileSystemDataSource''$sel:fileSystemId:FileSystemDataSource'/$sel:fileSystemAccessMode:FileSystemDataSource')$sel:fileSystemType:FileSystemDataSource'($sel:directoryPath:FileSystemDataSource'newFileSystemDataSource!fileSystemDataSource_fileSystemId)fileSystemDataSource_fileSystemAccessMode#fileSystemDataSource_fileSystemType"fileSystemDataSource_directoryPath$fToJSONFileSystemDataSource$fNFDataFileSystemDataSource$fHashableFileSystemDataSource$fFromJSONFileSystemDataSource$fEqFileSystemDataSource$fReadFileSystemDataSource$fShowFileSystemDataSource$fGenericFileSystemDataSourceFinalAutoMLJobObjectiveMetricFinalAutoMLJobObjectiveMetric')$sel:type':FinalAutoMLJobObjectiveMetric'.$sel:metricName:FinalAutoMLJobObjectiveMetric')$sel:value:FinalAutoMLJobObjectiveMetric' newFinalAutoMLJobObjectiveMetric"finalAutoMLJobObjectiveMetric_type(finalAutoMLJobObjectiveMetric_metricName#finalAutoMLJobObjectiveMetric_value%$fNFDataFinalAutoMLJobObjectiveMetric'$fHashableFinalAutoMLJobObjectiveMetric'$fFromJSONFinalAutoMLJobObjectiveMetric!$fEqFinalAutoMLJobObjectiveMetric#$fReadFinalAutoMLJobObjectiveMetric#$fShowFinalAutoMLJobObjectiveMetric&$fGenericFinalAutoMLJobObjectiveMetricFlowDefinitionOutputConfigFlowDefinitionOutputConfig')$sel:kmsKeyId:FlowDefinitionOutputConfig'-$sel:s3OutputPath:FlowDefinitionOutputConfig'newFlowDefinitionOutputConfig#flowDefinitionOutputConfig_kmsKeyId'flowDefinitionOutputConfig_s3OutputPath"$fToJSONFlowDefinitionOutputConfig"$fNFDataFlowDefinitionOutputConfig$$fHashableFlowDefinitionOutputConfig$$fFromJSONFlowDefinitionOutputConfig$fEqFlowDefinitionOutputConfig $fReadFlowDefinitionOutputConfig $fShowFlowDefinitionOutputConfig#$fGenericFlowDefinitionOutputConfigFlowDefinitionStatusFlowDefinitionStatus'fromFlowDefinitionStatus!FlowDefinitionStatus_InitializingFlowDefinitionStatus_FailedFlowDefinitionStatus_DeletingFlowDefinitionStatus_Active$fShowFlowDefinitionStatus$fReadFlowDefinitionStatus$fEqFlowDefinitionStatus$fOrdFlowDefinitionStatus$fGenericFlowDefinitionStatus$fHashableFlowDefinitionStatus$fNFDataFlowDefinitionStatus$fFromTextFlowDefinitionStatus$fToTextFlowDefinitionStatus"$fToByteStringFlowDefinitionStatus$fToLogFlowDefinitionStatus$fToHeaderFlowDefinitionStatus$fToQueryFlowDefinitionStatus$fFromJSONFlowDefinitionStatus!$fFromJSONKeyFlowDefinitionStatus$fToJSONFlowDefinitionStatus$fToJSONKeyFlowDefinitionStatus$fFromXMLFlowDefinitionStatus$fToXMLFlowDefinitionStatusFlowDefinitionSummaryFlowDefinitionSummary')$sel:failureReason:FlowDefinitionSummary'.$sel:flowDefinitionName:FlowDefinitionSummary'-$sel:flowDefinitionArn:FlowDefinitionSummary'0$sel:flowDefinitionStatus:FlowDefinitionSummary'($sel:creationTime:FlowDefinitionSummary'newFlowDefinitionSummary#flowDefinitionSummary_failureReason(flowDefinitionSummary_flowDefinitionName'flowDefinitionSummary_flowDefinitionArn*flowDefinitionSummary_flowDefinitionStatus"flowDefinitionSummary_creationTime$fNFDataFlowDefinitionSummary$fHashableFlowDefinitionSummary$fFromJSONFlowDefinitionSummary$fEqFlowDefinitionSummary$fReadFlowDefinitionSummary$fShowFlowDefinitionSummary$fGenericFlowDefinitionSummary Framework Framework' fromFrameworkFramework_XGBOOSTFramework_TFLITEFramework_TENSORFLOWFramework_SKLEARNFramework_PYTORCHFramework_ONNXFramework_MXNETFramework_KERASFramework_DARKNET$fShowFramework$fReadFramework $fEqFramework$fOrdFramework$fGenericFramework$fHashableFramework$fNFDataFramework$fFromTextFramework$fToTextFramework$fToByteStringFramework$fToLogFramework$fToHeaderFramework$fToQueryFramework$fFromJSONFramework$fFromJSONKeyFramework$fToJSONFramework$fToJSONKeyFramework$fFromXMLFramework$fToXMLFramework GitConfig GitConfig'$sel:branch:GitConfig'$sel:secretArn:GitConfig'$sel:repositoryUrl:GitConfig' newGitConfiggitConfig_branchgitConfig_secretArngitConfig_repositoryUrl$fToJSONGitConfig$fNFDataGitConfig$fHashableGitConfig$fFromJSONGitConfig $fEqGitConfig$fReadGitConfig$fShowGitConfig$fGenericGitConfigCodeRepositorySummaryCodeRepositorySummary'%$sel:gitConfig:CodeRepositorySummary'.$sel:codeRepositoryName:CodeRepositorySummary'-$sel:codeRepositoryArn:CodeRepositorySummary'($sel:creationTime:CodeRepositorySummary',$sel:lastModifiedTime:CodeRepositorySummary'newCodeRepositorySummarycodeRepositorySummary_gitConfig(codeRepositorySummary_codeRepositoryName'codeRepositorySummary_codeRepositoryArn"codeRepositorySummary_creationTime&codeRepositorySummary_lastModifiedTime$fNFDataCodeRepositorySummary$fHashableCodeRepositorySummary$fFromJSONCodeRepositorySummary$fEqCodeRepositorySummary$fReadCodeRepositorySummary$fShowCodeRepositorySummary$fGenericCodeRepositorySummaryGitConfigForUpdateGitConfigForUpdate'"$sel:secretArn:GitConfigForUpdate'newGitConfigForUpdategitConfigForUpdate_secretArn$fToJSONGitConfigForUpdate$fNFDataGitConfigForUpdate$fHashableGitConfigForUpdate$fEqGitConfigForUpdate$fReadGitConfigForUpdate$fShowGitConfigForUpdate$fGenericGitConfigForUpdateHubContentDependencyHubContentDependency'-$sel:dependencyCopyPath:HubContentDependency'/$sel:dependencyOriginPath:HubContentDependency'newHubContentDependency'hubContentDependency_dependencyCopyPath)hubContentDependency_dependencyOriginPath$fNFDataHubContentDependency$fHashableHubContentDependency$fFromJSONHubContentDependency$fEqHubContentDependency$fReadHubContentDependency$fShowHubContentDependency$fGenericHubContentDependencyHubContentSortByHubContentSortBy'fromHubContentSortBy!HubContentSortBy_HubContentStatusHubContentSortBy_HubContentNameHubContentSortBy_CreationTime$fShowHubContentSortBy$fReadHubContentSortBy$fEqHubContentSortBy$fOrdHubContentSortBy$fGenericHubContentSortBy$fHashableHubContentSortBy$fNFDataHubContentSortBy$fFromTextHubContentSortBy$fToTextHubContentSortBy$fToByteStringHubContentSortBy$fToLogHubContentSortBy$fToHeaderHubContentSortBy$fToQueryHubContentSortBy$fFromJSONHubContentSortBy$fFromJSONKeyHubContentSortBy$fToJSONHubContentSortBy$fToJSONKeyHubContentSortBy$fFromXMLHubContentSortBy$fToXMLHubContentSortByHubContentStatusHubContentStatus'fromHubContentStatusHubContentStatus_ImportingHubContentStatus_ImportFailedHubContentStatus_DeletingHubContentStatus_DeleteFailedHubContentStatus_Available$fShowHubContentStatus$fReadHubContentStatus$fEqHubContentStatus$fOrdHubContentStatus$fGenericHubContentStatus$fHashableHubContentStatus$fNFDataHubContentStatus$fFromTextHubContentStatus$fToTextHubContentStatus$fToByteStringHubContentStatus$fToLogHubContentStatus$fToHeaderHubContentStatus$fToQueryHubContentStatus$fFromJSONHubContentStatus$fFromJSONKeyHubContentStatus$fToJSONHubContentStatus$fToJSONKeyHubContentStatus$fFromXMLHubContentStatus$fToXMLHubContentStatusHubContentTypeHubContentType'fromHubContentTypeHubContentType_NotebookHubContentType_Model$fShowHubContentType$fReadHubContentType$fEqHubContentType$fOrdHubContentType$fGenericHubContentType$fHashableHubContentType$fNFDataHubContentType$fFromTextHubContentType$fToTextHubContentType$fToByteStringHubContentType$fToLogHubContentType$fToHeaderHubContentType$fToQueryHubContentType$fFromJSONHubContentType$fFromJSONKeyHubContentType$fToJSONHubContentType$fToJSONKeyHubContentType$fFromXMLHubContentType$fToXMLHubContentTypeHubContentInfoHubContentInfo'*$sel:hubContentDescription:HubContentInfo'*$sel:hubContentDisplayName:HubContentInfo'-$sel:hubContentSearchKeywords:HubContentInfo'#$sel:hubContentName:HubContentInfo'"$sel:hubContentArn:HubContentInfo'&$sel:hubContentVersion:HubContentInfo'#$sel:hubContentType:HubContentInfo'*$sel:documentSchemaVersion:HubContentInfo'%$sel:hubContentStatus:HubContentInfo'!$sel:creationTime:HubContentInfo'newHubContentInfo$hubContentInfo_hubContentDescription$hubContentInfo_hubContentDisplayName'hubContentInfo_hubContentSearchKeywordshubContentInfo_hubContentNamehubContentInfo_hubContentArn hubContentInfo_hubContentVersionhubContentInfo_hubContentType$hubContentInfo_documentSchemaVersionhubContentInfo_hubContentStatushubContentInfo_creationTime$fNFDataHubContentInfo$fHashableHubContentInfo$fFromJSONHubContentInfo$fEqHubContentInfo$fReadHubContentInfo$fShowHubContentInfo$fGenericHubContentInfoHubS3StorageConfigHubS3StorageConfig'%$sel:s3OutputPath:HubS3StorageConfig'newHubS3StorageConfighubS3StorageConfig_s3OutputPath$fToJSONHubS3StorageConfig$fNFDataHubS3StorageConfig$fHashableHubS3StorageConfig$fFromJSONHubS3StorageConfig$fEqHubS3StorageConfig$fReadHubS3StorageConfig$fShowHubS3StorageConfig$fGenericHubS3StorageConfig HubSortBy HubSortBy' fromHubSortByHubSortBy_HubStatusHubSortBy_HubNameHubSortBy_CreationTimeHubSortBy_AccountIdOwner$fShowHubSortBy$fReadHubSortBy $fEqHubSortBy$fOrdHubSortBy$fGenericHubSortBy$fHashableHubSortBy$fNFDataHubSortBy$fFromTextHubSortBy$fToTextHubSortBy$fToByteStringHubSortBy$fToLogHubSortBy$fToHeaderHubSortBy$fToQueryHubSortBy$fFromJSONHubSortBy$fFromJSONKeyHubSortBy$fToJSONHubSortBy$fToJSONKeyHubSortBy$fFromXMLHubSortBy$fToXMLHubSortBy HubStatus HubStatus' fromHubStatusHubStatus_UpdatingHubStatus_UpdateFailedHubStatus_InServiceHubStatus_DeletingHubStatus_DeleteFailedHubStatus_CreatingHubStatus_CreateFailed$fShowHubStatus$fReadHubStatus $fEqHubStatus$fOrdHubStatus$fGenericHubStatus$fHashableHubStatus$fNFDataHubStatus$fFromTextHubStatus$fToTextHubStatus$fToByteStringHubStatus$fToLogHubStatus$fToHeaderHubStatus$fToQueryHubStatus$fFromJSONHubStatus$fFromJSONKeyHubStatus$fToJSONHubStatus$fToJSONKeyHubStatus$fFromXMLHubStatus$fToXMLHubStatusHubInfoHubInfo'$sel:hubDescription:HubInfo'$sel:hubDisplayName:HubInfo'$sel:hubSearchKeywords:HubInfo'$sel:hubName:HubInfo'$sel:hubArn:HubInfo'$sel:hubStatus:HubInfo'$sel:creationTime:HubInfo'$sel:lastModifiedTime:HubInfo' newHubInfohubInfo_hubDescriptionhubInfo_hubDisplayNamehubInfo_hubSearchKeywordshubInfo_hubNamehubInfo_hubArnhubInfo_hubStatushubInfo_creationTimehubInfo_lastModifiedTime$fNFDataHubInfo$fHashableHubInfo$fFromJSONHubInfo $fEqHubInfo $fReadHubInfo $fShowHubInfo$fGenericHubInfo#HumanLoopActivationConditionsConfig$HumanLoopActivationConditionsConfig'$sel:humanLoopActivationConditions:HumanLoopActivationConditionsConfig'&newHumanLoopActivationConditionsConfighumanLoopActivationConditionsConfig_humanLoopActivationConditions+$fToJSONHumanLoopActivationConditionsConfig+$fNFDataHumanLoopActivationConditionsConfig-$fHashableHumanLoopActivationConditionsConfig-$fFromJSONHumanLoopActivationConditionsConfig'$fEqHumanLoopActivationConditionsConfig)$fReadHumanLoopActivationConditionsConfig)$fShowHumanLoopActivationConditionsConfig,$fGenericHumanLoopActivationConditionsConfigHumanLoopActivationConfigHumanLoopActivationConfig'$sel:humanLoopActivationConditionsConfig:HumanLoopActivationConfig'newHumanLoopActivationConfig=humanLoopActivationConfig_humanLoopActivationConditionsConfig!$fToJSONHumanLoopActivationConfig!$fNFDataHumanLoopActivationConfig#$fHashableHumanLoopActivationConfig#$fFromJSONHumanLoopActivationConfig$fEqHumanLoopActivationConfig$fReadHumanLoopActivationConfig$fShowHumanLoopActivationConfig"$fGenericHumanLoopActivationConfigHumanLoopRequestSourceHumanLoopRequestSource'=$sel:awsManagedHumanLoopRequestSource:HumanLoopRequestSource'newHumanLoopRequestSource7humanLoopRequestSource_awsManagedHumanLoopRequestSource$fToJSONHumanLoopRequestSource$fNFDataHumanLoopRequestSource $fHashableHumanLoopRequestSource $fFromJSONHumanLoopRequestSource$fEqHumanLoopRequestSource$fReadHumanLoopRequestSource$fShowHumanLoopRequestSource$fGenericHumanLoopRequestSourceHumanTaskUiStatusHumanTaskUiStatus'fromHumanTaskUiStatusHumanTaskUiStatus_DeletingHumanTaskUiStatus_Active$fShowHumanTaskUiStatus$fReadHumanTaskUiStatus$fEqHumanTaskUiStatus$fOrdHumanTaskUiStatus$fGenericHumanTaskUiStatus$fHashableHumanTaskUiStatus$fNFDataHumanTaskUiStatus$fFromTextHumanTaskUiStatus$fToTextHumanTaskUiStatus$fToByteStringHumanTaskUiStatus$fToLogHumanTaskUiStatus$fToHeaderHumanTaskUiStatus$fToQueryHumanTaskUiStatus$fFromJSONHumanTaskUiStatus$fFromJSONKeyHumanTaskUiStatus$fToJSONHumanTaskUiStatus$fToJSONKeyHumanTaskUiStatus$fFromXMLHumanTaskUiStatus$fToXMLHumanTaskUiStatusHumanTaskUiSummaryHumanTaskUiSummary'($sel:humanTaskUiName:HumanTaskUiSummary''$sel:humanTaskUiArn:HumanTaskUiSummary'%$sel:creationTime:HumanTaskUiSummary'newHumanTaskUiSummary"humanTaskUiSummary_humanTaskUiName!humanTaskUiSummary_humanTaskUiArnhumanTaskUiSummary_creationTime$fNFDataHumanTaskUiSummary$fHashableHumanTaskUiSummary$fFromJSONHumanTaskUiSummary$fEqHumanTaskUiSummary$fReadHumanTaskUiSummary$fShowHumanTaskUiSummary$fGenericHumanTaskUiSummaryHyperParameterScalingTypeHyperParameterScalingType'fromHyperParameterScalingType,HyperParameterScalingType_ReverseLogarithmic%HyperParameterScalingType_Logarithmic HyperParameterScalingType_LinearHyperParameterScalingType_Auto$fShowHyperParameterScalingType$fReadHyperParameterScalingType$fEqHyperParameterScalingType$fOrdHyperParameterScalingType"$fGenericHyperParameterScalingType#$fHashableHyperParameterScalingType!$fNFDataHyperParameterScalingType#$fFromTextHyperParameterScalingType!$fToTextHyperParameterScalingType'$fToByteStringHyperParameterScalingType $fToLogHyperParameterScalingType#$fToHeaderHyperParameterScalingType"$fToQueryHyperParameterScalingType#$fFromJSONHyperParameterScalingType&$fFromJSONKeyHyperParameterScalingType!$fToJSONHyperParameterScalingType$$fToJSONKeyHyperParameterScalingType"$fFromXMLHyperParameterScalingType $fToXMLHyperParameterScalingTypeContinuousParameterRangeContinuousParameterRange'*$sel:scalingType:ContinuousParameterRange'#$sel:name:ContinuousParameterRange''$sel:minValue:ContinuousParameterRange''$sel:maxValue:ContinuousParameterRange'newContinuousParameterRange$continuousParameterRange_scalingTypecontinuousParameterRange_name!continuousParameterRange_minValue!continuousParameterRange_maxValue $fToJSONContinuousParameterRange $fNFDataContinuousParameterRange"$fHashableContinuousParameterRange"$fFromJSONContinuousParameterRange$fEqContinuousParameterRange$fReadContinuousParameterRange$fShowContinuousParameterRange!$fGenericContinuousParameterRange&HyperParameterTuningAllocationStrategy'HyperParameterTuningAllocationStrategy'*fromHyperParameterTuningAllocationStrategy2HyperParameterTuningAllocationStrategy_Prioritized,$fShowHyperParameterTuningAllocationStrategy,$fReadHyperParameterTuningAllocationStrategy*$fEqHyperParameterTuningAllocationStrategy+$fOrdHyperParameterTuningAllocationStrategy/$fGenericHyperParameterTuningAllocationStrategy0$fHashableHyperParameterTuningAllocationStrategy.$fNFDataHyperParameterTuningAllocationStrategy0$fFromTextHyperParameterTuningAllocationStrategy.$fToTextHyperParameterTuningAllocationStrategy4$fToByteStringHyperParameterTuningAllocationStrategy-$fToLogHyperParameterTuningAllocationStrategy0$fToHeaderHyperParameterTuningAllocationStrategy/$fToQueryHyperParameterTuningAllocationStrategy0$fFromJSONHyperParameterTuningAllocationStrategy3$fFromJSONKeyHyperParameterTuningAllocationStrategy.$fToJSONHyperParameterTuningAllocationStrategy1$fToJSONKeyHyperParameterTuningAllocationStrategy/$fFromXMLHyperParameterTuningAllocationStrategy-$fToXMLHyperParameterTuningAllocationStrategy$HyperParameterTuningJobObjectiveType%HyperParameterTuningJobObjectiveType'(fromHyperParameterTuningJobObjectiveType-HyperParameterTuningJobObjectiveType_Minimize-HyperParameterTuningJobObjectiveType_Maximize*$fShowHyperParameterTuningJobObjectiveType*$fReadHyperParameterTuningJobObjectiveType($fEqHyperParameterTuningJobObjectiveType)$fOrdHyperParameterTuningJobObjectiveType-$fGenericHyperParameterTuningJobObjectiveType.$fHashableHyperParameterTuningJobObjectiveType,$fNFDataHyperParameterTuningJobObjectiveType.$fFromTextHyperParameterTuningJobObjectiveType,$fToTextHyperParameterTuningJobObjectiveType2$fToByteStringHyperParameterTuningJobObjectiveType+$fToLogHyperParameterTuningJobObjectiveType.$fToHeaderHyperParameterTuningJobObjectiveType-$fToQueryHyperParameterTuningJobObjectiveType.$fFromJSONHyperParameterTuningJobObjectiveType1$fFromJSONKeyHyperParameterTuningJobObjectiveType,$fToJSONHyperParameterTuningJobObjectiveType/$fToJSONKeyHyperParameterTuningJobObjectiveType-$fFromXMLHyperParameterTuningJobObjectiveType+$fToXMLHyperParameterTuningJobObjectiveType HyperParameterTuningJobObjective!HyperParameterTuningJobObjective',$sel:type':HyperParameterTuningJobObjective'1$sel:metricName:HyperParameterTuningJobObjective'#newHyperParameterTuningJobObjective%hyperParameterTuningJobObjective_type+hyperParameterTuningJobObjective_metricName($fToJSONHyperParameterTuningJobObjective($fNFDataHyperParameterTuningJobObjective*$fHashableHyperParameterTuningJobObjective*$fFromJSONHyperParameterTuningJobObjective$$fEqHyperParameterTuningJobObjective&$fReadHyperParameterTuningJobObjective&$fShowHyperParameterTuningJobObjective)$fGenericHyperParameterTuningJobObjective+FinalHyperParameterTuningJobObjectiveMetric,FinalHyperParameterTuningJobObjectiveMetric'7$sel:type':FinalHyperParameterTuningJobObjectiveMetric'<$sel:metricName:FinalHyperParameterTuningJobObjectiveMetric'7$sel:value:FinalHyperParameterTuningJobObjectiveMetric'.newFinalHyperParameterTuningJobObjectiveMetric0finalHyperParameterTuningJobObjectiveMetric_type6finalHyperParameterTuningJobObjectiveMetric_metricName1finalHyperParameterTuningJobObjectiveMetric_value3$fNFDataFinalHyperParameterTuningJobObjectiveMetric5$fHashableFinalHyperParameterTuningJobObjectiveMetric5$fFromJSONFinalHyperParameterTuningJobObjectiveMetric/$fEqFinalHyperParameterTuningJobObjectiveMetric1$fReadFinalHyperParameterTuningJobObjectiveMetric1$fShowFinalHyperParameterTuningJobObjectiveMetric4$fGenericFinalHyperParameterTuningJobObjectiveMetric$HyperParameterTuningJobSortByOptions%HyperParameterTuningJobSortByOptions'(fromHyperParameterTuningJobSortByOptions+HyperParameterTuningJobSortByOptions_Status)HyperParameterTuningJobSortByOptions_Name1HyperParameterTuningJobSortByOptions_CreationTime*$fShowHyperParameterTuningJobSortByOptions*$fReadHyperParameterTuningJobSortByOptions($fEqHyperParameterTuningJobSortByOptions)$fOrdHyperParameterTuningJobSortByOptions-$fGenericHyperParameterTuningJobSortByOptions.$fHashableHyperParameterTuningJobSortByOptions,$fNFDataHyperParameterTuningJobSortByOptions.$fFromTextHyperParameterTuningJobSortByOptions,$fToTextHyperParameterTuningJobSortByOptions2$fToByteStringHyperParameterTuningJobSortByOptions+$fToLogHyperParameterTuningJobSortByOptions.$fToHeaderHyperParameterTuningJobSortByOptions-$fToQueryHyperParameterTuningJobSortByOptions.$fFromJSONHyperParameterTuningJobSortByOptions1$fFromJSONKeyHyperParameterTuningJobSortByOptions,$fToJSONHyperParameterTuningJobSortByOptions/$fToJSONKeyHyperParameterTuningJobSortByOptions-$fFromXMLHyperParameterTuningJobSortByOptions+$fToXMLHyperParameterTuningJobSortByOptionsHyperParameterTuningJobStatusHyperParameterTuningJobStatus'!fromHyperParameterTuningJobStatus&HyperParameterTuningJobStatus_Stopping%HyperParameterTuningJobStatus_Stopped(HyperParameterTuningJobStatus_InProgress$HyperParameterTuningJobStatus_Failed'HyperParameterTuningJobStatus_Completed#$fShowHyperParameterTuningJobStatus#$fReadHyperParameterTuningJobStatus!$fEqHyperParameterTuningJobStatus"$fOrdHyperParameterTuningJobStatus&$fGenericHyperParameterTuningJobStatus'$fHashableHyperParameterTuningJobStatus%$fNFDataHyperParameterTuningJobStatus'$fFromTextHyperParameterTuningJobStatus%$fToTextHyperParameterTuningJobStatus+$fToByteStringHyperParameterTuningJobStatus$$fToLogHyperParameterTuningJobStatus'$fToHeaderHyperParameterTuningJobStatus&$fToQueryHyperParameterTuningJobStatus'$fFromJSONHyperParameterTuningJobStatus*$fFromJSONKeyHyperParameterTuningJobStatus%$fToJSONHyperParameterTuningJobStatus($fToJSONKeyHyperParameterTuningJobStatus&$fFromXMLHyperParameterTuningJobStatus$$fToXMLHyperParameterTuningJobStatus#HyperParameterTuningJobStrategyType$HyperParameterTuningJobStrategyType''fromHyperParameterTuningJobStrategyType*HyperParameterTuningJobStrategyType_Random-HyperParameterTuningJobStrategyType_Hyperband(HyperParameterTuningJobStrategyType_Grid,HyperParameterTuningJobStrategyType_Bayesian)$fShowHyperParameterTuningJobStrategyType)$fReadHyperParameterTuningJobStrategyType'$fEqHyperParameterTuningJobStrategyType($fOrdHyperParameterTuningJobStrategyType,$fGenericHyperParameterTuningJobStrategyType-$fHashableHyperParameterTuningJobStrategyType+$fNFDataHyperParameterTuningJobStrategyType-$fFromTextHyperParameterTuningJobStrategyType+$fToTextHyperParameterTuningJobStrategyType1$fToByteStringHyperParameterTuningJobStrategyType*$fToLogHyperParameterTuningJobStrategyType-$fToHeaderHyperParameterTuningJobStrategyType,$fToQueryHyperParameterTuningJobStrategyType-$fFromJSONHyperParameterTuningJobStrategyType0$fFromJSONKeyHyperParameterTuningJobStrategyType+$fToJSONHyperParameterTuningJobStrategyType.$fToJSONKeyHyperParameterTuningJobStrategyType,$fFromXMLHyperParameterTuningJobStrategyType*$fToXMLHyperParameterTuningJobStrategyType$HyperParameterTuningJobWarmStartType%HyperParameterTuningJobWarmStartType'(fromHyperParameterTuningJobWarmStartType5HyperParameterTuningJobWarmStartType_TransferLearning>HyperParameterTuningJobWarmStartType_IdenticalDataAndAlgorithm*$fShowHyperParameterTuningJobWarmStartType*$fReadHyperParameterTuningJobWarmStartType($fEqHyperParameterTuningJobWarmStartType)$fOrdHyperParameterTuningJobWarmStartType-$fGenericHyperParameterTuningJobWarmStartType.$fHashableHyperParameterTuningJobWarmStartType,$fNFDataHyperParameterTuningJobWarmStartType.$fFromTextHyperParameterTuningJobWarmStartType,$fToTextHyperParameterTuningJobWarmStartType2$fToByteStringHyperParameterTuningJobWarmStartType+$fToLogHyperParameterTuningJobWarmStartType.$fToHeaderHyperParameterTuningJobWarmStartType-$fToQueryHyperParameterTuningJobWarmStartType.$fFromJSONHyperParameterTuningJobWarmStartType1$fFromJSONKeyHyperParameterTuningJobWarmStartType,$fToJSONHyperParameterTuningJobWarmStartType/$fToJSONKeyHyperParameterTuningJobWarmStartType-$fFromXMLHyperParameterTuningJobWarmStartType+$fToXMLHyperParameterTuningJobWarmStartTypeHyperbandStrategyConfigHyperbandStrategyConfig')$sel:maxResource:HyperbandStrategyConfig')$sel:minResource:HyperbandStrategyConfig'newHyperbandStrategyConfig#hyperbandStrategyConfig_maxResource#hyperbandStrategyConfig_minResource$fToJSONHyperbandStrategyConfig$fNFDataHyperbandStrategyConfig!$fHashableHyperbandStrategyConfig!$fFromJSONHyperbandStrategyConfig$fEqHyperbandStrategyConfig$fReadHyperbandStrategyConfig$fShowHyperbandStrategyConfig $fGenericHyperbandStrategyConfig%HyperParameterTuningJobStrategyConfig&HyperParameterTuningJobStrategyConfig'$sel:hyperbandStrategyConfig:HyperParameterTuningJobStrategyConfig'(newHyperParameterTuningJobStrategyConfig=hyperParameterTuningJobStrategyConfig_hyperbandStrategyConfig-$fToJSONHyperParameterTuningJobStrategyConfig-$fNFDataHyperParameterTuningJobStrategyConfig/$fHashableHyperParameterTuningJobStrategyConfig/$fFromJSONHyperParameterTuningJobStrategyConfig)$fEqHyperParameterTuningJobStrategyConfig+$fReadHyperParameterTuningJobStrategyConfig+$fShowHyperParameterTuningJobStrategyConfig.$fGenericHyperParameterTuningJobStrategyConfig ImageSortBy ImageSortBy'fromImageSortByImageSortBy_LAST_MODIFIED_TIMEImageSortBy_IMAGE_NAMEImageSortBy_CREATION_TIME$fShowImageSortBy$fReadImageSortBy$fEqImageSortBy$fOrdImageSortBy$fGenericImageSortBy$fHashableImageSortBy$fNFDataImageSortBy$fFromTextImageSortBy$fToTextImageSortBy$fToByteStringImageSortBy$fToLogImageSortBy$fToHeaderImageSortBy$fToQueryImageSortBy$fFromJSONImageSortBy$fFromJSONKeyImageSortBy$fToJSONImageSortBy$fToJSONKeyImageSortBy$fFromXMLImageSortBy$fToXMLImageSortByImageSortOrderImageSortOrder'fromImageSortOrderImageSortOrder_DESCENDINGImageSortOrder_ASCENDING$fShowImageSortOrder$fReadImageSortOrder$fEqImageSortOrder$fOrdImageSortOrder$fGenericImageSortOrder$fHashableImageSortOrder$fNFDataImageSortOrder$fFromTextImageSortOrder$fToTextImageSortOrder$fToByteStringImageSortOrder$fToLogImageSortOrder$fToHeaderImageSortOrder$fToQueryImageSortOrder$fFromJSONImageSortOrder$fFromJSONKeyImageSortOrder$fToJSONImageSortOrder$fToJSONKeyImageSortOrder$fFromXMLImageSortOrder$fToXMLImageSortOrder ImageStatus ImageStatus'fromImageStatusImageStatus_UPDATINGImageStatus_UPDATE_FAILEDImageStatus_DELETINGImageStatus_DELETE_FAILEDImageStatus_CREATINGImageStatus_CREATE_FAILEDImageStatus_CREATED$fShowImageStatus$fReadImageStatus$fEqImageStatus$fOrdImageStatus$fGenericImageStatus$fHashableImageStatus$fNFDataImageStatus$fFromTextImageStatus$fToTextImageStatus$fToByteStringImageStatus$fToLogImageStatus$fToHeaderImageStatus$fToQueryImageStatus$fFromJSONImageStatus$fFromJSONKeyImageStatus$fToJSONImageStatus$fToJSONKeyImageStatus$fFromXMLImageStatus$fToXMLImageStatusImageImage'$sel:description:Image'$sel:displayName:Image'$sel:failureReason:Image'$sel:creationTime:Image'$sel:imageArn:Image'$sel:imageName:Image'$sel:imageStatus:Image'$sel:lastModifiedTime:Image'newImageimage_descriptionimage_displayNameimage_failureReasonimage_creationTimeimage_imageArnimage_imageNameimage_imageStatusimage_lastModifiedTime $fNFDataImage$fHashableImage$fFromJSONImage $fEqImage $fReadImage $fShowImage$fGenericImageImageVersionSortByImageVersionSortBy'fromImageVersionSortByImageVersionSortBy_VERSION%ImageVersionSortBy_LAST_MODIFIED_TIME ImageVersionSortBy_CREATION_TIME$fShowImageVersionSortBy$fReadImageVersionSortBy$fEqImageVersionSortBy$fOrdImageVersionSortBy$fGenericImageVersionSortBy$fHashableImageVersionSortBy$fNFDataImageVersionSortBy$fFromTextImageVersionSortBy$fToTextImageVersionSortBy $fToByteStringImageVersionSortBy$fToLogImageVersionSortBy$fToHeaderImageVersionSortBy$fToQueryImageVersionSortBy$fFromJSONImageVersionSortBy$fFromJSONKeyImageVersionSortBy$fToJSONImageVersionSortBy$fToJSONKeyImageVersionSortBy$fFromXMLImageVersionSortBy$fToXMLImageVersionSortByImageVersionSortOrderImageVersionSortOrder'fromImageVersionSortOrder ImageVersionSortOrder_DESCENDINGImageVersionSortOrder_ASCENDING$fShowImageVersionSortOrder$fReadImageVersionSortOrder$fEqImageVersionSortOrder$fOrdImageVersionSortOrder$fGenericImageVersionSortOrder$fHashableImageVersionSortOrder$fNFDataImageVersionSortOrder$fFromTextImageVersionSortOrder$fToTextImageVersionSortOrder#$fToByteStringImageVersionSortOrder$fToLogImageVersionSortOrder$fToHeaderImageVersionSortOrder$fToQueryImageVersionSortOrder$fFromJSONImageVersionSortOrder"$fFromJSONKeyImageVersionSortOrder$fToJSONImageVersionSortOrder $fToJSONKeyImageVersionSortOrder$fFromXMLImageVersionSortOrder$fToXMLImageVersionSortOrderImageVersionStatusImageVersionStatus'fromImageVersionStatusImageVersionStatus_DELETING ImageVersionStatus_DELETE_FAILEDImageVersionStatus_CREATING ImageVersionStatus_CREATE_FAILEDImageVersionStatus_CREATED$fShowImageVersionStatus$fReadImageVersionStatus$fEqImageVersionStatus$fOrdImageVersionStatus$fGenericImageVersionStatus$fHashableImageVersionStatus$fNFDataImageVersionStatus$fFromTextImageVersionStatus$fToTextImageVersionStatus $fToByteStringImageVersionStatus$fToLogImageVersionStatus$fToHeaderImageVersionStatus$fToQueryImageVersionStatus$fFromJSONImageVersionStatus$fFromJSONKeyImageVersionStatus$fToJSONImageVersionStatus$fToJSONKeyImageVersionStatus$fFromXMLImageVersionStatus$fToXMLImageVersionStatus ImageVersion ImageVersion' $sel:failureReason:ImageVersion'$sel:creationTime:ImageVersion'$sel:imageArn:ImageVersion'"$sel:imageVersionArn:ImageVersion'%$sel:imageVersionStatus:ImageVersion'#$sel:lastModifiedTime:ImageVersion'$sel:version:ImageVersion'newImageVersionimageVersion_failureReasonimageVersion_creationTimeimageVersion_imageArnimageVersion_imageVersionArnimageVersion_imageVersionStatusimageVersion_lastModifiedTimeimageVersion_version$fNFDataImageVersion$fHashableImageVersion$fFromJSONImageVersion$fEqImageVersion$fReadImageVersion$fShowImageVersion$fGenericImageVersionInferenceExecutionModeInferenceExecutionMode'fromInferenceExecutionModeInferenceExecutionMode_SerialInferenceExecutionMode_Direct$fShowInferenceExecutionMode$fReadInferenceExecutionMode$fEqInferenceExecutionMode$fOrdInferenceExecutionMode$fGenericInferenceExecutionMode $fHashableInferenceExecutionMode$fNFDataInferenceExecutionMode $fFromTextInferenceExecutionMode$fToTextInferenceExecutionMode$$fToByteStringInferenceExecutionMode$fToLogInferenceExecutionMode $fToHeaderInferenceExecutionMode$fToQueryInferenceExecutionMode $fFromJSONInferenceExecutionMode#$fFromJSONKeyInferenceExecutionMode$fToJSONInferenceExecutionMode!$fToJSONKeyInferenceExecutionMode$fFromXMLInferenceExecutionMode$fToXMLInferenceExecutionModeInferenceExecutionConfigInferenceExecutionConfig'#$sel:mode:InferenceExecutionConfig'newInferenceExecutionConfiginferenceExecutionConfig_mode $fToJSONInferenceExecutionConfig $fNFDataInferenceExecutionConfig"$fHashableInferenceExecutionConfig"$fFromJSONInferenceExecutionConfig$fEqInferenceExecutionConfig$fReadInferenceExecutionConfig$fShowInferenceExecutionConfig!$fGenericInferenceExecutionConfig$InferenceExperimentDataStorageConfig%InferenceExperimentDataStorageConfig'6$sel:contentType:InferenceExperimentDataStorageConfig'1$sel:kmsKey:InferenceExperimentDataStorageConfig'6$sel:destination:InferenceExperimentDataStorageConfig''newInferenceExperimentDataStorageConfig0inferenceExperimentDataStorageConfig_contentType+inferenceExperimentDataStorageConfig_kmsKey0inferenceExperimentDataStorageConfig_destination,$fToJSONInferenceExperimentDataStorageConfig,$fNFDataInferenceExperimentDataStorageConfig.$fHashableInferenceExperimentDataStorageConfig.$fFromJSONInferenceExperimentDataStorageConfig($fEqInferenceExperimentDataStorageConfig*$fReadInferenceExperimentDataStorageConfig*$fShowInferenceExperimentDataStorageConfig-$fGenericInferenceExperimentDataStorageConfigInferenceExperimentScheduleInferenceExperimentSchedule')$sel:endTime:InferenceExperimentSchedule'+$sel:startTime:InferenceExperimentSchedule'newInferenceExperimentSchedule#inferenceExperimentSchedule_endTime%inferenceExperimentSchedule_startTime#$fToJSONInferenceExperimentSchedule#$fNFDataInferenceExperimentSchedule%$fHashableInferenceExperimentSchedule%$fFromJSONInferenceExperimentSchedule$fEqInferenceExperimentSchedule!$fReadInferenceExperimentSchedule!$fShowInferenceExperimentSchedule$$fGenericInferenceExperimentScheduleInferenceExperimentStatusInferenceExperimentStatus'fromInferenceExperimentStatus"InferenceExperimentStatus_Updating"InferenceExperimentStatus_Stopping"InferenceExperimentStatus_Starting!InferenceExperimentStatus_Running"InferenceExperimentStatus_Creating!InferenceExperimentStatus_Created#InferenceExperimentStatus_Completed#InferenceExperimentStatus_Cancelled$fShowInferenceExperimentStatus$fReadInferenceExperimentStatus$fEqInferenceExperimentStatus$fOrdInferenceExperimentStatus"$fGenericInferenceExperimentStatus#$fHashableInferenceExperimentStatus!$fNFDataInferenceExperimentStatus#$fFromTextInferenceExperimentStatus!$fToTextInferenceExperimentStatus'$fToByteStringInferenceExperimentStatus $fToLogInferenceExperimentStatus#$fToHeaderInferenceExperimentStatus"$fToQueryInferenceExperimentStatus#$fFromJSONInferenceExperimentStatus&$fFromJSONKeyInferenceExperimentStatus!$fToJSONInferenceExperimentStatus$$fToJSONKeyInferenceExperimentStatus"$fFromXMLInferenceExperimentStatus $fToXMLInferenceExperimentStatus#InferenceExperimentStopDesiredState$InferenceExperimentStopDesiredState''fromInferenceExperimentStopDesiredState-InferenceExperimentStopDesiredState_Completed-InferenceExperimentStopDesiredState_Cancelled)$fShowInferenceExperimentStopDesiredState)$fReadInferenceExperimentStopDesiredState'$fEqInferenceExperimentStopDesiredState($fOrdInferenceExperimentStopDesiredState,$fGenericInferenceExperimentStopDesiredState-$fHashableInferenceExperimentStopDesiredState+$fNFDataInferenceExperimentStopDesiredState-$fFromTextInferenceExperimentStopDesiredState+$fToTextInferenceExperimentStopDesiredState1$fToByteStringInferenceExperimentStopDesiredState*$fToLogInferenceExperimentStopDesiredState-$fToHeaderInferenceExperimentStopDesiredState,$fToQueryInferenceExperimentStopDesiredState-$fFromJSONInferenceExperimentStopDesiredState0$fFromJSONKeyInferenceExperimentStopDesiredState+$fToJSONInferenceExperimentStopDesiredState.$fToJSONKeyInferenceExperimentStopDesiredState,$fFromXMLInferenceExperimentStopDesiredState*$fToXMLInferenceExperimentStopDesiredStateInferenceExperimentTypeInferenceExperimentType'fromInferenceExperimentType"InferenceExperimentType_ShadowMode$fShowInferenceExperimentType$fReadInferenceExperimentType$fEqInferenceExperimentType$fOrdInferenceExperimentType $fGenericInferenceExperimentType!$fHashableInferenceExperimentType$fNFDataInferenceExperimentType!$fFromTextInferenceExperimentType$fToTextInferenceExperimentType%$fToByteStringInferenceExperimentType$fToLogInferenceExperimentType!$fToHeaderInferenceExperimentType $fToQueryInferenceExperimentType!$fFromJSONInferenceExperimentType$$fFromJSONKeyInferenceExperimentType$fToJSONInferenceExperimentType"$fToJSONKeyInferenceExperimentType $fFromXMLInferenceExperimentType$fToXMLInferenceExperimentTypeInferenceExperimentSummaryInferenceExperimentSummary'/$sel:completionTime:InferenceExperimentSummary',$sel:description:InferenceExperimentSummary'($sel:roleArn:InferenceExperimentSummary')$sel:schedule:InferenceExperimentSummary'-$sel:statusReason:InferenceExperimentSummary'%$sel:name:InferenceExperimentSummary'&$sel:type':InferenceExperimentSummary''$sel:status:InferenceExperimentSummary'-$sel:creationTime:InferenceExperimentSummary'1$sel:lastModifiedTime:InferenceExperimentSummary'newInferenceExperimentSummary)inferenceExperimentSummary_completionTime&inferenceExperimentSummary_description"inferenceExperimentSummary_roleArn#inferenceExperimentSummary_schedule'inferenceExperimentSummary_statusReasoninferenceExperimentSummary_nameinferenceExperimentSummary_type!inferenceExperimentSummary_status'inferenceExperimentSummary_creationTime+inferenceExperimentSummary_lastModifiedTime"$fNFDataInferenceExperimentSummary$$fHashableInferenceExperimentSummary$$fFromJSONInferenceExperimentSummary$fEqInferenceExperimentSummary $fReadInferenceExperimentSummary $fShowInferenceExperimentSummary#$fGenericInferenceExperimentSummaryInferenceMetricsInferenceMetrics'%$sel:maxInvocations:InferenceMetrics'#$sel:modelLatency:InferenceMetrics'newInferenceMetricsinferenceMetrics_maxInvocationsinferenceMetrics_modelLatency$fNFDataInferenceMetrics$fHashableInferenceMetrics$fFromJSONInferenceMetrics$fEqInferenceMetrics$fReadInferenceMetrics$fShowInferenceMetrics$fGenericInferenceMetricsEndpointPerformanceEndpointPerformance'!$sel:metrics:EndpointPerformance'&$sel:endpointInfo:EndpointPerformance'newEndpointPerformanceendpointPerformance_metrics endpointPerformance_endpointInfo$fNFDataEndpointPerformance$fHashableEndpointPerformance$fFromJSONEndpointPerformance$fEqEndpointPerformance$fReadEndpointPerformance$fShowEndpointPerformance$fGenericEndpointPerformance InputConfig InputConfig'"$sel:frameworkVersion:InputConfig'$sel:s3Uri:InputConfig'!$sel:dataInputConfig:InputConfig'$sel:framework:InputConfig'newInputConfiginputConfig_frameworkVersioninputConfig_s3UriinputConfig_dataInputConfiginputConfig_framework$fToJSONInputConfig$fNFDataInputConfig$fHashableInputConfig$fFromJSONInputConfig$fEqInputConfig$fReadInputConfig$fShowInputConfig$fGenericInputConfig InputMode InputMode' fromInputModeInputMode_PipeInputMode_File$fShowInputMode$fReadInputMode $fEqInputMode$fOrdInputMode$fGenericInputMode$fHashableInputMode$fNFDataInputMode$fFromTextInputMode$fToTextInputMode$fToByteStringInputMode$fToLogInputMode$fToHeaderInputMode$fToQueryInputMode$fFromJSONInputMode$fFromJSONKeyInputMode$fToJSONInputMode$fToJSONKeyInputMode$fFromXMLInputMode$fToXMLInputMode$InstanceMetadataServiceConfiguration%InstanceMetadataServiceConfiguration'$sel:minimumInstanceMetadataServiceVersion:InstanceMetadataServiceConfiguration''newInstanceMetadataServiceConfigurationinstanceMetadataServiceConfiguration_minimumInstanceMetadataServiceVersion,$fToJSONInstanceMetadataServiceConfiguration,$fNFDataInstanceMetadataServiceConfiguration.$fHashableInstanceMetadataServiceConfiguration.$fFromJSONInstanceMetadataServiceConfiguration($fEqInstanceMetadataServiceConfiguration*$fReadInstanceMetadataServiceConfiguration*$fShowInstanceMetadataServiceConfiguration-$fGenericInstanceMetadataServiceConfiguration InstanceType InstanceType'fromInstanceTypeInstanceType_Ml_t3_xlargeInstanceType_Ml_t3_mediumInstanceType_Ml_t3_largeInstanceType_Ml_t3_2xlargeInstanceType_Ml_t2_xlargeInstanceType_Ml_t2_mediumInstanceType_Ml_t2_largeInstanceType_Ml_t2_2xlargeInstanceType_Ml_r5_xlargeInstanceType_Ml_r5_largeInstanceType_Ml_r5_8xlargeInstanceType_Ml_r5_4xlargeInstanceType_Ml_r5_2xlargeInstanceType_Ml_r5_24xlargeInstanceType_Ml_r5_16xlargeInstanceType_Ml_r5_12xlargeInstanceType_Ml_p3dn_24xlargeInstanceType_Ml_p3_8xlargeInstanceType_Ml_p3_2xlargeInstanceType_Ml_p3_16xlargeInstanceType_Ml_p2_xlargeInstanceType_Ml_p2_8xlargeInstanceType_Ml_p2_16xlargeInstanceType_Ml_m5d_xlargeInstanceType_Ml_m5d_largeInstanceType_Ml_m5d_8xlargeInstanceType_Ml_m5d_4xlargeInstanceType_Ml_m5d_2xlargeInstanceType_Ml_m5d_24xlargeInstanceType_Ml_m5d_16xlargeInstanceType_Ml_m5d_12xlargeInstanceType_Ml_m5_xlargeInstanceType_Ml_m5_4xlargeInstanceType_Ml_m5_2xlargeInstanceType_Ml_m5_24xlargeInstanceType_Ml_m5_12xlargeInstanceType_Ml_m4_xlargeInstanceType_Ml_m4_4xlargeInstanceType_Ml_m4_2xlargeInstanceType_Ml_m4_16xlargeInstanceType_Ml_m4_10xlargeInstanceType_Ml_g5_xlargeInstanceType_Ml_g5_8xlargeInstanceType_Ml_g5_4xlargeInstanceType_Ml_g5_48xlargeInstanceType_Ml_g5_2xlargeInstanceType_Ml_g5_24xlargeInstanceType_Ml_g5_16xlargeInstanceType_Ml_g5_12xlargeInstanceType_Ml_g4dn_xlargeInstanceType_Ml_g4dn_8xlargeInstanceType_Ml_g4dn_4xlargeInstanceType_Ml_g4dn_2xlargeInstanceType_Ml_g4dn_16xlargeInstanceType_Ml_g4dn_12xlargeInstanceType_Ml_c5d_xlargeInstanceType_Ml_c5d_9xlargeInstanceType_Ml_c5d_4xlargeInstanceType_Ml_c5d_2xlargeInstanceType_Ml_c5d_18xlargeInstanceType_Ml_c5_xlargeInstanceType_Ml_c5_9xlargeInstanceType_Ml_c5_4xlargeInstanceType_Ml_c5_2xlargeInstanceType_Ml_c5_18xlargeInstanceType_Ml_c4_xlargeInstanceType_Ml_c4_8xlargeInstanceType_Ml_c4_4xlargeInstanceType_Ml_c4_2xlarge$fShowInstanceType$fReadInstanceType$fEqInstanceType$fOrdInstanceType$fGenericInstanceType$fHashableInstanceType$fNFDataInstanceType$fFromTextInstanceType$fToTextInstanceType$fToByteStringInstanceType$fToLogInstanceType$fToHeaderInstanceType$fToQueryInstanceType$fFromJSONInstanceType$fFromJSONKeyInstanceType$fToJSONInstanceType$fToJSONKeyInstanceType$fFromXMLInstanceType$fToXMLInstanceTypeIntegerParameterRangeIntegerParameterRange''$sel:scalingType:IntegerParameterRange' $sel:name:IntegerParameterRange'$$sel:minValue:IntegerParameterRange'$$sel:maxValue:IntegerParameterRange'newIntegerParameterRange!integerParameterRange_scalingTypeintegerParameterRange_nameintegerParameterRange_minValueintegerParameterRange_maxValue$fToJSONIntegerParameterRange$fNFDataIntegerParameterRange$fHashableIntegerParameterRange$fFromJSONIntegerParameterRange$fEqIntegerParameterRange$fReadIntegerParameterRange$fShowIntegerParameterRange$fGenericIntegerParameterRange"IntegerParameterRangeSpecification#IntegerParameterRangeSpecification'1$sel:minValue:IntegerParameterRangeSpecification'1$sel:maxValue:IntegerParameterRangeSpecification'%newIntegerParameterRangeSpecification+integerParameterRangeSpecification_minValue+integerParameterRangeSpecification_maxValue*$fToJSONIntegerParameterRangeSpecification*$fNFDataIntegerParameterRangeSpecification,$fHashableIntegerParameterRangeSpecification,$fFromJSONIntegerParameterRangeSpecification&$fEqIntegerParameterRangeSpecification($fReadIntegerParameterRangeSpecification($fShowIntegerParameterRangeSpecification+$fGenericIntegerParameterRangeSpecificationJobTypeJobType' fromJobTypeJobType_TRAININGJobType_NOTEBOOK_KERNELJobType_INFERENCE $fShowJobType $fReadJobType $fEqJobType $fOrdJobType$fGenericJobType$fHashableJobType$fNFDataJobType$fFromTextJobType$fToTextJobType$fToByteStringJobType$fToLogJobType$fToHeaderJobType$fToQueryJobType$fFromJSONJobType$fFromJSONKeyJobType$fToJSONJobType$fToJSONKeyJobType$fFromXMLJobType$fToXMLJobType JoinSource JoinSource'fromJoinSourceJoinSource_NoneJoinSource_Input$fShowJoinSource$fReadJoinSource$fEqJoinSource$fOrdJoinSource$fGenericJoinSource$fHashableJoinSource$fNFDataJoinSource$fFromTextJoinSource$fToTextJoinSource$fToByteStringJoinSource$fToLogJoinSource$fToHeaderJoinSource$fToQueryJoinSource$fFromJSONJoinSource$fFromJSONKeyJoinSource$fToJSONJoinSource$fToJSONKeyJoinSource$fFromXMLJoinSource$fToXMLJoinSourceDataProcessingDataProcessing' $sel:inputFilter:DataProcessing'$sel:joinSource:DataProcessing'!$sel:outputFilter:DataProcessing'newDataProcessingdataProcessing_inputFilterdataProcessing_joinSourcedataProcessing_outputFilter$fToJSONDataProcessing$fNFDataDataProcessing$fHashableDataProcessing$fFromJSONDataProcessing$fEqDataProcessing$fReadDataProcessing$fShowDataProcessing$fGenericDataProcessing KernelSpec KernelSpec'$sel:displayName:KernelSpec'$sel:name:KernelSpec' newKernelSpeckernelSpec_displayNamekernelSpec_name$fToJSONKernelSpec$fNFDataKernelSpec$fHashableKernelSpec$fFromJSONKernelSpec$fEqKernelSpec$fReadKernelSpec$fShowKernelSpec$fGenericKernelSpecKernelGatewayImageConfigKernelGatewayImageConfig'/$sel:fileSystemConfig:KernelGatewayImageConfig'*$sel:kernelSpecs:KernelGatewayImageConfig'newKernelGatewayImageConfig)kernelGatewayImageConfig_fileSystemConfig$kernelGatewayImageConfig_kernelSpecs $fToJSONKernelGatewayImageConfig $fNFDataKernelGatewayImageConfig"$fHashableKernelGatewayImageConfig"$fFromJSONKernelGatewayImageConfig$fEqKernelGatewayImageConfig$fReadKernelGatewayImageConfig$fShowKernelGatewayImageConfig!$fGenericKernelGatewayImageConfigAppImageConfigDetailsAppImageConfigDetails'-$sel:appImageConfigArn:AppImageConfigDetails'.$sel:appImageConfigName:AppImageConfigDetails'($sel:creationTime:AppImageConfigDetails'4$sel:kernelGatewayImageConfig:AppImageConfigDetails',$sel:lastModifiedTime:AppImageConfigDetails'newAppImageConfigDetails'appImageConfigDetails_appImageConfigArn(appImageConfigDetails_appImageConfigName"appImageConfigDetails_creationTime.appImageConfigDetails_kernelGatewayImageConfig&appImageConfigDetails_lastModifiedTime$fNFDataAppImageConfigDetails$fHashableAppImageConfigDetails$fFromJSONAppImageConfigDetails$fEqAppImageConfigDetails$fReadAppImageConfigDetails$fShowAppImageConfigDetails$fGenericAppImageConfigDetails LabelCountersLabelCounters'+$sel:failedNonRetryableError:LabelCounters' $sel:humanLabeled:LabelCounters'"$sel:machineLabeled:LabelCounters' $sel:totalLabeled:LabelCounters'$sel:unlabeled:LabelCounters'newLabelCounters%labelCounters_failedNonRetryableErrorlabelCounters_humanLabeledlabelCounters_machineLabeledlabelCounters_totalLabeledlabelCounters_unlabeled$fNFDataLabelCounters$fHashableLabelCounters$fFromJSONLabelCounters$fEqLabelCounters$fReadLabelCounters$fShowLabelCounters$fGenericLabelCountersLabelCountersForWorkteamLabelCountersForWorkteam'+$sel:humanLabeled:LabelCountersForWorkteam'+$sel:pendingHuman:LabelCountersForWorkteam'$$sel:total:LabelCountersForWorkteam'newLabelCountersForWorkteam%labelCountersForWorkteam_humanLabeled%labelCountersForWorkteam_pendingHumanlabelCountersForWorkteam_total $fNFDataLabelCountersForWorkteam"$fHashableLabelCountersForWorkteam"$fFromJSONLabelCountersForWorkteam$fEqLabelCountersForWorkteam$fReadLabelCountersForWorkteam$fShowLabelCountersForWorkteam!$fGenericLabelCountersForWorkteamLabelingJobDataAttributesLabelingJobDataAttributes'2$sel:contentClassifiers:LabelingJobDataAttributes'newLabelingJobDataAttributes,labelingJobDataAttributes_contentClassifiers!$fToJSONLabelingJobDataAttributes!$fNFDataLabelingJobDataAttributes#$fHashableLabelingJobDataAttributes#$fFromJSONLabelingJobDataAttributes$fEqLabelingJobDataAttributes$fReadLabelingJobDataAttributes$fShowLabelingJobDataAttributes"$fGenericLabelingJobDataAttributesLabelingJobForWorkteamSummaryLabelingJobForWorkteamSummary'1$sel:labelCounters:LabelingJobForWorkteamSummary'3$sel:labelingJobName:LabelingJobForWorkteamSummary'$sel:numberOfHumanWorkersPerDataObject:LabelingJobForWorkteamSummary'4$sel:jobReferenceCode:LabelingJobForWorkteamSummary':$sel:workRequesterAccountId:LabelingJobForWorkteamSummary'0$sel:creationTime:LabelingJobForWorkteamSummary' newLabelingJobForWorkteamSummary+labelingJobForWorkteamSummary_labelCounters-labelingJobForWorkteamSummary_labelingJobName?labelingJobForWorkteamSummary_numberOfHumanWorkersPerDataObject.labelingJobForWorkteamSummary_jobReferenceCode4labelingJobForWorkteamSummary_workRequesterAccountId*labelingJobForWorkteamSummary_creationTime%$fNFDataLabelingJobForWorkteamSummary'$fHashableLabelingJobForWorkteamSummary'$fFromJSONLabelingJobForWorkteamSummary!$fEqLabelingJobForWorkteamSummary#$fReadLabelingJobForWorkteamSummary#$fShowLabelingJobForWorkteamSummary&$fGenericLabelingJobForWorkteamSummaryLabelingJobOutputLabelingJobOutput'3$sel:finalActiveLearningModelArn:LabelingJobOutput'*$sel:outputDatasetS3Uri:LabelingJobOutput'newLabelingJobOutput-labelingJobOutput_finalActiveLearningModelArn$labelingJobOutput_outputDatasetS3Uri$fNFDataLabelingJobOutput$fHashableLabelingJobOutput$fFromJSONLabelingJobOutput$fEqLabelingJobOutput$fReadLabelingJobOutput$fShowLabelingJobOutput$fGenericLabelingJobOutputLabelingJobOutputConfigLabelingJobOutputConfig'&$sel:kmsKeyId:LabelingJobOutputConfig')$sel:snsTopicArn:LabelingJobOutputConfig'*$sel:s3OutputPath:LabelingJobOutputConfig'newLabelingJobOutputConfig labelingJobOutputConfig_kmsKeyId#labelingJobOutputConfig_snsTopicArn$labelingJobOutputConfig_s3OutputPath$fToJSONLabelingJobOutputConfig$fNFDataLabelingJobOutputConfig!$fHashableLabelingJobOutputConfig!$fFromJSONLabelingJobOutputConfig$fEqLabelingJobOutputConfig$fReadLabelingJobOutputConfig$fShowLabelingJobOutputConfig $fGenericLabelingJobOutputConfigLabelingJobS3DataSourceLabelingJobS3DataSource'+$sel:manifestS3Uri:LabelingJobS3DataSource'newLabelingJobS3DataSource%labelingJobS3DataSource_manifestS3Uri$fToJSONLabelingJobS3DataSource$fNFDataLabelingJobS3DataSource!$fHashableLabelingJobS3DataSource!$fFromJSONLabelingJobS3DataSource$fEqLabelingJobS3DataSource$fReadLabelingJobS3DataSource$fShowLabelingJobS3DataSource $fGenericLabelingJobS3DataSourceLabelingJobSnsDataSourceLabelingJobSnsDataSource'*$sel:snsTopicArn:LabelingJobSnsDataSource'newLabelingJobSnsDataSource$labelingJobSnsDataSource_snsTopicArn $fToJSONLabelingJobSnsDataSource $fNFDataLabelingJobSnsDataSource"$fHashableLabelingJobSnsDataSource"$fFromJSONLabelingJobSnsDataSource$fEqLabelingJobSnsDataSource$fReadLabelingJobSnsDataSource$fShowLabelingJobSnsDataSource!$fGenericLabelingJobSnsDataSourceLabelingJobDataSourceLabelingJobDataSource'($sel:s3DataSource:LabelingJobDataSource')$sel:snsDataSource:LabelingJobDataSource'newLabelingJobDataSource"labelingJobDataSource_s3DataSource#labelingJobDataSource_snsDataSource$fToJSONLabelingJobDataSource$fNFDataLabelingJobDataSource$fHashableLabelingJobDataSource$fFromJSONLabelingJobDataSource$fEqLabelingJobDataSource$fReadLabelingJobDataSource$fShowLabelingJobDataSource$fGenericLabelingJobDataSourceLabelingJobInputConfigLabelingJobInputConfig'+$sel:dataAttributes:LabelingJobInputConfig''$sel:dataSource:LabelingJobInputConfig'newLabelingJobInputConfig%labelingJobInputConfig_dataAttributes!labelingJobInputConfig_dataSource$fToJSONLabelingJobInputConfig$fNFDataLabelingJobInputConfig $fHashableLabelingJobInputConfig $fFromJSONLabelingJobInputConfig$fEqLabelingJobInputConfig$fReadLabelingJobInputConfig$fShowLabelingJobInputConfig$fGenericLabelingJobInputConfigLabelingJobStatusLabelingJobStatus'fromLabelingJobStatusLabelingJobStatus_StoppingLabelingJobStatus_StoppedLabelingJobStatus_InitializingLabelingJobStatus_InProgressLabelingJobStatus_FailedLabelingJobStatus_Completed$fShowLabelingJobStatus$fReadLabelingJobStatus$fEqLabelingJobStatus$fOrdLabelingJobStatus$fGenericLabelingJobStatus$fHashableLabelingJobStatus$fNFDataLabelingJobStatus$fFromTextLabelingJobStatus$fToTextLabelingJobStatus$fToByteStringLabelingJobStatus$fToLogLabelingJobStatus$fToHeaderLabelingJobStatus$fToQueryLabelingJobStatus$fFromJSONLabelingJobStatus$fFromJSONKeyLabelingJobStatus$fToJSONLabelingJobStatus$fToJSONKeyLabelingJobStatus$fFromXMLLabelingJobStatus$fToXMLLabelingJobStatusLabelingJobStoppingConditionsLabelingJobStoppingConditions'>$sel:maxHumanLabeledObjectCount:LabelingJobStoppingConditions'$sel:maxPercentageOfInputDatasetLabeled:LabelingJobStoppingConditions' newLabelingJobStoppingConditions8labelingJobStoppingConditions_maxHumanLabeledObjectCountlabelingJobStoppingConditions_maxPercentageOfInputDatasetLabeled%$fToJSONLabelingJobStoppingConditions%$fNFDataLabelingJobStoppingConditions'$fHashableLabelingJobStoppingConditions'$fFromJSONLabelingJobStoppingConditions!$fEqLabelingJobStoppingConditions#$fReadLabelingJobStoppingConditions#$fShowLabelingJobStoppingConditions&$fGenericLabelingJobStoppingConditionsLabelingJobSummaryLabelingJobSummary'9$sel:annotationConsolidationLambdaArn:LabelingJobSummary'&$sel:failureReason:LabelingJobSummary'$$sel:inputConfig:LabelingJobSummary'*$sel:labelingJobOutput:LabelingJobSummary'($sel:labelingJobName:LabelingJobSummary''$sel:labelingJobArn:LabelingJobSummary'%$sel:creationTime:LabelingJobSummary')$sel:lastModifiedTime:LabelingJobSummary'*$sel:labelingJobStatus:LabelingJobSummary'&$sel:labelCounters:LabelingJobSummary'$$sel:workteamArn:LabelingJobSummary'.$sel:preHumanTaskLambdaArn:LabelingJobSummary'newLabelingJobSummary3labelingJobSummary_annotationConsolidationLambdaArn labelingJobSummary_failureReasonlabelingJobSummary_inputConfig$labelingJobSummary_labelingJobOutput"labelingJobSummary_labelingJobName!labelingJobSummary_labelingJobArnlabelingJobSummary_creationTime#labelingJobSummary_lastModifiedTime$labelingJobSummary_labelingJobStatus labelingJobSummary_labelCounterslabelingJobSummary_workteamArn(labelingJobSummary_preHumanTaskLambdaArn$fNFDataLabelingJobSummary$fHashableLabelingJobSummary$fFromJSONLabelingJobSummary$fEqLabelingJobSummary$fReadLabelingJobSummary$fShowLabelingJobSummary$fGenericLabelingJobSummaryLastUpdateStatusValueLastUpdateStatusValue'fromLastUpdateStatusValue LastUpdateStatusValue_Successful LastUpdateStatusValue_InProgressLastUpdateStatusValue_Failed$fShowLastUpdateStatusValue$fReadLastUpdateStatusValue$fEqLastUpdateStatusValue$fOrdLastUpdateStatusValue$fGenericLastUpdateStatusValue$fHashableLastUpdateStatusValue$fNFDataLastUpdateStatusValue$fFromTextLastUpdateStatusValue$fToTextLastUpdateStatusValue#$fToByteStringLastUpdateStatusValue$fToLogLastUpdateStatusValue$fToHeaderLastUpdateStatusValue$fToQueryLastUpdateStatusValue$fFromJSONLastUpdateStatusValue"$fFromJSONKeyLastUpdateStatusValue$fToJSONLastUpdateStatusValue $fToJSONKeyLastUpdateStatusValue$fFromXMLLastUpdateStatusValue$fToXMLLastUpdateStatusValueLastUpdateStatusLastUpdateStatus'$$sel:failureReason:LastUpdateStatus'$sel:status:LastUpdateStatus'newLastUpdateStatuslastUpdateStatus_failureReasonlastUpdateStatus_status$fNFDataLastUpdateStatus$fHashableLastUpdateStatus$fFromJSONLastUpdateStatus$fEqLastUpdateStatus$fReadLastUpdateStatus$fShowLastUpdateStatus$fGenericLastUpdateStatusLineageGroupSummaryLineageGroupSummary'&$sel:creationTime:LineageGroupSummary'%$sel:displayName:LineageGroupSummary'*$sel:lastModifiedTime:LineageGroupSummary')$sel:lineageGroupArn:LineageGroupSummary'*$sel:lineageGroupName:LineageGroupSummary'newLineageGroupSummary lineageGroupSummary_creationTimelineageGroupSummary_displayName$lineageGroupSummary_lastModifiedTime#lineageGroupSummary_lineageGroupArn$lineageGroupSummary_lineageGroupName$fNFDataLineageGroupSummary$fHashableLineageGroupSummary$fFromJSONLineageGroupSummary$fEqLineageGroupSummary$fReadLineageGroupSummary$fShowLineageGroupSummary$fGenericLineageGroupSummary LineageType LineageType'fromLineageTypeLineageType_TrialComponentLineageType_ContextLineageType_ArtifactLineageType_Action$fShowLineageType$fReadLineageType$fEqLineageType$fOrdLineageType$fGenericLineageType$fHashableLineageType$fNFDataLineageType$fFromTextLineageType$fToTextLineageType$fToByteStringLineageType$fToLogLineageType$fToHeaderLineageType$fToQueryLineageType$fFromJSONLineageType$fFromJSONKeyLineageType$fToJSONLineageType$fToJSONKeyLineageType$fFromXMLLineageType$fToXMLLineageTypeListCompilationJobsSortByListCompilationJobsSortBy'fromListCompilationJobsSortBy ListCompilationJobsSortBy_StatusListCompilationJobsSortBy_Name&ListCompilationJobsSortBy_CreationTime$fShowListCompilationJobsSortBy$fReadListCompilationJobsSortBy$fEqListCompilationJobsSortBy$fOrdListCompilationJobsSortBy"$fGenericListCompilationJobsSortBy#$fHashableListCompilationJobsSortBy!$fNFDataListCompilationJobsSortBy#$fFromTextListCompilationJobsSortBy!$fToTextListCompilationJobsSortBy'$fToByteStringListCompilationJobsSortBy $fToLogListCompilationJobsSortBy#$fToHeaderListCompilationJobsSortBy"$fToQueryListCompilationJobsSortBy#$fFromJSONListCompilationJobsSortBy&$fFromJSONKeyListCompilationJobsSortBy!$fToJSONListCompilationJobsSortBy$$fToJSONKeyListCompilationJobsSortBy"$fFromXMLListCompilationJobsSortBy $fToXMLListCompilationJobsSortByListDeviceFleetsSortByListDeviceFleetsSortBy'fromListDeviceFleetsSortByListDeviceFleetsSortBy_NAME)ListDeviceFleetsSortBy_LAST_MODIFIED_TIME$ListDeviceFleetsSortBy_CREATION_TIME$fShowListDeviceFleetsSortBy$fReadListDeviceFleetsSortBy$fEqListDeviceFleetsSortBy$fOrdListDeviceFleetsSortBy$fGenericListDeviceFleetsSortBy $fHashableListDeviceFleetsSortBy$fNFDataListDeviceFleetsSortBy $fFromTextListDeviceFleetsSortBy$fToTextListDeviceFleetsSortBy$$fToByteStringListDeviceFleetsSortBy$fToLogListDeviceFleetsSortBy $fToHeaderListDeviceFleetsSortBy$fToQueryListDeviceFleetsSortBy $fFromJSONListDeviceFleetsSortBy#$fFromJSONKeyListDeviceFleetsSortBy$fToJSONListDeviceFleetsSortBy!$fToJSONKeyListDeviceFleetsSortBy$fFromXMLListDeviceFleetsSortBy$fToXMLListDeviceFleetsSortByListEdgeDeploymentPlansSortByListEdgeDeploymentPlansSortBy'!fromListEdgeDeploymentPlansSortBy"ListEdgeDeploymentPlansSortBy_NAME0ListEdgeDeploymentPlansSortBy_LAST_MODIFIED_TIME/ListEdgeDeploymentPlansSortBy_DEVICE_FLEET_NAME+ListEdgeDeploymentPlansSortBy_CREATION_TIME#$fShowListEdgeDeploymentPlansSortBy#$fReadListEdgeDeploymentPlansSortBy!$fEqListEdgeDeploymentPlansSortBy"$fOrdListEdgeDeploymentPlansSortBy&$fGenericListEdgeDeploymentPlansSortBy'$fHashableListEdgeDeploymentPlansSortBy%$fNFDataListEdgeDeploymentPlansSortBy'$fFromTextListEdgeDeploymentPlansSortBy%$fToTextListEdgeDeploymentPlansSortBy+$fToByteStringListEdgeDeploymentPlansSortBy$$fToLogListEdgeDeploymentPlansSortBy'$fToHeaderListEdgeDeploymentPlansSortBy&$fToQueryListEdgeDeploymentPlansSortBy'$fFromJSONListEdgeDeploymentPlansSortBy*$fFromJSONKeyListEdgeDeploymentPlansSortBy%$fToJSONListEdgeDeploymentPlansSortBy($fToJSONKeyListEdgeDeploymentPlansSortBy&$fFromXMLListEdgeDeploymentPlansSortBy$$fToXMLListEdgeDeploymentPlansSortByListEdgePackagingJobsSortByListEdgePackagingJobsSortBy'fromListEdgePackagingJobsSortBy"ListEdgePackagingJobsSortBy_STATUS ListEdgePackagingJobsSortBy_NAME&ListEdgePackagingJobsSortBy_MODEL_NAME.ListEdgePackagingJobsSortBy_LAST_MODIFIED_TIME)ListEdgePackagingJobsSortBy_CREATION_TIME!$fShowListEdgePackagingJobsSortBy!$fReadListEdgePackagingJobsSortBy$fEqListEdgePackagingJobsSortBy $fOrdListEdgePackagingJobsSortBy$$fGenericListEdgePackagingJobsSortBy%$fHashableListEdgePackagingJobsSortBy#$fNFDataListEdgePackagingJobsSortBy%$fFromTextListEdgePackagingJobsSortBy#$fToTextListEdgePackagingJobsSortBy)$fToByteStringListEdgePackagingJobsSortBy"$fToLogListEdgePackagingJobsSortBy%$fToHeaderListEdgePackagingJobsSortBy$$fToQueryListEdgePackagingJobsSortBy%$fFromJSONListEdgePackagingJobsSortBy($fFromJSONKeyListEdgePackagingJobsSortBy#$fToJSONListEdgePackagingJobsSortBy&$fToJSONKeyListEdgePackagingJobsSortBy$$fFromXMLListEdgePackagingJobsSortBy"$fToXMLListEdgePackagingJobsSortBy&ListInferenceRecommendationsJobsSortBy'ListInferenceRecommendationsJobsSortBy'*fromListInferenceRecommendationsJobsSortBy-ListInferenceRecommendationsJobsSortBy_Status+ListInferenceRecommendationsJobsSortBy_Name3ListInferenceRecommendationsJobsSortBy_CreationTime,$fShowListInferenceRecommendationsJobsSortBy,$fReadListInferenceRecommendationsJobsSortBy*$fEqListInferenceRecommendationsJobsSortBy+$fOrdListInferenceRecommendationsJobsSortBy/$fGenericListInferenceRecommendationsJobsSortBy0$fHashableListInferenceRecommendationsJobsSortBy.$fNFDataListInferenceRecommendationsJobsSortBy0$fFromTextListInferenceRecommendationsJobsSortBy.$fToTextListInferenceRecommendationsJobsSortBy4$fToByteStringListInferenceRecommendationsJobsSortBy-$fToLogListInferenceRecommendationsJobsSortBy0$fToHeaderListInferenceRecommendationsJobsSortBy/$fToQueryListInferenceRecommendationsJobsSortBy0$fFromJSONListInferenceRecommendationsJobsSortBy3$fFromJSONKeyListInferenceRecommendationsJobsSortBy.$fToJSONListInferenceRecommendationsJobsSortBy1$fToJSONKeyListInferenceRecommendationsJobsSortBy/$fFromXMLListInferenceRecommendationsJobsSortBy-$fToXMLListInferenceRecommendationsJobsSortBy(ListLabelingJobsForWorkteamSortByOptions)ListLabelingJobsForWorkteamSortByOptions',fromListLabelingJobsForWorkteamSortByOptions5ListLabelingJobsForWorkteamSortByOptions_CreationTime.$fShowListLabelingJobsForWorkteamSortByOptions.$fReadListLabelingJobsForWorkteamSortByOptions,$fEqListLabelingJobsForWorkteamSortByOptions-$fOrdListLabelingJobsForWorkteamSortByOptions1$fGenericListLabelingJobsForWorkteamSortByOptions2$fHashableListLabelingJobsForWorkteamSortByOptions0$fNFDataListLabelingJobsForWorkteamSortByOptions2$fFromTextListLabelingJobsForWorkteamSortByOptions0$fToTextListLabelingJobsForWorkteamSortByOptions6$fToByteStringListLabelingJobsForWorkteamSortByOptions/$fToLogListLabelingJobsForWorkteamSortByOptions2$fToHeaderListLabelingJobsForWorkteamSortByOptions1$fToQueryListLabelingJobsForWorkteamSortByOptions2$fFromJSONListLabelingJobsForWorkteamSortByOptions5$fFromJSONKeyListLabelingJobsForWorkteamSortByOptions0$fToJSONListLabelingJobsForWorkteamSortByOptions3$fToJSONKeyListLabelingJobsForWorkteamSortByOptions1$fFromXMLListLabelingJobsForWorkteamSortByOptions/$fToXMLListLabelingJobsForWorkteamSortByOptionsListWorkforcesSortByOptionsListWorkforcesSortByOptions'fromListWorkforcesSortByOptions ListWorkforcesSortByOptions_Name&ListWorkforcesSortByOptions_CreateDate!$fShowListWorkforcesSortByOptions!$fReadListWorkforcesSortByOptions$fEqListWorkforcesSortByOptions $fOrdListWorkforcesSortByOptions$$fGenericListWorkforcesSortByOptions%$fHashableListWorkforcesSortByOptions#$fNFDataListWorkforcesSortByOptions%$fFromTextListWorkforcesSortByOptions#$fToTextListWorkforcesSortByOptions)$fToByteStringListWorkforcesSortByOptions"$fToLogListWorkforcesSortByOptions%$fToHeaderListWorkforcesSortByOptions$$fToQueryListWorkforcesSortByOptions%$fFromJSONListWorkforcesSortByOptions($fFromJSONKeyListWorkforcesSortByOptions#$fToJSONListWorkforcesSortByOptions&$fToJSONKeyListWorkforcesSortByOptions$$fFromXMLListWorkforcesSortByOptions"$fToXMLListWorkforcesSortByOptionsListWorkteamsSortByOptionsListWorkteamsSortByOptions'fromListWorkteamsSortByOptionsListWorkteamsSortByOptions_Name%ListWorkteamsSortByOptions_CreateDate $fShowListWorkteamsSortByOptions $fReadListWorkteamsSortByOptions$fEqListWorkteamsSortByOptions$fOrdListWorkteamsSortByOptions#$fGenericListWorkteamsSortByOptions$$fHashableListWorkteamsSortByOptions"$fNFDataListWorkteamsSortByOptions$$fFromTextListWorkteamsSortByOptions"$fToTextListWorkteamsSortByOptions($fToByteStringListWorkteamsSortByOptions!$fToLogListWorkteamsSortByOptions$$fToHeaderListWorkteamsSortByOptions#$fToQueryListWorkteamsSortByOptions$$fFromJSONListWorkteamsSortByOptions'$fFromJSONKeyListWorkteamsSortByOptions"$fToJSONListWorkteamsSortByOptions%$fToJSONKeyListWorkteamsSortByOptions#$fFromXMLListWorkteamsSortByOptions!$fToXMLListWorkteamsSortByOptionsMetadataPropertiesMetadataProperties'!$sel:commitId:MetadataProperties'$$sel:generatedBy:MetadataProperties'"$sel:projectId:MetadataProperties'#$sel:repository:MetadataProperties'newMetadataPropertiesmetadataProperties_commitIdmetadataProperties_generatedBymetadataProperties_projectIdmetadataProperties_repository$fToJSONMetadataProperties$fNFDataMetadataProperties$fHashableMetadataProperties$fFromJSONMetadataProperties$fEqMetadataProperties$fReadMetadataProperties$fShowMetadataProperties$fGenericMetadataProperties MetricData MetricData'$sel:metricName:MetricData'$sel:timestamp:MetricData'$sel:value:MetricData' newMetricDatametricData_metricNamemetricData_timestampmetricData_value$fNFDataMetricData$fHashableMetricData$fFromJSONMetricData$fEqMetricData$fReadMetricData$fShowMetricData$fGenericMetricDataMetricDefinitionMetricDefinition'$sel:name:MetricDefinition'$sel:regex:MetricDefinition'newMetricDefinitionmetricDefinition_namemetricDefinition_regex$fToJSONMetricDefinition$fNFDataMetricDefinition$fHashableMetricDefinition$fFromJSONMetricDefinition$fEqMetricDefinition$fReadMetricDefinition$fShowMetricDefinition$fGenericMetricDefinitionMetricSetSourceMetricSetSource'fromMetricSetSourceMetricSetSource_ValidationMetricSetSource_TrainMetricSetSource_Test$fShowMetricSetSource$fReadMetricSetSource$fEqMetricSetSource$fOrdMetricSetSource$fGenericMetricSetSource$fHashableMetricSetSource$fNFDataMetricSetSource$fFromTextMetricSetSource$fToTextMetricSetSource$fToByteStringMetricSetSource$fToLogMetricSetSource$fToHeaderMetricSetSource$fToQueryMetricSetSource$fFromJSONMetricSetSource$fFromJSONKeyMetricSetSource$fToJSONMetricSetSource$fToJSONKeyMetricSetSource$fFromXMLMetricSetSource$fToXMLMetricSetSource MetricDatum MetricDatum'$sel:metricName:MetricDatum'$sel:set:MetricDatum'$$sel:standardMetricName:MetricDatum'$sel:value:MetricDatum'newMetricDatummetricDatum_metricNamemetricDatum_setmetricDatum_standardMetricNamemetricDatum_value$fNFDataMetricDatum$fHashableMetricDatum$fFromJSONMetricDatum$fEqMetricDatum$fReadMetricDatum$fShowMetricDatum$fGenericMetricDatumCandidatePropertiesCandidateProperties'4$sel:candidateArtifactLocations:CandidateProperties'*$sel:candidateMetrics:CandidateProperties'newCandidateProperties.candidateProperties_candidateArtifactLocations$candidateProperties_candidateMetrics$fNFDataCandidateProperties$fHashableCandidateProperties$fFromJSONCandidateProperties$fEqCandidateProperties$fReadCandidateProperties$fShowCandidateProperties$fGenericCandidateProperties MetricsSourceMetricsSource'!$sel:contentDigest:MetricsSource'$sel:contentType:MetricsSource'$sel:s3Uri:MetricsSource'newMetricsSourcemetricsSource_contentDigestmetricsSource_contentTypemetricsSource_s3Uri$fToJSONMetricsSource$fNFDataMetricsSource$fHashableMetricsSource$fFromJSONMetricsSource$fEqMetricsSource$fReadMetricsSource$fShowMetricsSource$fGenericMetricsSourceExplainabilityExplainability'$sel:report:Explainability'newExplainabilityexplainability_report$fToJSONExplainability$fNFDataExplainability$fHashableExplainability$fFromJSONExplainability$fEqExplainability$fReadExplainability$fShowExplainability$fGenericExplainabilityDriftCheckModelQualityDriftCheckModelQuality'($sel:constraints:DriftCheckModelQuality''$sel:statistics:DriftCheckModelQuality'newDriftCheckModelQuality"driftCheckModelQuality_constraints!driftCheckModelQuality_statistics$fToJSONDriftCheckModelQuality$fNFDataDriftCheckModelQuality $fHashableDriftCheckModelQuality $fFromJSONDriftCheckModelQuality$fEqDriftCheckModelQuality$fReadDriftCheckModelQuality$fShowDriftCheckModelQuality$fGenericDriftCheckModelQualityDriftCheckModelDataQualityDriftCheckModelDataQuality',$sel:constraints:DriftCheckModelDataQuality'+$sel:statistics:DriftCheckModelDataQuality'newDriftCheckModelDataQuality&driftCheckModelDataQuality_constraints%driftCheckModelDataQuality_statistics"$fToJSONDriftCheckModelDataQuality"$fNFDataDriftCheckModelDataQuality$$fHashableDriftCheckModelDataQuality$$fFromJSONDriftCheckModelDataQuality$fEqDriftCheckModelDataQuality $fReadDriftCheckModelDataQuality $fShowDriftCheckModelDataQuality#$fGenericDriftCheckModelDataQualityDriftCheckExplainabilityDriftCheckExplainability')$sel:configFile:DriftCheckExplainability'*$sel:constraints:DriftCheckExplainability'newDriftCheckExplainability#driftCheckExplainability_configFile$driftCheckExplainability_constraints $fToJSONDriftCheckExplainability $fNFDataDriftCheckExplainability"$fHashableDriftCheckExplainability"$fFromJSONDriftCheckExplainability$fEqDriftCheckExplainability$fReadDriftCheckExplainability$fShowDriftCheckExplainability!$fGenericDriftCheckExplainabilityDriftCheckBiasDriftCheckBias'$sel:configFile:DriftCheckBias',$sel:postTrainingConstraints:DriftCheckBias'+$sel:preTrainingConstraints:DriftCheckBias'newDriftCheckBiasdriftCheckBias_configFile&driftCheckBias_postTrainingConstraints%driftCheckBias_preTrainingConstraints$fToJSONDriftCheckBias$fNFDataDriftCheckBias$fHashableDriftCheckBias$fFromJSONDriftCheckBias$fEqDriftCheckBias$fReadDriftCheckBias$fShowDriftCheckBias$fGenericDriftCheckBiasDriftCheckBaselinesDriftCheckBaselines'$sel:bias:DriftCheckBaselines'($sel:explainability:DriftCheckBaselines'*$sel:modelDataQuality:DriftCheckBaselines'&$sel:modelQuality:DriftCheckBaselines'newDriftCheckBaselinesdriftCheckBaselines_bias"driftCheckBaselines_explainability$driftCheckBaselines_modelDataQuality driftCheckBaselines_modelQuality$fToJSONDriftCheckBaselines$fNFDataDriftCheckBaselines$fHashableDriftCheckBaselines$fFromJSONDriftCheckBaselines$fEqDriftCheckBaselines$fReadDriftCheckBaselines$fShowDriftCheckBaselines$fGenericDriftCheckBaselinesBiasBias'$sel:postTrainingReport:Bias'$sel:preTrainingReport:Bias'$sel:report:Bias'newBiasbias_postTrainingReportbias_preTrainingReport bias_report $fToJSONBias $fNFDataBias$fHashableBias$fFromJSONBias$fEqBias $fReadBias $fShowBias $fGenericBiasModelApprovalStatusModelApprovalStatus'fromModelApprovalStatusModelApprovalStatus_Rejected)ModelApprovalStatus_PendingManualApprovalModelApprovalStatus_Approved$fShowModelApprovalStatus$fReadModelApprovalStatus$fEqModelApprovalStatus$fOrdModelApprovalStatus$fGenericModelApprovalStatus$fHashableModelApprovalStatus$fNFDataModelApprovalStatus$fFromTextModelApprovalStatus$fToTextModelApprovalStatus!$fToByteStringModelApprovalStatus$fToLogModelApprovalStatus$fToHeaderModelApprovalStatus$fToQueryModelApprovalStatus$fFromJSONModelApprovalStatus $fFromJSONKeyModelApprovalStatus$fToJSONModelApprovalStatus$fToJSONKeyModelApprovalStatus$fFromXMLModelApprovalStatus$fToXMLModelApprovalStatusModelArtifactsModelArtifacts'%$sel:s3ModelArtifacts:ModelArtifacts'newModelArtifactsmodelArtifacts_s3ModelArtifacts$fNFDataModelArtifacts$fHashableModelArtifacts$fFromJSONModelArtifacts$fEqModelArtifacts$fReadModelArtifacts$fShowModelArtifacts$fGenericModelArtifactsModelBiasAppSpecificationModelBiasAppSpecification'+$sel:environment:ModelBiasAppSpecification'($sel:imageUri:ModelBiasAppSpecification')$sel:configUri:ModelBiasAppSpecification'newModelBiasAppSpecification%modelBiasAppSpecification_environment"modelBiasAppSpecification_imageUri#modelBiasAppSpecification_configUri!$fToJSONModelBiasAppSpecification!$fNFDataModelBiasAppSpecification#$fHashableModelBiasAppSpecification#$fFromJSONModelBiasAppSpecification$fEqModelBiasAppSpecification$fReadModelBiasAppSpecification$fShowModelBiasAppSpecification"$fGenericModelBiasAppSpecificationModelCacheSettingModelCacheSetting'fromModelCacheSettingModelCacheSetting_EnabledModelCacheSetting_Disabled$fShowModelCacheSetting$fReadModelCacheSetting$fEqModelCacheSetting$fOrdModelCacheSetting$fGenericModelCacheSetting$fHashableModelCacheSetting$fNFDataModelCacheSetting$fFromTextModelCacheSetting$fToTextModelCacheSetting$fToByteStringModelCacheSetting$fToLogModelCacheSetting$fToHeaderModelCacheSetting$fToQueryModelCacheSetting$fFromJSONModelCacheSetting$fFromJSONKeyModelCacheSetting$fToJSONModelCacheSetting$fToJSONKeyModelCacheSetting$fFromXMLModelCacheSetting$fToXMLModelCacheSettingModelCardExportArtifactsModelCardExportArtifacts'0$sel:s3ExportArtifacts:ModelCardExportArtifacts'newModelCardExportArtifacts*modelCardExportArtifacts_s3ExportArtifacts $fNFDataModelCardExportArtifacts"$fHashableModelCardExportArtifacts"$fFromJSONModelCardExportArtifacts$fEqModelCardExportArtifacts$fReadModelCardExportArtifacts$fShowModelCardExportArtifacts!$fGenericModelCardExportArtifactsModelCardExportJobSortByModelCardExportJobSortBy'fromModelCardExportJobSortByModelCardExportJobSortBy_StatusModelCardExportJobSortBy_Name%ModelCardExportJobSortBy_CreationTime$fShowModelCardExportJobSortBy$fReadModelCardExportJobSortBy$fEqModelCardExportJobSortBy$fOrdModelCardExportJobSortBy!$fGenericModelCardExportJobSortBy"$fHashableModelCardExportJobSortBy $fNFDataModelCardExportJobSortBy"$fFromTextModelCardExportJobSortBy $fToTextModelCardExportJobSortBy&$fToByteStringModelCardExportJobSortBy$fToLogModelCardExportJobSortBy"$fToHeaderModelCardExportJobSortBy!$fToQueryModelCardExportJobSortBy"$fFromJSONModelCardExportJobSortBy%$fFromJSONKeyModelCardExportJobSortBy $fToJSONModelCardExportJobSortBy#$fToJSONKeyModelCardExportJobSortBy!$fFromXMLModelCardExportJobSortBy$fToXMLModelCardExportJobSortByModelCardExportJobSortOrderModelCardExportJobSortOrder'fromModelCardExportJobSortOrder&ModelCardExportJobSortOrder_Descending%ModelCardExportJobSortOrder_Ascending!$fShowModelCardExportJobSortOrder!$fReadModelCardExportJobSortOrder$fEqModelCardExportJobSortOrder $fOrdModelCardExportJobSortOrder$$fGenericModelCardExportJobSortOrder%$fHashableModelCardExportJobSortOrder#$fNFDataModelCardExportJobSortOrder%$fFromTextModelCardExportJobSortOrder#$fToTextModelCardExportJobSortOrder)$fToByteStringModelCardExportJobSortOrder"$fToLogModelCardExportJobSortOrder%$fToHeaderModelCardExportJobSortOrder$$fToQueryModelCardExportJobSortOrder%$fFromJSONModelCardExportJobSortOrder($fFromJSONKeyModelCardExportJobSortOrder#$fToJSONModelCardExportJobSortOrder&$fToJSONKeyModelCardExportJobSortOrder$$fFromXMLModelCardExportJobSortOrder"$fToXMLModelCardExportJobSortOrderModelCardExportJobStatusModelCardExportJobStatus'fromModelCardExportJobStatus#ModelCardExportJobStatus_InProgressModelCardExportJobStatus_Failed"ModelCardExportJobStatus_Completed$fShowModelCardExportJobStatus$fReadModelCardExportJobStatus$fEqModelCardExportJobStatus$fOrdModelCardExportJobStatus!$fGenericModelCardExportJobStatus"$fHashableModelCardExportJobStatus $fNFDataModelCardExportJobStatus"$fFromTextModelCardExportJobStatus $fToTextModelCardExportJobStatus&$fToByteStringModelCardExportJobStatus$fToLogModelCardExportJobStatus"$fToHeaderModelCardExportJobStatus!$fToQueryModelCardExportJobStatus"$fFromJSONModelCardExportJobStatus%$fFromJSONKeyModelCardExportJobStatus $fToJSONModelCardExportJobStatus#$fToJSONKeyModelCardExportJobStatus!$fFromXMLModelCardExportJobStatus$fToXMLModelCardExportJobStatusModelCardExportJobSummaryModelCardExportJobSummary'6$sel:modelCardExportJobName:ModelCardExportJobSummary'5$sel:modelCardExportJobArn:ModelCardExportJobSummary'&$sel:status:ModelCardExportJobSummary'-$sel:modelCardName:ModelCardExportJobSummary'0$sel:modelCardVersion:ModelCardExportJobSummary')$sel:createdAt:ModelCardExportJobSummary'.$sel:lastModifiedAt:ModelCardExportJobSummary'newModelCardExportJobSummary0modelCardExportJobSummary_modelCardExportJobName/modelCardExportJobSummary_modelCardExportJobArn modelCardExportJobSummary_status'modelCardExportJobSummary_modelCardName*modelCardExportJobSummary_modelCardVersion#modelCardExportJobSummary_createdAt(modelCardExportJobSummary_lastModifiedAt!$fNFDataModelCardExportJobSummary#$fHashableModelCardExportJobSummary#$fFromJSONModelCardExportJobSummary$fEqModelCardExportJobSummary$fReadModelCardExportJobSummary$fShowModelCardExportJobSummary"$fGenericModelCardExportJobSummaryModelCardExportOutputConfigModelCardExportOutputConfig'.$sel:s3OutputPath:ModelCardExportOutputConfig'newModelCardExportOutputConfig(modelCardExportOutputConfig_s3OutputPath#$fToJSONModelCardExportOutputConfig#$fNFDataModelCardExportOutputConfig%$fHashableModelCardExportOutputConfig%$fFromJSONModelCardExportOutputConfig$fEqModelCardExportOutputConfig!$fReadModelCardExportOutputConfig!$fShowModelCardExportOutputConfig$$fGenericModelCardExportOutputConfigModelCardProcessingStatusModelCardProcessingStatus'fromModelCardProcessingStatus+ModelCardProcessingStatus_ExportJobsDeleted'ModelCardProcessingStatus_DeletePending*ModelCardProcessingStatus_DeleteInProgress&ModelCardProcessingStatus_DeleteFailed)ModelCardProcessingStatus_DeleteCompleted(ModelCardProcessingStatus_ContentDeleted$fShowModelCardProcessingStatus$fReadModelCardProcessingStatus$fEqModelCardProcessingStatus$fOrdModelCardProcessingStatus"$fGenericModelCardProcessingStatus#$fHashableModelCardProcessingStatus!$fNFDataModelCardProcessingStatus#$fFromTextModelCardProcessingStatus!$fToTextModelCardProcessingStatus'$fToByteStringModelCardProcessingStatus $fToLogModelCardProcessingStatus#$fToHeaderModelCardProcessingStatus"$fToQueryModelCardProcessingStatus#$fFromJSONModelCardProcessingStatus&$fFromJSONKeyModelCardProcessingStatus!$fToJSONModelCardProcessingStatus$$fToJSONKeyModelCardProcessingStatus"$fFromXMLModelCardProcessingStatus $fToXMLModelCardProcessingStatusModelCardSecurityConfigModelCardSecurityConfig'&$sel:kmsKeyId:ModelCardSecurityConfig'newModelCardSecurityConfig modelCardSecurityConfig_kmsKeyId$fToJSONModelCardSecurityConfig$fNFDataModelCardSecurityConfig!$fHashableModelCardSecurityConfig!$fFromJSONModelCardSecurityConfig$fEqModelCardSecurityConfig$fReadModelCardSecurityConfig$fShowModelCardSecurityConfig $fGenericModelCardSecurityConfigModelCardSortByModelCardSortBy'fromModelCardSortByModelCardSortBy_NameModelCardSortBy_CreationTime$fShowModelCardSortBy$fReadModelCardSortBy$fEqModelCardSortBy$fOrdModelCardSortBy$fGenericModelCardSortBy$fHashableModelCardSortBy$fNFDataModelCardSortBy$fFromTextModelCardSortBy$fToTextModelCardSortBy$fToByteStringModelCardSortBy$fToLogModelCardSortBy$fToHeaderModelCardSortBy$fToQueryModelCardSortBy$fFromJSONModelCardSortBy$fFromJSONKeyModelCardSortBy$fToJSONModelCardSortBy$fToJSONKeyModelCardSortBy$fFromXMLModelCardSortBy$fToXMLModelCardSortByModelCardSortOrderModelCardSortOrder'fromModelCardSortOrderModelCardSortOrder_DescendingModelCardSortOrder_Ascending$fShowModelCardSortOrder$fReadModelCardSortOrder$fEqModelCardSortOrder$fOrdModelCardSortOrder$fGenericModelCardSortOrder$fHashableModelCardSortOrder$fNFDataModelCardSortOrder$fFromTextModelCardSortOrder$fToTextModelCardSortOrder $fToByteStringModelCardSortOrder$fToLogModelCardSortOrder$fToHeaderModelCardSortOrder$fToQueryModelCardSortOrder$fFromJSONModelCardSortOrder$fFromJSONKeyModelCardSortOrder$fToJSONModelCardSortOrder$fToJSONKeyModelCardSortOrder$fFromXMLModelCardSortOrder$fToXMLModelCardSortOrderModelCardStatusModelCardStatus'fromModelCardStatusModelCardStatus_PendingReviewModelCardStatus_DraftModelCardStatus_ArchivedModelCardStatus_Approved$fShowModelCardStatus$fReadModelCardStatus$fEqModelCardStatus$fOrdModelCardStatus$fGenericModelCardStatus$fHashableModelCardStatus$fNFDataModelCardStatus$fFromTextModelCardStatus$fToTextModelCardStatus$fToByteStringModelCardStatus$fToLogModelCardStatus$fToHeaderModelCardStatus$fToQueryModelCardStatus$fFromJSONModelCardStatus$fFromJSONKeyModelCardStatus$fToJSONModelCardStatus$fToJSONKeyModelCardStatus$fFromXMLModelCardStatus$fToXMLModelCardStatusModelCardSummaryModelCardSummary''$sel:lastModifiedTime:ModelCardSummary'$$sel:modelCardName:ModelCardSummary'#$sel:modelCardArn:ModelCardSummary'&$sel:modelCardStatus:ModelCardSummary'#$sel:creationTime:ModelCardSummary'newModelCardSummary!modelCardSummary_lastModifiedTimemodelCardSummary_modelCardNamemodelCardSummary_modelCardArn modelCardSummary_modelCardStatusmodelCardSummary_creationTime$fNFDataModelCardSummary$fHashableModelCardSummary$fFromJSONModelCardSummary$fEqModelCardSummary$fReadModelCardSummary$fShowModelCardSummary$fGenericModelCardSummaryModelCardVersionSortByModelCardVersionSortBy'fromModelCardVersionSortByModelCardVersionSortBy_Version$fShowModelCardVersionSortBy$fReadModelCardVersionSortBy$fEqModelCardVersionSortBy$fOrdModelCardVersionSortBy$fGenericModelCardVersionSortBy $fHashableModelCardVersionSortBy$fNFDataModelCardVersionSortBy $fFromTextModelCardVersionSortBy$fToTextModelCardVersionSortBy$$fToByteStringModelCardVersionSortBy$fToLogModelCardVersionSortBy $fToHeaderModelCardVersionSortBy$fToQueryModelCardVersionSortBy $fFromJSONModelCardVersionSortBy#$fFromJSONKeyModelCardVersionSortBy$fToJSONModelCardVersionSortBy!$fToJSONKeyModelCardVersionSortBy$fFromXMLModelCardVersionSortBy$fToXMLModelCardVersionSortByModelCardVersionSummaryModelCardVersionSummary'.$sel:lastModifiedTime:ModelCardVersionSummary'+$sel:modelCardName:ModelCardVersionSummary'*$sel:modelCardArn:ModelCardVersionSummary'-$sel:modelCardStatus:ModelCardVersionSummary'.$sel:modelCardVersion:ModelCardVersionSummary'*$sel:creationTime:ModelCardVersionSummary'newModelCardVersionSummary(modelCardVersionSummary_lastModifiedTime%modelCardVersionSummary_modelCardName$modelCardVersionSummary_modelCardArn'modelCardVersionSummary_modelCardStatus(modelCardVersionSummary_modelCardVersion$modelCardVersionSummary_creationTime$fNFDataModelCardVersionSummary!$fHashableModelCardVersionSummary!$fFromJSONModelCardVersionSummary$fEqModelCardVersionSummary$fReadModelCardVersionSummary$fShowModelCardVersionSummary $fGenericModelCardVersionSummaryModelClientConfigModelClientConfig'-$sel:invocationsMaxRetries:ModelClientConfig'3$sel:invocationsTimeoutInSeconds:ModelClientConfig'newModelClientConfig'modelClientConfig_invocationsMaxRetries-modelClientConfig_invocationsTimeoutInSeconds$fToJSONModelClientConfig$fNFDataModelClientConfig$fHashableModelClientConfig$fFromJSONModelClientConfig$fEqModelClientConfig$fReadModelClientConfig$fShowModelClientConfig$fGenericModelClientConfigModelConfigurationModelConfiguration'.$sel:environmentParameters:ModelConfiguration'3$sel:inferenceSpecificationName:ModelConfiguration'newModelConfiguration(modelConfiguration_environmentParameters-modelConfiguration_inferenceSpecificationName$fNFDataModelConfiguration$fHashableModelConfiguration$fFromJSONModelConfiguration$fEqModelConfiguration$fReadModelConfiguration$fShowModelConfiguration$fGenericModelConfigurationModelDashboardEndpointModelDashboardEndpoint')$sel:endpointName:ModelDashboardEndpoint'($sel:endpointArn:ModelDashboardEndpoint')$sel:creationTime:ModelDashboardEndpoint'-$sel:lastModifiedTime:ModelDashboardEndpoint'+$sel:endpointStatus:ModelDashboardEndpoint'newModelDashboardEndpoint#modelDashboardEndpoint_endpointName"modelDashboardEndpoint_endpointArn#modelDashboardEndpoint_creationTime'modelDashboardEndpoint_lastModifiedTime%modelDashboardEndpoint_endpointStatus$fNFDataModelDashboardEndpoint $fHashableModelDashboardEndpoint $fFromJSONModelDashboardEndpoint$fEqModelDashboardEndpoint$fReadModelDashboardEndpoint$fShowModelDashboardEndpoint$fGenericModelDashboardEndpointModelDashboardIndicatorActionModelDashboardIndicatorAction'+$sel:enabled:ModelDashboardIndicatorAction' newModelDashboardIndicatorAction%modelDashboardIndicatorAction_enabled%$fNFDataModelDashboardIndicatorAction'$fHashableModelDashboardIndicatorAction'$fFromJSONModelDashboardIndicatorAction!$fEqModelDashboardIndicatorAction#$fReadModelDashboardIndicatorAction#$fShowModelDashboardIndicatorAction&$fGenericModelDashboardIndicatorActionModelDataQualityModelDataQuality'"$sel:constraints:ModelDataQuality'!$sel:statistics:ModelDataQuality'newModelDataQualitymodelDataQuality_constraintsmodelDataQuality_statistics$fToJSONModelDataQuality$fNFDataModelDataQuality$fHashableModelDataQuality$fFromJSONModelDataQuality$fEqModelDataQuality$fReadModelDataQuality$fShowModelDataQuality$fGenericModelDataQualityModelDeployConfigModelDeployConfig'0$sel:autoGenerateEndpointName:ModelDeployConfig'$$sel:endpointName:ModelDeployConfig'newModelDeployConfig*modelDeployConfig_autoGenerateEndpointNamemodelDeployConfig_endpointName$fToJSONModelDeployConfig$fNFDataModelDeployConfig$fHashableModelDeployConfig$fFromJSONModelDeployConfig$fEqModelDeployConfig$fReadModelDeployConfig$fShowModelDeployConfig$fGenericModelDeployConfigModelDeployResultModelDeployResult'$$sel:endpointName:ModelDeployResult'newModelDeployResultmodelDeployResult_endpointName$fNFDataModelDeployResult$fHashableModelDeployResult$fFromJSONModelDeployResult$fEqModelDeployResult$fReadModelDeployResult$fShowModelDeployResult$fGenericModelDeployResult ModelDigests ModelDigests'!$sel:artifactDigest:ModelDigests'newModelDigestsmodelDigests_artifactDigest$fNFDataModelDigests$fHashableModelDigests$fFromJSONModelDigests$fEqModelDigests$fReadModelDigests$fShowModelDigests$fGenericModelDigests#ModelExplainabilityAppSpecification$ModelExplainabilityAppSpecification'5$sel:environment:ModelExplainabilityAppSpecification'2$sel:imageUri:ModelExplainabilityAppSpecification'3$sel:configUri:ModelExplainabilityAppSpecification'&newModelExplainabilityAppSpecification/modelExplainabilityAppSpecification_environment,modelExplainabilityAppSpecification_imageUri-modelExplainabilityAppSpecification_configUri+$fToJSONModelExplainabilityAppSpecification+$fNFDataModelExplainabilityAppSpecification-$fHashableModelExplainabilityAppSpecification-$fFromJSONModelExplainabilityAppSpecification'$fEqModelExplainabilityAppSpecification)$fReadModelExplainabilityAppSpecification)$fShowModelExplainabilityAppSpecification,$fGenericModelExplainabilityAppSpecificationModelInfrastructureTypeModelInfrastructureType'fromModelInfrastructureType)ModelInfrastructureType_RealTimeInference$fShowModelInfrastructureType$fReadModelInfrastructureType$fEqModelInfrastructureType$fOrdModelInfrastructureType $fGenericModelInfrastructureType!$fHashableModelInfrastructureType$fNFDataModelInfrastructureType!$fFromTextModelInfrastructureType$fToTextModelInfrastructureType%$fToByteStringModelInfrastructureType$fToLogModelInfrastructureType!$fToHeaderModelInfrastructureType $fToQueryModelInfrastructureType!$fFromJSONModelInfrastructureType$$fFromJSONKeyModelInfrastructureType$fToJSONModelInfrastructureType"$fToJSONKeyModelInfrastructureType $fFromXMLModelInfrastructureType$fToXMLModelInfrastructureType ModelInput ModelInput' $sel:dataInputConfig:ModelInput' newModelInputmodelInput_dataInputConfig$fToJSONModelInput$fNFDataModelInput$fHashableModelInput$fFromJSONModelInput$fEqModelInput$fReadModelInput$fShowModelInput$fGenericModelInputModelLatencyThresholdModelLatencyThreshold'&$sel:percentile:ModelLatencyThreshold'/$sel:valueInMilliseconds:ModelLatencyThreshold'newModelLatencyThreshold modelLatencyThreshold_percentile)modelLatencyThreshold_valueInMilliseconds$fToJSONModelLatencyThreshold$fNFDataModelLatencyThreshold$fHashableModelLatencyThreshold$fFromJSONModelLatencyThreshold$fEqModelLatencyThreshold$fReadModelLatencyThreshold$fShowModelLatencyThreshold$fGenericModelLatencyThresholdModelMetadataFilterTypeModelMetadataFilterType'fromModelMetadataFilterTypeModelMetadataFilterType_Task(ModelMetadataFilterType_FrameworkVersion!ModelMetadataFilterType_FrameworkModelMetadataFilterType_Domain$fShowModelMetadataFilterType$fReadModelMetadataFilterType$fEqModelMetadataFilterType$fOrdModelMetadataFilterType $fGenericModelMetadataFilterType!$fHashableModelMetadataFilterType$fNFDataModelMetadataFilterType!$fFromTextModelMetadataFilterType$fToTextModelMetadataFilterType%$fToByteStringModelMetadataFilterType$fToLogModelMetadataFilterType!$fToHeaderModelMetadataFilterType $fToQueryModelMetadataFilterType!$fFromJSONModelMetadataFilterType$$fFromJSONKeyModelMetadataFilterType$fToJSONModelMetadataFilterType"$fToJSONKeyModelMetadataFilterType $fFromXMLModelMetadataFilterType$fToXMLModelMetadataFilterTypeModelMetadataFilterModelMetadataFilter'$sel:name:ModelMetadataFilter'$sel:value:ModelMetadataFilter'newModelMetadataFiltermodelMetadataFilter_namemodelMetadataFilter_value$fToJSONModelMetadataFilter$fNFDataModelMetadataFilter$fHashableModelMetadataFilter$fEqModelMetadataFilter$fReadModelMetadataFilter$fShowModelMetadataFilter$fGenericModelMetadataFilterModelMetadataSearchExpressionModelMetadataSearchExpression'+$sel:filters:ModelMetadataSearchExpression' newModelMetadataSearchExpression%modelMetadataSearchExpression_filters%$fToJSONModelMetadataSearchExpression%$fNFDataModelMetadataSearchExpression'$fHashableModelMetadataSearchExpression!$fEqModelMetadataSearchExpression#$fReadModelMetadataSearchExpression#$fShowModelMetadataSearchExpression&$fGenericModelMetadataSearchExpressionModelMetadataSummaryModelMetadataSummary'!$sel:domain:ModelMetadataSummary'$$sel:framework:ModelMetadataSummary'$sel:task:ModelMetadataSummary' $sel:model:ModelMetadataSummary'+$sel:frameworkVersion:ModelMetadataSummary'newModelMetadataSummarymodelMetadataSummary_domainmodelMetadataSummary_frameworkmodelMetadataSummary_taskmodelMetadataSummary_model%modelMetadataSummary_frameworkVersion$fNFDataModelMetadataSummary$fHashableModelMetadataSummary$fFromJSONModelMetadataSummary$fEqModelMetadataSummary$fReadModelMetadataSummary$fShowModelMetadataSummary$fGenericModelMetadataSummaryModelPackageContainerDefinition ModelPackageContainerDefinition'7$sel:containerHostname:ModelPackageContainerDefinition'1$sel:environment:ModelPackageContainerDefinition'/$sel:framework:ModelPackageContainerDefinition'6$sel:frameworkVersion:ModelPackageContainerDefinition'1$sel:imageDigest:ModelPackageContainerDefinition'2$sel:modelDataUrl:ModelPackageContainerDefinition'0$sel:modelInput:ModelPackageContainerDefinition'6$sel:nearestModelName:ModelPackageContainerDefinition'/$sel:productId:ModelPackageContainerDefinition'+$sel:image:ModelPackageContainerDefinition'"newModelPackageContainerDefinition1modelPackageContainerDefinition_containerHostname+modelPackageContainerDefinition_environment)modelPackageContainerDefinition_framework0modelPackageContainerDefinition_frameworkVersion+modelPackageContainerDefinition_imageDigest,modelPackageContainerDefinition_modelDataUrl*modelPackageContainerDefinition_modelInput0modelPackageContainerDefinition_nearestModelName)modelPackageContainerDefinition_productId%modelPackageContainerDefinition_image'$fToJSONModelPackageContainerDefinition'$fNFDataModelPackageContainerDefinition)$fHashableModelPackageContainerDefinition)$fFromJSONModelPackageContainerDefinition#$fEqModelPackageContainerDefinition%$fReadModelPackageContainerDefinition%$fShowModelPackageContainerDefinition($fGenericModelPackageContainerDefinitionModelPackageGroupSortByModelPackageGroupSortBy'fromModelPackageGroupSortByModelPackageGroupSortBy_Name$ModelPackageGroupSortBy_CreationTime$fShowModelPackageGroupSortBy$fReadModelPackageGroupSortBy$fEqModelPackageGroupSortBy$fOrdModelPackageGroupSortBy $fGenericModelPackageGroupSortBy!$fHashableModelPackageGroupSortBy$fNFDataModelPackageGroupSortBy!$fFromTextModelPackageGroupSortBy$fToTextModelPackageGroupSortBy%$fToByteStringModelPackageGroupSortBy$fToLogModelPackageGroupSortBy!$fToHeaderModelPackageGroupSortBy $fToQueryModelPackageGroupSortBy!$fFromJSONModelPackageGroupSortBy$$fFromJSONKeyModelPackageGroupSortBy$fToJSONModelPackageGroupSortBy"$fToJSONKeyModelPackageGroupSortBy $fFromXMLModelPackageGroupSortBy$fToXMLModelPackageGroupSortByModelPackageGroupStatusModelPackageGroupStatus'fromModelPackageGroupStatusModelPackageGroupStatus_Pending"ModelPackageGroupStatus_InProgressModelPackageGroupStatus_Failed ModelPackageGroupStatus_Deleting$ModelPackageGroupStatus_DeleteFailed!ModelPackageGroupStatus_Completed$fShowModelPackageGroupStatus$fReadModelPackageGroupStatus$fEqModelPackageGroupStatus$fOrdModelPackageGroupStatus $fGenericModelPackageGroupStatus!$fHashableModelPackageGroupStatus$fNFDataModelPackageGroupStatus!$fFromTextModelPackageGroupStatus$fToTextModelPackageGroupStatus%$fToByteStringModelPackageGroupStatus$fToLogModelPackageGroupStatus!$fToHeaderModelPackageGroupStatus $fToQueryModelPackageGroupStatus!$fFromJSONModelPackageGroupStatus$$fFromJSONKeyModelPackageGroupStatus$fToJSONModelPackageGroupStatus"$fToJSONKeyModelPackageGroupStatus $fFromXMLModelPackageGroupStatus$fToXMLModelPackageGroupStatusModelPackageGroupSummaryModelPackageGroupSummary';$sel:modelPackageGroupDescription:ModelPackageGroupSummary'4$sel:modelPackageGroupName:ModelPackageGroupSummary'3$sel:modelPackageGroupArn:ModelPackageGroupSummary'+$sel:creationTime:ModelPackageGroupSummary'6$sel:modelPackageGroupStatus:ModelPackageGroupSummary'newModelPackageGroupSummary5modelPackageGroupSummary_modelPackageGroupDescription.modelPackageGroupSummary_modelPackageGroupName-modelPackageGroupSummary_modelPackageGroupArn%modelPackageGroupSummary_creationTime0modelPackageGroupSummary_modelPackageGroupStatus $fNFDataModelPackageGroupSummary"$fHashableModelPackageGroupSummary"$fFromJSONModelPackageGroupSummary$fEqModelPackageGroupSummary$fReadModelPackageGroupSummary$fShowModelPackageGroupSummary!$fGenericModelPackageGroupSummaryModelPackageSortByModelPackageSortBy'fromModelPackageSortByModelPackageSortBy_NameModelPackageSortBy_CreationTime$fShowModelPackageSortBy$fReadModelPackageSortBy$fEqModelPackageSortBy$fOrdModelPackageSortBy$fGenericModelPackageSortBy$fHashableModelPackageSortBy$fNFDataModelPackageSortBy$fFromTextModelPackageSortBy$fToTextModelPackageSortBy $fToByteStringModelPackageSortBy$fToLogModelPackageSortBy$fToHeaderModelPackageSortBy$fToQueryModelPackageSortBy$fFromJSONModelPackageSortBy$fFromJSONKeyModelPackageSortBy$fToJSONModelPackageSortBy$fToJSONKeyModelPackageSortBy$fFromXMLModelPackageSortBy$fToXMLModelPackageSortByModelPackageStatusModelPackageStatus'fromModelPackageStatusModelPackageStatus_PendingModelPackageStatus_InProgressModelPackageStatus_FailedModelPackageStatus_DeletingModelPackageStatus_Completed$fShowModelPackageStatus$fReadModelPackageStatus$fEqModelPackageStatus$fOrdModelPackageStatus$fGenericModelPackageStatus$fHashableModelPackageStatus$fNFDataModelPackageStatus$fFromTextModelPackageStatus$fToTextModelPackageStatus $fToByteStringModelPackageStatus$fToLogModelPackageStatus$fToHeaderModelPackageStatus$fToQueryModelPackageStatus$fFromJSONModelPackageStatus$fFromJSONKeyModelPackageStatus$fToJSONModelPackageStatus$fToJSONKeyModelPackageStatus$fFromXMLModelPackageStatus$fToXMLModelPackageStatusModelPackageStatusItemModelPackageStatusItem'*$sel:failureReason:ModelPackageStatusItem'!$sel:name:ModelPackageStatusItem'#$sel:status:ModelPackageStatusItem'newModelPackageStatusItem$modelPackageStatusItem_failureReasonmodelPackageStatusItem_namemodelPackageStatusItem_status$fNFDataModelPackageStatusItem $fHashableModelPackageStatusItem $fFromJSONModelPackageStatusItem$fEqModelPackageStatusItem$fReadModelPackageStatusItem$fShowModelPackageStatusItem$fGenericModelPackageStatusItemModelPackageStatusDetailsModelPackageStatusDetails'1$sel:imageScanStatuses:ModelPackageStatusDetails'2$sel:validationStatuses:ModelPackageStatusDetails'newModelPackageStatusDetails+modelPackageStatusDetails_imageScanStatuses,modelPackageStatusDetails_validationStatuses!$fNFDataModelPackageStatusDetails#$fHashableModelPackageStatusDetails#$fFromJSONModelPackageStatusDetails$fEqModelPackageStatusDetails$fReadModelPackageStatusDetails$fShowModelPackageStatusDetails"$fGenericModelPackageStatusDetailsModelPackageSummaryModelPackageSummary'-$sel:modelApprovalStatus:ModelPackageSummary'1$sel:modelPackageDescription:ModelPackageSummary'/$sel:modelPackageGroupName:ModelPackageSummary'-$sel:modelPackageVersion:ModelPackageSummary'*$sel:modelPackageName:ModelPackageSummary')$sel:modelPackageArn:ModelPackageSummary'&$sel:creationTime:ModelPackageSummary',$sel:modelPackageStatus:ModelPackageSummary'newModelPackageSummary'modelPackageSummary_modelApprovalStatus+modelPackageSummary_modelPackageDescription)modelPackageSummary_modelPackageGroupName'modelPackageSummary_modelPackageVersion$modelPackageSummary_modelPackageName#modelPackageSummary_modelPackageArn modelPackageSummary_creationTime&modelPackageSummary_modelPackageStatus$fNFDataModelPackageSummary$fHashableModelPackageSummary$fFromJSONModelPackageSummary$fEqModelPackageSummary$fReadModelPackageSummary$fShowModelPackageSummary$fGenericModelPackageSummaryModelPackageTypeModelPackageType'fromModelPackageTypeModelPackageType_VersionedModelPackageType_UnversionedModelPackageType_Both$fShowModelPackageType$fReadModelPackageType$fEqModelPackageType$fOrdModelPackageType$fGenericModelPackageType$fHashableModelPackageType$fNFDataModelPackageType$fFromTextModelPackageType$fToTextModelPackageType$fToByteStringModelPackageType$fToLogModelPackageType$fToHeaderModelPackageType$fToQueryModelPackageType$fFromJSONModelPackageType$fFromJSONKeyModelPackageType$fToJSONModelPackageType$fToJSONKeyModelPackageType$fFromXMLModelPackageType$fToXMLModelPackageType ModelQuality ModelQuality'$sel:constraints:ModelQuality'$sel:statistics:ModelQuality'newModelQualitymodelQuality_constraintsmodelQuality_statistics$fToJSONModelQuality$fNFDataModelQuality$fHashableModelQuality$fFromJSONModelQuality$fEqModelQuality$fReadModelQuality$fShowModelQuality$fGenericModelQuality ModelMetrics ModelMetrics'$sel:bias:ModelMetrics'!$sel:explainability:ModelMetrics'#$sel:modelDataQuality:ModelMetrics'$sel:modelQuality:ModelMetrics'newModelMetricsmodelMetrics_biasmodelMetrics_explainabilitymodelMetrics_modelDataQualitymodelMetrics_modelQuality$fToJSONModelMetrics$fNFDataModelMetrics$fHashableModelMetrics$fFromJSONModelMetrics$fEqModelMetrics$fReadModelMetrics$fShowModelMetrics$fGenericModelMetrics ModelSortKey ModelSortKey'fromModelSortKeyModelSortKey_NameModelSortKey_CreationTime$fShowModelSortKey$fReadModelSortKey$fEqModelSortKey$fOrdModelSortKey$fGenericModelSortKey$fHashableModelSortKey$fNFDataModelSortKey$fFromTextModelSortKey$fToTextModelSortKey$fToByteStringModelSortKey$fToLogModelSortKey$fToHeaderModelSortKey$fToQueryModelSortKey$fFromJSONModelSortKey$fFromJSONKeyModelSortKey$fToJSONModelSortKey$fToJSONKeyModelSortKey$fFromXMLModelSortKey$fToXMLModelSortKeyModelStepMetadataModelStepMetadata'$sel:arn:ModelStepMetadata'newModelStepMetadatamodelStepMetadata_arn$fNFDataModelStepMetadata$fHashableModelStepMetadata$fFromJSONModelStepMetadata$fEqModelStepMetadata$fReadModelStepMetadata$fShowModelStepMetadata$fGenericModelStepMetadata ModelSummary ModelSummary'$sel:modelName:ModelSummary'$sel:modelArn:ModelSummary'$sel:creationTime:ModelSummary'newModelSummarymodelSummary_modelNamemodelSummary_modelArnmodelSummary_creationTime$fNFDataModelSummary$fHashableModelSummary$fFromJSONModelSummary$fEqModelSummary$fReadModelSummary$fShowModelSummary$fGenericModelSummaryModelVariantActionModelVariantAction'fromModelVariantActionModelVariantAction_RetainModelVariantAction_RemoveModelVariantAction_Promote$fShowModelVariantAction$fReadModelVariantAction$fEqModelVariantAction$fOrdModelVariantAction$fGenericModelVariantAction$fHashableModelVariantAction$fNFDataModelVariantAction$fFromTextModelVariantAction$fToTextModelVariantAction $fToByteStringModelVariantAction$fToLogModelVariantAction$fToHeaderModelVariantAction$fToQueryModelVariantAction$fFromJSONModelVariantAction$fFromJSONKeyModelVariantAction$fToJSONModelVariantAction$fToJSONKeyModelVariantAction$fFromXMLModelVariantAction$fToXMLModelVariantActionModelVariantStatusModelVariantStatus'fromModelVariantStatusModelVariantStatus_UpdatingModelVariantStatus_InServiceModelVariantStatus_DeletingModelVariantStatus_DeletedModelVariantStatus_Creating$fShowModelVariantStatus$fReadModelVariantStatus$fEqModelVariantStatus$fOrdModelVariantStatus$fGenericModelVariantStatus$fHashableModelVariantStatus$fNFDataModelVariantStatus$fFromTextModelVariantStatus$fToTextModelVariantStatus $fToByteStringModelVariantStatus$fToLogModelVariantStatus$fToHeaderModelVariantStatus$fToQueryModelVariantStatus$fFromJSONModelVariantStatus$fFromJSONKeyModelVariantStatus$fToJSONModelVariantStatus$fToJSONKeyModelVariantStatus$fFromXMLModelVariantStatus$fToXMLModelVariantStatusMonitoringAlertActionsMonitoringAlertActions'4$sel:modelDashboardIndicator:MonitoringAlertActions'newMonitoringAlertActions.monitoringAlertActions_modelDashboardIndicator$fNFDataMonitoringAlertActions $fHashableMonitoringAlertActions $fFromJSONMonitoringAlertActions$fEqMonitoringAlertActions$fReadMonitoringAlertActions$fShowMonitoringAlertActions$fGenericMonitoringAlertActionsMonitoringAlertHistorySortKeyMonitoringAlertHistorySortKey'!fromMonitoringAlertHistorySortKey$MonitoringAlertHistorySortKey_Status*MonitoringAlertHistorySortKey_CreationTime#$fShowMonitoringAlertHistorySortKey#$fReadMonitoringAlertHistorySortKey!$fEqMonitoringAlertHistorySortKey"$fOrdMonitoringAlertHistorySortKey&$fGenericMonitoringAlertHistorySortKey'$fHashableMonitoringAlertHistorySortKey%$fNFDataMonitoringAlertHistorySortKey'$fFromTextMonitoringAlertHistorySortKey%$fToTextMonitoringAlertHistorySortKey+$fToByteStringMonitoringAlertHistorySortKey$$fToLogMonitoringAlertHistorySortKey'$fToHeaderMonitoringAlertHistorySortKey&$fToQueryMonitoringAlertHistorySortKey'$fFromJSONMonitoringAlertHistorySortKey*$fFromJSONKeyMonitoringAlertHistorySortKey%$fToJSONMonitoringAlertHistorySortKey($fToJSONKeyMonitoringAlertHistorySortKey&$fFromXMLMonitoringAlertHistorySortKey$$fToXMLMonitoringAlertHistorySortKeyMonitoringAlertStatusMonitoringAlertStatus'fromMonitoringAlertStatusMonitoringAlertStatus_OKMonitoringAlertStatus_InAlert$fShowMonitoringAlertStatus$fReadMonitoringAlertStatus$fEqMonitoringAlertStatus$fOrdMonitoringAlertStatus$fGenericMonitoringAlertStatus$fHashableMonitoringAlertStatus$fNFDataMonitoringAlertStatus$fFromTextMonitoringAlertStatus$fToTextMonitoringAlertStatus#$fToByteStringMonitoringAlertStatus$fToLogMonitoringAlertStatus$fToHeaderMonitoringAlertStatus$fToQueryMonitoringAlertStatus$fFromJSONMonitoringAlertStatus"$fFromJSONKeyMonitoringAlertStatus$fToJSONMonitoringAlertStatus $fToJSONKeyMonitoringAlertStatus$fFromXMLMonitoringAlertStatus$fToXMLMonitoringAlertStatusMonitoringAlertHistorySummaryMonitoringAlertHistorySummary':$sel:monitoringScheduleName:MonitoringAlertHistorySummary'7$sel:monitoringAlertName:MonitoringAlertHistorySummary'0$sel:creationTime:MonitoringAlertHistorySummary'/$sel:alertStatus:MonitoringAlertHistorySummary' newMonitoringAlertHistorySummary4monitoringAlertHistorySummary_monitoringScheduleName1monitoringAlertHistorySummary_monitoringAlertName*monitoringAlertHistorySummary_creationTime)monitoringAlertHistorySummary_alertStatus%$fNFDataMonitoringAlertHistorySummary'$fHashableMonitoringAlertHistorySummary'$fFromJSONMonitoringAlertHistorySummary!$fEqMonitoringAlertHistorySummary#$fReadMonitoringAlertHistorySummary#$fShowMonitoringAlertHistorySummary&$fGenericMonitoringAlertHistorySummaryMonitoringAlertSummaryMonitoringAlertSummary'0$sel:monitoringAlertName:MonitoringAlertSummary')$sel:creationTime:MonitoringAlertSummary'-$sel:lastModifiedTime:MonitoringAlertSummary'($sel:alertStatus:MonitoringAlertSummary'.$sel:datapointsToAlert:MonitoringAlertSummary'-$sel:evaluationPeriod:MonitoringAlertSummary'$$sel:actions:MonitoringAlertSummary'newMonitoringAlertSummary*monitoringAlertSummary_monitoringAlertName#monitoringAlertSummary_creationTime'monitoringAlertSummary_lastModifiedTime"monitoringAlertSummary_alertStatus(monitoringAlertSummary_datapointsToAlert'monitoringAlertSummary_evaluationPeriodmonitoringAlertSummary_actions$fNFDataMonitoringAlertSummary $fHashableMonitoringAlertSummary $fFromJSONMonitoringAlertSummary$fEqMonitoringAlertSummary$fReadMonitoringAlertSummary$fShowMonitoringAlertSummary$fGenericMonitoringAlertSummaryMonitoringAppSpecificationMonitoringAppSpecification'3$sel:containerArguments:MonitoringAppSpecification'4$sel:containerEntrypoint:MonitoringAppSpecification'$sel:postAnalyticsProcessorSourceUri:MonitoringAppSpecification'<$sel:recordPreprocessorSourceUri:MonitoringAppSpecification')$sel:imageUri:MonitoringAppSpecification'newMonitoringAppSpecification-monitoringAppSpecification_containerArguments.monitoringAppSpecification_containerEntrypoint:monitoringAppSpecification_postAnalyticsProcessorSourceUri6monitoringAppSpecification_recordPreprocessorSourceUri#monitoringAppSpecification_imageUri"$fToJSONMonitoringAppSpecification"$fNFDataMonitoringAppSpecification$$fHashableMonitoringAppSpecification$$fFromJSONMonitoringAppSpecification$fEqMonitoringAppSpecification $fReadMonitoringAppSpecification $fShowMonitoringAppSpecification#$fGenericMonitoringAppSpecificationMonitoringConstraintsResourceMonitoringConstraintsResource')$sel:s3Uri:MonitoringConstraintsResource' newMonitoringConstraintsResource#monitoringConstraintsResource_s3Uri%$fToJSONMonitoringConstraintsResource%$fNFDataMonitoringConstraintsResource'$fHashableMonitoringConstraintsResource'$fFromJSONMonitoringConstraintsResource!$fEqMonitoringConstraintsResource#$fReadMonitoringConstraintsResource#$fShowMonitoringConstraintsResource&$fGenericMonitoringConstraintsResourceModelQualityBaselineConfigModelQualityBaselineConfig'2$sel:baseliningJobName:ModelQualityBaselineConfig'4$sel:constraintsResource:ModelQualityBaselineConfig'newModelQualityBaselineConfig,modelQualityBaselineConfig_baseliningJobName.modelQualityBaselineConfig_constraintsResource"$fToJSONModelQualityBaselineConfig"$fNFDataModelQualityBaselineConfig$$fHashableModelQualityBaselineConfig$$fFromJSONModelQualityBaselineConfig$fEqModelQualityBaselineConfig $fReadModelQualityBaselineConfig $fShowModelQualityBaselineConfig#$fGenericModelQualityBaselineConfig!ModelExplainabilityBaselineConfig"ModelExplainabilityBaselineConfig'9$sel:baseliningJobName:ModelExplainabilityBaselineConfig';$sel:constraintsResource:ModelExplainabilityBaselineConfig'$newModelExplainabilityBaselineConfig3modelExplainabilityBaselineConfig_baseliningJobName5modelExplainabilityBaselineConfig_constraintsResource)$fToJSONModelExplainabilityBaselineConfig)$fNFDataModelExplainabilityBaselineConfig+$fHashableModelExplainabilityBaselineConfig+$fFromJSONModelExplainabilityBaselineConfig%$fEqModelExplainabilityBaselineConfig'$fReadModelExplainabilityBaselineConfig'$fShowModelExplainabilityBaselineConfig*$fGenericModelExplainabilityBaselineConfigModelBiasBaselineConfigModelBiasBaselineConfig'/$sel:baseliningJobName:ModelBiasBaselineConfig'1$sel:constraintsResource:ModelBiasBaselineConfig'newModelBiasBaselineConfig)modelBiasBaselineConfig_baseliningJobName+modelBiasBaselineConfig_constraintsResource$fToJSONModelBiasBaselineConfig$fNFDataModelBiasBaselineConfig!$fHashableModelBiasBaselineConfig!$fFromJSONModelBiasBaselineConfig$fEqModelBiasBaselineConfig$fReadModelBiasBaselineConfig$fShowModelBiasBaselineConfig $fGenericModelBiasBaselineConfigMonitoringCsvDatasetFormatMonitoringCsvDatasetFormat''$sel:header:MonitoringCsvDatasetFormat'newMonitoringCsvDatasetFormat!monitoringCsvDatasetFormat_header"$fToJSONMonitoringCsvDatasetFormat"$fNFDataMonitoringCsvDatasetFormat$$fHashableMonitoringCsvDatasetFormat$$fFromJSONMonitoringCsvDatasetFormat$fEqMonitoringCsvDatasetFormat $fReadMonitoringCsvDatasetFormat $fShowMonitoringCsvDatasetFormat#$fGenericMonitoringCsvDatasetFormatMonitoringExecutionSortKeyMonitoringExecutionSortKey'fromMonitoringExecutionSortKey!MonitoringExecutionSortKey_Status(MonitoringExecutionSortKey_ScheduledTime'MonitoringExecutionSortKey_CreationTime $fShowMonitoringExecutionSortKey $fReadMonitoringExecutionSortKey$fEqMonitoringExecutionSortKey$fOrdMonitoringExecutionSortKey#$fGenericMonitoringExecutionSortKey$$fHashableMonitoringExecutionSortKey"$fNFDataMonitoringExecutionSortKey$$fFromTextMonitoringExecutionSortKey"$fToTextMonitoringExecutionSortKey($fToByteStringMonitoringExecutionSortKey!$fToLogMonitoringExecutionSortKey$$fToHeaderMonitoringExecutionSortKey#$fToQueryMonitoringExecutionSortKey$$fFromJSONMonitoringExecutionSortKey'$fFromJSONKeyMonitoringExecutionSortKey"$fToJSONMonitoringExecutionSortKey%$fToJSONKeyMonitoringExecutionSortKey#$fFromXMLMonitoringExecutionSortKey!$fToXMLMonitoringExecutionSortKeyMonitoringGroundTruthS3InputMonitoringGroundTruthS3Input'($sel:s3Uri:MonitoringGroundTruthS3Input'newMonitoringGroundTruthS3Input"monitoringGroundTruthS3Input_s3Uri$$fToJSONMonitoringGroundTruthS3Input$$fNFDataMonitoringGroundTruthS3Input&$fHashableMonitoringGroundTruthS3Input&$fFromJSONMonitoringGroundTruthS3Input $fEqMonitoringGroundTruthS3Input"$fReadMonitoringGroundTruthS3Input"$fShowMonitoringGroundTruthS3Input%$fGenericMonitoringGroundTruthS3InputMonitoringJobDefinitionSortKeyMonitoringJobDefinitionSortKey'"fromMonitoringJobDefinitionSortKey#MonitoringJobDefinitionSortKey_Name+MonitoringJobDefinitionSortKey_CreationTime$$fShowMonitoringJobDefinitionSortKey$$fReadMonitoringJobDefinitionSortKey"$fEqMonitoringJobDefinitionSortKey#$fOrdMonitoringJobDefinitionSortKey'$fGenericMonitoringJobDefinitionSortKey($fHashableMonitoringJobDefinitionSortKey&$fNFDataMonitoringJobDefinitionSortKey($fFromTextMonitoringJobDefinitionSortKey&$fToTextMonitoringJobDefinitionSortKey,$fToByteStringMonitoringJobDefinitionSortKey%$fToLogMonitoringJobDefinitionSortKey($fToHeaderMonitoringJobDefinitionSortKey'$fToQueryMonitoringJobDefinitionSortKey($fFromJSONMonitoringJobDefinitionSortKey+$fFromJSONKeyMonitoringJobDefinitionSortKey&$fToJSONMonitoringJobDefinitionSortKey)$fToJSONKeyMonitoringJobDefinitionSortKey'$fFromXMLMonitoringJobDefinitionSortKey%$fToXMLMonitoringJobDefinitionSortKeyMonitoringJobDefinitionSummaryMonitoringJobDefinitionSummary'$sel:monitoringJobDefinitionName:MonitoringJobDefinitionSummary'?$sel:monitoringJobDefinitionArn:MonitoringJobDefinitionSummary'1$sel:creationTime:MonitoringJobDefinitionSummary'1$sel:endpointName:MonitoringJobDefinitionSummary'!newMonitoringJobDefinitionSummary:monitoringJobDefinitionSummary_monitoringJobDefinitionName9monitoringJobDefinitionSummary_monitoringJobDefinitionArn+monitoringJobDefinitionSummary_creationTime+monitoringJobDefinitionSummary_endpointName&$fNFDataMonitoringJobDefinitionSummary($fHashableMonitoringJobDefinitionSummary($fFromJSONMonitoringJobDefinitionSummary"$fEqMonitoringJobDefinitionSummary$$fReadMonitoringJobDefinitionSummary$$fShowMonitoringJobDefinitionSummary'$fGenericMonitoringJobDefinitionSummaryMonitoringJsonDatasetFormatMonitoringJsonDatasetFormat'&$sel:line:MonitoringJsonDatasetFormat'newMonitoringJsonDatasetFormat monitoringJsonDatasetFormat_line#$fToJSONMonitoringJsonDatasetFormat#$fNFDataMonitoringJsonDatasetFormat%$fHashableMonitoringJsonDatasetFormat%$fFromJSONMonitoringJsonDatasetFormat$fEqMonitoringJsonDatasetFormat!$fReadMonitoringJsonDatasetFormat!$fShowMonitoringJsonDatasetFormat$$fGenericMonitoringJsonDatasetFormatMonitoringParquetDatasetFormatMonitoringParquetDatasetFormat'!newMonitoringParquetDatasetFormat&$fToJSONMonitoringParquetDatasetFormat&$fNFDataMonitoringParquetDatasetFormat($fHashableMonitoringParquetDatasetFormat($fFromJSONMonitoringParquetDatasetFormat"$fEqMonitoringParquetDatasetFormat$$fReadMonitoringParquetDatasetFormat$$fShowMonitoringParquetDatasetFormat'$fGenericMonitoringParquetDatasetFormatMonitoringDatasetFormatMonitoringDatasetFormat'!$sel:csv:MonitoringDatasetFormat'"$sel:json:MonitoringDatasetFormat'%$sel:parquet:MonitoringDatasetFormat'newMonitoringDatasetFormatmonitoringDatasetFormat_csvmonitoringDatasetFormat_jsonmonitoringDatasetFormat_parquet$fToJSONMonitoringDatasetFormat$fNFDataMonitoringDatasetFormat!$fHashableMonitoringDatasetFormat!$fFromJSONMonitoringDatasetFormat$fEqMonitoringDatasetFormat$fReadMonitoringDatasetFormat$fShowMonitoringDatasetFormat $fGenericMonitoringDatasetFormatMonitoringProblemTypeMonitoringProblemType'fromMonitoringProblemType MonitoringProblemType_Regression.MonitoringProblemType_MulticlassClassification*MonitoringProblemType_BinaryClassification$fShowMonitoringProblemType$fReadMonitoringProblemType$fEqMonitoringProblemType$fOrdMonitoringProblemType$fGenericMonitoringProblemType$fHashableMonitoringProblemType$fNFDataMonitoringProblemType$fFromTextMonitoringProblemType$fToTextMonitoringProblemType#$fToByteStringMonitoringProblemType$fToLogMonitoringProblemType$fToHeaderMonitoringProblemType$fToQueryMonitoringProblemType$fFromJSONMonitoringProblemType"$fFromJSONKeyMonitoringProblemType$fToJSONMonitoringProblemType $fToJSONKeyMonitoringProblemType$fFromXMLMonitoringProblemType$fToXMLMonitoringProblemTypeModelQualityAppSpecificationModelQualityAppSpecification'5$sel:containerArguments:ModelQualityAppSpecification'6$sel:containerEntrypoint:ModelQualityAppSpecification'.$sel:environment:ModelQualityAppSpecification'$sel:postAnalyticsProcessorSourceUri:ModelQualityAppSpecification'.$sel:problemType:ModelQualityAppSpecification'>$sel:recordPreprocessorSourceUri:ModelQualityAppSpecification'+$sel:imageUri:ModelQualityAppSpecification'newModelQualityAppSpecification/modelQualityAppSpecification_containerArguments0modelQualityAppSpecification_containerEntrypoint(modelQualityAppSpecification_environmentrStudioServerProDomainSettingsForUpdate_domainExecutionRoleArn/$fToJSONRStudioServerProDomainSettingsForUpdate/$fNFDataRStudioServerProDomainSettingsForUpdate1$fHashableRStudioServerProDomainSettingsForUpdate+$fEqRStudioServerProDomainSettingsForUpdate-$fReadRStudioServerProDomainSettingsForUpdate-$fShowRStudioServerProDomainSettingsForUpdate0$fGenericRStudioServerProDomainSettingsForUpdateDomainSettingsForUpdateDomainSettingsForUpdate'9$sel:executionRoleIdentityConfig:DomainSettingsForUpdate'$sel:rStudioServerProDomainSettingsForUpdate:DomainSettingsForUpdate'.$sel:securityGroupIds:DomainSettingsForUpdate'newDomainSettingsForUpdate3domainSettingsForUpdate_executionRoleIdentityConfig?domainSettingsForUpdate_rStudioServerProDomainSettingsForUpdate(domainSettingsForUpdate_securityGroupIds$fToJSONDomainSettingsForUpdate$fNFDataDomainSettingsForUpdate!$fHashableDomainSettingsForUpdate$fEqDomainSettingsForUpdate$fReadDomainSettingsForUpdate$fShowDomainSettingsForUpdate $fGenericDomainSettingsForUpdateRStudioServerProDomainSettingsRStudioServerProDomainSettings'8$sel:defaultResourceSpec:RStudioServerProDomainSettings'6$sel:rStudioConnectUrl:RStudioServerProDomainSettings'=$sel:rStudioPackageManagerUrl:RStudioServerProDomainSettings';$sel:domainExecutionRoleArn:RStudioServerProDomainSettings'!newRStudioServerProDomainSettings2rStudioServerProDomainSettings_defaultResourceSpec0rStudioServerProDomainSettings_rStudioConnectUrl7rStudioServerProDomainSettings_rStudioPackageManagerUrl5rStudioServerProDomainSettings_domainExecutionRoleArn&$fToJSONRStudioServerProDomainSettings&$fNFDataRStudioServerProDomainSettings($fHashableRStudioServerProDomainSettings($fFromJSONRStudioServerProDomainSettings"$fEqRStudioServerProDomainSettings$$fReadRStudioServerProDomainSettings$$fShowRStudioServerProDomainSettings'$fGenericRStudioServerProDomainSettingsDomainSettingsDomainSettings'0$sel:executionRoleIdentityConfig:DomainSettings'3$sel:rStudioServerProDomainSettings:DomainSettings'%$sel:securityGroupIds:DomainSettings'newDomainSettings*domainSettings_executionRoleIdentityConfig-domainSettings_rStudioServerProDomainSettingsdomainSettings_securityGroupIds$fToJSONDomainSettings$fNFDataDomainSettings$fHashableDomainSettings$fFromJSONDomainSettings$fEqDomainSettings$fReadDomainSettings$fShowDomainSettings$fGenericDomainSettingsRSessionAppSettingsRSessionAppSettings'&$sel:customImages:RSessionAppSettings'-$sel:defaultResourceSpec:RSessionAppSettings'newRSessionAppSettings rSessionAppSettings_customImages'rSessionAppSettings_defaultResourceSpec$fToJSONRSessionAppSettings$fNFDataRSessionAppSettings$fHashableRSessionAppSettings$fFromJSONRSessionAppSettings$fEqRSessionAppSettings$fReadRSessionAppSettings$fShowRSessionAppSettings$fGenericRSessionAppSettingsKernelGatewayAppSettingsKernelGatewayAppSettings'+$sel:customImages:KernelGatewayAppSettings'2$sel:defaultResourceSpec:KernelGatewayAppSettings'2$sel:lifecycleConfigArns:KernelGatewayAppSettings'newKernelGatewayAppSettings%kernelGatewayAppSettings_customImages,kernelGatewayAppSettings_defaultResourceSpec,kernelGatewayAppSettings_lifecycleConfigArns $fToJSONKernelGatewayAppSettings $fNFDataKernelGatewayAppSettings"$fHashableKernelGatewayAppSettings"$fFromJSONKernelGatewayAppSettings$fEqKernelGatewayAppSettings$fReadKernelGatewayAppSettings$fShowKernelGatewayAppSettings!$fGenericKernelGatewayAppSettingsJupyterServerAppSettingsJupyterServerAppSettings'/$sel:codeRepositories:JupyterServerAppSettings'2$sel:defaultResourceSpec:JupyterServerAppSettings'2$sel:lifecycleConfigArns:JupyterServerAppSettings'newJupyterServerAppSettings)jupyterServerAppSettings_codeRepositories,jupyterServerAppSettings_defaultResourceSpec,jupyterServerAppSettings_lifecycleConfigArns $fToJSONJupyterServerAppSettings $fNFDataJupyterServerAppSettings"$fHashableJupyterServerAppSettings"$fFromJSONJupyterServerAppSettings$fEqJupyterServerAppSettings$fReadJupyterServerAppSettings$fShowJupyterServerAppSettings!$fGenericJupyterServerAppSettingsDefaultSpaceSettingsDefaultSpaceSettings'($sel:executionRole:DefaultSpaceSettings'3$sel:jupyterServerAppSettings:DefaultSpaceSettings'3$sel:kernelGatewayAppSettings:DefaultSpaceSettings')$sel:securityGroups:DefaultSpaceSettings'newDefaultSpaceSettings"defaultSpaceSettings_executionRole-defaultSpaceSettings_jupyterServerAppSettings-defaultSpaceSettings_kernelGatewayAppSettings#defaultSpaceSettings_securityGroups$fToJSONDefaultSpaceSettings$fNFDataDefaultSpaceSettings$fHashableDefaultSpaceSettings$fFromJSONDefaultSpaceSettings$fEqDefaultSpaceSettings$fReadDefaultSpaceSettings$fShowDefaultSpaceSettings$fGenericDefaultSpaceSettings ResourceType ResourceType'fromResourceTypeResourceType_TrainingJobResourceType_ProjectResourceType_PipelineExecutionResourceType_PipelineResourceType_ModelPackageGroupResourceType_ModelPackageResourceType_ModelCardResourceType_Model$ResourceType_HyperParameterTuningJobResourceType_FeatureMetadataResourceType_FeatureGroup%ResourceType_ExperimentTrialComponentResourceType_ExperimentTrialResourceType_ExperimentResourceType_Endpoint$fShowResourceType$fReadResourceType$fEqResourceType$fOrdResourceType$fGenericResourceType$fHashableResourceType$fNFDataResourceType$fFromTextResourceType$fToTextResourceType$fToByteStringResourceType$fToLogResourceType$fToHeaderResourceType$fToQueryResourceType$fFromJSONResourceType$fFromJSONKeyResourceType$fToJSONResourceType$fToJSONKeyResourceType$fFromXMLResourceType$fToXMLResourceType RetentionTypeRetentionType'fromRetentionTypeRetentionType_RetainRetentionType_Delete$fShowRetentionType$fReadRetentionType$fEqRetentionType$fOrdRetentionType$fGenericRetentionType$fHashableRetentionType$fNFDataRetentionType$fFromTextRetentionType$fToTextRetentionType$fToByteStringRetentionType$fToLogRetentionType$fToHeaderRetentionType$fToQueryRetentionType$fFromJSONRetentionType$fFromJSONKeyRetentionType$fToJSONRetentionType$fToJSONKeyRetentionType$fFromXMLRetentionType$fToXMLRetentionTypeRetentionPolicyRetentionPolicy''$sel:homeEfsFileSystem:RetentionPolicy'newRetentionPolicy!retentionPolicy_homeEfsFileSystem$fToJSONRetentionPolicy$fNFDataRetentionPolicy$fHashableRetentionPolicy$fEqRetentionPolicy$fReadRetentionPolicy$fShowRetentionPolicy$fGenericRetentionPolicy RetryStrategyRetryStrategy'($sel:maximumRetryAttempts:RetryStrategy'newRetryStrategy"retryStrategy_maximumRetryAttempts$fToJSONRetryStrategy$fNFDataRetryStrategy$fHashableRetryStrategy$fFromJSONRetryStrategy$fEqRetryStrategy$fReadRetryStrategy$fShowRetryStrategy$fGenericRetryStrategy RootAccess RootAccess'fromRootAccessRootAccess_EnabledRootAccess_Disabled$fShowRootAccess$fReadRootAccess$fEqRootAccess$fOrdRootAccess$fGenericRootAccess$fHashableRootAccess$fNFDataRootAccess$fFromTextRootAccess$fToTextRootAccess$fToByteStringRootAccess$fToLogRootAccess$fToHeaderRootAccess$fToQueryRootAccess$fFromJSONRootAccess$fFromJSONKeyRootAccess$fToJSONRootAccess$fToJSONKeyRootAccess$fFromXMLRootAccess$fToXMLRootAccessRuleEvaluationStatusRuleEvaluationStatus'fromRuleEvaluationStatusRuleEvaluationStatus_StoppingRuleEvaluationStatus_Stopped"RuleEvaluationStatus_NoIssuesFound RuleEvaluationStatus_IssuesFoundRuleEvaluationStatus_InProgressRuleEvaluationStatus_Error$fShowRuleEvaluationStatus$fReadRuleEvaluationStatus$fEqRuleEvaluationStatus$fOrdRuleEvaluationStatus$fGenericRuleEvaluationStatus$fHashableRuleEvaluationStatus$fNFDataRuleEvaluationStatus$fFromTextRuleEvaluationStatus$fToTextRuleEvaluationStatus"$fToByteStringRuleEvaluationStatus$fToLogRuleEvaluationStatus$fToHeaderRuleEvaluationStatus$fToQueryRuleEvaluationStatus$fFromJSONRuleEvaluationStatus!$fFromJSONKeyRuleEvaluationStatus$fToJSONRuleEvaluationStatus$fToJSONKeyRuleEvaluationStatus$fFromXMLRuleEvaluationStatus$fToXMLRuleEvaluationStatusProfilerRuleEvaluationStatusProfilerRuleEvaluationStatus'3$sel:lastModifiedTime:ProfilerRuleEvaluationStatus'8$sel:ruleConfigurationName:ProfilerRuleEvaluationStatus'7$sel:ruleEvaluationJobArn:ProfilerRuleEvaluationStatus'7$sel:ruleEvaluationStatus:ProfilerRuleEvaluationStatus'0$sel:statusDetails:ProfilerRuleEvaluationStatus'newProfilerRuleEvaluationStatus-profilerRuleEvaluationStatus_lastModifiedTime2profilerRuleEvaluationStatus_ruleConfigurationName1profilerRuleEvaluationStatus_ruleEvaluationJobArn1profilerRuleEvaluationStatus_ruleEvaluationStatus*profilerRuleEvaluationStatus_statusDetails$$fNFDataProfilerRuleEvaluationStatus&$fHashableProfilerRuleEvaluationStatus&$fFromJSONProfilerRuleEvaluationStatus $fEqProfilerRuleEvaluationStatus"$fReadProfilerRuleEvaluationStatus"$fShowProfilerRuleEvaluationStatus%$fGenericProfilerRuleEvaluationStatusDebugRuleEvaluationStatusDebugRuleEvaluationStatus'0$sel:lastModifiedTime:DebugRuleEvaluationStatus'5$sel:ruleConfigurationName:DebugRuleEvaluationStatus'4$sel:ruleEvaluationJobArn:DebugRuleEvaluationStatus'4$sel:ruleEvaluationStatus:DebugRuleEvaluationStatus'-$sel:statusDetails:DebugRuleEvaluationStatus'newDebugRuleEvaluationStatus*debugRuleEvaluationStatus_lastModifiedTime/debugRuleEvaluationStatus_ruleConfigurationName.debugRuleEvaluationStatus_ruleEvaluationJobArn.debugRuleEvaluationStatus_ruleEvaluationStatus'debugRuleEvaluationStatus_statusDetails!$fNFDataDebugRuleEvaluationStatus#$fHashableDebugRuleEvaluationStatus#$fFromJSONDebugRuleEvaluationStatus$fEqDebugRuleEvaluationStatus$fReadDebugRuleEvaluationStatus$fShowDebugRuleEvaluationStatus"$fGenericDebugRuleEvaluationStatusS3DataDistributionS3DataDistribution'fromS3DataDistribution!S3DataDistribution_ShardedByS3Key"S3DataDistribution_FullyReplicated$fShowS3DataDistribution$fReadS3DataDistribution$fEqS3DataDistribution$fOrdS3DataDistribution$fGenericS3DataDistribution$fHashableS3DataDistribution$fNFDataS3DataDistribution$fFromTextS3DataDistribution$fToTextS3DataDistribution $fToByteStringS3DataDistribution$fToLogS3DataDistribution$fToHeaderS3DataDistribution$fToQueryS3DataDistribution$fFromJSONS3DataDistribution$fFromJSONKeyS3DataDistribution$fToJSONS3DataDistribution$fToJSONKeyS3DataDistribution$fFromXMLS3DataDistribution$fToXMLS3DataDistribution S3DataType S3DataType'fromS3DataTypeS3DataType_S3PrefixS3DataType_ManifestFile S3DataType_AugmentedManifestFile$fShowS3DataType$fReadS3DataType$fEqS3DataType$fOrdS3DataType$fGenericS3DataType$fHashableS3DataType$fNFDataS3DataType$fFromTextS3DataType$fToTextS3DataType$fToByteStringS3DataType$fToLogS3DataType$fToHeaderS3DataType$fToQueryS3DataType$fFromJSONS3DataType$fFromJSONKeyS3DataType$fToJSONS3DataType$fToJSONKeyS3DataType$fFromXMLS3DataType$fToXMLS3DataType S3DataSource S3DataSource'!$sel:attributeNames:S3DataSource'%$sel:instanceGroupNames:S3DataSource')$sel:s3DataDistributionType:S3DataSource'$sel:s3DataType:S3DataSource'$sel:s3Uri:S3DataSource'newS3DataSources3DataSource_attributeNamess3DataSource_instanceGroupNames#s3DataSource_s3DataDistributionTypes3DataSource_s3DataTypes3DataSource_s3Uri$fToJSONS3DataSource$fNFDataS3DataSource$fHashableS3DataSource$fFromJSONS3DataSource$fEqS3DataSource$fReadS3DataSource$fShowS3DataSource$fGenericS3DataSource DataSource DataSource'%$sel:fileSystemDataSource:DataSource'$sel:s3DataSource:DataSource' newDataSourcedataSource_fileSystemDataSourcedataSource_s3DataSource$fToJSONDataSource$fNFDataDataSource$fHashableDataSource$fFromJSONDataSource$fEqDataSource$fReadDataSource$fShowDataSource$fGenericDataSourceS3StorageConfigS3StorageConfig'$sel:kmsKeyId:S3StorageConfig')$sel:resolvedOutputS3Uri:S3StorageConfig'$sel:s3Uri:S3StorageConfig'newS3StorageConfigs3StorageConfig_kmsKeyId#s3StorageConfig_resolvedOutputS3Uris3StorageConfig_s3Uri$fToJSONS3StorageConfig$fNFDataS3StorageConfig$fHashableS3StorageConfig$fFromJSONS3StorageConfig$fEqS3StorageConfig$fReadS3StorageConfig$fShowS3StorageConfig$fGenericS3StorageConfigSagemakerServicecatalogStatusSagemakerServicecatalogStatus'!fromSagemakerServicecatalogStatus%SagemakerServicecatalogStatus_Enabled&SagemakerServicecatalogStatus_Disabled#$fShowSagemakerServicecatalogStatus#$fReadSagemakerServicecatalogStatus!$fEqSagemakerServicecatalogStatus"$fOrdSagemakerServicecatalogStatus&$fGenericSagemakerServicecatalogStatus'$fHashableSagemakerServicecatalogStatus%$fNFDataSagemakerServicecatalogStatus'$fFromTextSagemakerServicecatalogStatus%$fToTextSagemakerServicecatalogStatus+$fToByteStringSagemakerServicecatalogStatus$$fToLogSagemakerServicecatalogStatus'$fToHeaderSagemakerServicecatalogStatus&$fToQuerySagemakerServicecatalogStatus'$fFromJSONSagemakerServicecatalogStatus*$fFromJSONKeySagemakerServicecatalogStatus%$fToJSONSagemakerServicecatalogStatus($fToJSONKeySagemakerServicecatalogStatus&$fFromXMLSagemakerServicecatalogStatus$$fToXMLSagemakerServicecatalogStatusScheduleConfigScheduleConfig''$sel:scheduleExpression:ScheduleConfig'newScheduleConfig!scheduleConfig_scheduleExpression$fToJSONScheduleConfig$fNFDataScheduleConfig$fHashableScheduleConfig$fFromJSONScheduleConfig$fEqScheduleConfig$fReadScheduleConfig$fShowScheduleConfig$fGenericScheduleConfigScheduleStatusScheduleStatus'fromScheduleStatusScheduleStatus_StoppedScheduleStatus_ScheduledScheduleStatus_PendingScheduleStatus_Failed$fShowScheduleStatus$fReadScheduleStatus$fEqScheduleStatus$fOrdScheduleStatus$fGenericScheduleStatus$fHashableScheduleStatus$fNFDataScheduleStatus$fFromTextScheduleStatus$fToTextScheduleStatus$fToByteStringScheduleStatus$fToLogScheduleStatus$fToHeaderScheduleStatus$fToQueryScheduleStatus$fFromJSONScheduleStatus$fFromJSONKeyScheduleStatus$fToJSONScheduleStatus$fToJSONKeyScheduleStatus$fFromXMLScheduleStatus$fToXMLScheduleStatusMonitoringScheduleSummaryMonitoringScheduleSummary',$sel:endpointName:MonitoringScheduleSummary';$sel:monitoringJobDefinitionName:MonitoringScheduleSummary'.$sel:monitoringType:MonitoringScheduleSummary'6$sel:monitoringScheduleName:MonitoringScheduleSummary'5$sel:monitoringScheduleArn:MonitoringScheduleSummary',$sel:creationTime:MonitoringScheduleSummary'0$sel:lastModifiedTime:MonitoringScheduleSummary'8$sel:monitoringScheduleStatus:MonitoringScheduleSummary'newMonitoringScheduleSummary&monitoringScheduleSummary_endpointName5monitoringScheduleSummary_monitoringJobDefinitionName(monitoringScheduleSummary_monitoringType0monitoringScheduleSummary_monitoringScheduleName/monitoringScheduleSummary_monitoringScheduleArn&monitoringScheduleSummary_creationTime*monitoringScheduleSummary_lastModifiedTime2monitoringScheduleSummary_monitoringScheduleStatus!$fNFDataMonitoringScheduleSummary#$fHashableMonitoringScheduleSummary#$fFromJSONMonitoringScheduleSummary$fEqMonitoringScheduleSummary$fReadMonitoringScheduleSummary$fShowMonitoringScheduleSummary"$fGenericMonitoringScheduleSummarySearchExpressionSearchExpression'$sel:filters:SearchExpression'$$sel:nestedFilters:SearchExpression'$sel:operator:SearchExpression'%$sel:subExpressions:SearchExpression'newSearchExpressionsearchExpression_filterssearchExpression_nestedFilterssearchExpression_operatorsearchExpression_subExpressions$fToJSONSearchExpression$fNFDataSearchExpression$fHashableSearchExpression$fEqSearchExpression$fReadSearchExpression$fShowSearchExpression$fGenericSearchExpressionSearchSortOrderSearchSortOrder'fromSearchSortOrderSearchSortOrder_DescendingSearchSortOrder_Ascending$fShowSearchSortOrder$fReadSearchSortOrder$fEqSearchSortOrder$fOrdSearchSortOrder$fGenericSearchSortOrder$fHashableSearchSortOrder$fNFDataSearchSortOrder$fFromTextSearchSortOrder$fToTextSearchSortOrder$fToByteStringSearchSortOrder$fToLogSearchSortOrder$fToHeaderSearchSortOrder$fToQuerySearchSortOrder$fFromJSONSearchSortOrder$fFromJSONKeySearchSortOrder$fToJSONSearchSortOrder$fToJSONKeySearchSortOrder$fFromXMLSearchSortOrder$fToXMLSearchSortOrderSecondaryStatusSecondaryStatus'fromSecondaryStatusSecondaryStatus_UploadingSecondaryStatus_UpdatingSecondaryStatus_TrainingSecondaryStatus_StoppingSecondaryStatus_StoppedSecondaryStatus_StartingSecondaryStatus_Restarting&SecondaryStatus_PreparingTrainingStack#SecondaryStatus_MaxWaitTimeExceeded"SecondaryStatus_MaxRuntimeExceeded$SecondaryStatus_LaunchingMLInstancesSecondaryStatus_InterruptedSecondaryStatus_Failed(SecondaryStatus_DownloadingTrainingImageSecondaryStatus_DownloadingSecondaryStatus_Completed$fShowSecondaryStatus$fReadSecondaryStatus$fEqSecondaryStatus$fOrdSecondaryStatus$fGenericSecondaryStatus$fHashableSecondaryStatus$fNFDataSecondaryStatus$fFromTextSecondaryStatus$fToTextSecondaryStatus$fToByteStringSecondaryStatus$fToLogSecondaryStatus$fToHeaderSecondaryStatus$fToQuerySecondaryStatus$fFromJSONSecondaryStatus$fFromJSONKeySecondaryStatus$fToJSONSecondaryStatus$fToJSONKeySecondaryStatus$fFromXMLSecondaryStatus$fToXMLSecondaryStatusSecondaryStatusTransitionSecondaryStatusTransition''$sel:endTime:SecondaryStatusTransition'-$sel:statusMessage:SecondaryStatusTransition'&$sel:status:SecondaryStatusTransition')$sel:startTime:SecondaryStatusTransition'newSecondaryStatusTransition!secondaryStatusTransition_endTime'secondaryStatusTransition_statusMessage secondaryStatusTransition_status#secondaryStatusTransition_startTime!$fNFDataSecondaryStatusTransition#$fHashableSecondaryStatusTransition#$fFromJSONSecondaryStatusTransition$fEqSecondaryStatusTransition$fReadSecondaryStatusTransition$fShowSecondaryStatusTransition"$fGenericSecondaryStatusTransition'ServiceCatalogProvisionedProductDetails(ServiceCatalogProvisionedProductDetails'$sel:provisionedProductId:ServiceCatalogProvisionedProductDetails'$sel:provisionedProductStatusMessage:ServiceCatalogProvisionedProductDetails'*newServiceCatalogProvisionedProductDetails$sel:provisioningArtifactId:ServiceCatalogProvisioningDetails'>$sel:provisioningParameters:ServiceCatalogProvisioningDetails'1$sel:productId:ServiceCatalogProvisioningDetails'$newServiceCatalogProvisioningDetails(serviceCatalogProvisioningDetails_pathId8serviceCatalogProvisioningDetails_provisioningArtifactId8serviceCatalogProvisioningDetails_provisioningParameters+serviceCatalogProvisioningDetails_productId)$fToJSONServiceCatalogProvisioningDetails)$fNFDataServiceCatalogProvisioningDetails+$fHashableServiceCatalogProvisioningDetails+$fFromJSONServiceCatalogProvisioningDetails%$fEqServiceCatalogProvisioningDetails'$fReadServiceCatalogProvisioningDetails'$fShowServiceCatalogProvisioningDetails*$fGenericServiceCatalogProvisioningDetails'ServiceCatalogProvisioningUpdateDetails(ServiceCatalogProvisioningUpdateDetails'$sel:provisioningArtifactId:ServiceCatalogProvisioningUpdateDetails'$sel:provisioningParameters:ServiceCatalogProvisioningUpdateDetails'*newServiceCatalogProvisioningUpdateDetails>serviceCatalogProvisioningUpdateDetails_provisioningArtifactId>serviceCatalogProvisioningUpdateDetails_provisioningParameters/$fToJSONServiceCatalogProvisioningUpdateDetails/$fNFDataServiceCatalogProvisioningUpdateDetails1$fHashableServiceCatalogProvisioningUpdateDetails+$fEqServiceCatalogProvisioningUpdateDetails-$fReadServiceCatalogProvisioningUpdateDetails-$fShowServiceCatalogProvisioningUpdateDetails0$fGenericServiceCatalogProvisioningUpdateDetailsShadowModelVariantConfigShadowModelVariantConfig'5$sel:shadowModelVariantName:ShadowModelVariantConfig'1$sel:samplingPercentage:ShadowModelVariantConfig'newShadowModelVariantConfig/shadowModelVariantConfig_shadowModelVariantName+shadowModelVariantConfig_samplingPercentage $fToJSONShadowModelVariantConfig $fNFDataShadowModelVariantConfig"$fHashableShadowModelVariantConfig"$fFromJSONShadowModelVariantConfig$fEqShadowModelVariantConfig$fReadShadowModelVariantConfig$fShowShadowModelVariantConfig!$fGenericShadowModelVariantConfigShadowModeConfigShadowModeConfig'-$sel:sourceModelVariantName:ShadowModeConfig'*$sel:shadowModelVariants:ShadowModeConfig'newShadowModeConfig'shadowModeConfig_sourceModelVariantName$shadowModeConfig_shadowModelVariants$fToJSONShadowModeConfig$fNFDataShadowModeConfig$fHashableShadowModeConfig$fFromJSONShadowModeConfig$fEqShadowModeConfig$fReadShadowModeConfig$fShowShadowModeConfig$fGenericShadowModeConfigSharingSettingsSharingSettings'*$sel:notebookOutputOption:SharingSettings' $sel:s3KmsKeyId:SharingSettings'"$sel:s3OutputPath:SharingSettings'newSharingSettings$sharingSettings_notebookOutputOptionsharingSettings_s3KmsKeyIdsharingSettings_s3OutputPath$fToJSONSharingSettings$fNFDataSharingSettings$fHashableSharingSettings$fFromJSONSharingSettings$fEqSharingSettings$fReadSharingSettings$fShowSharingSettings$fGenericSharingSettings ShuffleConfigShuffleConfig'$sel:seed:ShuffleConfig'newShuffleConfigshuffleConfig_seed$fToJSONShuffleConfig$fNFDataShuffleConfig$fHashableShuffleConfig$fFromJSONShuffleConfig$fEqShuffleConfig$fReadShuffleConfig$fShowShuffleConfig$fGenericShuffleConfig SortActionsBySortActionsBy'fromSortActionsBySortActionsBy_NameSortActionsBy_CreationTime$fShowSortActionsBy$fReadSortActionsBy$fEqSortActionsBy$fOrdSortActionsBy$fGenericSortActionsBy$fHashableSortActionsBy$fNFDataSortActionsBy$fFromTextSortActionsBy$fToTextSortActionsBy$fToByteStringSortActionsBy$fToLogSortActionsBy$fToHeaderSortActionsBy$fToQuerySortActionsBy$fFromJSONSortActionsBy$fFromJSONKeySortActionsBy$fToJSONSortActionsBy$fToJSONKeySortActionsBy$fFromXMLSortActionsBy$fToXMLSortActionsBySortArtifactsBySortArtifactsBy'fromSortArtifactsBySortArtifactsBy_CreationTime$fShowSortArtifactsBy$fReadSortArtifactsBy$fEqSortArtifactsBy$fOrdSortArtifactsBy$fGenericSortArtifactsBy$fHashableSortArtifactsBy$fNFDataSortArtifactsBy$fFromTextSortArtifactsBy$fToTextSortArtifactsBy$fToByteStringSortArtifactsBy$fToLogSortArtifactsBy$fToHeaderSortArtifactsBy$fToQuerySortArtifactsBy$fFromJSONSortArtifactsBy$fFromJSONKeySortArtifactsBy$fToJSONSortArtifactsBy$fToJSONKeySortArtifactsBy$fFromXMLSortArtifactsBy$fToXMLSortArtifactsBySortAssociationsBySortAssociationsBy'fromSortAssociationsBySortAssociationsBy_SourceTypeSortAssociationsBy_SourceArn"SortAssociationsBy_DestinationType!SortAssociationsBy_DestinationArnSortAssociationsBy_CreationTime$fShowSortAssociationsBy$fReadSortAssociationsBy$fEqSortAssociationsBy$fOrdSortAssociationsBy$fGenericSortAssociationsBy$fHashableSortAssociationsBy$fNFDataSortAssociationsBy$fFromTextSortAssociationsBy$fToTextSortAssociationsBy $fToByteStringSortAssociationsBy$fToLogSortAssociationsBy$fToHeaderSortAssociationsBy$fToQuerySortAssociationsBy$fFromJSONSortAssociationsBy$fFromJSONKeySortAssociationsBy$fToJSONSortAssociationsBy$fToJSONKeySortAssociationsBy$fFromXMLSortAssociationsBy$fToXMLSortAssociationsBySortBySortBy' fromSortBy SortBy_Status SortBy_NameSortBy_CreationTime $fShowSortBy $fReadSortBy $fEqSortBy $fOrdSortBy$fGenericSortBy$fHashableSortBy$fNFDataSortBy$fFromTextSortBy$fToTextSortBy$fToByteStringSortBy $fToLogSortBy$fToHeaderSortBy$fToQuerySortBy$fFromJSONSortBy$fFromJSONKeySortBy$fToJSONSortBy$fToJSONKeySortBy$fFromXMLSortBy $fToXMLSortBySortContextsBySortContextsBy'fromSortContextsBySortContextsBy_NameSortContextsBy_CreationTime$fShowSortContextsBy$fReadSortContextsBy$fEqSortContextsBy$fOrdSortContextsBy$fGenericSortContextsBy$fHashableSortContextsBy$fNFDataSortContextsBy$fFromTextSortContextsBy$fToTextSortContextsBy$fToByteStringSortContextsBy$fToLogSortContextsBy$fToHeaderSortContextsBy$fToQuerySortContextsBy$fFromJSONSortContextsBy$fFromJSONKeySortContextsBy$fToJSONSortContextsBy$fToJSONKeySortContextsBy$fFromXMLSortContextsBy$fToXMLSortContextsBySortExperimentsBySortExperimentsBy'fromSortExperimentsBySortExperimentsBy_NameSortExperimentsBy_CreationTime$fShowSortExperimentsBy$fReadSortExperimentsBy$fEqSortExperimentsBy$fOrdSortExperimentsBy$fGenericSortExperimentsBy$fHashableSortExperimentsBy$fNFDataSortExperimentsBy$fFromTextSortExperimentsBy$fToTextSortExperimentsBy$fToByteStringSortExperimentsBy$fToLogSortExperimentsBy$fToHeaderSortExperimentsBy$fToQuerySortExperimentsBy$fFromJSONSortExperimentsBy$fFromJSONKeySortExperimentsBy$fToJSONSortExperimentsBy$fToJSONKeySortExperimentsBy$fFromXMLSortExperimentsBy$fToXMLSortExperimentsBySortInferenceExperimentsBySortInferenceExperimentsBy'fromSortInferenceExperimentsBy!SortInferenceExperimentsBy_StatusSortInferenceExperimentsBy_Name'SortInferenceExperimentsBy_CreationTime $fShowSortInferenceExperimentsBy $fReadSortInferenceExperimentsBy$fEqSortInferenceExperimentsBy$fOrdSortInferenceExperimentsBy#$fGenericSortInferenceExperimentsBy$$fHashableSortInferenceExperimentsBy"$fNFDataSortInferenceExperimentsBy$$fFromTextSortInferenceExperimentsBy"$fToTextSortInferenceExperimentsBy($fToByteStringSortInferenceExperimentsBy!$fToLogSortInferenceExperimentsBy$$fToHeaderSortInferenceExperimentsBy#$fToQuerySortInferenceExperimentsBy$$fFromJSONSortInferenceExperimentsBy'$fFromJSONKeySortInferenceExperimentsBy"$fToJSONSortInferenceExperimentsBy%$fToJSONKeySortInferenceExperimentsBy#$fFromXMLSortInferenceExperimentsBy!$fToXMLSortInferenceExperimentsBySortLineageGroupsBySortLineageGroupsBy'fromSortLineageGroupsBySortLineageGroupsBy_Name SortLineageGroupsBy_CreationTime$fShowSortLineageGroupsBy$fReadSortLineageGroupsBy$fEqSortLineageGroupsBy$fOrdSortLineageGroupsBy$fGenericSortLineageGroupsBy$fHashableSortLineageGroupsBy$fNFDataSortLineageGroupsBy$fFromTextSortLineageGroupsBy$fToTextSortLineageGroupsBy!$fToByteStringSortLineageGroupsBy$fToLogSortLineageGroupsBy$fToHeaderSortLineageGroupsBy$fToQuerySortLineageGroupsBy$fFromJSONSortLineageGroupsBy $fFromJSONKeySortLineageGroupsBy$fToJSONSortLineageGroupsBy$fToJSONKeySortLineageGroupsBy$fFromXMLSortLineageGroupsBy$fToXMLSortLineageGroupsBy SortOrder SortOrder' fromSortOrderSortOrder_DescendingSortOrder_Ascending$fShowSortOrder$fReadSortOrder $fEqSortOrder$fOrdSortOrder$fGenericSortOrder$fHashableSortOrder$fNFDataSortOrder$fFromTextSortOrder$fToTextSortOrder$fToByteStringSortOrder$fToLogSortOrder$fToHeaderSortOrder$fToQuerySortOrder$fFromJSONSortOrder$fFromJSONKeySortOrder$fToJSONSortOrder$fToJSONKeySortOrder$fFromXMLSortOrder$fToXMLSortOrderSortPipelineExecutionsBySortPipelineExecutionsBy'fromSortPipelineExecutionsBy-SortPipelineExecutionsBy_PipelineExecutionArn%SortPipelineExecutionsBy_CreationTime$fShowSortPipelineExecutionsBy$fReadSortPipelineExecutionsBy$fEqSortPipelineExecutionsBy$fOrdSortPipelineExecutionsBy!$fGenericSortPipelineExecutionsBy"$fHashableSortPipelineExecutionsBy $fNFDataSortPipelineExecutionsBy"$fFromTextSortPipelineExecutionsBy $fToTextSortPipelineExecutionsBy&$fToByteStringSortPipelineExecutionsBy$fToLogSortPipelineExecutionsBy"$fToHeaderSortPipelineExecutionsBy!$fToQuerySortPipelineExecutionsBy"$fFromJSONSortPipelineExecutionsBy%$fFromJSONKeySortPipelineExecutionsBy $fToJSONSortPipelineExecutionsBy#$fToJSONKeySortPipelineExecutionsBy!$fFromXMLSortPipelineExecutionsBy$fToXMLSortPipelineExecutionsBySortPipelinesBySortPipelinesBy'fromSortPipelinesBySortPipelinesBy_NameSortPipelinesBy_CreationTime$fShowSortPipelinesBy$fReadSortPipelinesBy$fEqSortPipelinesBy$fOrdSortPipelinesBy$fGenericSortPipelinesBy$fHashableSortPipelinesBy$fNFDataSortPipelinesBy$fFromTextSortPipelinesBy$fToTextSortPipelinesBy$fToByteStringSortPipelinesBy$fToLogSortPipelinesBy$fToHeaderSortPipelinesBy$fToQuerySortPipelinesBy$fFromJSONSortPipelinesBy$fFromJSONKeySortPipelinesBy$fToJSONSortPipelinesBy$fToJSONKeySortPipelinesBy$fFromXMLSortPipelinesBy$fToXMLSortPipelinesBySortTrialComponentsBySortTrialComponentsBy'fromSortTrialComponentsBySortTrialComponentsBy_Name"SortTrialComponentsBy_CreationTime$fShowSortTrialComponentsBy$fReadSortTrialComponentsBy$fEqSortTrialComponentsBy$fOrdSortTrialComponentsBy$fGenericSortTrialComponentsBy$fHashableSortTrialComponentsBy$fNFDataSortTrialComponentsBy$fFromTextSortTrialComponentsBy$fToTextSortTrialComponentsBy#$fToByteStringSortTrialComponentsBy$fToLogSortTrialComponentsBy$fToHeaderSortTrialComponentsBy$fToQuerySortTrialComponentsBy$fFromJSONSortTrialComponentsBy"$fFromJSONKeySortTrialComponentsBy$fToJSONSortTrialComponentsBy $fToJSONKeySortTrialComponentsBy$fFromXMLSortTrialComponentsBy$fToXMLSortTrialComponentsBy SortTrialsBy SortTrialsBy'fromSortTrialsBySortTrialsBy_NameSortTrialsBy_CreationTime$fShowSortTrialsBy$fReadSortTrialsBy$fEqSortTrialsBy$fOrdSortTrialsBy$fGenericSortTrialsBy$fHashableSortTrialsBy$fNFDataSortTrialsBy$fFromTextSortTrialsBy$fToTextSortTrialsBy$fToByteStringSortTrialsBy$fToLogSortTrialsBy$fToHeaderSortTrialsBy$fToQuerySortTrialsBy$fFromJSONSortTrialsBy$fFromJSONKeySortTrialsBy$fToJSONSortTrialsBy$fToJSONKeySortTrialsBy$fFromXMLSortTrialsBy$fToXMLSortTrialsBySourceAlgorithmSourceAlgorithm'"$sel:modelDataUrl:SourceAlgorithm'#$sel:algorithmName:SourceAlgorithm'newSourceAlgorithmsourceAlgorithm_modelDataUrlsourceAlgorithm_algorithmName$fToJSONSourceAlgorithm$fNFDataSourceAlgorithm$fHashableSourceAlgorithm$fFromJSONSourceAlgorithm$fEqSourceAlgorithm$fReadSourceAlgorithm$fShowSourceAlgorithm$fGenericSourceAlgorithmSourceAlgorithmSpecificationSourceAlgorithmSpecification'3$sel:sourceAlgorithms:SourceAlgorithmSpecification'newSourceAlgorithmSpecification-sourceAlgorithmSpecification_sourceAlgorithms$$fToJSONSourceAlgorithmSpecification$$fNFDataSourceAlgorithmSpecification&$fHashableSourceAlgorithmSpecification&$fFromJSONSourceAlgorithmSpecification $fEqSourceAlgorithmSpecification"$fReadSourceAlgorithmSpecification"$fShowSourceAlgorithmSpecification%$fGenericSourceAlgorithmSpecificationSourceIpConfigSourceIpConfig'$sel:cidrs:SourceIpConfig'newSourceIpConfigsourceIpConfig_cidrs$fToJSONSourceIpConfig$fNFDataSourceIpConfig$fHashableSourceIpConfig$fFromJSONSourceIpConfig$fEqSourceIpConfig$fReadSourceIpConfig$fShowSourceIpConfig$fGenericSourceIpConfig SpaceSettingsSpaceSettings',$sel:jupyterServerAppSettings:SpaceSettings',$sel:kernelGatewayAppSettings:SpaceSettings'newSpaceSettings&spaceSettings_jupyterServerAppSettings&spaceSettings_kernelGatewayAppSettings$fToJSONSpaceSettings$fNFDataSpaceSettings$fHashableSpaceSettings$fFromJSONSpaceSettings$fEqSpaceSettings$fReadSpaceSettings$fShowSpaceSettings$fGenericSpaceSettings SpaceSortKey SpaceSortKey'fromSpaceSortKeySpaceSortKey_LastModifiedTimeSpaceSortKey_CreationTime$fShowSpaceSortKey$fReadSpaceSortKey$fEqSpaceSortKey$fOrdSpaceSortKey$fGenericSpaceSortKey$fHashableSpaceSortKey$fNFDataSpaceSortKey$fFromTextSpaceSortKey$fToTextSpaceSortKey$fToByteStringSpaceSortKey$fToLogSpaceSortKey$fToHeaderSpaceSortKey$fToQuerySpaceSortKey$fFromJSONSpaceSortKey$fFromJSONKeySpaceSortKey$fToJSONSpaceSortKey$fToJSONKeySpaceSortKey$fFromXMLSpaceSortKey$fToXMLSpaceSortKey SpaceStatus SpaceStatus'fromSpaceStatusSpaceStatus_UpdatingSpaceStatus_Update_FailedSpaceStatus_PendingSpaceStatus_InServiceSpaceStatus_FailedSpaceStatus_DeletingSpaceStatus_Delete_Failed$fShowSpaceStatus$fReadSpaceStatus$fEqSpaceStatus$fOrdSpaceStatus$fGenericSpaceStatus$fHashableSpaceStatus$fNFDataSpaceStatus$fFromTextSpaceStatus$fToTextSpaceStatus$fToByteStringSpaceStatus$fToLogSpaceStatus$fToHeaderSpaceStatus$fToQuerySpaceStatus$fFromJSONSpaceStatus$fFromJSONKeySpaceStatus$fToJSONSpaceStatus$fToJSONKeySpaceStatus$fFromXMLSpaceStatus$fToXMLSpaceStatus SpaceDetails SpaceDetails'$sel:creationTime:SpaceDetails'$sel:domainId:SpaceDetails'#$sel:lastModifiedTime:SpaceDetails'$sel:spaceName:SpaceDetails'$sel:status:SpaceDetails'newSpaceDetailsspaceDetails_creationTimespaceDetails_domainIdspaceDetails_lastModifiedTimespaceDetails_spaceNamespaceDetails_status$fNFDataSpaceDetails$fHashableSpaceDetails$fFromJSONSpaceDetails$fEqSpaceDetails$fReadSpaceDetails$fShowSpaceDetails$fGenericSpaceDetails SplitType SplitType' fromSplitTypeSplitType_TFRecordSplitType_RecordIOSplitType_NoneSplitType_Line$fShowSplitType$fReadSplitType $fEqSplitType$fOrdSplitType$fGenericSplitType$fHashableSplitType$fNFDataSplitType$fFromTextSplitType$fToTextSplitType$fToByteStringSplitType$fToLogSplitType$fToHeaderSplitType$fToQuerySplitType$fFromJSONSplitType$fFromJSONKeySplitType$fToJSONSplitType$fToJSONKeySplitType$fFromXMLSplitType$fToXMLSplitType StageStatus StageStatus'fromStageStatusStageStatus_STOPPINGStageStatus_STOPPEDStageStatus_STARTINGStageStatus_READYTODEPLOYStageStatus_INPROGRESSStageStatus_FAILEDStageStatus_DEPLOYEDStageStatus_CREATING$fShowStageStatus$fReadStageStatus$fEqStageStatus$fOrdStageStatus$fGenericStageStatus$fHashableStageStatus$fNFDataStageStatus$fFromTextStageStatus$fToTextStageStatus$fToByteStringStageStatus$fToLogStageStatus$fToHeaderStageStatus$fToQueryStageStatus$fFromJSONStageStatus$fFromJSONKeyStageStatus$fToJSONStageStatus$fToJSONKeyStageStatus$fFromXMLStageStatus$fToXMLStageStatusEdgeDeploymentStatusEdgeDeploymentStatus'7$sel:edgeDeploymentStageStartTime:EdgeDeploymentStatus'6$sel:edgeDeploymentStatusMessage:EdgeDeploymentStatus'&$sel:stageStatus:EdgeDeploymentStatus'7$sel:edgeDeploymentSuccessInStage:EdgeDeploymentStatus'7$sel:edgeDeploymentPendingInStage:EdgeDeploymentStatus'6$sel:edgeDeploymentFailedInStage:EdgeDeploymentStatus'newEdgeDeploymentStatus1edgeDeploymentStatus_edgeDeploymentStageStartTime0edgeDeploymentStatus_edgeDeploymentStatusMessage edgeDeploymentStatus_stageStatus1edgeDeploymentStatus_edgeDeploymentSuccessInStage1edgeDeploymentStatus_edgeDeploymentPendingInStage0edgeDeploymentStatus_edgeDeploymentFailedInStage$fNFDataEdgeDeploymentStatus$fHashableEdgeDeploymentStatus$fFromJSONEdgeDeploymentStatus$fEqEdgeDeploymentStatus$fReadEdgeDeploymentStatus$fShowEdgeDeploymentStatus$fGenericEdgeDeploymentStatusDeploymentStageStatusSummaryDeploymentStageStatusSummary',$sel:stageName:DeploymentStageStatusSummary'8$sel:deviceSelectionConfig:DeploymentStageStatusSummary'3$sel:deploymentConfig:DeploymentStageStatusSummary'3$sel:deploymentStatus:DeploymentStageStatusSummary'newDeploymentStageStatusSummary&deploymentStageStatusSummary_stageName2deploymentStageStatusSummary_deviceSelectionConfig-deploymentStageStatusSummary_deploymentConfig-deploymentStageStatusSummary_deploymentStatus$$fNFDataDeploymentStageStatusSummary&$fHashableDeploymentStageStatusSummary&$fFromJSONDeploymentStageStatusSummary $fEqDeploymentStageStatusSummary"$fReadDeploymentStageStatusSummary"$fShowDeploymentStageStatusSummary%$fGenericDeploymentStageStatusSummary StepStatus StepStatus'fromStepStatusStepStatus_SucceededStepStatus_StoppingStepStatus_StoppedStepStatus_StartingStepStatus_FailedStepStatus_Executing$fShowStepStatus$fReadStepStatus$fEqStepStatus$fOrdStepStatus$fGenericStepStatus$fHashableStepStatus$fNFDataStepStatus$fFromTextStepStatus$fToTextStepStatus$fToByteStringStepStatus$fToLogStepStatus$fToHeaderStepStatus$fToQueryStepStatus$fFromJSONStepStatus$fFromJSONKeyStepStatus$fToJSONStepStatus$fToJSONKeyStepStatus$fFromXMLStepStatus$fToXMLStepStatusStoppingConditionStoppingCondition'+$sel:maxRuntimeInSeconds:StoppingCondition',$sel:maxWaitTimeInSeconds:StoppingCondition'newStoppingCondition%stoppingCondition_maxRuntimeInSeconds&stoppingCondition_maxWaitTimeInSeconds$fToJSONStoppingCondition$fNFDataStoppingCondition$fHashableStoppingCondition$fFromJSONStoppingCondition$fEqStoppingCondition$fReadStoppingCondition$fShowStoppingCondition$fGenericStoppingConditionStudioLifecycleConfigAppTypeStudioLifecycleConfigAppType' fromStudioLifecycleConfigAppType*StudioLifecycleConfigAppType_KernelGateway*StudioLifecycleConfigAppType_JupyterServer"$fShowStudioLifecycleConfigAppType"$fReadStudioLifecycleConfigAppType $fEqStudioLifecycleConfigAppType!$fOrdStudioLifecycleConfigAppType%$fGenericStudioLifecycleConfigAppType&$fHashableStudioLifecycleConfigAppType$$fNFDataStudioLifecycleConfigAppType&$fFromTextStudioLifecycleConfigAppType$$fToTextStudioLifecycleConfigAppType*$fToByteStringStudioLifecycleConfigAppType#$fToLogStudioLifecycleConfigAppType&$fToHeaderStudioLifecycleConfigAppType%$fToQueryStudioLifecycleConfigAppType&$fFromJSONStudioLifecycleConfigAppType)$fFromJSONKeyStudioLifecycleConfigAppType$$fToJSONStudioLifecycleConfigAppType'$fToJSONKeyStudioLifecycleConfigAppType%$fFromXMLStudioLifecycleConfigAppType#$fToXMLStudioLifecycleConfigAppTypeStudioLifecycleConfigDetailsStudioLifecycleConfigDetails'/$sel:creationTime:StudioLifecycleConfigDetails'3$sel:lastModifiedTime:StudioLifecycleConfigDetails'?$sel:studioLifecycleConfigAppType:StudioLifecycleConfigDetails';$sel:studioLifecycleConfigArn:StudioLifecycleConfigDetails'<$sel:studioLifecycleConfigName:StudioLifecycleConfigDetails'newStudioLifecycleConfigDetails)studioLifecycleConfigDetails_creationTime-studioLifecycleConfigDetails_lastModifiedTime9studioLifecycleConfigDetails_studioLifecycleConfigAppType5studioLifecycleConfigDetails_studioLifecycleConfigArn6studioLifecycleConfigDetails_studioLifecycleConfigName$$fNFDataStudioLifecycleConfigDetails&$fHashableStudioLifecycleConfigDetails&$fFromJSONStudioLifecycleConfigDetails $fEqStudioLifecycleConfigDetails"$fReadStudioLifecycleConfigDetails"$fShowStudioLifecycleConfigDetails%$fGenericStudioLifecycleConfigDetailsStudioLifecycleConfigSortKeyStudioLifecycleConfigSortKey' fromStudioLifecycleConfigSortKey!StudioLifecycleConfigSortKey_Name-StudioLifecycleConfigSortKey_LastModifiedTime)StudioLifecycleConfigSortKey_CreationTime"$fShowStudioLifecycleConfigSortKey"$fReadStudioLifecycleConfigSortKey $fEqStudioLifecycleConfigSortKey!$fOrdStudioLifecycleConfigSortKey%$fGenericStudioLifecycleConfigSortKey&$fHashableStudioLifecycleConfigSortKey$$fNFDataStudioLifecycleConfigSortKey&$fFromTextStudioLifecycleConfigSortKey$$fToTextStudioLifecycleConfigSortKey*$fToByteStringStudioLifecycleConfigSortKey#$fToLogStudioLifecycleConfigSortKey&$fToHeaderStudioLifecycleConfigSortKey%$fToQueryStudioLifecycleConfigSortKey&$fFromJSONStudioLifecycleConfigSortKey)$fFromJSONKeyStudioLifecycleConfigSortKey$$fToJSONStudioLifecycleConfigSortKey'$fToJSONKeyStudioLifecycleConfigSortKey%$fFromXMLStudioLifecycleConfigSortKey#$fToXMLStudioLifecycleConfigSortKeySubscribedWorkteamSubscribedWorkteam'"$sel:listingId:SubscribedWorkteam'/$sel:marketplaceDescription:SubscribedWorkteam')$sel:marketplaceTitle:SubscribedWorkteam'#$sel:sellerName:SubscribedWorkteam'$$sel:workteamArn:SubscribedWorkteam'newSubscribedWorkteamsubscribedWorkteam_listingId)subscribedWorkteam_marketplaceDescription#subscribedWorkteam_marketplaceTitlesubscribedWorkteam_sellerNamesubscribedWorkteam_workteamArn$fNFDataSubscribedWorkteam$fHashableSubscribedWorkteam$fFromJSONSubscribedWorkteam$fEqSubscribedWorkteam$fReadSubscribedWorkteam$fShowSubscribedWorkteam$fGenericSubscribedWorkteamSuggestionQuerySuggestionQuery''$sel:propertyNameQuery:SuggestionQuery'newSuggestionQuery!suggestionQuery_propertyNameQuery$fToJSONSuggestionQuery$fNFDataSuggestionQuery$fHashableSuggestionQuery$fEqSuggestionQuery$fReadSuggestionQuery$fShowSuggestionQuery$fGenericSuggestionQuery TableFormat TableFormat'fromTableFormatTableFormat_IcebergTableFormat_Glue$fShowTableFormat$fReadTableFormat$fEqTableFormat$fOrdTableFormat$fGenericTableFormat$fHashableTableFormat$fNFDataTableFormat$fFromTextTableFormat$fToTextTableFormat$fToByteStringTableFormat$fToLogTableFormat$fToHeaderTableFormat$fToQueryTableFormat$fFromJSONTableFormat$fFromJSONKeyTableFormat$fToJSONTableFormat$fToJSONKeyTableFormat$fFromXMLTableFormat$fToXMLTableFormatOfflineStoreConfigOfflineStoreConfig'*$sel:dataCatalogConfig:OfflineStoreConfig'1$sel:disableGlueTableCreation:OfflineStoreConfig'$$sel:tableFormat:OfflineStoreConfig'($sel:s3StorageConfig:OfflineStoreConfig'newOfflineStoreConfig$offlineStoreConfig_dataCatalogConfig+offlineStoreConfig_disableGlueTableCreationofflineStoreConfig_tableFormat"offlineStoreConfig_s3StorageConfig$fToJSONOfflineStoreConfig$fNFDataOfflineStoreConfig$fHashableOfflineStoreConfig$fFromJSONOfflineStoreConfig$fEqOfflineStoreConfig$fReadOfflineStoreConfig$fShowOfflineStoreConfig$fGenericOfflineStoreConfigTagTag' $sel:key:Tag'$sel:value:Tag'newTagtag_key tag_value $fToJSONTag $fNFDataTag $fHashableTag $fFromJSONTag$fEqTag $fReadTag $fShowTag $fGenericTag FeatureGroup FeatureGroup'$sel:creationTime:FeatureGroup'$sel:description:FeatureGroup''$sel:eventTimeFeatureName:FeatureGroup' $sel:failureReason:FeatureGroup'%$sel:featureDefinitions:FeatureGroup'"$sel:featureGroupArn:FeatureGroup'#$sel:featureGroupName:FeatureGroup'%$sel:featureGroupStatus:FeatureGroup'#$sel:lastModifiedTime:FeatureGroup'#$sel:lastUpdateStatus:FeatureGroup'%$sel:offlineStoreConfig:FeatureGroup'%$sel:offlineStoreStatus:FeatureGroup'$$sel:onlineStoreConfig:FeatureGroup'.$sel:recordIdentifierFeatureName:FeatureGroup'$sel:roleArn:FeatureGroup'$sel:tags:FeatureGroup'newFeatureGroupfeatureGroup_creationTimefeatureGroup_description!featureGroup_eventTimeFeatureNamefeatureGroup_failureReasonfeatureGroup_featureDefinitionsfeatureGroup_featureGroupArnfeatureGroup_featureGroupNamefeatureGroup_featureGroupStatusfeatureGroup_lastModifiedTimefeatureGroup_lastUpdateStatusfeatureGroup_offlineStoreConfigfeatureGroup_offlineStoreStatusfeatureGroup_onlineStoreConfig(featureGroup_recordIdentifierFeatureNamefeatureGroup_roleArnfeatureGroup_tags$fNFDataFeatureGroup$fHashableFeatureGroup$fFromJSONFeatureGroup$fEqFeatureGroup$fReadFeatureGroup$fShowFeatureGroup$fGenericFeatureGroup TargetDevice TargetDevice'fromTargetDeviceTargetDevice_X86_win64TargetDevice_X86_win32TargetDevice_Sitara_am57xTargetDevice_Sbe_cTargetDevice_Rk3399TargetDevice_Rk3288TargetDevice_Rasp3bTargetDevice_Qcs605TargetDevice_Qcs603TargetDevice_Ml_p3TargetDevice_Ml_p2TargetDevice_Ml_m5TargetDevice_Ml_m4TargetDevice_Ml_inf1TargetDevice_Ml_g4dnTargetDevice_Ml_eia2TargetDevice_Ml_c5TargetDevice_Ml_c4TargetDevice_LambdaTargetDevice_Jetson_xavierTargetDevice_Jetson_tx2TargetDevice_Jetson_tx1TargetDevice_Jetson_nanoTargetDevice_Jacinto_tda4vmTargetDevice_Imx8qmTargetDevice_Imx8mplusTargetDevice_DeeplensTargetDevice_CoremlTargetDevice_Amba_cv25TargetDevice_Amba_cv22TargetDevice_Amba_cv2TargetDevice_Aisage$fShowTargetDevice$fReadTargetDevice$fEqTargetDevice$fOrdTargetDevice$fGenericTargetDevice$fHashableTargetDevice$fNFDataTargetDevice$fFromTextTargetDevice$fToTextTargetDevice$fToByteStringTargetDevice$fToLogTargetDevice$fToHeaderTargetDevice$fToQueryTargetDevice$fFromJSONTargetDevice$fFromJSONKeyTargetDevice$fToJSONTargetDevice$fToJSONKeyTargetDevice$fFromXMLTargetDevice$fToXMLTargetDeviceTargetPlatformAcceleratorTargetPlatformAccelerator'fromTargetPlatformAccelerator TargetPlatformAccelerator_NVIDIATargetPlatformAccelerator_NNATargetPlatformAccelerator_MALI(TargetPlatformAccelerator_INTEL_GRAPHICS$fShowTargetPlatformAccelerator$fReadTargetPlatformAccelerator$fEqTargetPlatformAccelerator$fOrdTargetPlatformAccelerator"$fGenericTargetPlatformAccelerator#$fHashableTargetPlatformAccelerator!$fNFDataTargetPlatformAccelerator#$fFromTextTargetPlatformAccelerator!$fToTextTargetPlatformAccelerator'$fToByteStringTargetPlatformAccelerator $fToLogTargetPlatformAccelerator#$fToHeaderTargetPlatformAccelerator"$fToQueryTargetPlatformAccelerator#$fFromJSONTargetPlatformAccelerator&$fFromJSONKeyTargetPlatformAccelerator!$fToJSONTargetPlatformAccelerator$$fToJSONKeyTargetPlatformAccelerator"$fFromXMLTargetPlatformAccelerator $fToXMLTargetPlatformAcceleratorTargetPlatformArchTargetPlatformArch'fromTargetPlatformArchTargetPlatformArch_X86_64TargetPlatformArch_X86TargetPlatformArch_ARM_EABIHFTargetPlatformArch_ARM_EABITargetPlatformArch_ARM64$fShowTargetPlatformArch$fReadTargetPlatformArch$fEqTargetPlatformArch$fOrdTargetPlatformArch$fGenericTargetPlatformArch$fHashableTargetPlatformArch$fNFDataTargetPlatformArch$fFromTextTargetPlatformArch$fToTextTargetPlatformArch $fToByteStringTargetPlatformArch$fToLogTargetPlatformArch$fToHeaderTargetPlatformArch$fToQueryTargetPlatformArch$fFromJSONTargetPlatformArch$fFromJSONKeyTargetPlatformArch$fToJSONTargetPlatformArch$fToJSONKeyTargetPlatformArch$fFromXMLTargetPlatformArch$fToXMLTargetPlatformArchTargetPlatformOsTargetPlatformOs'fromTargetPlatformOsTargetPlatformOs_LINUXTargetPlatformOs_ANDROID$fShowTargetPlatformOs$fReadTargetPlatformOs$fEqTargetPlatformOs$fOrdTargetPlatformOs$fGenericTargetPlatformOs$fHashableTargetPlatformOs$fNFDataTargetPlatformOs$fFromTextTargetPlatformOs$fToTextTargetPlatformOs$fToByteStringTargetPlatformOs$fToLogTargetPlatformOs$fToHeaderTargetPlatformOs$fToQueryTargetPlatformOs$fFromJSONTargetPlatformOs$fFromJSONKeyTargetPlatformOs$fToJSONTargetPlatformOs$fToJSONKeyTargetPlatformOs$fFromXMLTargetPlatformOs$fToXMLTargetPlatformOsTargetPlatformTargetPlatform' $sel:accelerator:TargetPlatform'$sel:os:TargetPlatform'$sel:arch:TargetPlatform'newTargetPlatformtargetPlatform_acceleratortargetPlatform_ostargetPlatform_arch$fToJSONTargetPlatform$fNFDataTargetPlatform$fHashableTargetPlatform$fFromJSONTargetPlatform$fEqTargetPlatform$fReadTargetPlatform$fShowTargetPlatform$fGenericTargetPlatform OutputConfig OutputConfig'"$sel:compilerOptions:OutputConfig'$sel:kmsKeyId:OutputConfig'$sel:targetDevice:OutputConfig'!$sel:targetPlatform:OutputConfig'#$sel:s3OutputLocation:OutputConfig'newOutputConfigoutputConfig_compilerOptionsoutputConfig_kmsKeyIdoutputConfig_targetDeviceoutputConfig_targetPlatformoutputConfig_s3OutputLocation$fToJSONOutputConfig$fNFDataOutputConfig$fHashableOutputConfig$fFromJSONOutputConfig$fEqOutputConfig$fReadOutputConfig$fShowOutputConfig$fGenericOutputConfigCompilationJobSummaryCompilationJobSummary'.$sel:compilationEndTime:CompilationJobSummary'0$sel:compilationStartTime:CompilationJobSummary'3$sel:compilationTargetDevice:CompilationJobSummary'$sel:compilationTargetPlatformAccelerator:CompilationJobSummary'9$sel:compilationTargetPlatformArch:CompilationJobSummary'7$sel:compilationTargetPlatformOs:CompilationJobSummary',$sel:lastModifiedTime:CompilationJobSummary'.$sel:compilationJobName:CompilationJobSummary'-$sel:compilationJobArn:CompilationJobSummary'($sel:creationTime:CompilationJobSummary'0$sel:compilationJobStatus:CompilationJobSummary'newCompilationJobSummary(compilationJobSummary_compilationEndTime*compilationJobSummary_compilationStartTime-compilationJobSummary_compilationTargetDevice:compilationJobSummary_compilationTargetPlatformAccelerator3compilationJobSummary_compilationTargetPlatformArch1compilationJobSummary_compilationTargetPlatformOs&compilationJobSummary_lastModifiedTime(compilationJobSummary_compilationJobName'compilationJobSummary_compilationJobArn"compilationJobSummary_creationTime*compilationJobSummary_compilationJobStatus$fNFDataCompilationJobSummary$fHashableCompilationJobSummary$fFromJSONCompilationJobSummary$fEqCompilationJobSummary$fReadCompilationJobSummary$fShowCompilationJobSummary$fGenericCompilationJobSummaryTensorBoardAppSettingsTensorBoardAppSettings'0$sel:defaultResourceSpec:TensorBoardAppSettings'newTensorBoardAppSettings*tensorBoardAppSettings_defaultResourceSpec$fToJSONTensorBoardAppSettings$fNFDataTensorBoardAppSettings $fHashableTensorBoardAppSettings $fFromJSONTensorBoardAppSettings$fEqTensorBoardAppSettings$fReadTensorBoardAppSettings$fShowTensorBoardAppSettings$fGenericTensorBoardAppSettingsTensorBoardOutputConfigTensorBoardOutputConfig''$sel:localPath:TensorBoardOutputConfig'*$sel:s3OutputPath:TensorBoardOutputConfig'newTensorBoardOutputConfig!tensorBoardOutputConfig_localPath$tensorBoardOutputConfig_s3OutputPath$fToJSONTensorBoardOutputConfig$fNFDataTensorBoardOutputConfig!$fHashableTensorBoardOutputConfig!$fFromJSONTensorBoardOutputConfig$fEqTensorBoardOutputConfig$fReadTensorBoardOutputConfig$fShowTensorBoardOutputConfig $fGenericTensorBoardOutputConfigTimeSeriesForecastingSettingsTimeSeriesForecastingSettings'9$sel:amazonForecastRoleArn:TimeSeriesForecastingSettings'*$sel:status:TimeSeriesForecastingSettings' newTimeSeriesForecastingSettings3timeSeriesForecastingSettings_amazonForecastRoleArn$timeSeriesForecastingSettings_status%$fToJSONTimeSeriesForecastingSettings%$fNFDataTimeSeriesForecastingSettings'$fHashableTimeSeriesForecastingSettings'$fFromJSONTimeSeriesForecastingSettings!$fEqTimeSeriesForecastingSettings#$fReadTimeSeriesForecastingSettings#$fShowTimeSeriesForecastingSettings&$fGenericTimeSeriesForecastingSettingsCanvasAppSettingsCanvasAppSettings'5$sel:timeSeriesForecastingSettings:CanvasAppSettings'newCanvasAppSettings/canvasAppSettings_timeSeriesForecastingSettings$fToJSONCanvasAppSettings$fNFDataCanvasAppSettings$fHashableCanvasAppSettings$fFromJSONCanvasAppSettings$fEqCanvasAppSettings$fReadCanvasAppSettings$fShowCanvasAppSettings$fGenericCanvasAppSettingsTrafficRoutingConfigTypeTrafficRoutingConfigType'fromTrafficRoutingConfigTypeTrafficRoutingConfigType_LINEARTrafficRoutingConfigType_CANARY$TrafficRoutingConfigType_ALL_AT_ONCE$fShowTrafficRoutingConfigType$fReadTrafficRoutingConfigType$fEqTrafficRoutingConfigType$fOrdTrafficRoutingConfigType!$fGenericTrafficRoutingConfigType"$fHashableTrafficRoutingConfigType $fNFDataTrafficRoutingConfigType"$fFromTextTrafficRoutingConfigType $fToTextTrafficRoutingConfigType&$fToByteStringTrafficRoutingConfigType$fToLogTrafficRoutingConfigType"$fToHeaderTrafficRoutingConfigType!$fToQueryTrafficRoutingConfigType"$fFromJSONTrafficRoutingConfigType%$fFromJSONKeyTrafficRoutingConfigType $fToJSONTrafficRoutingConfigType#$fToJSONKeyTrafficRoutingConfigType!$fFromXMLTrafficRoutingConfigType$fToXMLTrafficRoutingConfigTypeTrafficRoutingConfigTrafficRoutingConfig'%$sel:canarySize:TrafficRoutingConfig')$sel:linearStepSize:TrafficRoutingConfig' $sel:type':TrafficRoutingConfig'0$sel:waitIntervalInSeconds:TrafficRoutingConfig'newTrafficRoutingConfigtrafficRoutingConfig_canarySize#trafficRoutingConfig_linearStepSizetrafficRoutingConfig_type*trafficRoutingConfig_waitIntervalInSeconds$fToJSONTrafficRoutingConfig$fNFDataTrafficRoutingConfig$fHashableTrafficRoutingConfig$fFromJSONTrafficRoutingConfig$fEqTrafficRoutingConfig$fReadTrafficRoutingConfig$fShowTrafficRoutingConfig$fGenericTrafficRoutingConfigBlueGreenUpdatePolicyBlueGreenUpdatePolicy'<$sel:maximumExecutionTimeoutInSeconds:BlueGreenUpdatePolicy'4$sel:terminationWaitInSeconds:BlueGreenUpdatePolicy'7$sel:trafficRoutingConfiguration:BlueGreenUpdatePolicy'newBlueGreenUpdatePolicy6blueGreenUpdatePolicy_maximumExecutionTimeoutInSeconds.blueGreenUpdatePolicy_terminationWaitInSeconds1blueGreenUpdatePolicy_trafficRoutingConfiguration$fToJSONBlueGreenUpdatePolicy$fNFDataBlueGreenUpdatePolicy$fHashableBlueGreenUpdatePolicy$fFromJSONBlueGreenUpdatePolicy$fEqBlueGreenUpdatePolicy$fReadBlueGreenUpdatePolicy$fShowBlueGreenUpdatePolicy$fGenericBlueGreenUpdatePolicyDeploymentConfigDeploymentConfig'0$sel:autoRollbackConfiguration:DeploymentConfig',$sel:blueGreenUpdatePolicy:DeploymentConfig'newDeploymentConfig*deploymentConfig_autoRollbackConfiguration&deploymentConfig_blueGreenUpdatePolicy$fToJSONDeploymentConfig$fNFDataDeploymentConfig$fHashableDeploymentConfig$fFromJSONDeploymentConfig$fEqDeploymentConfig$fReadDeploymentConfig$fShowDeploymentConfig$fGenericDeploymentConfig TrafficType TrafficType'fromTrafficTypeTrafficType_PHASES$fShowTrafficType$fReadTrafficType$fEqTrafficType$fOrdTrafficType$fGenericTrafficType$fHashableTrafficType$fNFDataTrafficType$fFromTextTrafficType$fToTextTrafficType$fToByteStringTrafficType$fToLogTrafficType$fToHeaderTrafficType$fToQueryTrafficType$fFromJSONTrafficType$fFromJSONKeyTrafficType$fToJSONTrafficType$fToJSONKeyTrafficType$fFromXMLTrafficType$fToXMLTrafficTypeTrafficPatternTrafficPattern'$sel:phases:TrafficPattern' $sel:trafficType:TrafficPattern'newTrafficPatterntrafficPattern_phasestrafficPattern_trafficType$fToJSONTrafficPattern$fNFDataTrafficPattern$fHashableTrafficPattern$fFromJSONTrafficPattern$fEqTrafficPattern$fReadTrafficPattern$fShowTrafficPattern$fGenericTrafficPatternRecommendationJobInputConfigRecommendationJobInputConfig'2$sel:containerConfig:RecommendationJobInputConfig'9$sel:endpointConfigurations:RecommendationJobInputConfig',$sel:endpoints:RecommendationJobInputConfig'7$sel:jobDurationInSeconds:RecommendationJobInputConfig'0$sel:resourceLimit:RecommendationJobInputConfig'1$sel:trafficPattern:RecommendationJobInputConfig'1$sel:volumeKmsKeyId:RecommendationJobInputConfig',$sel:vpcConfig:RecommendationJobInputConfig'9$sel:modelPackageVersionArn:RecommendationJobInputConfig'newRecommendationJobInputConfig,recommendationJobInputConfig_containerConfig3recommendationJobInputConfig_endpointConfigurations&recommendationJobInputConfig_endpoints1recommendationJobInputConfig_jobDurationInSeconds*recommendationJobInputConfig_resourceLimit+recommendationJobInputConfig_trafficPattern+recommendationJobInputConfig_volumeKmsKeyId&recommendationJobInputConfig_vpcConfig3recommendationJobInputConfig_modelPackageVersionArn$$fToJSONRecommendationJobInputConfig$$fNFDataRecommendationJobInputConfig&$fHashableRecommendationJobInputConfig&$fFromJSONRecommendationJobInputConfig $fEqRecommendationJobInputConfig"$fReadRecommendationJobInputConfig"$fShowRecommendationJobInputConfig%$fGenericRecommendationJobInputConfigTrainingInputModeTrainingInputMode'fromTrainingInputModeTrainingInputMode_PipeTrainingInputMode_FileTrainingInputMode_FastFile$fShowTrainingInputMode$fReadTrainingInputMode$fEqTrainingInputMode$fOrdTrainingInputMode$fGenericTrainingInputMode$fHashableTrainingInputMode$fNFDataTrainingInputMode$fFromTextTrainingInputMode$fToTextTrainingInputMode$fToByteStringTrainingInputMode$fToLogTrainingInputMode$fToHeaderTrainingInputMode$fToQueryTrainingInputMode$fFromJSONTrainingInputMode$fFromJSONKeyTrainingInputMode$fToJSONTrainingInputMode$fToJSONKeyTrainingInputMode$fFromXMLTrainingInputMode$fToXMLTrainingInputMode$HyperParameterAlgorithmSpecification%HyperParameterAlgorithmSpecification'8$sel:algorithmName:HyperParameterAlgorithmSpecification'<$sel:metricDefinitions:HyperParameterAlgorithmSpecification'8$sel:trainingImage:HyperParameterAlgorithmSpecification'<$sel:trainingInputMode:HyperParameterAlgorithmSpecification''newHyperParameterAlgorithmSpecification2hyperParameterAlgorithmSpecification_algorithmName6hyperParameterAlgorithmSpecification_metricDefinitions2hyperParameterAlgorithmSpecification_trainingImage6hyperParameterAlgorithmSpecification_trainingInputMode,$fToJSONHyperParameterAlgorithmSpecification,$fNFDataHyperParameterAlgorithmSpecification.$fHashableHyperParameterAlgorithmSpecification.$fFromJSONHyperParameterAlgorithmSpecification($fEqHyperParameterAlgorithmSpecification*$fReadHyperParameterAlgorithmSpecification*$fShowHyperParameterAlgorithmSpecification-$fGenericHyperParameterAlgorithmSpecificationChannelSpecificationChannelSpecification'&$sel:description:ChannelSpecification'%$sel:isRequired:ChannelSpecification'4$sel:supportedCompressionTypes:ChannelSpecification'$sel:name:ChannelSpecification'0$sel:supportedContentTypes:ChannelSpecification'.$sel:supportedInputModes:ChannelSpecification'newChannelSpecification channelSpecification_descriptionchannelSpecification_isRequired.channelSpecification_supportedCompressionTypeschannelSpecification_name*channelSpecification_supportedContentTypes(channelSpecification_supportedInputModes$fToJSONChannelSpecification$fNFDataChannelSpecification$fHashableChannelSpecification$fFromJSONChannelSpecification$fEqChannelSpecification$fReadChannelSpecification$fShowChannelSpecification$fGenericChannelSpecificationChannelChannel'$sel:compressionType:Channel'$sel:contentType:Channel'$sel:inputMode:Channel'$sel:recordWrapperType:Channel'$sel:shuffleConfig:Channel'$sel:channelName:Channel'$sel:dataSource:Channel' newChannelchannel_compressionTypechannel_contentTypechannel_inputModechannel_recordWrapperTypechannel_shuffleConfigchannel_channelNamechannel_dataSource$fToJSONChannel$fNFDataChannel$fHashableChannel$fFromJSONChannel $fEqChannel $fReadChannel $fShowChannel$fGenericChannelAlgorithmSpecificationAlgorithmSpecification'*$sel:algorithmName:AlgorithmSpecification'/$sel:containerArguments:AlgorithmSpecification'0$sel:containerEntrypoint:AlgorithmSpecification'=$sel:enableSageMakerMetricsTimeSeries:AlgorithmSpecification'.$sel:metricDefinitions:AlgorithmSpecification'*$sel:trainingImage:AlgorithmSpecification'.$sel:trainingInputMode:AlgorithmSpecification'newAlgorithmSpecification$algorithmSpecification_algorithmName)algorithmSpecification_containerArguments*algorithmSpecification_containerEntrypoint7algorithmSpecification_enableSageMakerMetricsTimeSeries(algorithmSpecification_metricDefinitions$algorithmSpecification_trainingImage(algorithmSpecification_trainingInputMode$fToJSONAlgorithmSpecification$fNFDataAlgorithmSpecification $fHashableAlgorithmSpecification $fFromJSONAlgorithmSpecification$fEqAlgorithmSpecification$fReadAlgorithmSpecification$fShowAlgorithmSpecification$fGenericAlgorithmSpecificationTrainingInstanceTypeTrainingInstanceType'fromTrainingInstanceType%TrainingInstanceType_Ml_trn1_32xlarge$TrainingInstanceType_Ml_trn1_2xlarge$TrainingInstanceType_Ml_p4d_24xlarge%TrainingInstanceType_Ml_p3dn_24xlarge"TrainingInstanceType_Ml_p3_8xlarge"TrainingInstanceType_Ml_p3_2xlarge#TrainingInstanceType_Ml_p3_16xlarge!TrainingInstanceType_Ml_p2_xlarge"TrainingInstanceType_Ml_p2_8xlarge#TrainingInstanceType_Ml_p2_16xlarge!TrainingInstanceType_Ml_m5_xlarge TrainingInstanceType_Ml_m5_large"TrainingInstanceType_Ml_m5_4xlarge"TrainingInstanceType_Ml_m5_2xlarge#TrainingInstanceType_Ml_m5_24xlarge#TrainingInstanceType_Ml_m5_12xlarge!TrainingInstanceType_Ml_m4_xlarge"TrainingInstanceType_Ml_m4_4xlarge"TrainingInstanceType_Ml_m4_2xlarge#TrainingInstanceType_Ml_m4_16xlarge#TrainingInstanceType_Ml_m4_10xlarge!TrainingInstanceType_Ml_g5_xlarge"TrainingInstanceType_Ml_g5_8xlarge"TrainingInstanceType_Ml_g5_4xlarge#TrainingInstanceType_Ml_g5_48xlarge"TrainingInstanceType_Ml_g5_2xlarge#TrainingInstanceType_Ml_g5_24xlarge#TrainingInstanceType_Ml_g5_16xlarge#TrainingInstanceType_Ml_g5_12xlarge#TrainingInstanceType_Ml_g4dn_xlarge$TrainingInstanceType_Ml_g4dn_8xlarge$TrainingInstanceType_Ml_g4dn_4xlarge$TrainingInstanceType_Ml_g4dn_2xlarge%TrainingInstanceType_Ml_g4dn_16xlarge%TrainingInstanceType_Ml_g4dn_12xlarge"TrainingInstanceType_Ml_c5n_xlarge#TrainingInstanceType_Ml_c5n_9xlarge#TrainingInstanceType_Ml_c5n_4xlarge#TrainingInstanceType_Ml_c5n_2xlarge$TrainingInstanceType_Ml_c5n_18xlarge!TrainingInstanceType_Ml_c5_xlarge"TrainingInstanceType_Ml_c5_9xlarge"TrainingInstanceType_Ml_c5_4xlarge"TrainingInstanceType_Ml_c5_2xlarge#TrainingInstanceType_Ml_c5_18xlarge!TrainingInstanceType_Ml_c4_xlarge"TrainingInstanceType_Ml_c4_8xlarge"TrainingInstanceType_Ml_c4_4xlarge"TrainingInstanceType_Ml_c4_2xlarge$fShowTrainingInstanceType$fReadTrainingInstanceType$fEqTrainingInstanceType$fOrdTrainingInstanceType$fGenericTrainingInstanceType$fHashableTrainingInstanceType$fNFDataTrainingInstanceType$fFromTextTrainingInstanceType$fToTextTrainingInstanceType"$fToByteStringTrainingInstanceType$fToLogTrainingInstanceType$fToHeaderTrainingInstanceType$fToQueryTrainingInstanceType$fFromJSONTrainingInstanceType!$fFromJSONKeyTrainingInstanceType$fToJSONTrainingInstanceType$fToJSONKeyTrainingInstanceType$fFromXMLTrainingInstanceType$fToXMLTrainingInstanceType InstanceGroupInstanceGroup' $sel:instanceType:InstanceGroup'!$sel:instanceCount:InstanceGroup'%$sel:instanceGroupName:InstanceGroup'newInstanceGroupinstanceGroup_instanceTypeinstanceGroup_instanceCountinstanceGroup_instanceGroupName$fToJSONInstanceGroup$fNFDataInstanceGroup$fHashableInstanceGroup$fFromJSONInstanceGroup$fEqInstanceGroup$fReadInstanceGroup$fShowInstanceGroup$fGenericInstanceGroupResourceConfigResourceConfig'"$sel:instanceCount:ResourceConfig'#$sel:instanceGroups:ResourceConfig'!$sel:instanceType:ResourceConfig'-$sel:keepAlivePeriodInSeconds:ResourceConfig'#$sel:volumeKmsKeyId:ResourceConfig'#$sel:volumeSizeInGB:ResourceConfig'newResourceConfigresourceConfig_instanceCountresourceConfig_instanceGroupsresourceConfig_instanceType'resourceConfig_keepAlivePeriodInSecondsresourceConfig_volumeKmsKeyIdresourceConfig_volumeSizeInGB$fToJSONResourceConfig$fNFDataResourceConfig$fHashableResourceConfig$fFromJSONResourceConfig$fEqResourceConfig$fReadResourceConfig$fShowResourceConfig$fGenericResourceConfig"HyperParameterTuningInstanceConfig#HyperParameterTuningInstanceConfig'5$sel:instanceType:HyperParameterTuningInstanceConfig'6$sel:instanceCount:HyperParameterTuningInstanceConfig'7$sel:volumeSizeInGB:HyperParameterTuningInstanceConfig'%newHyperParameterTuningInstanceConfig/hyperParameterTuningInstanceConfig_instanceType0hyperParameterTuningInstanceConfig_instanceCount1hyperParameterTuningInstanceConfig_volumeSizeInGB*$fToJSONHyperParameterTuningInstanceConfig*$fNFDataHyperParameterTuningInstanceConfig,$fHashableHyperParameterTuningInstanceConfig,$fFromJSONHyperParameterTuningInstanceConfig&$fEqHyperParameterTuningInstanceConfig($fReadHyperParameterTuningInstanceConfig($fShowHyperParameterTuningInstanceConfig+$fGenericHyperParameterTuningInstanceConfig"HyperParameterTuningResourceConfig#HyperParameterTuningResourceConfig';$sel:allocationStrategy:HyperParameterTuningResourceConfig'8$sel:instanceConfigs:HyperParameterTuningResourceConfig'6$sel:instanceCount:HyperParameterTuningResourceConfig'5$sel:instanceType:HyperParameterTuningResourceConfig'7$sel:volumeKmsKeyId:HyperParameterTuningResourceConfig'7$sel:volumeSizeInGB:HyperParameterTuningResourceConfig'%newHyperParameterTuningResourceConfig5hyperParameterTuningResourceConfig_allocationStrategy2hyperParameterTuningResourceConfig_instanceConfigs0hyperParameterTuningResourceConfig_instanceCount/hyperParameterTuningResourceConfig_instanceType1hyperParameterTuningResourceConfig_volumeKmsKeyId1hyperParameterTuningResourceConfig_volumeSizeInGB*$fToJSONHyperParameterTuningResourceConfig*$fNFDataHyperParameterTuningResourceConfig,$fHashableHyperParameterTuningResourceConfig,$fFromJSONHyperParameterTuningResourceConfig&$fEqHyperParameterTuningResourceConfig($fReadHyperParameterTuningResourceConfig($fShowHyperParameterTuningResourceConfig+$fGenericHyperParameterTuningResourceConfigTrainingJobDefinitionTrainingJobDefinition'+$sel:hyperParameters:TrainingJobDefinition'-$sel:trainingInputMode:TrainingJobDefinition'+$sel:inputDataConfig:TrainingJobDefinition',$sel:outputDataConfig:TrainingJobDefinition'*$sel:resourceConfig:TrainingJobDefinition'-$sel:stoppingCondition:TrainingJobDefinition'newTrainingJobDefinition%trainingJobDefinition_hyperParameters'trainingJobDefinition_trainingInputMode%trainingJobDefinition_inputDataConfig&trainingJobDefinition_outputDataConfig$trainingJobDefinition_resourceConfig'trainingJobDefinition_stoppingCondition$fToJSONTrainingJobDefinition$fNFDataTrainingJobDefinition$fHashableTrainingJobDefinition$fFromJSONTrainingJobDefinition$fEqTrainingJobDefinition$fReadTrainingJobDefinition$fShowTrainingJobDefinition$fGenericTrainingJobDefinitionTrainingJobEarlyStoppingTypeTrainingJobEarlyStoppingType' fromTrainingJobEarlyStoppingType TrainingJobEarlyStoppingType_Off!TrainingJobEarlyStoppingType_Auto"$fShowTrainingJobEarlyStoppingType"$fReadTrainingJobEarlyStoppingType $fEqTrainingJobEarlyStoppingType!$fOrdTrainingJobEarlyStoppingType%$fGenericTrainingJobEarlyStoppingType&$fHashableTrainingJobEarlyStoppingType$$fNFDataTrainingJobEarlyStoppingType&$fFromTextTrainingJobEarlyStoppingType$$fToTextTrainingJobEarlyStoppingType*$fToByteStringTrainingJobEarlyStoppingType#$fToLogTrainingJobEarlyStoppingType&$fToHeaderTrainingJobEarlyStoppingType%$fToQueryTrainingJobEarlyStoppingType&$fFromJSONTrainingJobEarlyStoppingType)$fFromJSONKeyTrainingJobEarlyStoppingType$$fToJSONTrainingJobEarlyStoppingType'$fToJSONKeyTrainingJobEarlyStoppingType%$fFromXMLTrainingJobEarlyStoppingType#$fToXMLTrainingJobEarlyStoppingTypeTrainingJobSortByOptionsTrainingJobSortByOptions'fromTrainingJobSortByOptionsTrainingJobSortByOptions_StatusTrainingJobSortByOptions_Name2TrainingJobSortByOptions_FinalObjectiveMetricValue%TrainingJobSortByOptions_CreationTime$fShowTrainingJobSortByOptions$fReadTrainingJobSortByOptions$fEqTrainingJobSortByOptions$fOrdTrainingJobSortByOptions!$fGenericTrainingJobSortByOptions"$fHashableTrainingJobSortByOptions $fNFDataTrainingJobSortByOptions"$fFromTextTrainingJobSortByOptions $fToTextTrainingJobSortByOptions&$fToByteStringTrainingJobSortByOptions$fToLogTrainingJobSortByOptions"$fToHeaderTrainingJobSortByOptions!$fToQueryTrainingJobSortByOptions"$fFromJSONTrainingJobSortByOptions%$fFromJSONKeyTrainingJobSortByOptions $fToJSONTrainingJobSortByOptions#$fToJSONKeyTrainingJobSortByOptions!$fFromXMLTrainingJobSortByOptions$fToXMLTrainingJobSortByOptionsTrainingJobStatusTrainingJobStatus'fromTrainingJobStatusTrainingJobStatus_StoppingTrainingJobStatus_StoppedTrainingJobStatus_InProgressTrainingJobStatus_FailedTrainingJobStatus_Completed$fShowTrainingJobStatus$fReadTrainingJobStatus$fEqTrainingJobStatus$fOrdTrainingJobStatus$fGenericTrainingJobStatus$fHashableTrainingJobStatus$fNFDataTrainingJobStatus$fFromTextTrainingJobStatus$fToTextTrainingJobStatus$fToByteStringTrainingJobStatus$fToLogTrainingJobStatus$fToHeaderTrainingJobStatus$fToQueryTrainingJobStatus$fFromJSONTrainingJobStatus$fFromJSONKeyTrainingJobStatus$fToJSONTrainingJobStatus$fToJSONKeyTrainingJobStatus$fFromXMLTrainingJobStatus$fToXMLTrainingJobStatus HyperParameterTrainingJobSummary!HyperParameterTrainingJobSummary'4$sel:failureReason:HyperParameterTrainingJobSummary'$sel:finalHyperParameterTuningJobObjectiveMetric:HyperParameterTrainingJobSummary'6$sel:objectiveStatus:HyperParameterTrainingJobSummary'6$sel:trainingEndTime:HyperParameterTrainingJobSummary'$sel:trainingJobDefinitionName:HyperParameterTrainingJobSummary'8$sel:trainingStartTime:HyperParameterTrainingJobSummary'4$sel:tuningJobName:HyperParameterTrainingJobSummary'6$sel:trainingJobName:HyperParameterTrainingJobSummary'5$sel:trainingJobArn:HyperParameterTrainingJobSummary'3$sel:creationTime:HyperParameterTrainingJobSummary'8$sel:trainingJobStatus:HyperParameterTrainingJobSummary';$sel:tunedHyperParameters:HyperParameterTrainingJobSummary'#newHyperParameterTrainingJobSummary.hyperParameterTrainingJobSummary_failureReasonhyperParameterTrainingJobSummary_finalHyperParameterTuningJobObjectiveMetric0hyperParameterTrainingJobSummary_objectiveStatus0hyperParameterTrainingJobSummary_trainingEndTime:hyperParameterTrainingJobSummary_trainingJobDefinitionName2hyperParameterTrainingJobSummary_trainingStartTime.hyperParameterTrainingJobSummary_tuningJobName0hyperParameterTrainingJobSummary_trainingJobName/hyperParameterTrainingJobSummary_trainingJobArn-hyperParameterTrainingJobSummary_creationTime2hyperParameterTrainingJobSummary_trainingJobStatus5hyperParameterTrainingJobSummary_tunedHyperParameters($fNFDataHyperParameterTrainingJobSummary*$fHashableHyperParameterTrainingJobSummary*$fFromJSONHyperParameterTrainingJobSummary$$fEqHyperParameterTrainingJobSummary&$fReadHyperParameterTrainingJobSummary&$fShowHyperParameterTrainingJobSummary)$fGenericHyperParameterTrainingJobSummaryTrainingJobStatusCountersTrainingJobStatusCounters')$sel:completed:TrainingJobStatusCounters'*$sel:inProgress:TrainingJobStatusCounters'1$sel:nonRetryableError:TrainingJobStatusCounters'.$sel:retryableError:TrainingJobStatusCounters''$sel:stopped:TrainingJobStatusCounters'newTrainingJobStatusCounters#trainingJobStatusCounters_completed$trainingJobStatusCounters_inProgress+trainingJobStatusCounters_nonRetryableError(trainingJobStatusCounters_retryableError!trainingJobStatusCounters_stopped!$fNFDataTrainingJobStatusCounters#$fHashableTrainingJobStatusCounters#$fFromJSONTrainingJobStatusCounters$fEqTrainingJobStatusCounters$fReadTrainingJobStatusCounters$fShowTrainingJobStatusCounters"$fGenericTrainingJobStatusCountersHyperParameterTuningJobSummaryHyperParameterTuningJobSummary'$sel:hyperParameterTuningEndTime:HyperParameterTuningJobSummary'5$sel:lastModifiedTime:HyperParameterTuningJobSummary'3$sel:resourceLimits:HyperParameterTuningJobSummary'$sel:hyperParameterTuningJobName:HyperParameterTuningJobSummary'?$sel:hyperParameterTuningJobArn:HyperParameterTuningJobSummary'$sel:hyperParameterTuningJobStatus:HyperParameterTuningJobSummary'-$sel:strategy:HyperParameterTuningJobSummary'1$sel:creationTime:HyperParameterTuningJobSummary'>$sel:trainingJobStatusCounters:HyperParameterTuningJobSummary'<$sel:objectiveStatusCounters:HyperParameterTuningJobSummary'!newHyperParameterTuningJobSummary:hyperParameterTuningJobSummary_hyperParameterTuningEndTime/hyperParameterTuningJobSummary_lastModifiedTime-hyperParameterTuningJobSummary_resourceLimits:hyperParameterTuningJobSummary_hyperParameterTuningJobName9hyperParameterTuningJobSummary_hyperParameterTuningJobArn$sel:supportedTuningJobObjectiveMetrics:TrainingSpecification'7$sel:supportsDistributedTraining:TrainingSpecification'/$sel:trainingImageDigest:TrainingSpecification')$sel:trainingImage:TrainingSpecification':$sel:supportedTrainingInstanceTypes:TrainingSpecification',$sel:trainingChannels:TrainingSpecification'newTrainingSpecification'trainingSpecification_metricDefinitions.trainingSpecification_supportedHyperParameters8trainingSpecification_supportedTuningJobObjectiveMetrics1trainingSpecification_supportsDistributedTraining)trainingSpecification_trainingImageDigest#trainingSpecification_trainingImage4trainingSpecification_supportedTrainingInstanceTypes&trainingSpecification_trainingChannels$fToJSONTrainingSpecification$fNFDataTrainingSpecification$fHashableTrainingSpecification$fFromJSONTrainingSpecification$fEqTrainingSpecification$fReadTrainingSpecification$fShowTrainingSpecification$fGenericTrainingSpecificationTransformInstanceTypeTransformInstanceType'fromTransformInstanceType#TransformInstanceType_Ml_p3_8xlarge#TransformInstanceType_Ml_p3_2xlarge$TransformInstanceType_Ml_p3_16xlarge"TransformInstanceType_Ml_p2_xlarge#TransformInstanceType_Ml_p2_8xlarge$TransformInstanceType_Ml_p2_16xlarge"TransformInstanceType_Ml_m5_xlarge!TransformInstanceType_Ml_m5_large#TransformInstanceType_Ml_m5_4xlarge#TransformInstanceType_Ml_m5_2xlarge$TransformInstanceType_Ml_m5_24xlarge$TransformInstanceType_Ml_m5_12xlarge"TransformInstanceType_Ml_m4_xlarge#TransformInstanceType_Ml_m4_4xlarge#TransformInstanceType_Ml_m4_2xlarge$TransformInstanceType_Ml_m4_16xlarge$TransformInstanceType_Ml_m4_10xlarge$TransformInstanceType_Ml_g4dn_xlarge%TransformInstanceType_Ml_g4dn_8xlarge%TransformInstanceType_Ml_g4dn_4xlarge%TransformInstanceType_Ml_g4dn_2xlarge&TransformInstanceType_Ml_g4dn_16xlarge&TransformInstanceType_Ml_g4dn_12xlarge"TransformInstanceType_Ml_c5_xlarge#TransformInstanceType_Ml_c5_9xlarge#TransformInstanceType_Ml_c5_4xlarge#TransformInstanceType_Ml_c5_2xlarge$TransformInstanceType_Ml_c5_18xlarge"TransformInstanceType_Ml_c4_xlarge#TransformInstanceType_Ml_c4_8xlarge#TransformInstanceType_Ml_c4_4xlarge#TransformInstanceType_Ml_c4_2xlarge$fShowTransformInstanceType$fReadTransformInstanceType$fEqTransformInstanceType$fOrdTransformInstanceType$fGenericTransformInstanceType$fHashableTransformInstanceType$fNFDataTransformInstanceType$fFromTextTransformInstanceType$fToTextTransformInstanceType#$fToByteStringTransformInstanceType$fToLogTransformInstanceType$fToHeaderTransformInstanceType$fToQueryTransformInstanceType$fFromJSONTransformInstanceType"$fFromJSONKeyTransformInstanceType$fToJSONTransformInstanceType $fToJSONKeyTransformInstanceType$fFromXMLTransformInstanceType$fToXMLTransformInstanceTypeInferenceSpecificationInferenceSpecification'$sel:supportedRealtimeInferenceInstanceTypes:InferenceSpecification'<$sel:supportedTransformInstanceTypes:InferenceSpecification''$sel:containers:InferenceSpecification'2$sel:supportedContentTypes:InferenceSpecification'7$sel:supportedResponseMIMETypes:InferenceSpecification'newInferenceSpecification>inferenceSpecification_supportedRealtimeInferenceInstanceTypes6inferenceSpecification_supportedTransformInstanceTypes!inferenceSpecification_containers,inferenceSpecification_supportedContentTypes1inferenceSpecification_supportedResponseMIMETypes$fToJSONInferenceSpecification$fNFDataInferenceSpecification $fHashableInferenceSpecification $fFromJSONInferenceSpecification$fEqInferenceSpecification$fReadInferenceSpecification$fShowInferenceSpecification$fGenericInferenceSpecification BatchDescribeModelPackageSummary!BatchDescribeModelPackageSummary':$sel:modelApprovalStatus:BatchDescribeModelPackageSummary'>$sel:modelPackageDescription:BatchDescribeModelPackageSummary':$sel:modelPackageVersion:BatchDescribeModelPackageSummary'<$sel:modelPackageGroupName:BatchDescribeModelPackageSummary'6$sel:modelPackageArn:BatchDescribeModelPackageSummary'3$sel:creationTime:BatchDescribeModelPackageSummary'=$sel:inferenceSpecification:BatchDescribeModelPackageSummary'9$sel:modelPackageStatus:BatchDescribeModelPackageSummary'#newBatchDescribeModelPackageSummary4batchDescribeModelPackageSummary_modelApprovalStatus8batchDescribeModelPackageSummary_modelPackageDescription4batchDescribeModelPackageSummary_modelPackageVersion6batchDescribeModelPackageSummary_modelPackageGroupName0batchDescribeModelPackageSummary_modelPackageArn-batchDescribeModelPackageSummary_creationTime7batchDescribeModelPackageSummary_inferenceSpecification3batchDescribeModelPackageSummary_modelPackageStatus($fNFDataBatchDescribeModelPackageSummary*$fHashableBatchDescribeModelPackageSummary*$fFromJSONBatchDescribeModelPackageSummary$$fEqBatchDescribeModelPackageSummary&$fReadBatchDescribeModelPackageSummary&$fShowBatchDescribeModelPackageSummary)$fGenericBatchDescribeModelPackageSummary*AdditionalInferenceSpecificationDefinition+AdditionalInferenceSpecificationDefinition'<$sel:description:AdditionalInferenceSpecificationDefinition'$sel:supportedContentTypes:AdditionalInferenceSpecificationDefinition'$sel:supportedRealtimeInferenceInstanceTypes:AdditionalInferenceSpecificationDefinition'$sel:supportedResponseMIMETypes:AdditionalInferenceSpecificationDefinition'$sel:supportedTransformInstanceTypes:AdditionalInferenceSpecificationDefinition'5$sel:name:AdditionalInferenceSpecificationDefinition';$sel:containers:AdditionalInferenceSpecificationDefinition'-newAdditionalInferenceSpecificationDefinition6additionalInferenceSpecificationDefinition_descriptionadditionalInferenceSpecificationDefinition_supportedContentTypesadditionalInferenceSpecificationDefinition_supportedRealtimeInferenceInstanceTypesadditionalInferenceSpecificationDefinition_supportedResponseMIMETypesadditionalInferenceSpecificationDefinition_supportedTransformInstanceTypes/additionalInferenceSpecificationDefinition_name5additionalInferenceSpecificationDefinition_containers2$fToJSONAdditionalInferenceSpecificationDefinition2$fNFDataAdditionalInferenceSpecificationDefinition4$fHashableAdditionalInferenceSpecificationDefinition4$fFromJSONAdditionalInferenceSpecificationDefinition.$fEqAdditionalInferenceSpecificationDefinition0$fReadAdditionalInferenceSpecificationDefinition0$fShowAdditionalInferenceSpecificationDefinition3$fGenericAdditionalInferenceSpecificationDefinitionTransformJobStatusTransformJobStatus'fromTransformJobStatusTransformJobStatus_StoppingTransformJobStatus_StoppedTransformJobStatus_InProgressTransformJobStatus_FailedTransformJobStatus_Completed$fShowTransformJobStatus$fReadTransformJobStatus$fEqTransformJobStatus$fOrdTransformJobStatus$fGenericTransformJobStatus$fHashableTransformJobStatus$fNFDataTransformJobStatus$fFromTextTransformJobStatus$fToTextTransformJobStatus $fToByteStringTransformJobStatus$fToLogTransformJobStatus$fToHeaderTransformJobStatus$fToQueryTransformJobStatus$fFromJSONTransformJobStatus$fFromJSONKeyTransformJobStatus$fToJSONTransformJobStatus$fToJSONKeyTransformJobStatus$fFromXMLTransformJobStatus$fToXMLTransformJobStatusTransformJobStepMetadataTransformJobStepMetadata'"$sel:arn:TransformJobStepMetadata'newTransformJobStepMetadatatransformJobStepMetadata_arn $fNFDataTransformJobStepMetadata"$fHashableTransformJobStepMetadata"$fFromJSONTransformJobStepMetadata$fEqTransformJobStepMetadata$fReadTransformJobStepMetadata$fShowTransformJobStepMetadata!$fGenericTransformJobStepMetadataTransformJobSummaryTransformJobSummary''$sel:failureReason:TransformJobSummary'*$sel:lastModifiedTime:TransformJobSummary'*$sel:transformEndTime:TransformJobSummary'*$sel:transformJobName:TransformJobSummary')$sel:transformJobArn:TransformJobSummary'&$sel:creationTime:TransformJobSummary',$sel:transformJobStatus:TransformJobSummary'newTransformJobSummary!transformJobSummary_failureReason$transformJobSummary_lastModifiedTime$transformJobSummary_transformEndTime$transformJobSummary_transformJobName#transformJobSummary_transformJobArn transformJobSummary_creationTime&transformJobSummary_transformJobStatus$fNFDataTransformJobSummary$fHashableTransformJobSummary$fFromJSONTransformJobSummary$fEqTransformJobSummary$fReadTransformJobSummary$fShowTransformJobSummary$fGenericTransformJobSummaryTransformOutputTransformOutput'$sel:accept:TransformOutput'"$sel:assembleWith:TransformOutput'$sel:kmsKeyId:TransformOutput'"$sel:s3OutputPath:TransformOutput'newTransformOutputtransformOutput_accepttransformOutput_assembleWithtransformOutput_kmsKeyIdtransformOutput_s3OutputPath$fToJSONTransformOutput$fNFDataTransformOutput$fHashableTransformOutput$fFromJSONTransformOutput$fEqTransformOutput$fReadTransformOutput$fShowTransformOutput$fGenericTransformOutputTransformResourcesTransformResources''$sel:volumeKmsKeyId:TransformResources'%$sel:instanceType:TransformResources'&$sel:instanceCount:TransformResources'newTransformResources!transformResources_volumeKmsKeyIdtransformResources_instanceType transformResources_instanceCount$fToJSONTransformResources$fNFDataTransformResources$fHashableTransformResources$fFromJSONTransformResources$fEqTransformResources$fReadTransformResources$fShowTransformResources$fGenericTransformResourcesTransformS3DataSourceTransformS3DataSource'&$sel:s3DataType:TransformS3DataSource'!$sel:s3Uri:TransformS3DataSource'newTransformS3DataSource transformS3DataSource_s3DataTypetransformS3DataSource_s3Uri$fToJSONTransformS3DataSource$fNFDataTransformS3DataSource$fHashableTransformS3DataSource$fFromJSONTransformS3DataSource$fEqTransformS3DataSource$fReadTransformS3DataSource$fShowTransformS3DataSource$fGenericTransformS3DataSourceTransformDataSourceTransformDataSource'&$sel:s3DataSource:TransformDataSource'newTransformDataSource transformDataSource_s3DataSource$fToJSONTransformDataSource$fNFDataTransformDataSource$fHashableTransformDataSource$fFromJSONTransformDataSource$fEqTransformDataSource$fReadTransformDataSource$fShowTransformDataSource$fGenericTransformDataSourceTransformInputTransformInput'$$sel:compressionType:TransformInput' $sel:contentType:TransformInput'$sel:splitType:TransformInput'$sel:dataSource:TransformInput'newTransformInputtransformInput_compressionTypetransformInput_contentTypetransformInput_splitTypetransformInput_dataSource$fToJSONTransformInput$fNFDataTransformInput$fHashableTransformInput$fFromJSONTransformInput$fEqTransformInput$fReadTransformInput$fShowTransformInput$fGenericTransformInputTransformJobDefinitionTransformJobDefinition'*$sel:batchStrategy:TransformJobDefinition'($sel:environment:TransformJobDefinition'4$sel:maxConcurrentTransforms:TransformJobDefinition'+$sel:maxPayloadInMB:TransformJobDefinition'+$sel:transformInput:TransformJobDefinition',$sel:transformOutput:TransformJobDefinition'/$sel:transformResources:TransformJobDefinition'newTransformJobDefinition$transformJobDefinition_batchStrategy"transformJobDefinition_environment.transformJobDefinition_maxConcurrentTransforms%transformJobDefinition_maxPayloadInMB%transformJobDefinition_transformInput&transformJobDefinition_transformOutput)transformJobDefinition_transformResources$fToJSONTransformJobDefinition$fNFDataTransformJobDefinition $fHashableTransformJobDefinition $fFromJSONTransformJobDefinition$fEqTransformJobDefinition$fReadTransformJobDefinition$fShowTransformJobDefinition$fGenericTransformJobDefinitionModelPackageValidationProfileModelPackageValidationProfile'/$sel:profileName:ModelPackageValidationProfile':$sel:transformJobDefinition:ModelPackageValidationProfile' newModelPackageValidationProfile)modelPackageValidationProfile_profileName4modelPackageValidationProfile_transformJobDefinition%$fToJSONModelPackageValidationProfile%$fNFDataModelPackageValidationProfile'$fHashableModelPackageValidationProfile'$fFromJSONModelPackageValidationProfile!$fEqModelPackageValidationProfile#$fReadModelPackageValidationProfile#$fShowModelPackageValidationProfile&$fGenericModelPackageValidationProfile#ModelPackageValidationSpecification$ModelPackageValidationSpecification'8$sel:validationRole:ModelPackageValidationSpecification'<$sel:validationProfiles:ModelPackageValidationSpecification'&newModelPackageValidationSpecification2modelPackageValidationSpecification_validationRole6modelPackageValidationSpecification_validationProfiles+$fToJSONModelPackageValidationSpecification+$fNFDataModelPackageValidationSpecification-$fHashableModelPackageValidationSpecification-$fFromJSONModelPackageValidationSpecification'$fEqModelPackageValidationSpecification)$fReadModelPackageValidationSpecification)$fShowModelPackageValidationSpecification,$fGenericModelPackageValidationSpecificationAlgorithmValidationProfileAlgorithmValidationProfile'7$sel:transformJobDefinition:AlgorithmValidationProfile',$sel:profileName:AlgorithmValidationProfile'6$sel:trainingJobDefinition:AlgorithmValidationProfile'newAlgorithmValidationProfile1algorithmValidationProfile_transformJobDefinition&algorithmValidationProfile_profileName0algorithmValidationProfile_trainingJobDefinition"$fToJSONAlgorithmValidationProfile"$fNFDataAlgorithmValidationProfile$$fHashableAlgorithmValidationProfile$$fFromJSONAlgorithmValidationProfile$fEqAlgorithmValidationProfile $fReadAlgorithmValidationProfile $fShowAlgorithmValidationProfile#$fGenericAlgorithmValidationProfile AlgorithmValidationSpecification!AlgorithmValidationSpecification'5$sel:validationRole:AlgorithmValidationSpecification'9$sel:validationProfiles:AlgorithmValidationSpecification'#newAlgorithmValidationSpecification/algorithmValidationSpecification_validationRole3algorithmValidationSpecification_validationProfiles($fToJSONAlgorithmValidationSpecification($fNFDataAlgorithmValidationSpecification*$fHashableAlgorithmValidationSpecification*$fFromJSONAlgorithmValidationSpecification$$fEqAlgorithmValidationSpecification&$fReadAlgorithmValidationSpecification&$fShowAlgorithmValidationSpecification)$fGenericAlgorithmValidationSpecification TransformJob TransformJob'$sel:autoMLJobArn:TransformJob' $sel:batchStrategy:TransformJob'$sel:creationTime:TransformJob'!$sel:dataProcessing:TransformJob'$sel:environment:TransformJob'#$sel:experimentConfig:TransformJob' $sel:failureReason:TransformJob'!$sel:labelingJobArn:TransformJob'*$sel:maxConcurrentTransforms:TransformJob'!$sel:maxPayloadInMB:TransformJob'$$sel:modelClientConfig:TransformJob'$sel:modelName:TransformJob'$sel:tags:TransformJob'#$sel:transformEndTime:TransformJob'!$sel:transformInput:TransformJob'"$sel:transformJobArn:TransformJob'#$sel:transformJobName:TransformJob'%$sel:transformJobStatus:TransformJob'"$sel:transformOutput:TransformJob'%$sel:transformResources:TransformJob'%$sel:transformStartTime:TransformJob'newTransformJobtransformJob_autoMLJobArntransformJob_batchStrategytransformJob_creationTimetransformJob_dataProcessingtransformJob_environmenttransformJob_experimentConfigtransformJob_failureReasontransformJob_labelingJobArn$transformJob_maxConcurrentTransformstransformJob_maxPayloadInMBtransformJob_modelClientConfigtransformJob_modelNametransformJob_tagstransformJob_transformEndTimetransformJob_transformInputtransformJob_transformJobArntransformJob_transformJobNametransformJob_transformJobStatustransformJob_transformOutputtransformJob_transformResourcestransformJob_transformStartTime$fNFDataTransformJob$fHashableTransformJob$fFromJSONTransformJob$fEqTransformJob$fReadTransformJob$fShowTransformJob$fGenericTransformJobTrialComponentArtifactTrialComponentArtifact'&$sel:mediaType:TrialComponentArtifact'"$sel:value:TrialComponentArtifact'newTrialComponentArtifact trialComponentArtifact_mediaTypetrialComponentArtifact_value$fToJSONTrialComponentArtifact$fNFDataTrialComponentArtifact $fHashableTrialComponentArtifact $fFromJSONTrialComponentArtifact$fEqTrialComponentArtifact$fReadTrialComponentArtifact$fShowTrialComponentArtifact$fGenericTrialComponentArtifactTrialComponentMetricSummaryTrialComponentMetricSummary'%$sel:avg:TrialComponentMetricSummary''$sel:count:TrialComponentMetricSummary'&$sel:last:TrialComponentMetricSummary'%$sel:max:TrialComponentMetricSummary',$sel:metricName:TrialComponentMetricSummary'%$sel:min:TrialComponentMetricSummary'+$sel:sourceArn:TrialComponentMetricSummary'($sel:stdDev:TrialComponentMetricSummary'+$sel:timeStamp:TrialComponentMetricSummary'newTrialComponentMetricSummarytrialComponentMetricSummary_avg!trialComponentMetricSummary_count trialComponentMetricSummary_lasttrialComponentMetricSummary_max&trialComponentMetricSummary_metricNametrialComponentMetricSummary_min%trialComponentMetricSummary_sourceArn"trialComponentMetricSummary_stdDev%trialComponentMetricSummary_timeStamp#$fNFDataTrialComponentMetricSummary%$fHashableTrialComponentMetricSummary%$fFromJSONTrialComponentMetricSummary$fEqTrialComponentMetricSummary!$fReadTrialComponentMetricSummary!$fShowTrialComponentMetricSummary$$fGenericTrialComponentMetricSummaryTrialComponentParameterValueTrialComponentParameterValue'.$sel:numberValue:TrialComponentParameterValue'.$sel:stringValue:TrialComponentParameterValue'newTrialComponentParameterValue(trialComponentParameterValue_numberValue(trialComponentParameterValue_stringValue$$fToJSONTrialComponentParameterValue$$fNFDataTrialComponentParameterValue&$fHashableTrialComponentParameterValue&$fFromJSONTrialComponentParameterValue $fEqTrialComponentParameterValue"$fReadTrialComponentParameterValue"$fShowTrialComponentParameterValue%$fGenericTrialComponentParameterValueTrialComponentPrimaryStatusTrialComponentPrimaryStatus'fromTrialComponentPrimaryStatus$TrialComponentPrimaryStatus_Stopping#TrialComponentPrimaryStatus_Stopped&TrialComponentPrimaryStatus_InProgress"TrialComponentPrimaryStatus_Failed%TrialComponentPrimaryStatus_Completed!$fShowTrialComponentPrimaryStatus!$fReadTrialComponentPrimaryStatus$fEqTrialComponentPrimaryStatus $fOrdTrialComponentPrimaryStatus$$fGenericTrialComponentPrimaryStatus%$fHashableTrialComponentPrimaryStatus#$fNFDataTrialComponentPrimaryStatus%$fFromTextTrialComponentPrimaryStatus#$fToTextTrialComponentPrimaryStatus)$fToByteStringTrialComponentPrimaryStatus"$fToLogTrialComponentPrimaryStatus%$fToHeaderTrialComponentPrimaryStatus$$fToQueryTrialComponentPrimaryStatus%$fFromJSONTrialComponentPrimaryStatus($fFromJSONKeyTrialComponentPrimaryStatus#$fToJSONTrialComponentPrimaryStatus&$fToJSONKeyTrialComponentPrimaryStatus$$fFromXMLTrialComponentPrimaryStatus"$fToXMLTrialComponentPrimaryStatusTrialComponentSourceTrialComponentSource'%$sel:sourceType:TrialComponentSource'$$sel:sourceArn:TrialComponentSource'newTrialComponentSourcetrialComponentSource_sourceTypetrialComponentSource_sourceArn$fNFDataTrialComponentSource$fHashableTrialComponentSource$fFromJSONTrialComponentSource$fEqTrialComponentSource$fReadTrialComponentSource$fShowTrialComponentSource$fGenericTrialComponentSourceTrialComponentStatusTrialComponentStatus'"$sel:message:TrialComponentStatus'($sel:primaryStatus:TrialComponentStatus'newTrialComponentStatustrialComponentStatus_message"trialComponentStatus_primaryStatus$fToJSONTrialComponentStatus$fNFDataTrialComponentStatus$fHashableTrialComponentStatus$fFromJSONTrialComponentStatus$fEqTrialComponentStatus$fReadTrialComponentStatus$fShowTrialComponentStatus$fGenericTrialComponentStatus TrialSource TrialSource'$sel:sourceType:TrialSource'$sel:sourceArn:TrialSource'newTrialSourcetrialSource_sourceTypetrialSource_sourceArn$fNFDataTrialSource$fHashableTrialSource$fFromJSONTrialSource$fEqTrialSource$fReadTrialSource$fShowTrialSource$fGenericTrialSource TrialSummary TrialSummary'$sel:creationTime:TrialSummary'$sel:displayName:TrialSummary'#$sel:lastModifiedTime:TrialSummary'$sel:trialArn:TrialSummary'$sel:trialName:TrialSummary'$sel:trialSource:TrialSummary'newTrialSummarytrialSummary_creationTimetrialSummary_displayNametrialSummary_lastModifiedTimetrialSummary_trialArntrialSummary_trialNametrialSummary_trialSource$fNFDataTrialSummary$fHashableTrialSummary$fFromJSONTrialSummary$fEqTrialSummary$fReadTrialSummary$fShowTrialSummary$fGenericTrialSummaryTuningJobCompletionCriteriaTuningJobCompletionCriteria'<$sel:targetObjectiveMetricValue:TuningJobCompletionCriteria'newTuningJobCompletionCriteria6tuningJobCompletionCriteria_targetObjectiveMetricValue#$fToJSONTuningJobCompletionCriteria#$fNFDataTuningJobCompletionCriteria%$fHashableTuningJobCompletionCriteria%$fFromJSONTuningJobCompletionCriteria$fEqTuningJobCompletionCriteria!$fReadTuningJobCompletionCriteria!$fShowTuningJobCompletionCriteria$$fGenericTuningJobCompletionCriteriaHyperParameterTuningJobConfigHyperParameterTuningJobConfig'$sel:hyperParameterTuningJobObjective:HyperParameterTuningJobConfig'3$sel:parameterRanges:HyperParameterTuningJobConfig'.$sel:randomSeed:HyperParameterTuningJobConfig'2$sel:strategyConfig:HyperParameterTuningJobConfig'$sel:trainingJobEarlyStoppingType:HyperParameterTuningJobConfig'?$sel:tuningJobCompletionCriteria:HyperParameterTuningJobConfig',$sel:strategy:HyperParameterTuningJobConfig'2$sel:resourceLimits:HyperParameterTuningJobConfig' newHyperParameterTuningJobConfig>hyperParameterTuningJobConfig_hyperParameterTuningJobObjective-hyperParameterTuningJobConfig_parameterRanges(hyperParameterTuningJobConfig_randomSeed,hyperParameterTuningJobConfig_strategyConfig:hyperParameterTuningJobConfig_trainingJobEarlyStoppingType9hyperParameterTuningJobConfig_tuningJobCompletionCriteria&hyperParameterTuningJobConfig_strategy,hyperParameterTuningJobConfig_resourceLimits%$fToJSONHyperParameterTuningJobConfig%$fNFDataHyperParameterTuningJobConfig'$fHashableHyperParameterTuningJobConfig'$fFromJSONHyperParameterTuningJobConfig!$fEqHyperParameterTuningJobConfig#$fReadHyperParameterTuningJobConfig#$fShowHyperParameterTuningJobConfig&$fGenericHyperParameterTuningJobConfigTuningJobStepMetaDataTuningJobStepMetaData'$sel:arn:TuningJobStepMetaData'newTuningJobStepMetaDatatuningJobStepMetaData_arn$fNFDataTuningJobStepMetaData$fHashableTuningJobStepMetaData$fFromJSONTuningJobStepMetaData$fEqTuningJobStepMetaData$fReadTuningJobStepMetaData$fShowTuningJobStepMetaData$fGenericTuningJobStepMetaDataPipelineExecutionStepMetadataPipelineExecutionStepMetadata'-$sel:autoMLJob:PipelineExecutionStepMetadata',$sel:callback:PipelineExecutionStepMetadata'0$sel:clarifyCheck:PipelineExecutionStepMetadata'-$sel:condition:PipelineExecutionStepMetadata''$sel:emr:PipelineExecutionStepMetadata'($sel:fail:PipelineExecutionStepMetadata'*$sel:lambda:PipelineExecutionStepMetadata')$sel:model:PipelineExecutionStepMetadata'1$sel:processingJob:PipelineExecutionStepMetadata'0$sel:qualityCheck:PipelineExecutionStepMetadata'1$sel:registerModel:PipelineExecutionStepMetadata'/$sel:trainingJob:PipelineExecutionStepMetadata'0$sel:transformJob:PipelineExecutionStepMetadata'-$sel:tuningJob:PipelineExecutionStepMetadata' newPipelineExecutionStepMetadata'pipelineExecutionStepMetadata_autoMLJob&pipelineExecutionStepMetadata_callback*pipelineExecutionStepMetadata_clarifyCheck'pipelineExecutionStepMetadata_condition!pipelineExecutionStepMetadata_emr"pipelineExecutionStepMetadata_fail$pipelineExecutionStepMetadata_lambda#pipelineExecutionStepMetadata_model+pipelineExecutionStepMetadata_processingJob*pipelineExecutionStepMetadata_qualityCheck+pipelineExecutionStepMetadata_registerModel)pipelineExecutionStepMetadata_trainingJob*pipelineExecutionStepMetadata_transformJob'pipelineExecutionStepMetadata_tuningJob%$fNFDataPipelineExecutionStepMetadata'$fHashablePipelineExecutionStepMetadata'$fFromJSONPipelineExecutionStepMetadata!$fEqPipelineExecutionStepMetadata#$fReadPipelineExecutionStepMetadata#$fShowPipelineExecutionStepMetadata&$fGenericPipelineExecutionStepMetadataPipelineExecutionStepPipelineExecutionStep'($sel:attemptCount:PipelineExecutionStep'*$sel:cacheHitResult:PipelineExecutionStep'#$sel:endTime:PipelineExecutionStep')$sel:failureReason:PipelineExecutionStep'$$sel:metadata:PipelineExecutionStep'%$sel:startTime:PipelineExecutionStep'+$sel:stepDescription:PipelineExecutionStep'+$sel:stepDisplayName:PipelineExecutionStep'$$sel:stepName:PipelineExecutionStep'&$sel:stepStatus:PipelineExecutionStep'newPipelineExecutionStep"pipelineExecutionStep_attemptCount$pipelineExecutionStep_cacheHitResultpipelineExecutionStep_endTime#pipelineExecutionStep_failureReasonpipelineExecutionStep_metadatapipelineExecutionStep_startTime%pipelineExecutionStep_stepDescription%pipelineExecutionStep_stepDisplayNamepipelineExecutionStep_stepName pipelineExecutionStep_stepStatus$fNFDataPipelineExecutionStep$fHashablePipelineExecutionStep$fFromJSONPipelineExecutionStep$fEqPipelineExecutionStep$fReadPipelineExecutionStep$fShowPipelineExecutionStep$fGenericPipelineExecutionStepUSDUSD'$sel:cents:USD'$sel:dollars:USD'$sel:tenthFractionsOfACent:USD'newUSD usd_cents usd_dollarsusd_tenthFractionsOfACent $fToJSONUSD $fNFDataUSD $fHashableUSD $fFromJSONUSD$fEqUSD $fReadUSD $fShowUSD $fGenericUSDPublicWorkforceTaskPricePublicWorkforceTaskPrice'*$sel:amountInUsd:PublicWorkforceTaskPrice'newPublicWorkforceTaskPrice$publicWorkforceTaskPrice_amountInUsd $fToJSONPublicWorkforceTaskPrice $fNFDataPublicWorkforceTaskPrice"$fHashablePublicWorkforceTaskPrice"$fFromJSONPublicWorkforceTaskPrice$fEqPublicWorkforceTaskPrice$fReadPublicWorkforceTaskPrice$fShowPublicWorkforceTaskPrice!$fGenericPublicWorkforceTaskPriceHumanLoopConfigHumanLoopConfig'.$sel:publicWorkforceTaskPrice:HumanLoopConfig'7$sel:taskAvailabilityLifetimeInSeconds:HumanLoopConfig'"$sel:taskKeywords:HumanLoopConfig',$sel:taskTimeLimitInSeconds:HumanLoopConfig'!$sel:workteamArn:HumanLoopConfig'$$sel:humanTaskUiArn:HumanLoopConfig'$sel:taskTitle:HumanLoopConfig'%$sel:taskDescription:HumanLoopConfig'$sel:taskCount:HumanLoopConfig'newHumanLoopConfig(humanLoopConfig_publicWorkforceTaskPrice1humanLoopConfig_taskAvailabilityLifetimeInSecondshumanLoopConfig_taskKeywords&humanLoopConfig_taskTimeLimitInSecondshumanLoopConfig_workteamArnhumanLoopConfig_humanTaskUiArnhumanLoopConfig_taskTitlehumanLoopConfig_taskDescriptionhumanLoopConfig_taskCount$fToJSONHumanLoopConfig$fNFDataHumanLoopConfig$fHashableHumanLoopConfig$fFromJSONHumanLoopConfig$fEqHumanLoopConfig$fReadHumanLoopConfig$fShowHumanLoopConfig$fGenericHumanLoopConfigUiConfig UiConfig'$sel:humanTaskUiArn:UiConfig'$sel:uiTemplateS3Uri:UiConfig' newUiConfiguiConfig_humanTaskUiArnuiConfig_uiTemplateS3Uri$fToJSONUiConfig$fNFDataUiConfig$fHashableUiConfig$fFromJSONUiConfig $fEqUiConfig$fReadUiConfig$fShowUiConfig$fGenericUiConfigHumanTaskConfigHumanTaskConfig',$sel:maxConcurrentTaskCount:HumanTaskConfig'.$sel:publicWorkforceTaskPrice:HumanTaskConfig'7$sel:taskAvailabilityLifetimeInSeconds:HumanTaskConfig'"$sel:taskKeywords:HumanTaskConfig'!$sel:workteamArn:HumanTaskConfig'$sel:uiConfig:HumanTaskConfig'+$sel:preHumanTaskLambdaArn:HumanTaskConfig'$sel:taskTitle:HumanTaskConfig'%$sel:taskDescription:HumanTaskConfig'7$sel:numberOfHumanWorkersPerDataObject:HumanTaskConfig',$sel:taskTimeLimitInSeconds:HumanTaskConfig'3$sel:annotationConsolidationConfig:HumanTaskConfig'newHumanTaskConfig&humanTaskConfig_maxConcurrentTaskCount(humanTaskConfig_publicWorkforceTaskPrice1humanTaskConfig_taskAvailabilityLifetimeInSecondshumanTaskConfig_taskKeywordshumanTaskConfig_workteamArnhumanTaskConfig_uiConfig%humanTaskConfig_preHumanTaskLambdaArnhumanTaskConfig_taskTitlehumanTaskConfig_taskDescription1humanTaskConfig_numberOfHumanWorkersPerDataObject&humanTaskConfig_taskTimeLimitInSeconds-humanTaskConfig_annotationConsolidationConfig$fToJSONHumanTaskConfig$fNFDataHumanTaskConfig$fHashableHumanTaskConfig$fFromJSONHumanTaskConfig$fEqHumanTaskConfig$fReadHumanTaskConfig$fShowHumanTaskConfig$fGenericHumanTaskConfig UiTemplate UiTemplate'$sel:content:UiTemplate' newUiTemplateuiTemplate_content$fToJSONUiTemplate$fNFDataUiTemplate$fHashableUiTemplate$fEqUiTemplate$fReadUiTemplate$fShowUiTemplate$fGenericUiTemplateUiTemplateInfoUiTemplateInfo'"$sel:contentSha256:UiTemplateInfo'$sel:url:UiTemplateInfo'newUiTemplateInfouiTemplateInfo_contentSha256uiTemplateInfo_url$fNFDataUiTemplateInfo$fHashableUiTemplateInfo$fFromJSONUiTemplateInfo$fEqUiTemplateInfo$fReadUiTemplateInfo$fShowUiTemplateInfo$fGenericUiTemplateInfo UserContext UserContext'$sel:domainId:UserContext' $sel:userProfileArn:UserContext'!$sel:userProfileName:UserContext'newUserContextuserContext_domainIduserContext_userProfileArnuserContext_userProfileName$fNFDataUserContext$fHashableUserContext$fFromJSONUserContext$fEqUserContext$fReadUserContext$fShowUserContext$fGenericUserContextTrialComponentSummaryTrialComponentSummary'%$sel:createdBy:TrialComponentSummary'($sel:creationTime:TrialComponentSummary''$sel:displayName:TrialComponentSummary'#$sel:endTime:TrialComponentSummary'*$sel:lastModifiedBy:TrialComponentSummary',$sel:lastModifiedTime:TrialComponentSummary'%$sel:startTime:TrialComponentSummary'"$sel:status:TrialComponentSummary'-$sel:trialComponentArn:TrialComponentSummary'.$sel:trialComponentName:TrialComponentSummary'0$sel:trialComponentSource:TrialComponentSummary'newTrialComponentSummarytrialComponentSummary_createdBy"trialComponentSummary_creationTime!trialComponentSummary_displayNametrialComponentSummary_endTime$trialComponentSummary_lastModifiedBy&trialComponentSummary_lastModifiedTimetrialComponentSummary_startTimetrialComponentSummary_status'trialComponentSummary_trialComponentArn(trialComponentSummary_trialComponentName*trialComponentSummary_trialComponentSource$fNFDataTrialComponentSummary$fHashableTrialComponentSummary$fFromJSONTrialComponentSummary$fEqTrialComponentSummary$fReadTrialComponentSummary$fShowTrialComponentSummary$fGenericTrialComponentSummaryTrialComponentSimpleSummaryTrialComponentSimpleSummary'+$sel:createdBy:TrialComponentSimpleSummary'.$sel:creationTime:TrialComponentSimpleSummary'3$sel:trialComponentArn:TrialComponentSimpleSummary'4$sel:trialComponentName:TrialComponentSimpleSummary'6$sel:trialComponentSource:TrialComponentSimpleSummary'newTrialComponentSimpleSummary%trialComponentSimpleSummary_createdBy(trialComponentSimpleSummary_creationTime-trialComponentSimpleSummary_trialComponentArn.trialComponentSimpleSummary_trialComponentName0trialComponentSimpleSummary_trialComponentSource#$fNFDataTrialComponentSimpleSummary%$fHashableTrialComponentSimpleSummary%$fFromJSONTrialComponentSimpleSummary$fEqTrialComponentSimpleSummary!$fReadTrialComponentSimpleSummary!$fShowTrialComponentSimpleSummary$$fGenericTrialComponentSimpleSummaryTrialTrial'$sel:createdBy:Trial'$sel:creationTime:Trial'$sel:displayName:Trial'$sel:experimentName:Trial'$sel:lastModifiedBy:Trial'$sel:lastModifiedTime:Trial'$sel:metadataProperties:Trial'$sel:source:Trial'$sel:tags:Trial'$sel:trialArn:Trial'#$sel:trialComponentSummaries:Trial'$sel:trialName:Trial'newTrialtrial_createdBytrial_creationTimetrial_displayNametrial_experimentNametrial_lastModifiedBytrial_lastModifiedTimetrial_metadataProperties trial_source trial_tagstrial_trialArntrial_trialComponentSummariestrial_trialName $fNFDataTrial$fHashableTrial$fFromJSONTrial $fEqTrial $fReadTrial $fShowTrial$fGenericTrialProjectProject'$sel:createdBy:Project'$sel:creationTime:Project'$sel:lastModifiedBy:Project'$sel:lastModifiedTime:Project'$sel:projectArn:Project' $sel:projectDescription:Project'$sel:projectId:Project'$sel:projectName:Project'$sel:projectStatus:Project'5$sel:serviceCatalogProvisionedProductDetails:Project'/$sel:serviceCatalogProvisioningDetails:Project'$sel:tags:Project' newProjectproject_createdByproject_creationTimeproject_lastModifiedByproject_lastModifiedTimeproject_projectArnproject_projectDescriptionproject_projectIdproject_projectNameproject_projectStatus/project_serviceCatalogProvisionedProductDetails)project_serviceCatalogProvisioningDetails project_tags$fNFDataProject$fHashableProject$fFromJSONProject $fEqProject $fReadProject $fShowProject$fGenericProjectPipelineExecutionPipelineExecution'!$sel:createdBy:PipelineExecution'$$sel:creationTime:PipelineExecution'%$sel:failureReason:PipelineExecution'&$sel:lastModifiedBy:PipelineExecution'($sel:lastModifiedTime:PipelineExecution'0$sel:parallelismConfiguration:PipelineExecution'#$sel:pipelineArn:PipelineExecution',$sel:pipelineExecutionArn:PipelineExecution'4$sel:pipelineExecutionDescription:PipelineExecution'4$sel:pipelineExecutionDisplayName:PipelineExecution'/$sel:pipelineExecutionStatus:PipelineExecution'0$sel:pipelineExperimentConfig:PipelineExecution'*$sel:pipelineParameters:PipelineExecution'newPipelineExecutionpipelineExecution_createdBypipelineExecution_creationTimepipelineExecution_failureReason pipelineExecution_lastModifiedBy"pipelineExecution_lastModifiedTime*pipelineExecution_parallelismConfigurationpipelineExecution_pipelineArn&pipelineExecution_pipelineExecutionArn.pipelineExecution_pipelineExecutionDescription.pipelineExecution_pipelineExecutionDisplayName)pipelineExecution_pipelineExecutionStatus*pipelineExecution_pipelineExperimentConfig$pipelineExecution_pipelineParameters$fNFDataPipelineExecution$fHashablePipelineExecution$fFromJSONPipelineExecution$fEqPipelineExecution$fReadPipelineExecution$fShowPipelineExecution$fGenericPipelineExecutionPipeline Pipeline'$sel:createdBy:Pipeline'$sel:creationTime:Pipeline'$sel:lastModifiedBy:Pipeline'$sel:lastModifiedTime:Pipeline'$sel:lastRunTime:Pipeline''$sel:parallelismConfiguration:Pipeline'$sel:pipelineArn:Pipeline'"$sel:pipelineDescription:Pipeline'"$sel:pipelineDisplayName:Pipeline'$sel:pipelineName:Pipeline'$sel:pipelineStatus:Pipeline'$sel:roleArn:Pipeline'$sel:tags:Pipeline' newPipelinepipeline_createdBypipeline_creationTimepipeline_lastModifiedBypipeline_lastModifiedTimepipeline_lastRunTime!pipeline_parallelismConfigurationpipeline_pipelineArnpipeline_pipelineDescriptionpipeline_pipelineDisplayNamepipeline_pipelineNamepipeline_pipelineStatuspipeline_roleArn pipeline_tags$fNFDataPipeline$fHashablePipeline$fFromJSONPipeline $fEqPipeline$fReadPipeline$fShowPipeline$fGenericPipelineModelPackageGroupModelPackageGroup'!$sel:createdBy:ModelPackageGroup'$$sel:creationTime:ModelPackageGroup',$sel:modelPackageGroupArn:ModelPackageGroup'4$sel:modelPackageGroupDescription:ModelPackageGroup'-$sel:modelPackageGroupName:ModelPackageGroup'/$sel:modelPackageGroupStatus:ModelPackageGroup'$sel:tags:ModelPackageGroup'newModelPackageGroupmodelPackageGroup_createdBymodelPackageGroup_creationTime&modelPackageGroup_modelPackageGroupArn.modelPackageGroup_modelPackageGroupDescription'modelPackageGroup_modelPackageGroupName)modelPackageGroup_modelPackageGroupStatusmodelPackageGroup_tags$fNFDataModelPackageGroup$fHashableModelPackageGroup$fFromJSONModelPackageGroup$fEqModelPackageGroup$fReadModelPackageGroup$fShowModelPackageGroup$fGenericModelPackageGroup ModelPackage ModelPackage'4$sel:additionalInferenceSpecifications:ModelPackage'&$sel:approvalDescription:ModelPackage'($sel:certifyForMarketplace:ModelPackage'$sel:createdBy:ModelPackage'$sel:creationTime:ModelPackage'-$sel:customerMetadataProperties:ModelPackage'$sel:domain:ModelPackage'&$sel:driftCheckBaselines:ModelPackage')$sel:inferenceSpecification:ModelPackage'!$sel:lastModifiedBy:ModelPackage'#$sel:lastModifiedTime:ModelPackage'%$sel:metadataProperties:ModelPackage'&$sel:modelApprovalStatus:ModelPackage'$sel:modelMetrics:ModelPackage'"$sel:modelPackageArn:ModelPackage'*$sel:modelPackageDescription:ModelPackage'($sel:modelPackageGroupName:ModelPackage'#$sel:modelPackageName:ModelPackage'%$sel:modelPackageStatus:ModelPackage',$sel:modelPackageStatusDetails:ModelPackage'&$sel:modelPackageVersion:ModelPackage'#$sel:samplePayloadUrl:ModelPackage'/$sel:sourceAlgorithmSpecification:ModelPackage'$sel:tags:ModelPackage'$sel:task:ModelPackage'*$sel:validationSpecification:ModelPackage'newModelPackage.modelPackage_additionalInferenceSpecifications modelPackage_approvalDescription"modelPackage_certifyForMarketplacemodelPackage_createdBymodelPackage_creationTime'modelPackage_customerMetadataPropertiesmodelPackage_domain modelPackage_driftCheckBaselines#modelPackage_inferenceSpecificationmodelPackage_lastModifiedBymodelPackage_lastModifiedTimemodelPackage_metadataProperties modelPackage_modelApprovalStatusmodelPackage_modelMetricsmodelPackage_modelPackageArn$modelPackage_modelPackageDescription"modelPackage_modelPackageGroupNamemodelPackage_modelPackageNamemodelPackage_modelPackageStatus&modelPackage_modelPackageStatusDetails modelPackage_modelPackageVersionmodelPackage_samplePayloadUrl)modelPackage_sourceAlgorithmSpecificationmodelPackage_tagsmodelPackage_task$modelPackage_validationSpecification$fNFDataModelPackage$fHashableModelPackage$fFromJSONModelPackage$fEqModelPackage$fReadModelPackage$fShowModelPackage$fGenericModelPackageModelDashboardModelCardModelDashboardModelCard''$sel:createdBy:ModelDashboardModelCard'*$sel:creationTime:ModelDashboardModelCard',$sel:lastModifiedBy:ModelDashboardModelCard'.$sel:lastModifiedTime:ModelDashboardModelCard'*$sel:modelCardArn:ModelDashboardModelCard'+$sel:modelCardName:ModelDashboardModelCard'-$sel:modelCardStatus:ModelDashboardModelCard'.$sel:modelCardVersion:ModelDashboardModelCard'%$sel:modelId:ModelDashboardModelCard'($sel:riskRating:ModelDashboardModelCard',$sel:securityConfig:ModelDashboardModelCard'"$sel:tags:ModelDashboardModelCard'newModelDashboardModelCard!modelDashboardModelCard_createdBy$modelDashboardModelCard_creationTime&modelDashboardModelCard_lastModifiedBy(modelDashboardModelCard_lastModifiedTime$modelDashboardModelCard_modelCardArn%modelDashboardModelCard_modelCardName'modelDashboardModelCard_modelCardStatus(modelDashboardModelCard_modelCardVersionmodelDashboardModelCard_modelId"modelDashboardModelCard_riskRating&modelDashboardModelCard_securityConfigmodelDashboardModelCard_tags$fNFDataModelDashboardModelCard!$fHashableModelDashboardModelCard!$fFromJSONModelDashboardModelCard$fEqModelDashboardModelCard$fReadModelDashboardModelCard$fShowModelDashboardModelCard $fGenericModelDashboardModelCard ModelCard ModelCard'$sel:content:ModelCard'$sel:createdBy:ModelCard'$sel:creationTime:ModelCard'$sel:lastModifiedBy:ModelCard' $sel:lastModifiedTime:ModelCard'$sel:modelCardArn:ModelCard'$sel:modelCardName:ModelCard'$sel:modelCardStatus:ModelCard' $sel:modelCardVersion:ModelCard'$sel:modelId:ModelCard'$sel:riskRating:ModelCard'$sel:securityConfig:ModelCard'$sel:tags:ModelCard' newModelCardmodelCard_contentmodelCard_createdBymodelCard_creationTimemodelCard_lastModifiedBymodelCard_lastModifiedTimemodelCard_modelCardArnmodelCard_modelCardNamemodelCard_modelCardStatusmodelCard_modelCardVersionmodelCard_modelIdmodelCard_riskRatingmodelCard_securityConfigmodelCard_tags$fNFDataModelCard$fHashableModelCard$fFromJSONModelCard $fEqModelCard$fShowModelCard$fGenericModelCard Experiment Experiment'$sel:createdBy:Experiment'$sel:creationTime:Experiment'$sel:description:Experiment'$sel:displayName:Experiment'$sel:experimentArn:Experiment'$sel:experimentName:Experiment'$sel:lastModifiedBy:Experiment'!$sel:lastModifiedTime:Experiment'$sel:source:Experiment'$sel:tags:Experiment' newExperimentexperiment_createdByexperiment_creationTimeexperiment_descriptionexperiment_displayNameexperiment_experimentArnexperiment_experimentNameexperiment_lastModifiedByexperiment_lastModifiedTimeexperiment_sourceexperiment_tags$fNFDataExperiment$fHashableExperiment$fFromJSONExperiment$fEqExperiment$fReadExperiment$fShowExperiment$fGenericExperimentAssociationSummaryAssociationSummary'($sel:associationType:AssociationSummary'"$sel:createdBy:AssociationSummary'%$sel:creationTime:AssociationSummary''$sel:destinationArn:AssociationSummary'($sel:destinationName:AssociationSummary'($sel:destinationType:AssociationSummary'"$sel:sourceArn:AssociationSummary'#$sel:sourceName:AssociationSummary'#$sel:sourceType:AssociationSummary'newAssociationSummary"associationSummary_associationTypeassociationSummary_createdByassociationSummary_creationTime!associationSummary_destinationArn"associationSummary_destinationName"associationSummary_destinationTypeassociationSummary_sourceArnassociationSummary_sourceNameassociationSummary_sourceType$fNFDataAssociationSummary$fHashableAssociationSummary$fFromJSONAssociationSummary$fEqAssociationSummary$fReadAssociationSummary$fShowAssociationSummary$fGenericAssociationSummaryUserProfileSortKeyUserProfileSortKey'fromUserProfileSortKey#UserProfileSortKey_LastModifiedTimeUserProfileSortKey_CreationTime$fShowUserProfileSortKey$fReadUserProfileSortKey$fEqUserProfileSortKey$fOrdUserProfileSortKey$fGenericUserProfileSortKey$fHashableUserProfileSortKey$fNFDataUserProfileSortKey$fFromTextUserProfileSortKey$fToTextUserProfileSortKey $fToByteStringUserProfileSortKey$fToLogUserProfileSortKey$fToHeaderUserProfileSortKey$fToQueryUserProfileSortKey$fFromJSONUserProfileSortKey$fFromJSONKeyUserProfileSortKey$fToJSONUserProfileSortKey$fToJSONKeyUserProfileSortKey$fFromXMLUserProfileSortKey$fToXMLUserProfileSortKeyUserProfileStatusUserProfileStatus'fromUserProfileStatusUserProfileStatus_UpdatingUserProfileStatus_Update_FailedUserProfileStatus_PendingUserProfileStatus_InServiceUserProfileStatus_FailedUserProfileStatus_DeletingUserProfileStatus_Delete_Failed$fShowUserProfileStatus$fReadUserProfileStatus$fEqUserProfileStatus$fOrdUserProfileStatus$fGenericUserProfileStatus$fHashableUserProfileStatus$fNFDataUserProfileStatus$fFromTextUserProfileStatus$fToTextUserProfileStatus$fToByteStringUserProfileStatus$fToLogUserProfileStatus$fToHeaderUserProfileStatus$fToQueryUserProfileStatus$fFromJSONUserProfileStatus$fFromJSONKeyUserProfileStatus$fToJSONUserProfileStatus$fToJSONKeyUserProfileStatus$fFromXMLUserProfileStatus$fToXMLUserProfileStatusUserProfileDetailsUserProfileDetails'%$sel:creationTime:UserProfileDetails'!$sel:domainId:UserProfileDetails')$sel:lastModifiedTime:UserProfileDetails'$sel:status:UserProfileDetails'($sel:userProfileName:UserProfileDetails'newUserProfileDetailsuserProfileDetails_creationTimeuserProfileDetails_domainId#userProfileDetails_lastModifiedTimeuserProfileDetails_status"userProfileDetails_userProfileName$fNFDataUserProfileDetails$fHashableUserProfileDetails$fFromJSONUserProfileDetails$fEqUserProfileDetails$fReadUserProfileDetails$fShowUserProfileDetails$fGenericUserProfileDetails UserSettings UserSettings'$$sel:canvasAppSettings:UserSettings' $sel:executionRole:UserSettings'+$sel:jupyterServerAppSettings:UserSettings'+$sel:kernelGatewayAppSettings:UserSettings'&$sel:rSessionAppSettings:UserSettings'.$sel:rStudioServerProAppSettings:UserSettings'!$sel:securityGroups:UserSettings'"$sel:sharingSettings:UserSettings')$sel:tensorBoardAppSettings:UserSettings'newUserSettingsuserSettings_canvasAppSettingsuserSettings_executionRole%userSettings_jupyterServerAppSettings%userSettings_kernelGatewayAppSettings userSettings_rSessionAppSettings(userSettings_rStudioServerProAppSettingsuserSettings_securityGroupsuserSettings_sharingSettings#userSettings_tensorBoardAppSettings$fToJSONUserSettings$fNFDataUserSettings$fHashableUserSettings$fFromJSONUserSettings$fEqUserSettings$fReadUserSettings$fShowUserSettings$fGenericUserSettingsVariantPropertyTypeVariantPropertyType'fromVariantPropertyType!VariantPropertyType_DesiredWeight(VariantPropertyType_DesiredInstanceCount%VariantPropertyType_DataCaptureConfig$fShowVariantPropertyType$fReadVariantPropertyType$fEqVariantPropertyType$fOrdVariantPropertyType$fGenericVariantPropertyType$fHashableVariantPropertyType$fNFDataVariantPropertyType$fFromTextVariantPropertyType$fToTextVariantPropertyType!$fToByteStringVariantPropertyType$fToLogVariantPropertyType$fToHeaderVariantPropertyType$fToQueryVariantPropertyType$fFromJSONVariantPropertyType $fFromJSONKeyVariantPropertyType$fToJSONVariantPropertyType$fToJSONKeyVariantPropertyType$fFromXMLVariantPropertyType$fToXMLVariantPropertyTypeVariantPropertyVariantProperty')$sel:variantPropertyType:VariantProperty'newVariantProperty#variantProperty_variantPropertyType$fToJSONVariantProperty$fNFDataVariantProperty$fHashableVariantProperty$fEqVariantProperty$fReadVariantProperty$fShowVariantProperty$fGenericVariantProperty VariantStatusVariantStatus'fromVariantStatusVariantStatus_UpdatingVariantStatus_DeletingVariantStatus_CreatingVariantStatus_BakingVariantStatus_ActivatingTraffic$fShowVariantStatus$fReadVariantStatus$fEqVariantStatus$fOrdVariantStatus$fGenericVariantStatus$fHashableVariantStatus$fNFDataVariantStatus$fFromTextVariantStatus$fToTextVariantStatus$fToByteStringVariantStatus$fToLogVariantStatus$fToHeaderVariantStatus$fToQueryVariantStatus$fFromJSONVariantStatus$fFromJSONKeyVariantStatus$fToJSONVariantStatus$fToJSONKeyVariantStatus$fFromXMLVariantStatus$fToXMLVariantStatusProductionVariantStatusProductionVariantStatus''$sel:startTime:ProductionVariantStatus'+$sel:statusMessage:ProductionVariantStatus'$$sel:status:ProductionVariantStatus'newProductionVariantStatus!productionVariantStatus_startTime%productionVariantStatus_statusMessageproductionVariantStatus_status$fNFDataProductionVariantStatus!$fHashableProductionVariantStatus!$fFromJSONProductionVariantStatus$fEqProductionVariantStatus$fReadProductionVariantStatus$fShowProductionVariantStatus $fGenericProductionVariantStatusProductionVariantSummaryProductionVariantSummary'3$sel:currentInstanceCount:ProductionVariantSummary'6$sel:currentServerlessConfig:ProductionVariantSummary',$sel:currentWeight:ProductionVariantSummary'-$sel:deployedImages:ProductionVariantSummary'3$sel:desiredInstanceCount:ProductionVariantSummary'6$sel:desiredServerlessConfig:ProductionVariantSummary',$sel:desiredWeight:ProductionVariantSummary',$sel:variantStatus:ProductionVariantSummary'*$sel:variantName:ProductionVariantSummary'newProductionVariantSummary-productionVariantSummary_currentInstanceCount0productionVariantSummary_currentServerlessConfig&productionVariantSummary_currentWeight'productionVariantSummary_deployedImages-productionVariantSummary_desiredInstanceCount0productionVariantSummary_desiredServerlessConfig&productionVariantSummary_desiredWeight&productionVariantSummary_variantStatus$productionVariantSummary_variantName $fNFDataProductionVariantSummary"$fHashableProductionVariantSummary"$fFromJSONProductionVariantSummary$fEqProductionVariantSummary$fReadProductionVariantSummary$fShowProductionVariantSummary!$fGenericProductionVariantSummaryPendingProductionVariantSummary PendingProductionVariantSummary'5$sel:acceleratorType:PendingProductionVariantSummary':$sel:currentInstanceCount:PendingProductionVariantSummary'=$sel:currentServerlessConfig:PendingProductionVariantSummary'3$sel:currentWeight:PendingProductionVariantSummary'4$sel:deployedImages:PendingProductionVariantSummary':$sel:desiredInstanceCount:PendingProductionVariantSummary'=$sel:desiredServerlessConfig:PendingProductionVariantSummary'3$sel:desiredWeight:PendingProductionVariantSummary'2$sel:instanceType:PendingProductionVariantSummary'3$sel:variantStatus:PendingProductionVariantSummary'1$sel:variantName:PendingProductionVariantSummary'"newPendingProductionVariantSummary/pendingProductionVariantSummary_acceleratorType4pendingProductionVariantSummary_currentInstanceCount7pendingProductionVariantSummary_currentServerlessConfig-pendingProductionVariantSummary_currentWeight.pendingProductionVariantSummary_deployedImages4pendingProductionVariantSummary_desiredInstanceCount7pendingProductionVariantSummary_desiredServerlessConfig-pendingProductionVariantSummary_desiredWeight,pendingProductionVariantSummary_instanceType-pendingProductionVariantSummary_variantStatus+pendingProductionVariantSummary_variantName'$fNFDataPendingProductionVariantSummary)$fHashablePendingProductionVariantSummary)$fFromJSONPendingProductionVariantSummary#$fEqPendingProductionVariantSummary%$fReadPendingProductionVariantSummary%$fShowPendingProductionVariantSummary($fGenericPendingProductionVariantSummaryPendingDeploymentSummaryPendingDeploymentSummary'1$sel:productionVariants:PendingDeploymentSummary'7$sel:shadowProductionVariants:PendingDeploymentSummary'($sel:startTime:PendingDeploymentSummary'1$sel:endpointConfigName:PendingDeploymentSummary'newPendingDeploymentSummary+pendingDeploymentSummary_productionVariants1pendingDeploymentSummary_shadowProductionVariants"pendingDeploymentSummary_startTime+pendingDeploymentSummary_endpointConfigName $fNFDataPendingDeploymentSummary"$fHashablePendingDeploymentSummary"$fFromJSONPendingDeploymentSummary$fEqPendingDeploymentSummary$fReadPendingDeploymentSummary$fShowPendingDeploymentSummary!$fGenericPendingDeploymentSummaryVendorGuidanceVendorGuidance'fromVendorGuidanceVendorGuidance_TO_BE_ARCHIVEDVendorGuidance_STABLEVendorGuidance_NOT_PROVIDEDVendorGuidance_ARCHIVED$fShowVendorGuidance$fReadVendorGuidance$fEqVendorGuidance$fOrdVendorGuidance$fGenericVendorGuidance$fHashableVendorGuidance$fNFDataVendorGuidance$fFromTextVendorGuidance$fToTextVendorGuidance$fToByteStringVendorGuidance$fToLogVendorGuidance$fToHeaderVendorGuidance$fToQueryVendorGuidance$fFromJSONVendorGuidance$fFromJSONKeyVendorGuidance$fToJSONVendorGuidance$fToJSONKeyVendorGuidance$fFromXMLVendorGuidance$fToXMLVendorGuidanceVertexVertex'$sel:arn:Vertex'$sel:lineageType:Vertex'$sel:type':Vertex' newVertex vertex_arnvertex_lineageType vertex_type$fNFDataVertex$fHashableVertex$fFromJSONVertex $fEqVertex $fReadVertex $fShowVertex$fGenericVertex VpcConfig VpcConfig' $sel:securityGroupIds:VpcConfig'$sel:subnets:VpcConfig' newVpcConfigvpcConfig_securityGroupIdsvpcConfig_subnets$fToJSONVpcConfig$fNFDataVpcConfig$fHashableVpcConfig$fFromJSONVpcConfig $fEqVpcConfig$fReadVpcConfig$fShowVpcConfig$fGenericVpcConfig TrainingJob TrainingJob'($sel:algorithmSpecification:TrainingJob'$sel:autoMLJobArn:TrainingJob''$sel:billableTimeInSeconds:TrainingJob'"$sel:checkpointConfig:TrainingJob'$sel:creationTime:TrainingJob'!$sel:debugHookConfig:TrainingJob')$sel:debugRuleConfigurations:TrainingJob'-$sel:debugRuleEvaluationStatuses:TrainingJob'7$sel:enableInterContainerTrafficEncryption:TrainingJob'+$sel:enableManagedSpotTraining:TrainingJob'($sel:enableNetworkIsolation:TrainingJob'$sel:environment:TrainingJob'"$sel:experimentConfig:TrainingJob'$sel:failureReason:TrainingJob'%$sel:finalMetricDataList:TrainingJob'!$sel:hyperParameters:TrainingJob'!$sel:inputDataConfig:TrainingJob' $sel:labelingJobArn:TrainingJob'"$sel:lastModifiedTime:TrainingJob' $sel:modelArtifacts:TrainingJob'"$sel:outputDataConfig:TrainingJob' $sel:resourceConfig:TrainingJob'$sel:retryStrategy:TrainingJob'$sel:roleArn:TrainingJob'!$sel:secondaryStatus:TrainingJob',$sel:secondaryStatusTransitions:TrainingJob'#$sel:stoppingCondition:TrainingJob'$sel:tags:TrainingJob')$sel:tensorBoardOutputConfig:TrainingJob'!$sel:trainingEndTime:TrainingJob' $sel:trainingJobArn:TrainingJob'!$sel:trainingJobName:TrainingJob'#$sel:trainingJobStatus:TrainingJob'#$sel:trainingStartTime:TrainingJob''$sel:trainingTimeInSeconds:TrainingJob'$sel:tuningJobArn:TrainingJob'$sel:vpcConfig:TrainingJob'newTrainingJob"trainingJob_algorithmSpecificationtrainingJob_autoMLJobArn!trainingJob_billableTimeInSecondstrainingJob_checkpointConfigtrainingJob_creationTimetrainingJob_debugHookConfig#trainingJob_debugRuleConfigurations'trainingJob_debugRuleEvaluationStatuses1trainingJob_enableInterContainerTrafficEncryption%trainingJob_enableManagedSpotTraining"trainingJob_enableNetworkIsolationtrainingJob_environmenttrainingJob_experimentConfigtrainingJob_failureReasontrainingJob_finalMetricDataListtrainingJob_hyperParameterstrainingJob_inputDataConfigtrainingJob_labelingJobArntrainingJob_lastModifiedTimetrainingJob_modelArtifactstrainingJob_outputDataConfigtrainingJob_resourceConfigtrainingJob_retryStrategytrainingJob_roleArntrainingJob_secondaryStatus&trainingJob_secondaryStatusTransitionstrainingJob_stoppingConditiontrainingJob_tags#trainingJob_tensorBoardOutputConfigtrainingJob_trainingEndTimetrainingJob_trainingJobArntrainingJob_trainingJobNametrainingJob_trainingJobStatustrainingJob_trainingStartTime!trainingJob_trainingTimeInSecondstrainingJob_tuningJobArntrainingJob_vpcConfig$fNFDataTrainingJob$fHashableTrainingJob$fFromJSONTrainingJob$fEqTrainingJob$fReadTrainingJob$fShowTrainingJob$fGenericTrainingJob NetworkConfigNetworkConfig'9$sel:enableInterContainerTrafficEncryption:NetworkConfig'*$sel:enableNetworkIsolation:NetworkConfig'$sel:vpcConfig:NetworkConfig'newNetworkConfig3networkConfig_enableInterContainerTrafficEncryption$networkConfig_enableNetworkIsolationnetworkConfig_vpcConfig$fToJSONNetworkConfig$fNFDataNetworkConfig$fHashableNetworkConfig$fFromJSONNetworkConfig$fEqNetworkConfig$fReadNetworkConfig$fShowNetworkConfig$fGenericNetworkConfig ProcessingJobProcessingJob'$$sel:appSpecification:ProcessingJob' $sel:autoMLJobArn:ProcessingJob' $sel:creationTime:ProcessingJob'$sel:environment:ProcessingJob'$sel:exitMessage:ProcessingJob'$$sel:experimentConfig:ProcessingJob'!$sel:failureReason:ProcessingJob'$$sel:lastModifiedTime:ProcessingJob')$sel:monitoringScheduleArn:ProcessingJob'!$sel:networkConfig:ProcessingJob'%$sel:processingEndTime:ProcessingJob'$$sel:processingInputs:ProcessingJob'$$sel:processingJobArn:ProcessingJob'%$sel:processingJobName:ProcessingJob''$sel:processingJobStatus:ProcessingJob'*$sel:processingOutputConfig:ProcessingJob''$sel:processingResources:ProcessingJob''$sel:processingStartTime:ProcessingJob'$sel:roleArn:ProcessingJob'%$sel:stoppingCondition:ProcessingJob'$sel:tags:ProcessingJob'"$sel:trainingJobArn:ProcessingJob'newProcessingJobprocessingJob_appSpecificationprocessingJob_autoMLJobArnprocessingJob_creationTimeprocessingJob_environmentprocessingJob_exitMessageprocessingJob_experimentConfigprocessingJob_failureReasonprocessingJob_lastModifiedTime#processingJob_monitoringScheduleArnprocessingJob_networkConfigprocessingJob_processingEndTimeprocessingJob_processingInputsprocessingJob_processingJobArnprocessingJob_processingJobName!processingJob_processingJobStatus$processingJob_processingOutputConfig!processingJob_processingResources!processingJob_processingStartTimeprocessingJob_roleArnprocessingJob_stoppingConditionprocessingJob_tagsprocessingJob_trainingJobArn$fNFDataProcessingJob$fHashableProcessingJob$fFromJSONProcessingJob$fEqProcessingJob$fReadProcessingJob$fShowProcessingJob$fGenericProcessingJobTrialComponentSourceDetailTrialComponentSourceDetail'.$sel:processingJob:TrialComponentSourceDetail'*$sel:sourceArn:TrialComponentSourceDetail',$sel:trainingJob:TrialComponentSourceDetail'-$sel:transformJob:TrialComponentSourceDetail'newTrialComponentSourceDetail(trialComponentSourceDetail_processingJob$trialComponentSourceDetail_sourceArn&trialComponentSourceDetail_trainingJob'trialComponentSourceDetail_transformJob"$fNFDataTrialComponentSourceDetail$$fHashableTrialComponentSourceDetail$$fFromJSONTrialComponentSourceDetail$fEqTrialComponentSourceDetail $fReadTrialComponentSourceDetail $fShowTrialComponentSourceDetail#$fGenericTrialComponentSourceDetailTrialComponentTrialComponent'$sel:createdBy:TrialComponent'!$sel:creationTime:TrialComponent' $sel:displayName:TrialComponent'$sel:endTime:TrialComponent'#$sel:inputArtifacts:TrialComponent'#$sel:lastModifiedBy:TrialComponent'%$sel:lastModifiedTime:TrialComponent'$$sel:lineageGroupArn:TrialComponent''$sel:metadataProperties:TrialComponent'$sel:metrics:TrialComponent'$$sel:outputArtifacts:TrialComponent'$sel:parameters:TrialComponent'$sel:parents:TrialComponent'$sel:runName:TrialComponent'$sel:source:TrialComponent'!$sel:sourceDetail:TrialComponent'$sel:startTime:TrialComponent'$sel:status:TrialComponent'$sel:tags:TrialComponent'&$sel:trialComponentArn:TrialComponent''$sel:trialComponentName:TrialComponent'newTrialComponenttrialComponent_createdBytrialComponent_creationTimetrialComponent_displayNametrialComponent_endTimetrialComponent_inputArtifactstrialComponent_lastModifiedBytrialComponent_lastModifiedTimetrialComponent_lineageGroupArn!trialComponent_metadataPropertiestrialComponent_metricstrialComponent_outputArtifactstrialComponent_parameterstrialComponent_parentstrialComponent_runNametrialComponent_sourcetrialComponent_sourceDetailtrialComponent_startTimetrialComponent_statustrialComponent_tags trialComponent_trialComponentArn!trialComponent_trialComponentName$fNFDataTrialComponent$fHashableTrialComponent$fFromJSONTrialComponent$fEqTrialComponent$fReadTrialComponent$fShowTrialComponent$fGenericTrialComponentMonitoringJobDefinitionMonitoringJobDefinition',$sel:baselineConfig:MonitoringJobDefinition')$sel:environment:MonitoringJobDefinition'+$sel:networkConfig:MonitoringJobDefinition'/$sel:stoppingCondition:MonitoringJobDefinition'.$sel:monitoringInputs:MonitoringJobDefinition'4$sel:monitoringOutputConfig:MonitoringJobDefinition'1$sel:monitoringResources:MonitoringJobDefinition'8$sel:monitoringAppSpecification:MonitoringJobDefinition'%$sel:roleArn:MonitoringJobDefinition'newMonitoringJobDefinition&monitoringJobDefinition_baselineConfig#monitoringJobDefinition_environment%monitoringJobDefinition_networkConfig)monitoringJobDefinition_stoppingCondition(monitoringJobDefinition_monitoringInputs.monitoringJobDefinition_monitoringOutputConfig+monitoringJobDefinition_monitoringResources2monitoringJobDefinition_monitoringAppSpecificationmonitoringJobDefinition_roleArn$fToJSONMonitoringJobDefinition$fNFDataMonitoringJobDefinition!$fHashableMonitoringJobDefinition!$fFromJSONMonitoringJobDefinition$fEqMonitoringJobDefinition$fReadMonitoringJobDefinition$fShowMonitoringJobDefinition $fGenericMonitoringJobDefinitionMonitoringScheduleConfigMonitoringScheduleConfig'6$sel:monitoringJobDefinition:MonitoringScheduleConfig':$sel:monitoringJobDefinitionName:MonitoringScheduleConfig'-$sel:monitoringType:MonitoringScheduleConfig'-$sel:scheduleConfig:MonitoringScheduleConfig'newMonitoringScheduleConfig0monitoringScheduleConfig_monitoringJobDefinition4monitoringScheduleConfig_monitoringJobDefinitionName'monitoringScheduleConfig_monitoringType'monitoringScheduleConfig_scheduleConfig $fToJSONMonitoringScheduleConfig $fNFDataMonitoringScheduleConfig"$fHashableMonitoringScheduleConfig"$fFromJSONMonitoringScheduleConfig$fEqMonitoringScheduleConfig$fReadMonitoringScheduleConfig$fShowMonitoringScheduleConfig!$fGenericMonitoringScheduleConfigMonitoringScheduleMonitoringSchedule'%$sel:creationTime:MonitoringSchedule'%$sel:endpointName:MonitoringSchedule'&$sel:failureReason:MonitoringSchedule')$sel:lastModifiedTime:MonitoringSchedule'7$sel:lastMonitoringExecutionSummary:MonitoringSchedule'.$sel:monitoringScheduleArn:MonitoringSchedule'1$sel:monitoringScheduleConfig:MonitoringSchedule'/$sel:monitoringScheduleName:MonitoringSchedule'1$sel:monitoringScheduleStatus:MonitoringSchedule''$sel:monitoringType:MonitoringSchedule'$sel:tags:MonitoringSchedule'newMonitoringSchedulemonitoringSchedule_creationTimemonitoringSchedule_endpointName monitoringSchedule_failureReason#monitoringSchedule_lastModifiedTime1monitoringSchedule_lastMonitoringExecutionSummary(monitoringSchedule_monitoringScheduleArn+monitoringSchedule_monitoringScheduleConfig)monitoringSchedule_monitoringScheduleName+monitoringSchedule_monitoringScheduleStatus!monitoringSchedule_monitoringTypemonitoringSchedule_tags$fNFDataMonitoringSchedule$fHashableMonitoringSchedule$fFromJSONMonitoringSchedule$fEqMonitoringSchedule$fReadMonitoringSchedule$fShowMonitoringSchedule$fGenericMonitoringScheduleEndpoint Endpoint' $sel:dataCaptureConfig:Endpoint'$sel:failureReason:Endpoint'"$sel:monitoringSchedules:Endpoint'!$sel:productionVariants:Endpoint''$sel:shadowProductionVariants:Endpoint'$sel:tags:Endpoint'$sel:endpointName:Endpoint'$sel:endpointArn:Endpoint'!$sel:endpointConfigName:Endpoint'$sel:endpointStatus:Endpoint'$sel:creationTime:Endpoint'$sel:lastModifiedTime:Endpoint' newEndpointendpoint_dataCaptureConfigendpoint_failureReasonendpoint_monitoringSchedulesendpoint_productionVariants!endpoint_shadowProductionVariants endpoint_tagsendpoint_endpointNameendpoint_endpointArnendpoint_endpointConfigNameendpoint_endpointStatusendpoint_creationTimeendpoint_lastModifiedTime$fNFDataEndpoint$fHashableEndpoint$fFromJSONEndpoint $fEqEndpoint$fReadEndpoint$fShowEndpoint$fGenericEndpoint ModelDashboardMonitoringSchedule!ModelDashboardMonitoringSchedule'3$sel:creationTime:ModelDashboardMonitoringSchedule'3$sel:endpointName:ModelDashboardMonitoringSchedule'4$sel:failureReason:ModelDashboardMonitoringSchedule'7$sel:lastModifiedTime:ModelDashboardMonitoringSchedule'$sel:lastMonitoringExecutionSummary:ModelDashboardMonitoringSchedule'?$sel:monitoringAlertSummaries:ModelDashboardMonitoringSchedule'<$sel:monitoringScheduleArn:ModelDashboardMonitoringSchedule'?$sel:monitoringScheduleConfig:ModelDashboardMonitoringSchedule'=$sel:monitoringScheduleName:ModelDashboardMonitoringSchedule'?$sel:monitoringScheduleStatus:ModelDashboardMonitoringSchedule'5$sel:monitoringType:ModelDashboardMonitoringSchedule'#newModelDashboardMonitoringSchedule-modelDashboardMonitoringSchedule_creationTime-modelDashboardMonitoringSchedule_endpointName.modelDashboardMonitoringSchedule_failureReason1modelDashboardMonitoringSchedule_lastModifiedTime?modelDashboardMonitoringSchedule_lastMonitoringExecutionSummary9modelDashboardMonitoringSchedule_monitoringAlertSummaries6modelDashboardMonitoringSchedule_monitoringScheduleArn9modelDashboardMonitoringSchedule_monitoringScheduleConfig7modelDashboardMonitoringSchedule_monitoringScheduleName9modelDashboardMonitoringSchedule_monitoringScheduleStatus/modelDashboardMonitoringSchedule_monitoringType($fNFDataModelDashboardMonitoringSchedule*$fHashableModelDashboardMonitoringSchedule*$fFromJSONModelDashboardMonitoringSchedule$$fEqModelDashboardMonitoringSchedule&$fReadModelDashboardMonitoringSchedule&$fShowModelDashboardMonitoringSchedule)$fGenericModelDashboardMonitoringScheduleMonitoringNetworkConfigMonitoringNetworkConfig'$sel:enableInterContainerTrafficEncryption:MonitoringNetworkConfig'4$sel:enableNetworkIsolation:MonitoringNetworkConfig''$sel:vpcConfig:MonitoringNetworkConfig'newMonitoringNetworkConfig=monitoringNetworkConfig_enableInterContainerTrafficEncryption.monitoringNetworkConfig_enableNetworkIsolation!monitoringNetworkConfig_vpcConfig$fToJSONMonitoringNetworkConfig$fNFDataMonitoringNetworkConfig!$fHashableMonitoringNetworkConfig!$fFromJSONMonitoringNetworkConfig$fEqMonitoringNetworkConfig$fReadMonitoringNetworkConfig$fShowMonitoringNetworkConfig $fGenericMonitoringNetworkConfigModelModel'$sel:containers:Model'$sel:creationTime:Model'"$sel:enableNetworkIsolation:Model'$sel:executionRoleArn:Model'$$sel:inferenceExecutionConfig:Model'$sel:modelArn:Model'$sel:modelName:Model'$sel:primaryContainer:Model'$sel:tags:Model'$sel:vpcConfig:Model'newModelmodel_containersmodel_creationTimemodel_enableNetworkIsolationmodel_executionRoleArnmodel_inferenceExecutionConfigmodel_modelArnmodel_modelNamemodel_primaryContainer model_tagsmodel_vpcConfig $fNFDataModel$fHashableModel$fFromJSONModel $fEqModel $fReadModel $fShowModel$fGenericModelModelDashboardModelModelDashboardModel'#$sel:endpoints:ModelDashboardModel'/$sel:lastBatchTransformJob:ModelDashboardModel'$sel:model:ModelDashboardModel'#$sel:modelCard:ModelDashboardModel'-$sel:monitoringSchedules:ModelDashboardModel'newModelDashboardModelmodelDashboardModel_endpoints)modelDashboardModel_lastBatchTransformJobmodelDashboardModel_modelmodelDashboardModel_modelCard'modelDashboardModel_monitoringSchedules$fNFDataModelDashboardModel$fHashableModelDashboardModel$fFromJSONModelDashboardModel$fEqModelDashboardModel$fReadModelDashboardModel$fShowModelDashboardModel$fGenericModelDashboardModelLabelingJobResourceConfigLabelingJobResourceConfig'.$sel:volumeKmsKeyId:LabelingJobResourceConfig')$sel:vpcConfig:LabelingJobResourceConfig'newLabelingJobResourceConfig(labelingJobResourceConfig_volumeKmsKeyId#labelingJobResourceConfig_vpcConfig!$fToJSONLabelingJobResourceConfig!$fNFDataLabelingJobResourceConfig#$fHashableLabelingJobResourceConfig#$fFromJSONLabelingJobResourceConfig$fEqLabelingJobResourceConfig$fReadLabelingJobResourceConfig$fShowLabelingJobResourceConfig"$fGenericLabelingJobResourceConfigLabelingJobAlgorithmsConfigLabelingJobAlgorithmsConfig'?$sel:initialActiveLearningModelArn:LabelingJobAlgorithmsConfig';$sel:labelingJobResourceConfig:LabelingJobAlgorithmsConfig'$sel:labelingJobAlgorithmSpecificationArn:LabelingJobAlgorithmsConfig'newLabelingJobAlgorithmsConfig9labelingJobAlgorithmsConfig_initialActiveLearningModelArn5labelingJobAlgorithmsConfig_labelingJobResourceConfiglabelingJobAlgorithmsConfig_labelingJobAlgorithmSpecificationArn#$fToJSONLabelingJobAlgorithmsConfig#$fNFDataLabelingJobAlgorithmsConfig%$fHashableLabelingJobAlgorithmsConfig%$fFromJSONLabelingJobAlgorithmsConfig$fEqLabelingJobAlgorithmsConfig!$fReadLabelingJobAlgorithmsConfig!$fShowLabelingJobAlgorithmsConfig$$fGenericLabelingJobAlgorithmsConfig#HyperParameterTrainingJobDefinition$HyperParameterTrainingJobDefinition':$sel:checkpointConfig:HyperParameterTrainingJobDefinition'8$sel:definitionName:HyperParameterTrainingJobDefinition'$sel:enableInterContainerTrafficEncryption:HyperParameterTrainingJobDefinition'$sel:enableManagedSpotTraining:HyperParameterTrainingJobDefinition'$sel:enableNetworkIsolation:HyperParameterTrainingJobDefinition'>$sel:hyperParameterRanges:HyperParameterTrainingJobDefinition'$sel:hyperParameterTuningResourceConfig:HyperParameterTrainingJobDefinition'9$sel:inputDataConfig:HyperParameterTrainingJobDefinition'8$sel:resourceConfig:HyperParameterTrainingJobDefinition'7$sel:retryStrategy:HyperParameterTrainingJobDefinition'?$sel:staticHyperParameters:HyperParameterTrainingJobDefinition'9$sel:tuningObjective:HyperParameterTrainingJobDefinition'3$sel:vpcConfig:HyperParameterTrainingJobDefinition'$sel:algorithmSpecification:HyperParameterTrainingJobDefinition'1$sel:roleArn:HyperParameterTrainingJobDefinition':$sel:outputDataConfig:HyperParameterTrainingJobDefinition';$sel:stoppingCondition:HyperParameterTrainingJobDefinition'&newHyperParameterTrainingJobDefinition4hyperParameterTrainingJobDefinition_checkpointConfig2hyperParameterTrainingJobDefinition_definitionNamehyperParameterTrainingJobDefinition_enableInterContainerTrafficEncryption=hyperParameterTrainingJobDefinition_enableManagedSpotTraining:hyperParameterTrainingJobDefinition_enableNetworkIsolation8hyperParameterTrainingJobDefinition_hyperParameterRangeshyperParameterTrainingJobDefinition_hyperParameterTuningResourceConfig3hyperParameterTrainingJobDefinition_inputDataConfig2hyperParameterTrainingJobDefinition_resourceConfig1hyperParameterTrainingJobDefinition_retryStrategy9hyperParameterTrainingJobDefinition_staticHyperParameters3hyperParameterTrainingJobDefinition_tuningObjective-hyperParameterTrainingJobDefinition_vpcConfig:hyperParameterTrainingJobDefinition_algorithmSpecification+hyperParameterTrainingJobDefinition_roleArn4hyperParameterTrainingJobDefinition_outputDataConfig5hyperParameterTrainingJobDefinition_stoppingCondition+$fToJSONHyperParameterTrainingJobDefinition+$fNFDataHyperParameterTrainingJobDefinition-$fHashableHyperParameterTrainingJobDefinition-$fFromJSONHyperParameterTrainingJobDefinition'$fEqHyperParameterTrainingJobDefinition)$fReadHyperParameterTrainingJobDefinition)$fShowHyperParameterTrainingJobDefinition,$fGenericHyperParameterTrainingJobDefinition#HyperParameterTuningJobSearchEntity$HyperParameterTuningJobSearchEntity'9$sel:bestTrainingJob:HyperParameterTuningJobSearchEntity'6$sel:creationTime:HyperParameterTuningJobSearchEntity'7$sel:failureReason:HyperParameterTuningJobSearchEntity'$sel:hyperParameterTuningEndTime:HyperParameterTuningJobSearchEntity'$sel:hyperParameterTuningJobArn:HyperParameterTuningJobSearchEntity'$sel:hyperParameterTuningJobConfig:HyperParameterTuningJobSearchEntity'$sel:hyperParameterTuningJobName:HyperParameterTuningJobSearchEntity'$sel:hyperParameterTuningJobStatus:HyperParameterTuningJobSearchEntity':$sel:lastModifiedTime:HyperParameterTuningJobSearchEntity'$sel:objectiveStatusCounters:HyperParameterTuningJobSearchEntity'$sel:overallBestTrainingJob:HyperParameterTuningJobSearchEntity'.$sel:tags:HyperParameterTuningJobSearchEntity'?$sel:trainingJobDefinition:HyperParameterTuningJobSearchEntity'$sel:trainingJobDefinitions:HyperParameterTuningJobSearchEntity'$sel:trainingJobStatusCounters:HyperParameterTuningJobSearchEntity'9$sel:warmStartConfig:HyperParameterTuningJobSearchEntity'&newHyperParameterTuningJobSearchEntity3hyperParameterTuningJobSearchEntity_bestTrainingJob0hyperParameterTuningJobSearchEntity_creationTime1hyperParameterTuningJobSearchEntity_failureReason?hyperParameterTuningJobSearchEntity_hyperParameterTuningEndTime>hyperParameterTuningJobSearchEntity_hyperParameterTuningJobArnhyperParameterTuningJobSearchEntity_hyperParameterTuningJobConfig?hyperParameterTuningJobSearchEntity_hyperParameterTuningJobNamehyperParameterTuningJobSearchEntity_hyperParameterTuningJobStatus4hyperParameterTuningJobSearchEntity_lastModifiedTime;hyperParameterTuningJobSearchEntity_objectiveStatusCounters:hyperParameterTuningJobSearchEntity_overallBestTrainingJob(hyperParameterTuningJobSearchEntity_tags9hyperParameterTuningJobSearchEntity_trainingJobDefinition:hyperParameterTuningJobSearchEntity_trainingJobDefinitions=hyperParameterTuningJobSearchEntity_trainingJobStatusCounters3hyperParameterTuningJobSearchEntity_warmStartConfig+$fNFDataHyperParameterTuningJobSearchEntity-$fHashableHyperParameterTuningJobSearchEntity-$fFromJSONHyperParameterTuningJobSearchEntity'$fEqHyperParameterTuningJobSearchEntity)$fReadHyperParameterTuningJobSearchEntity)$fShowHyperParameterTuningJobSearchEntity,$fGenericHyperParameterTuningJobSearchEntity SearchRecord SearchRecord'$sel:endpoint:SearchRecord'$sel:experiment:SearchRecord'$sel:featureGroup:SearchRecord'"$sel:featureMetadata:SearchRecord'*$sel:hyperParameterTuningJob:SearchRecord'$sel:model:SearchRecord'$sel:modelCard:SearchRecord'$sel:modelPackage:SearchRecord'$$sel:modelPackageGroup:SearchRecord'$sel:pipeline:SearchRecord'$$sel:pipelineExecution:SearchRecord'$sel:project:SearchRecord'$sel:trainingJob:SearchRecord'$sel:trial:SearchRecord'!$sel:trialComponent:SearchRecord'newSearchRecordsearchRecord_endpointsearchRecord_experimentsearchRecord_featureGroupsearchRecord_featureMetadata$searchRecord_hyperParameterTuningJobsearchRecord_modelsearchRecord_modelCardsearchRecord_modelPackagesearchRecord_modelPackageGroupsearchRecord_pipelinesearchRecord_pipelineExecutionsearchRecord_projectsearchRecord_trainingJobsearchRecord_trialsearchRecord_trialComponent$fNFDataSearchRecord$fHashableSearchRecord$fFromJSONSearchRecord$fEqSearchRecord$fShowSearchRecord$fGenericSearchRecordAutoMLSecurityConfigAutoMLSecurityConfig'$sel:enableInterContainerTrafficEncryption:AutoMLSecurityConfig')$sel:volumeKmsKeyId:AutoMLSecurityConfig'$$sel:vpcConfig:AutoMLSecurityConfig'newAutoMLSecurityConfig:autoMLSecurityConfig_enableInterContainerTrafficEncryption#autoMLSecurityConfig_volumeKmsKeyIdautoMLSecurityConfig_vpcConfig$fToJSONAutoMLSecurityConfig$fNFDataAutoMLSecurityConfig$fHashableAutoMLSecurityConfig$fFromJSONAutoMLSecurityConfig$fEqAutoMLSecurityConfig$fReadAutoMLSecurityConfig$fShowAutoMLSecurityConfig$fGenericAutoMLSecurityConfigAutoMLJobConfigAutoMLJobConfig'/$sel:candidateGenerationConfig:AutoMLJobConfig'($sel:completionCriteria:AutoMLJobConfig'%$sel:dataSplitConfig:AutoMLJobConfig'$sel:mode:AutoMLJobConfig'$$sel:securityConfig:AutoMLJobConfig'newAutoMLJobConfig)autoMLJobConfig_candidateGenerationConfig"autoMLJobConfig_completionCriteriaautoMLJobConfig_dataSplitConfigautoMLJobConfig_modeautoMLJobConfig_securityConfig$fToJSONAutoMLJobConfig$fNFDataAutoMLJobConfig$fHashableAutoMLJobConfig$fFromJSONAutoMLJobConfig$fEqAutoMLJobConfig$fReadAutoMLJobConfig$fShowAutoMLJobConfig$fGenericAutoMLJobConfigWarmPoolResourceStatusWarmPoolResourceStatus'fromWarmPoolResourceStatus!WarmPoolResourceStatus_TerminatedWarmPoolResourceStatus_ReusedWarmPoolResourceStatus_InUse WarmPoolResourceStatus_Available$fShowWarmPoolResourceStatus$fReadWarmPoolResourceStatus$fEqWarmPoolResourceStatus$fOrdWarmPoolResourceStatus$fGenericWarmPoolResourceStatus $fHashableWarmPoolResourceStatus$fNFDataWarmPoolResourceStatus $fFromTextWarmPoolResourceStatus$fToTextWarmPoolResourceStatus$$fToByteStringWarmPoolResourceStatus$fToLogWarmPoolResourceStatus $fToHeaderWarmPoolResourceStatus$fToQueryWarmPoolResourceStatus $fFromJSONWarmPoolResourceStatus#$fFromJSONKeyWarmPoolResourceStatus$fToJSONWarmPoolResourceStatus!$fToJSONKeyWarmPoolResourceStatus$fFromXMLWarmPoolResourceStatus$fToXMLWarmPoolResourceStatusWarmPoolStatusWarmPoolStatus':$sel:resourceRetainedBillableTimeInSeconds:WarmPoolStatus' $sel:reusedByJob:WarmPoolStatus'$sel:status:WarmPoolStatus'newWarmPoolStatus4warmPoolStatus_resourceRetainedBillableTimeInSecondswarmPoolStatus_reusedByJobwarmPoolStatus_status$fNFDataWarmPoolStatus$fHashableWarmPoolStatus$fFromJSONWarmPoolStatus$fEqWarmPoolStatus$fReadWarmPoolStatus$fShowWarmPoolStatus$fGenericWarmPoolStatusTrainingJobSummaryTrainingJobSummary')$sel:lastModifiedTime:TrainingJobSummary'($sel:trainingEndTime:TrainingJobSummary''$sel:warmPoolStatus:TrainingJobSummary'($sel:trainingJobName:TrainingJobSummary''$sel:trainingJobArn:TrainingJobSummary'%$sel:creationTime:TrainingJobSummary'*$sel:trainingJobStatus:TrainingJobSummary'newTrainingJobSummary#trainingJobSummary_lastModifiedTime"trainingJobSummary_trainingEndTime!trainingJobSummary_warmPoolStatus"trainingJobSummary_trainingJobName!trainingJobSummary_trainingJobArntrainingJobSummary_creationTime$trainingJobSummary_trainingJobStatus$fNFDataTrainingJobSummary$fHashableTrainingJobSummary$fFromJSONTrainingJobSummary$fEqTrainingJobSummary$fReadTrainingJobSummary$fShowTrainingJobSummary$fGenericTrainingJobSummaryWorkforceStatusWorkforceStatus'fromWorkforceStatusWorkforceStatus_UpdatingWorkforceStatus_InitializingWorkforceStatus_FailedWorkforceStatus_DeletingWorkforceStatus_Active$fShowWorkforceStatus$fReadWorkforceStatus$fEqWorkforceStatus$fOrdWorkforceStatus$fGenericWorkforceStatus$fHashableWorkforceStatus$fNFDataWorkforceStatus$fFromTextWorkforceStatus$fToTextWorkforceStatus$fToByteStringWorkforceStatus$fToLogWorkforceStatus$fToHeaderWorkforceStatus$fToQueryWorkforceStatus$fFromJSONWorkforceStatus$fFromJSONKeyWorkforceStatus$fToJSONWorkforceStatus$fToJSONKeyWorkforceStatus$fFromXMLWorkforceStatus$fToXMLWorkforceStatusWorkforceVpcConfigRequestWorkforceVpcConfigRequest'0$sel:securityGroupIds:WorkforceVpcConfigRequest''$sel:subnets:WorkforceVpcConfigRequest'%$sel:vpcId:WorkforceVpcConfigRequest'newWorkforceVpcConfigRequest*workforceVpcConfigRequest_securityGroupIds!workforceVpcConfigRequest_subnetsworkforceVpcConfigRequest_vpcId!$fToJSONWorkforceVpcConfigRequest!$fNFDataWorkforceVpcConfigRequest#$fHashableWorkforceVpcConfigRequest$fEqWorkforceVpcConfigRequest$fReadWorkforceVpcConfigRequest$fShowWorkforceVpcConfigRequest"$fGenericWorkforceVpcConfigRequestWorkforceVpcConfigResponseWorkforceVpcConfigResponse'.$sel:vpcEndpointId:WorkforceVpcConfigResponse'&$sel:vpcId:WorkforceVpcConfigResponse'1$sel:securityGroupIds:WorkforceVpcConfigResponse'($sel:subnets:WorkforceVpcConfigResponse'newWorkforceVpcConfigResponse(workforceVpcConfigResponse_vpcEndpointId workforceVpcConfigResponse_vpcId+workforceVpcConfigResponse_securityGroupIds"workforceVpcConfigResponse_subnets"$fNFDataWorkforceVpcConfigResponse$$fHashableWorkforceVpcConfigResponse$$fFromJSONWorkforceVpcConfigResponse$fEqWorkforceVpcConfigResponse $fReadWorkforceVpcConfigResponse $fShowWorkforceVpcConfigResponse#$fGenericWorkforceVpcConfigResponse Workforce Workforce'$sel:cognitoConfig:Workforce'$sel:createDate:Workforce'$sel:failureReason:Workforce'$sel:lastUpdatedDate:Workforce'$sel:oidcConfig:Workforce'$sel:sourceIpConfig:Workforce'$sel:status:Workforce'$sel:subDomain:Workforce'"$sel:workforceVpcConfig:Workforce'$sel:workforceName:Workforce'$sel:workforceArn:Workforce' newWorkforceworkforce_cognitoConfigworkforce_createDateworkforce_failureReasonworkforce_lastUpdatedDateworkforce_oidcConfigworkforce_sourceIpConfigworkforce_statusworkforce_subDomainworkforce_workforceVpcConfigworkforce_workforceNameworkforce_workforceArn$fNFDataWorkforce$fHashableWorkforce$fFromJSONWorkforce $fEqWorkforce$fReadWorkforce$fShowWorkforce$fGenericWorkforceWorkteam Workteam'$sel:createDate:Workteam'$sel:lastUpdatedDate:Workteam'($sel:notificationConfiguration:Workteam' $sel:productListingIds:Workteam'$sel:subDomain:Workteam'$sel:workforceArn:Workteam'$sel:workteamName:Workteam' $sel:memberDefinitions:Workteam'$sel:workteamArn:Workteam'$sel:description:Workteam' newWorkteamworkteam_createDateworkteam_lastUpdatedDate"workteam_notificationConfigurationworkteam_productListingIdsworkteam_subDomainworkteam_workforceArnworkteam_workteamNameworkteam_memberDefinitionsworkteam_workteamArnworkteam_description$fNFDataWorkteam$fHashableWorkteam$fFromJSONWorkteam $fEqWorkteam$fReadWorkteam$fShowWorkteam$fGenericWorkteamdefaultService_ConflictException_ResourceInUse_ResourceLimitExceeded_ResourceNotFoundStopTransformJobResponseStopTransformJobResponse'StopTransformJobStopTransformJob''$sel:transformJobName:StopTransformJob'newStopTransformJob!stopTransformJob_transformJobNamenewStopTransformJobResponse$fToQueryStopTransformJob$fToPathStopTransformJob$fToJSONStopTransformJob$fToHeadersStopTransformJob$fNFDataStopTransformJob$fHashableStopTransformJob $fNFDataStopTransformJobResponse$fAWSRequestStopTransformJob$fEqStopTransformJobResponse$fReadStopTransformJobResponse$fShowStopTransformJobResponse!$fGenericStopTransformJobResponse$fEqStopTransformJob$fReadStopTransformJob$fShowStopTransformJob$fGenericStopTransformJobStopTrainingJobResponseStopTrainingJobResponse'StopTrainingJobStopTrainingJob'%$sel:trainingJobName:StopTrainingJob'newStopTrainingJobstopTrainingJob_trainingJobNamenewStopTrainingJobResponse$fToQueryStopTrainingJob$fToPathStopTrainingJob$fToJSONStopTrainingJob$fToHeadersStopTrainingJob$fNFDataStopTrainingJob$fHashableStopTrainingJob$fNFDataStopTrainingJobResponse$fAWSRequestStopTrainingJob$fEqStopTrainingJobResponse$fReadStopTrainingJobResponse$fShowStopTrainingJobResponse $fGenericStopTrainingJobResponse$fEqStopTrainingJob$fReadStopTrainingJob$fShowStopTrainingJob$fGenericStopTrainingJobStopProcessingJobResponseStopProcessingJobResponse'StopProcessingJobStopProcessingJob')$sel:processingJobName:StopProcessingJob'newStopProcessingJob#stopProcessingJob_processingJobNamenewStopProcessingJobResponse$fToQueryStopProcessingJob$fToPathStopProcessingJob$fToJSONStopProcessingJob$fToHeadersStopProcessingJob$fNFDataStopProcessingJob$fHashableStopProcessingJob!$fNFDataStopProcessingJobResponse$fAWSRequestStopProcessingJob$fEqStopProcessingJobResponse$fReadStopProcessingJobResponse$fShowStopProcessingJobResponse"$fGenericStopProcessingJobResponse$fEqStopProcessingJob$fReadStopProcessingJob$fShowStopProcessingJob$fGenericStopProcessingJobStopPipelineExecutionResponseStopPipelineExecutionResponse'8$sel:pipelineExecutionArn:StopPipelineExecutionResponse'.$sel:httpStatus:StopPipelineExecutionResponse'StopPipelineExecutionStopPipelineExecution'0$sel:pipelineExecutionArn:StopPipelineExecution'.$sel:clientRequestToken:StopPipelineExecution'newStopPipelineExecution*stopPipelineExecution_pipelineExecutionArn(stopPipelineExecution_clientRequestToken newStopPipelineExecutionResponse2stopPipelineExecutionResponse_pipelineExecutionArn(stopPipelineExecutionResponse_httpStatus$fToQueryStopPipelineExecution$fToPathStopPipelineExecution$fToJSONStopPipelineExecution $fToHeadersStopPipelineExecution$fNFDataStopPipelineExecution$fHashableStopPipelineExecution%$fNFDataStopPipelineExecutionResponse!$fAWSRequestStopPipelineExecution!$fEqStopPipelineExecutionResponse#$fReadStopPipelineExecutionResponse#$fShowStopPipelineExecutionResponse&$fGenericStopPipelineExecutionResponse$fEqStopPipelineExecution$fReadStopPipelineExecution$fShowStopPipelineExecution$fGenericStopPipelineExecutionStopNotebookInstanceResponseStopNotebookInstanceResponse'StopNotebookInstanceStopNotebookInstance'/$sel:notebookInstanceName:StopNotebookInstance'newStopNotebookInstance)stopNotebookInstance_notebookInstanceNamenewStopNotebookInstanceResponse$fToQueryStopNotebookInstance$fToPathStopNotebookInstance$fToJSONStopNotebookInstance$fToHeadersStopNotebookInstance$fNFDataStopNotebookInstance$fHashableStopNotebookInstance$$fNFDataStopNotebookInstanceResponse $fAWSRequestStopNotebookInstance $fEqStopNotebookInstanceResponse"$fReadStopNotebookInstanceResponse"$fShowStopNotebookInstanceResponse%$fGenericStopNotebookInstanceResponse$fEqStopNotebookInstance$fReadStopNotebookInstance$fShowStopNotebookInstance$fGenericStopNotebookInstanceStopMonitoringScheduleResponseStopMonitoringScheduleResponse'StopMonitoringScheduleStopMonitoringSchedule'3$sel:monitoringScheduleName:StopMonitoringSchedule'newStopMonitoringSchedule-stopMonitoringSchedule_monitoringScheduleName!newStopMonitoringScheduleResponse$fToQueryStopMonitoringSchedule$fToPathStopMonitoringSchedule$fToJSONStopMonitoringSchedule!$fToHeadersStopMonitoringSchedule$fNFDataStopMonitoringSchedule $fHashableStopMonitoringSchedule&$fNFDataStopMonitoringScheduleResponse"$fAWSRequestStopMonitoringSchedule"$fEqStopMonitoringScheduleResponse$$fReadStopMonitoringScheduleResponse$$fShowStopMonitoringScheduleResponse'$fGenericStopMonitoringScheduleResponse$fEqStopMonitoringSchedule$fReadStopMonitoringSchedule$fShowStopMonitoringSchedule$fGenericStopMonitoringScheduleStopLabelingJobResponseStopLabelingJobResponse'StopLabelingJobStopLabelingJob'%$sel:labelingJobName:StopLabelingJob'newStopLabelingJobstopLabelingJob_labelingJobNamenewStopLabelingJobResponse$fToQueryStopLabelingJob$fToPathStopLabelingJob$fToJSONStopLabelingJob$fToHeadersStopLabelingJob$fNFDataStopLabelingJob$fHashableStopLabelingJob$fNFDataStopLabelingJobResponse$fAWSRequestStopLabelingJob$fEqStopLabelingJobResponse$fReadStopLabelingJobResponse$fShowStopLabelingJobResponse $fGenericStopLabelingJobResponse$fEqStopLabelingJob$fReadStopLabelingJob$fShowStopLabelingJob$fGenericStopLabelingJob'StopInferenceRecommendationsJobResponse(StopInferenceRecommendationsJobResponse'StopInferenceRecommendationsJob StopInferenceRecommendationsJob'-$sel:jobName:StopInferenceRecommendationsJob'"newStopInferenceRecommendationsJob'stopInferenceRecommendationsJob_jobName*newStopInferenceRecommendationsJobResponse($fToQueryStopInferenceRecommendationsJob'$fToPathStopInferenceRecommendationsJob'$fToJSONStopInferenceRecommendationsJob*$fToHeadersStopInferenceRecommendationsJob'$fNFDataStopInferenceRecommendationsJob)$fHashableStopInferenceRecommendationsJob/$fNFDataStopInferenceRecommendationsJobResponse+$fAWSRequestStopInferenceRecommendationsJob+$fEqStopInferenceRecommendationsJobResponse-$fReadStopInferenceRecommendationsJobResponse-$fShowStopInferenceRecommendationsJobResponse0$fGenericStopInferenceRecommendationsJobResponse#$fEqStopInferenceRecommendationsJob%$fReadStopInferenceRecommendationsJob%$fShowStopInferenceRecommendationsJob($fGenericStopInferenceRecommendationsJobStopInferenceExperimentResponse StopInferenceExperimentResponse'0$sel:httpStatus:StopInferenceExperimentResponse'<$sel:inferenceExperimentArn:StopInferenceExperimentResponse'StopInferenceExperimentStopInferenceExperiment'2$sel:desiredModelVariants:StopInferenceExperiment'*$sel:desiredState:StopInferenceExperiment'$$sel:reason:StopInferenceExperiment'"$sel:name:StopInferenceExperiment'1$sel:modelVariantActions:StopInferenceExperiment'newStopInferenceExperiment,stopInferenceExperiment_desiredModelVariants$stopInferenceExperiment_desiredStatestopInferenceExperiment_reasonstopInferenceExperiment_name+stopInferenceExperiment_modelVariantActions"newStopInferenceExperimentResponse*stopInferenceExperimentResponse_httpStatus6stopInferenceExperimentResponse_inferenceExperimentArn $fToQueryStopInferenceExperiment$fToPathStopInferenceExperiment$fToJSONStopInferenceExperiment"$fToHeadersStopInferenceExperiment$fNFDataStopInferenceExperiment!$fHashableStopInferenceExperiment'$fNFDataStopInferenceExperimentResponse#$fAWSRequestStopInferenceExperiment#$fEqStopInferenceExperimentResponse%$fReadStopInferenceExperimentResponse%$fShowStopInferenceExperimentResponse($fGenericStopInferenceExperimentResponse$fEqStopInferenceExperiment$fReadStopInferenceExperiment$fShowStopInferenceExperiment $fGenericStopInferenceExperiment#StopHyperParameterTuningJobResponse$StopHyperParameterTuningJobResponse'StopHyperParameterTuningJobStopHyperParameterTuningJob'=$sel:hyperParameterTuningJobName:StopHyperParameterTuningJob'newStopHyperParameterTuningJob7stopHyperParameterTuningJob_hyperParameterTuningJobName&newStopHyperParameterTuningJobResponse$$fToQueryStopHyperParameterTuningJob#$fToPathStopHyperParameterTuningJob#$fToJSONStopHyperParameterTuningJob&$fToHeadersStopHyperParameterTuningJob#$fNFDataStopHyperParameterTuningJob%$fHashableStopHyperParameterTuningJob+$fNFDataStopHyperParameterTuningJobResponse'$fAWSRequestStopHyperParameterTuningJob'$fEqStopHyperParameterTuningJobResponse)$fReadStopHyperParameterTuningJobResponse)$fShowStopHyperParameterTuningJobResponse,$fGenericStopHyperParameterTuningJobResponse$fEqStopHyperParameterTuningJob!$fReadStopHyperParameterTuningJob!$fShowStopHyperParameterTuningJob$$fGenericStopHyperParameterTuningJobStopEdgePackagingJobResponseStopEdgePackagingJobResponse'StopEdgePackagingJobStopEdgePackagingJob'/$sel:edgePackagingJobName:StopEdgePackagingJob'newStopEdgePackagingJob)stopEdgePackagingJob_edgePackagingJobNamenewStopEdgePackagingJobResponse$fToQueryStopEdgePackagingJob$fToPathStopEdgePackagingJob$fToJSONStopEdgePackagingJob$fToHeadersStopEdgePackagingJob$fNFDataStopEdgePackagingJob$fHashableStopEdgePackagingJob$$fNFDataStopEdgePackagingJobResponse $fAWSRequestStopEdgePackagingJob $fEqStopEdgePackagingJobResponse"$fReadStopEdgePackagingJobResponse"$fShowStopEdgePackagingJobResponse%$fGenericStopEdgePackagingJobResponse$fEqStopEdgePackagingJob$fReadStopEdgePackagingJob$fShowStopEdgePackagingJob$fGenericStopEdgePackagingJobStopEdgeDeploymentStageResponse StopEdgeDeploymentStageResponse'StopEdgeDeploymentStageStopEdgeDeploymentStage'4$sel:edgeDeploymentPlanName:StopEdgeDeploymentStage''$sel:stageName:StopEdgeDeploymentStage'newStopEdgeDeploymentStage.stopEdgeDeploymentStage_edgeDeploymentPlanName!stopEdgeDeploymentStage_stageName"newStopEdgeDeploymentStageResponse $fToQueryStopEdgeDeploymentStage$fToPathStopEdgeDeploymentStage$fToJSONStopEdgeDeploymentStage"$fToHeadersStopEdgeDeploymentStage$fNFDataStopEdgeDeploymentStage!$fHashableStopEdgeDeploymentStage'$fNFDataStopEdgeDeploymentStageResponse#$fAWSRequestStopEdgeDeploymentStage#$fEqStopEdgeDeploymentStageResponse%$fReadStopEdgeDeploymentStageResponse%$fShowStopEdgeDeploymentStageResponse($fGenericStopEdgeDeploymentStageResponse$fEqStopEdgeDeploymentStage$fReadStopEdgeDeploymentStage$fShowStopEdgeDeploymentStage $fGenericStopEdgeDeploymentStageStopCompilationJobResponseStopCompilationJobResponse'StopCompilationJobStopCompilationJob'+$sel:compilationJobName:StopCompilationJob'newStopCompilationJob%stopCompilationJob_compilationJobNamenewStopCompilationJobResponse$fToQueryStopCompilationJob$fToPathStopCompilationJob$fToJSONStopCompilationJob$fToHeadersStopCompilationJob$fNFDataStopCompilationJob$fHashableStopCompilationJob"$fNFDataStopCompilationJobResponse$fAWSRequestStopCompilationJob$fEqStopCompilationJobResponse $fReadStopCompilationJobResponse $fShowStopCompilationJobResponse#$fGenericStopCompilationJobResponse$fEqStopCompilationJob$fReadStopCompilationJob$fShowStopCompilationJob$fGenericStopCompilationJobStopAutoMLJobResponseStopAutoMLJobResponse' StopAutoMLJobStopAutoMLJob'!$sel:autoMLJobName:StopAutoMLJob'newStopAutoMLJobstopAutoMLJob_autoMLJobNamenewStopAutoMLJobResponse$fToQueryStopAutoMLJob$fToPathStopAutoMLJob$fToJSONStopAutoMLJob$fToHeadersStopAutoMLJob$fNFDataStopAutoMLJob$fHashableStopAutoMLJob$fNFDataStopAutoMLJobResponse$fAWSRequestStopAutoMLJob$fEqStopAutoMLJobResponse$fReadStopAutoMLJobResponse$fShowStopAutoMLJobResponse$fGenericStopAutoMLJobResponse$fEqStopAutoMLJob$fReadStopAutoMLJob$fShowStopAutoMLJob$fGenericStopAutoMLJobStartPipelineExecutionResponseStartPipelineExecutionResponse'9$sel:pipelineExecutionArn:StartPipelineExecutionResponse'/$sel:httpStatus:StartPipelineExecutionResponse'StartPipelineExecutionStartPipelineExecution'5$sel:parallelismConfiguration:StartPipelineExecution'9$sel:pipelineExecutionDescription:StartPipelineExecution'9$sel:pipelineExecutionDisplayName:StartPipelineExecution'/$sel:pipelineParameters:StartPipelineExecution')$sel:pipelineName:StartPipelineExecution'/$sel:clientRequestToken:StartPipelineExecution'newStartPipelineExecution/startPipelineExecution_parallelismConfiguration3startPipelineExecution_pipelineExecutionDescription3startPipelineExecution_pipelineExecutionDisplayName)startPipelineExecution_pipelineParameters#startPipelineExecution_pipelineName)startPipelineExecution_clientRequestToken!newStartPipelineExecutionResponse3startPipelineExecutionResponse_pipelineExecutionArn)startPipelineExecutionResponse_httpStatus$fToQueryStartPipelineExecution$fToPathStartPipelineExecution$fToJSONStartPipelineExecution!$fToHeadersStartPipelineExecution$fNFDataStartPipelineExecution $fHashableStartPipelineExecution&$fNFDataStartPipelineExecutionResponse"$fAWSRequestStartPipelineExecution"$fEqStartPipelineExecutionResponse$$fReadStartPipelineExecutionResponse$$fShowStartPipelineExecutionResponse'$fGenericStartPipelineExecutionResponse$fEqStartPipelineExecution$fReadStartPipelineExecution$fShowStartPipelineExecution$fGenericStartPipelineExecutionStartNotebookInstanceResponseStartNotebookInstanceResponse'StartNotebookInstanceStartNotebookInstance'0$sel:notebookInstanceName:StartNotebookInstance'newStartNotebookInstance*startNotebookInstance_notebookInstanceName newStartNotebookInstanceResponse$fToQueryStartNotebookInstance$fToPathStartNotebookInstance$fToJSONStartNotebookInstance $fToHeadersStartNotebookInstance$fNFDataStartNotebookInstance$fHashableStartNotebookInstance%$fNFDataStartNotebookInstanceResponse!$fAWSRequestStartNotebookInstance!$fEqStartNotebookInstanceResponse#$fReadStartNotebookInstanceResponse#$fShowStartNotebookInstanceResponse&$fGenericStartNotebookInstanceResponse$fEqStartNotebookInstance$fReadStartNotebookInstance$fShowStartNotebookInstance$fGenericStartNotebookInstanceStartMonitoringScheduleResponse StartMonitoringScheduleResponse'StartMonitoringScheduleStartMonitoringSchedule'4$sel:monitoringScheduleName:StartMonitoringSchedule'newStartMonitoringSchedule.startMonitoringSchedule_monitoringScheduleName"newStartMonitoringScheduleResponse $fToQueryStartMonitoringSchedule$fToPathStartMonitoringSchedule$fToJSONStartMonitoringSchedule"$fToHeadersStartMonitoringSchedule$fNFDataStartMonitoringSchedule!$fHashableStartMonitoringSchedule'$fNFDataStartMonitoringScheduleResponse#$fAWSRequestStartMonitoringSchedule#$fEqStartMonitoringScheduleResponse%$fReadStartMonitoringScheduleResponse%$fShowStartMonitoringScheduleResponse($fGenericStartMonitoringScheduleResponse$fEqStartMonitoringSchedule$fReadStartMonitoringSchedule$fShowStartMonitoringSchedule $fGenericStartMonitoringSchedule StartInferenceExperimentResponse!StartInferenceExperimentResponse'1$sel:httpStatus:StartInferenceExperimentResponse'=$sel:inferenceExperimentArn:StartInferenceExperimentResponse'StartInferenceExperimentStartInferenceExperiment'#$sel:name:StartInferenceExperiment'newStartInferenceExperimentstartInferenceExperiment_name#newStartInferenceExperimentResponse+startInferenceExperimentResponse_httpStatus7startInferenceExperimentResponse_inferenceExperimentArn!$fToQueryStartInferenceExperiment $fToPathStartInferenceExperiment $fToJSONStartInferenceExperiment#$fToHeadersStartInferenceExperiment $fNFDataStartInferenceExperiment"$fHashableStartInferenceExperiment($fNFDataStartInferenceExperimentResponse$$fAWSRequestStartInferenceExperiment$$fEqStartInferenceExperimentResponse&$fReadStartInferenceExperimentResponse&$fShowStartInferenceExperimentResponse)$fGenericStartInferenceExperimentResponse$fEqStartInferenceExperiment$fReadStartInferenceExperiment$fShowStartInferenceExperiment!$fGenericStartInferenceExperiment StartEdgeDeploymentStageResponse!StartEdgeDeploymentStageResponse'StartEdgeDeploymentStageStartEdgeDeploymentStage'5$sel:edgeDeploymentPlanName:StartEdgeDeploymentStage'($sel:stageName:StartEdgeDeploymentStage'newStartEdgeDeploymentStage/startEdgeDeploymentStage_edgeDeploymentPlanName"startEdgeDeploymentStage_stageName#newStartEdgeDeploymentStageResponse!$fToQueryStartEdgeDeploymentStage $fToPathStartEdgeDeploymentStage $fToJSONStartEdgeDeploymentStage#$fToHeadersStartEdgeDeploymentStage $fNFDataStartEdgeDeploymentStage"$fHashableStartEdgeDeploymentStage($fNFDataStartEdgeDeploymentStageResponse$$fAWSRequestStartEdgeDeploymentStage$$fEqStartEdgeDeploymentStageResponse&$fReadStartEdgeDeploymentStageResponse&$fShowStartEdgeDeploymentStageResponse)$fGenericStartEdgeDeploymentStageResponse$fEqStartEdgeDeploymentStage$fReadStartEdgeDeploymentStage$fShowStartEdgeDeploymentStage!$fGenericStartEdgeDeploymentStage(SendPipelineExecutionStepSuccessResponse)SendPipelineExecutionStepSuccessResponse'$sel:pipelineExecutionArn:SendPipelineExecutionStepSuccessResponse'9$sel:httpStatus:SendPipelineExecutionStepSuccessResponse' SendPipelineExecutionStepSuccess!SendPipelineExecutionStepSuccess'9$sel:clientRequestToken:SendPipelineExecutionStepSuccess'7$sel:outputParameters:SendPipelineExecutionStepSuccess'4$sel:callbackToken:SendPipelineExecutionStepSuccess'#newSendPipelineExecutionStepSuccess3sendPipelineExecutionStepSuccess_clientRequestToken1sendPipelineExecutionStepSuccess_outputParameters.sendPipelineExecutionStepSuccess_callbackToken+newSendPipelineExecutionStepSuccessResponse=sendPipelineExecutionStepSuccessResponse_pipelineExecutionArn3sendPipelineExecutionStepSuccessResponse_httpStatus)$fToQuerySendPipelineExecutionStepSuccess($fToPathSendPipelineExecutionStepSuccess($fToJSONSendPipelineExecutionStepSuccess+$fToHeadersSendPipelineExecutionStepSuccess($fNFDataSendPipelineExecutionStepSuccess*$fHashableSendPipelineExecutionStepSuccess0$fNFDataSendPipelineExecutionStepSuccessResponse,$fAWSRequestSendPipelineExecutionStepSuccess,$fEqSendPipelineExecutionStepSuccessResponse.$fReadSendPipelineExecutionStepSuccessResponse.$fShowSendPipelineExecutionStepSuccessResponse1$fGenericSendPipelineExecutionStepSuccessResponse$$fEqSendPipelineExecutionStepSuccess&$fReadSendPipelineExecutionStepSuccess&$fShowSendPipelineExecutionStepSuccess)$fGenericSendPipelineExecutionStepSuccess(SendPipelineExecutionStepFailureResponse)SendPipelineExecutionStepFailureResponse'$sel:pipelineExecutionArn:SendPipelineExecutionStepFailureResponse'9$sel:httpStatus:SendPipelineExecutionStepFailureResponse' SendPipelineExecutionStepFailure!SendPipelineExecutionStepFailure'9$sel:clientRequestToken:SendPipelineExecutionStepFailure'4$sel:failureReason:SendPipelineExecutionStepFailure'4$sel:callbackToken:SendPipelineExecutionStepFailure'#newSendPipelineExecutionStepFailure3sendPipelineExecutionStepFailure_clientRequestToken.sendPipelineExecutionStepFailure_failureReason.sendPipelineExecutionStepFailure_callbackToken+newSendPipelineExecutionStepFailureResponse=sendPipelineExecutionStepFailureResponse_pipelineExecutionArn3sendPipelineExecutionStepFailureResponse_httpStatus)$fToQuerySendPipelineExecutionStepFailure($fToPathSendPipelineExecutionStepFailure($fToJSONSendPipelineExecutionStepFailure+$fToHeadersSendPipelineExecutionStepFailure($fNFDataSendPipelineExecutionStepFailure*$fHashableSendPipelineExecutionStepFailure0$fNFDataSendPipelineExecutionStepFailureResponse,$fAWSRequestSendPipelineExecutionStepFailure,$fEqSendPipelineExecutionStepFailureResponse.$fReadSendPipelineExecutionStepFailureResponse.$fShowSendPipelineExecutionStepFailureResponse1$fGenericSendPipelineExecutionStepFailureResponse$$fEqSendPipelineExecutionStepFailure&$fReadSendPipelineExecutionStepFailure&$fShowSendPipelineExecutionStepFailure)$fGenericSendPipelineExecutionStepFailureSearchResponseSearchResponse'$sel:nextToken:SearchResponse'$sel:results:SearchResponse'$sel:httpStatus:SearchResponse'SearchSearch'$sel:maxResults:Search'$sel:nextToken:Search'$sel:searchExpression:Search'$sel:sortBy:Search'$sel:sortOrder:Search'$sel:resource:Search' newSearchsearch_maxResultssearch_nextTokensearch_searchExpression search_sortBysearch_sortOrdersearch_resourcenewSearchResponsesearchResponse_nextTokensearchResponse_resultssearchResponse_httpStatus$fToQuerySearch$fToPathSearch$fToJSONSearch$fToHeadersSearch$fNFDataSearch$fHashableSearch$fAWSPagerSearch$fNFDataSearchResponse$fAWSRequestSearch$fEqSearchResponse$fShowSearchResponse$fGenericSearchResponse $fEqSearch $fReadSearch $fShowSearch$fGenericSearchRetryPipelineExecutionResponseRetryPipelineExecutionResponse'9$sel:pipelineExecutionArn:RetryPipelineExecutionResponse'/$sel:httpStatus:RetryPipelineExecutionResponse'RetryPipelineExecutionRetryPipelineExecution'5$sel:parallelismConfiguration:RetryPipelineExecution'1$sel:pipelineExecutionArn:RetryPipelineExecution'/$sel:clientRequestToken:RetryPipelineExecution'newRetryPipelineExecution/retryPipelineExecution_parallelismConfiguration+retryPipelineExecution_pipelineExecutionArn)retryPipelineExecution_clientRequestToken!newRetryPipelineExecutionResponse3retryPipelineExecutionResponse_pipelineExecutionArn)retryPipelineExecutionResponse_httpStatus$fToQueryRetryPipelineExecution$fToPathRetryPipelineExecution$fToJSONRetryPipelineExecution!$fToHeadersRetryPipelineExecution$fNFDataRetryPipelineExecution $fHashableRetryPipelineExecution&$fNFDataRetryPipelineExecutionResponse"$fAWSRequestRetryPipelineExecution"$fEqRetryPipelineExecutionResponse$$fReadRetryPipelineExecutionResponse$$fShowRetryPipelineExecutionResponse'$fGenericRetryPipelineExecutionResponse$fEqRetryPipelineExecution$fReadRetryPipelineExecution$fShowRetryPipelineExecution$fGenericRetryPipelineExecutionRenderUiTemplateResponseRenderUiTemplateResponse')$sel:httpStatus:RenderUiTemplateResponse'.$sel:renderedContent:RenderUiTemplateResponse'%$sel:errors:RenderUiTemplateResponse'RenderUiTemplateRenderUiTemplate'%$sel:humanTaskUiArn:RenderUiTemplate'!$sel:uiTemplate:RenderUiTemplate'$sel:task:RenderUiTemplate'$sel:roleArn:RenderUiTemplate'newRenderUiTemplaterenderUiTemplate_humanTaskUiArnrenderUiTemplate_uiTemplaterenderUiTemplate_taskrenderUiTemplate_roleArnnewRenderUiTemplateResponse#renderUiTemplateResponse_httpStatus(renderUiTemplateResponse_renderedContentrenderUiTemplateResponse_errors$fToQueryRenderUiTemplate$fToPathRenderUiTemplate$fToJSONRenderUiTemplate$fToHeadersRenderUiTemplate$fNFDataRenderUiTemplate$fHashableRenderUiTemplate $fNFDataRenderUiTemplateResponse$fAWSRequestRenderUiTemplate$fEqRenderUiTemplateResponse$fReadRenderUiTemplateResponse$fShowRenderUiTemplateResponse!$fGenericRenderUiTemplateResponse$fEqRenderUiTemplate$fReadRenderUiTemplate$fShowRenderUiTemplate$fGenericRenderUiTemplateRegisterDevicesResponseRegisterDevicesResponse'RegisterDevicesRegisterDevices'$sel:tags:RegisterDevices'%$sel:deviceFleetName:RegisterDevices'$sel:devices:RegisterDevices'newRegisterDevicesregisterDevices_tagsregisterDevices_deviceFleetNameregisterDevices_devicesnewRegisterDevicesResponse$fToQueryRegisterDevices$fToPathRegisterDevices$fToJSONRegisterDevices$fToHeadersRegisterDevices$fNFDataRegisterDevices$fHashableRegisterDevices$fNFDataRegisterDevicesResponse$fAWSRequestRegisterDevices$fEqRegisterDevicesResponse$fReadRegisterDevicesResponse$fShowRegisterDevicesResponse $fGenericRegisterDevicesResponse$fEqRegisterDevices$fReadRegisterDevices$fShowRegisterDevices$fGenericRegisterDevicesQueryLineageResponseQueryLineageResponse' $sel:edges:QueryLineageResponse'$$sel:nextToken:QueryLineageResponse'#$sel:vertices:QueryLineageResponse'%$sel:httpStatus:QueryLineageResponse' QueryLineage QueryLineage'$sel:direction:QueryLineage'$sel:filters:QueryLineage'$sel:includeEdges:QueryLineage'$sel:maxDepth:QueryLineage'$sel:maxResults:QueryLineage'$sel:nextToken:QueryLineage'$sel:startArns:QueryLineage'newQueryLineagequeryLineage_directionqueryLineage_filtersqueryLineage_includeEdgesqueryLineage_maxDepthqueryLineage_maxResultsqueryLineage_nextTokenqueryLineage_startArnsnewQueryLineageResponsequeryLineageResponse_edgesqueryLineageResponse_nextTokenqueryLineageResponse_verticesqueryLineageResponse_httpStatus$fToQueryQueryLineage$fToPathQueryLineage$fToJSONQueryLineage$fToHeadersQueryLineage$fNFDataQueryLineage$fHashableQueryLineage$fNFDataQueryLineageResponse$fAWSRequestQueryLineage$fEqQueryLineageResponse$fReadQueryLineageResponse$fShowQueryLineageResponse$fGenericQueryLineageResponse$fEqQueryLineage$fReadQueryLineage$fShowQueryLineage$fGenericQueryLineage"PutModelPackageGroupPolicyResponse#PutModelPackageGroupPolicyResponse'3$sel:httpStatus:PutModelPackageGroupPolicyResponse'=$sel:modelPackageGroupArn:PutModelPackageGroupPolicyResponse'PutModelPackageGroupPolicyPutModelPackageGroupPolicy'6$sel:modelPackageGroupName:PutModelPackageGroupPolicy'/$sel:resourcePolicy:PutModelPackageGroupPolicy'newPutModelPackageGroupPolicy0putModelPackageGroupPolicy_modelPackageGroupName)putModelPackageGroupPolicy_resourcePolicy%newPutModelPackageGroupPolicyResponse-putModelPackageGroupPolicyResponse_httpStatus7putModelPackageGroupPolicyResponse_modelPackageGroupArn#$fToQueryPutModelPackageGroupPolicy"$fToPathPutModelPackageGroupPolicy"$fToJSONPutModelPackageGroupPolicy%$fToHeadersPutModelPackageGroupPolicy"$fNFDataPutModelPackageGroupPolicy$$fHashablePutModelPackageGroupPolicy*$fNFDataPutModelPackageGroupPolicyResponse&$fAWSRequestPutModelPackageGroupPolicy&$fEqPutModelPackageGroupPolicyResponse($fReadPutModelPackageGroupPolicyResponse($fShowPutModelPackageGroupPolicyResponse+$fGenericPutModelPackageGroupPolicyResponse$fEqPutModelPackageGroupPolicy $fReadPutModelPackageGroupPolicy $fShowPutModelPackageGroupPolicy#$fGenericPutModelPackageGroupPolicyListWorkteamsResponseListWorkteamsResponse'%$sel:nextToken:ListWorkteamsResponse'&$sel:httpStatus:ListWorkteamsResponse'%$sel:workteams:ListWorkteamsResponse' ListWorkteamsListWorkteams'$sel:maxResults:ListWorkteams' $sel:nameContains:ListWorkteams'$sel:nextToken:ListWorkteams'$sel:sortBy:ListWorkteams'$sel:sortOrder:ListWorkteams'newListWorkteamslistWorkteams_maxResultslistWorkteams_nameContainslistWorkteams_nextTokenlistWorkteams_sortBylistWorkteams_sortOrdernewListWorkteamsResponselistWorkteamsResponse_nextToken listWorkteamsResponse_httpStatuslistWorkteamsResponse_workteams$fToQueryListWorkteams$fToPathListWorkteams$fToJSONListWorkteams$fToHeadersListWorkteams$fNFDataListWorkteams$fHashableListWorkteams$fAWSPagerListWorkteams$fNFDataListWorkteamsResponse$fAWSRequestListWorkteams$fEqListWorkteamsResponse$fReadListWorkteamsResponse$fShowListWorkteamsResponse$fGenericListWorkteamsResponse$fEqListWorkteams$fReadListWorkteams$fShowListWorkteams$fGenericListWorkteamsListWorkforcesResponseListWorkforcesResponse'&$sel:nextToken:ListWorkforcesResponse''$sel:httpStatus:ListWorkforcesResponse''$sel:workforces:ListWorkforcesResponse'ListWorkforcesListWorkforces'$sel:maxResults:ListWorkforces'!$sel:nameContains:ListWorkforces'$sel:nextToken:ListWorkforces'$sel:sortBy:ListWorkforces'$sel:sortOrder:ListWorkforces'newListWorkforceslistWorkforces_maxResultslistWorkforces_nameContainslistWorkforces_nextTokenlistWorkforces_sortBylistWorkforces_sortOrdernewListWorkforcesResponse listWorkforcesResponse_nextToken!listWorkforcesResponse_httpStatus!listWorkforcesResponse_workforces$fToQueryListWorkforces$fToPathListWorkforces$fToJSONListWorkforces$fToHeadersListWorkforces$fNFDataListWorkforces$fHashableListWorkforces$fAWSPagerListWorkforces$fNFDataListWorkforcesResponse$fAWSRequestListWorkforces$fEqListWorkforcesResponse$fReadListWorkforcesResponse$fShowListWorkforcesResponse$fGenericListWorkforcesResponse$fEqListWorkforces$fReadListWorkforces$fShowListWorkforces$fGenericListWorkforcesListUserProfilesResponseListUserProfilesResponse'($sel:nextToken:ListUserProfilesResponse'+$sel:userProfiles:ListUserProfilesResponse')$sel:httpStatus:ListUserProfilesResponse'ListUserProfilesListUserProfiles'%$sel:domainIdEquals:ListUserProfiles'!$sel:maxResults:ListUserProfiles' $sel:nextToken:ListUserProfiles'$sel:sortBy:ListUserProfiles' $sel:sortOrder:ListUserProfiles'.$sel:userProfileNameContains:ListUserProfiles'newListUserProfileslistUserProfiles_domainIdEqualslistUserProfiles_maxResultslistUserProfiles_nextTokenlistUserProfiles_sortBylistUserProfiles_sortOrder(listUserProfiles_userProfileNameContainsnewListUserProfilesResponse"listUserProfilesResponse_nextToken%listUserProfilesResponse_userProfiles#listUserProfilesResponse_httpStatus$fToQueryListUserProfiles$fToPathListUserProfiles$fToJSONListUserProfiles$fToHeadersListUserProfiles$fNFDataListUserProfiles$fHashableListUserProfiles$fAWSPagerListUserProfiles $fNFDataListUserProfilesResponse$fAWSRequestListUserProfiles$fEqListUserProfilesResponse$fReadListUserProfilesResponse$fShowListUserProfilesResponse!$fGenericListUserProfilesResponse$fEqListUserProfiles$fReadListUserProfiles$fShowListUserProfiles$fGenericListUserProfilesListTrialsResponseListTrialsResponse'"$sel:nextToken:ListTrialsResponse''$sel:trialSummaries:ListTrialsResponse'#$sel:httpStatus:ListTrialsResponse' ListTrials ListTrials'$sel:createdAfter:ListTrials'$sel:createdBefore:ListTrials'$sel:experimentName:ListTrials'$sel:maxResults:ListTrials'$sel:nextToken:ListTrials'$sel:sortBy:ListTrials'$sel:sortOrder:ListTrials'#$sel:trialComponentName:ListTrials' newListTrialslistTrials_createdAfterlistTrials_createdBeforelistTrials_experimentNamelistTrials_maxResultslistTrials_nextTokenlistTrials_sortBylistTrials_sortOrderlistTrials_trialComponentNamenewListTrialsResponselistTrialsResponse_nextToken!listTrialsResponse_trialSummarieslistTrialsResponse_httpStatus$fToQueryListTrials$fToPathListTrials$fToJSONListTrials$fToHeadersListTrials$fNFDataListTrials$fHashableListTrials$fAWSPagerListTrials$fNFDataListTrialsResponse$fAWSRequestListTrials$fEqListTrialsResponse$fReadListTrialsResponse$fShowListTrialsResponse$fGenericListTrialsResponse$fEqListTrials$fReadListTrials$fShowListTrials$fGenericListTrialsListTrialComponentsResponseListTrialComponentsResponse'+$sel:nextToken:ListTrialComponentsResponse'9$sel:trialComponentSummaries:ListTrialComponentsResponse',$sel:httpStatus:ListTrialComponentsResponse'ListTrialComponentsListTrialComponents'&$sel:createdAfter:ListTrialComponents''$sel:createdBefore:ListTrialComponents'($sel:experimentName:ListTrialComponents'$$sel:maxResults:ListTrialComponents'#$sel:nextToken:ListTrialComponents' $sel:sortBy:ListTrialComponents'#$sel:sortOrder:ListTrialComponents'#$sel:sourceArn:ListTrialComponents'#$sel:trialName:ListTrialComponents'newListTrialComponents listTrialComponents_createdAfter!listTrialComponents_createdBefore"listTrialComponents_experimentNamelistTrialComponents_maxResultslistTrialComponents_nextTokenlistTrialComponents_sortBylistTrialComponents_sortOrderlistTrialComponents_sourceArnlistTrialComponents_trialNamenewListTrialComponentsResponse%listTrialComponentsResponse_nextToken3listTrialComponentsResponse_trialComponentSummaries&listTrialComponentsResponse_httpStatus$fToQueryListTrialComponents$fToPathListTrialComponents$fToJSONListTrialComponents$fToHeadersListTrialComponents$fNFDataListTrialComponents$fHashableListTrialComponents$fAWSPagerListTrialComponents#$fNFDataListTrialComponentsResponse$fAWSRequestListTrialComponents$fEqListTrialComponentsResponse!$fReadListTrialComponentsResponse!$fShowListTrialComponentsResponse$$fGenericListTrialComponentsResponse$fEqListTrialComponents$fReadListTrialComponents$fShowListTrialComponents$fGenericListTrialComponentsListTransformJobsResponseListTransformJobsResponse')$sel:nextToken:ListTransformJobsResponse'*$sel:httpStatus:ListTransformJobsResponse'5$sel:transformJobSummaries:ListTransformJobsResponse'ListTransformJobsListTransformJobs')$sel:creationTimeAfter:ListTransformJobs'*$sel:creationTimeBefore:ListTransformJobs'-$sel:lastModifiedTimeAfter:ListTransformJobs'.$sel:lastModifiedTimeBefore:ListTransformJobs'"$sel:maxResults:ListTransformJobs'$$sel:nameContains:ListTransformJobs'!$sel:nextToken:ListTransformJobs'$sel:sortBy:ListTransformJobs'!$sel:sortOrder:ListTransformJobs'$$sel:statusEquals:ListTransformJobs'newListTransformJobs#listTransformJobs_creationTimeAfter$listTransformJobs_creationTimeBefore'listTransformJobs_lastModifiedTimeAfter(listTransformJobs_lastModifiedTimeBeforelistTransformJobs_maxResultslistTransformJobs_nameContainslistTransformJobs_nextTokenlistTransformJobs_sortBylistTransformJobs_sortOrderlistTransformJobs_statusEqualsnewListTransformJobsResponse#listTransformJobsResponse_nextToken$listTransformJobsResponse_httpStatus/listTransformJobsResponse_transformJobSummaries$fToQueryListTransformJobs$fToPathListTransformJobs$fToJSONListTransformJobs$fToHeadersListTransformJobs$fNFDataListTransformJobs$fHashableListTransformJobs$fAWSPagerListTransformJobs!$fNFDataListTransformJobsResponse$fAWSRequestListTransformJobs$fEqListTransformJobsResponse$fReadListTransformJobsResponse$fShowListTransformJobsResponse"$fGenericListTransformJobsResponse$fEqListTransformJobs$fReadListTransformJobs$fShowListTransformJobs$fGenericListTransformJobs2ListTrainingJobsForHyperParameterTuningJobResponse3ListTrainingJobsForHyperParameterTuningJobResponse'$sel:nextToken:ListTrainingJobsForHyperParameterTuningJobResponse'$sel:httpStatus:ListTrainingJobsForHyperParameterTuningJobResponse'$sel:trainingJobSummaries:ListTrainingJobsForHyperParameterTuningJobResponse'*ListTrainingJobsForHyperParameterTuningJob+ListTrainingJobsForHyperParameterTuningJob';$sel:maxResults:ListTrainingJobsForHyperParameterTuningJob':$sel:nextToken:ListTrainingJobsForHyperParameterTuningJob'7$sel:sortBy:ListTrainingJobsForHyperParameterTuningJob':$sel:sortOrder:ListTrainingJobsForHyperParameterTuningJob'=$sel:statusEquals:ListTrainingJobsForHyperParameterTuningJob'$sel:hyperParameterTuningJobName:ListTrainingJobsForHyperParameterTuningJob'-newListTrainingJobsForHyperParameterTuningJob5listTrainingJobsForHyperParameterTuningJob_maxResults4listTrainingJobsForHyperParameterTuningJob_nextToken1listTrainingJobsForHyperParameterTuningJob_sortBy4listTrainingJobsForHyperParameterTuningJob_sortOrder7listTrainingJobsForHyperParameterTuningJob_statusEqualslistTrainingJobsForHyperParameterTuningJob_hyperParameterTuningJobName5newListTrainingJobsForHyperParameterTuningJobResponse$sel:httpStatus:ListModelExplainabilityJobDefinitionsResponse'$sel:jobDefinitionSummaries:ListModelExplainabilityJobDefinitionsResponse'%ListModelExplainabilityJobDefinitions&ListModelExplainabilityJobDefinitions'=$sel:creationTimeAfter:ListModelExplainabilityJobDefinitions'>$sel:creationTimeBefore:ListModelExplainabilityJobDefinitions'8$sel:endpointName:ListModelExplainabilityJobDefinitions'6$sel:maxResults:ListModelExplainabilityJobDefinitions'8$sel:nameContains:ListModelExplainabilityJobDefinitions'5$sel:nextToken:ListModelExplainabilityJobDefinitions'2$sel:sortBy:ListModelExplainabilityJobDefinitions'5$sel:sortOrder:ListModelExplainabilityJobDefinitions'(newListModelExplainabilityJobDefinitions7listModelExplainabilityJobDefinitions_creationTimeAfter8listModelExplainabilityJobDefinitions_creationTimeBefore2listModelExplainabilityJobDefinitions_endpointName0listModelExplainabilityJobDefinitions_maxResults2listModelExplainabilityJobDefinitions_nameContains/listModelExplainabilityJobDefinitions_nextToken,listModelExplainabilityJobDefinitions_sortBy/listModelExplainabilityJobDefinitions_sortOrder0newListModelExplainabilityJobDefinitionsResponse7listModelExplainabilityJobDefinitionsResponse_nextToken8listModelExplainabilityJobDefinitionsResponse_httpStatuslistModelExplainabilityJobDefinitionsResponse_jobDefinitionSummaries.$fToQueryListModelExplainabilityJobDefinitions-$fToPathListModelExplainabilityJobDefinitions-$fToJSONListModelExplainabilityJobDefinitions0$fToHeadersListModelExplainabilityJobDefinitions-$fNFDataListModelExplainabilityJobDefinitions/$fHashableListModelExplainabilityJobDefinitions/$fAWSPagerListModelExplainabilityJobDefinitions5$fNFDataListModelExplainabilityJobDefinitionsResponse1$fAWSRequestListModelExplainabilityJobDefinitions1$fEqListModelExplainabilityJobDefinitionsResponse3$fReadListModelExplainabilityJobDefinitionsResponse3$fShowListModelExplainabilityJobDefinitionsResponse6$fGenericListModelExplainabilityJobDefinitionsResponse)$fEqListModelExplainabilityJobDefinitions+$fReadListModelExplainabilityJobDefinitions+$fShowListModelExplainabilityJobDefinitions.$fGenericListModelExplainabilityJobDefinitionsListModelCardsResponseListModelCardsResponse'&$sel:nextToken:ListModelCardsResponse''$sel:httpStatus:ListModelCardsResponse'/$sel:modelCardSummaries:ListModelCardsResponse'ListModelCardsListModelCards'&$sel:creationTimeAfter:ListModelCards''$sel:creationTimeBefore:ListModelCards'$sel:maxResults:ListModelCards'$$sel:modelCardStatus:ListModelCards'!$sel:nameContains:ListModelCards'$sel:nextToken:ListModelCards'$sel:sortBy:ListModelCards'$sel:sortOrder:ListModelCards'newListModelCards listModelCards_creationTimeAfter!listModelCards_creationTimeBeforelistModelCards_maxResultslistModelCards_modelCardStatuslistModelCards_nameContainslistModelCards_nextTokenlistModelCards_sortBylistModelCards_sortOrdernewListModelCardsResponse listModelCardsResponse_nextToken!listModelCardsResponse_httpStatus)listModelCardsResponse_modelCardSummaries$fToQueryListModelCards$fToPathListModelCards$fToJSONListModelCards$fToHeadersListModelCards$fNFDataListModelCards$fHashableListModelCards$fAWSPagerListModelCards$fNFDataListModelCardsResponse$fAWSRequestListModelCards$fEqListModelCardsResponse$fReadListModelCardsResponse$fShowListModelCardsResponse$fGenericListModelCardsResponse$fEqListModelCards$fReadListModelCards$fShowListModelCards$fGenericListModelCardsListModelCardVersionsResponseListModelCardVersionsResponse'-$sel:nextToken:ListModelCardVersionsResponse'.$sel:httpStatus:ListModelCardVersionsResponse'?$sel:modelCardVersionSummaryList:ListModelCardVersionsResponse'ListModelCardVersionsListModelCardVersions'-$sel:creationTimeAfter:ListModelCardVersions'.$sel:creationTimeBefore:ListModelCardVersions'&$sel:maxResults:ListModelCardVersions'+$sel:modelCardStatus:ListModelCardVersions'%$sel:nextToken:ListModelCardVersions'"$sel:sortBy:ListModelCardVersions'%$sel:sortOrder:ListModelCardVersions')$sel:modelCardName:ListModelCardVersions'newListModelCardVersions'listModelCardVersions_creationTimeAfter(listModelCardVersions_creationTimeBefore listModelCardVersions_maxResults%listModelCardVersions_modelCardStatuslistModelCardVersions_nextTokenlistModelCardVersions_sortBylistModelCardVersions_sortOrder#listModelCardVersions_modelCardName newListModelCardVersionsResponse'listModelCardVersionsResponse_nextToken(listModelCardVersionsResponse_httpStatus9listModelCardVersionsResponse_modelCardVersionSummaryList$fToQueryListModelCardVersions$fToPathListModelCardVersions$fToJSONListModelCardVersions $fToHeadersListModelCardVersions$fNFDataListModelCardVersions$fHashableListModelCardVersions$fAWSPagerListModelCardVersions%$fNFDataListModelCardVersionsResponse!$fAWSRequestListModelCardVersions!$fEqListModelCardVersionsResponse#$fReadListModelCardVersionsResponse#$fShowListModelCardVersionsResponse&$fGenericListModelCardVersionsResponse$fEqListModelCardVersions$fReadListModelCardVersions$fShowListModelCardVersions$fGenericListModelCardVersionsListModelCardExportJobsResponse ListModelCardExportJobsResponse'/$sel:nextToken:ListModelCardExportJobsResponse'0$sel:httpStatus:ListModelCardExportJobsResponse'$sel:modelCardExportJobSummaries:ListModelCardExportJobsResponse'ListModelCardExportJobsListModelCardExportJobs'/$sel:creationTimeAfter:ListModelCardExportJobs'0$sel:creationTimeBefore:ListModelCardExportJobs'($sel:maxResults:ListModelCardExportJobs'<$sel:modelCardExportJobNameContains:ListModelCardExportJobs'.$sel:modelCardVersion:ListModelCardExportJobs''$sel:nextToken:ListModelCardExportJobs'$$sel:sortBy:ListModelCardExportJobs''$sel:sortOrder:ListModelCardExportJobs'*$sel:statusEquals:ListModelCardExportJobs'+$sel:modelCardName:ListModelCardExportJobs'newListModelCardExportJobs)listModelCardExportJobs_creationTimeAfter*listModelCardExportJobs_creationTimeBefore"listModelCardExportJobs_maxResults6listModelCardExportJobs_modelCardExportJobNameContains(listModelCardExportJobs_modelCardVersion!listModelCardExportJobs_nextTokenlistModelCardExportJobs_sortBy!listModelCardExportJobs_sortOrder$listModelCardExportJobs_statusEquals%listModelCardExportJobs_modelCardName"newListModelCardExportJobsResponse)listModelCardExportJobsResponse_nextToken*listModelCardExportJobsResponse_httpStatus;listModelCardExportJobsResponse_modelCardExportJobSummaries $fToQueryListModelCardExportJobs$fToPathListModelCardExportJobs$fToJSONListModelCardExportJobs"$fToHeadersListModelCardExportJobs$fNFDataListModelCardExportJobs!$fHashableListModelCardExportJobs!$fAWSPagerListModelCardExportJobs'$fNFDataListModelCardExportJobsResponse#$fAWSRequestListModelCardExportJobs#$fEqListModelCardExportJobsResponse%$fReadListModelCardExportJobsResponse%$fShowListModelCardExportJobsResponse($fGenericListModelCardExportJobsResponse$fEqListModelCardExportJobs$fReadListModelCardExportJobs$fShowListModelCardExportJobs $fGenericListModelCardExportJobs#ListModelBiasJobDefinitionsResponse$ListModelBiasJobDefinitionsResponse'3$sel:nextToken:ListModelBiasJobDefinitionsResponse'4$sel:httpStatus:ListModelBiasJobDefinitionsResponse'$sel:jobDefinitionSummaries:ListModelBiasJobDefinitionsResponse'ListModelBiasJobDefinitionsListModelBiasJobDefinitions'3$sel:creationTimeAfter:ListModelBiasJobDefinitions'4$sel:creationTimeBefore:ListModelBiasJobDefinitions'.$sel:endpointName:ListModelBiasJobDefinitions',$sel:maxResults:ListModelBiasJobDefinitions'.$sel:nameContains:ListModelBiasJobDefinitions'+$sel:nextToken:ListModelBiasJobDefinitions'($sel:sortBy:ListModelBiasJobDefinitions'+$sel:sortOrder:ListModelBiasJobDefinitions'newListModelBiasJobDefinitions-listModelBiasJobDefinitions_creationTimeAfter.listModelBiasJobDefinitions_creationTimeBefore(listModelBiasJobDefinitions_endpointName&listModelBiasJobDefinitions_maxResults(listModelBiasJobDefinitions_nameContains%listModelBiasJobDefinitions_nextToken"listModelBiasJobDefinitions_sortBy%listModelBiasJobDefinitions_sortOrder&newListModelBiasJobDefinitionsResponse-listModelBiasJobDefinitionsResponse_nextToken.listModelBiasJobDefinitionsResponse_httpStatus:listModelBiasJobDefinitionsResponse_jobDefinitionSummaries$$fToQueryListModelBiasJobDefinitions#$fToPathListModelBiasJobDefinitions#$fToJSONListModelBiasJobDefinitions&$fToHeadersListModelBiasJobDefinitions#$fNFDataListModelBiasJobDefinitions%$fHashableListModelBiasJobDefinitions%$fAWSPagerListModelBiasJobDefinitions+$fNFDataListModelBiasJobDefinitionsResponse'$fAWSRequestListModelBiasJobDefinitions'$fEqListModelBiasJobDefinitionsResponse)$fReadListModelBiasJobDefinitionsResponse)$fShowListModelBiasJobDefinitionsResponse,$fGenericListModelBiasJobDefinitionsResponse$fEqListModelBiasJobDefinitions!$fReadListModelBiasJobDefinitions!$fShowListModelBiasJobDefinitions$$fGenericListModelBiasJobDefinitionsListLineageGroupsResponseListLineageGroupsResponse'5$sel:lineageGroupSummaries:ListLineageGroupsResponse')$sel:nextToken:ListLineageGroupsResponse'*$sel:httpStatus:ListLineageGroupsResponse'ListLineageGroupsListLineageGroups'$$sel:createdAfter:ListLineageGroups'%$sel:createdBefore:ListLineageGroups'"$sel:maxResults:ListLineageGroups'!$sel:nextToken:ListLineageGroups'$sel:sortBy:ListLineageGroups'!$sel:sortOrder:ListLineageGroups'newListLineageGroupslistLineageGroups_createdAfterlistLineageGroups_createdBeforelistLineageGroups_maxResultslistLineageGroups_nextTokenlistLineageGroups_sortBylistLineageGroups_sortOrdernewListLineageGroupsResponse/listLineageGroupsResponse_lineageGroupSummaries#listLineageGroupsResponse_nextToken$listLineageGroupsResponse_httpStatus$fToQueryListLineageGroups$fToPathListLineageGroups$fToJSONListLineageGroups$fToHeadersListLineageGroups$fNFDataListLineageGroups$fHashableListLineageGroups$fAWSPagerListLineageGroups!$fNFDataListLineageGroupsResponse$fAWSRequestListLineageGroups$fEqListLineageGroupsResponse$fReadListLineageGroupsResponse$fShowListLineageGroupsResponse"$fGenericListLineageGroupsResponse$fEqListLineageGroups$fReadListLineageGroups$fShowListLineageGroups$fGenericListLineageGroups#ListLabelingJobsForWorkteamResponse$ListLabelingJobsForWorkteamResponse'3$sel:nextToken:ListLabelingJobsForWorkteamResponse'4$sel:httpStatus:ListLabelingJobsForWorkteamResponse'$sel:labelingJobSummaryList:ListLabelingJobsForWorkteamResponse'ListLabelingJobsForWorkteamListLabelingJobsForWorkteam'3$sel:creationTimeAfter:ListLabelingJobsForWorkteam'4$sel:creationTimeBefore:ListLabelingJobsForWorkteam':$sel:jobReferenceCodeContains:ListLabelingJobsForWorkteam',$sel:maxResults:ListLabelingJobsForWorkteam'+$sel:nextToken:ListLabelingJobsForWorkteam'($sel:sortBy:ListLabelingJobsForWorkteam'+$sel:sortOrder:ListLabelingJobsForWorkteam'-$sel:workteamArn:ListLabelingJobsForWorkteam'newListLabelingJobsForWorkteam-listLabelingJobsForWorkteam_creationTimeAfter.listLabelingJobsForWorkteam_creationTimeBefore4listLabelingJobsForWorkteam_jobReferenceCodeContains&listLabelingJobsForWorkteam_maxResults%listLabelingJobsForWorkteam_nextToken"listLabelingJobsForWorkteam_sortBy%listLabelingJobsForWorkteam_sortOrder'listLabelingJobsForWorkteam_workteamArn&newListLabelingJobsForWorkteamResponse-listLabelingJobsForWorkteamResponse_nextToken.listLabelingJobsForWorkteamResponse_httpStatus:listLabelingJobsForWorkteamResponse_labelingJobSummaryList$$fToQueryListLabelingJobsForWorkteam#$fToPathListLabelingJobsForWorkteam#$fToJSONListLabelingJobsForWorkteam&$fToHeadersListLabelingJobsForWorkteam#$fNFDataListLabelingJobsForWorkteam%$fHashableListLabelingJobsForWorkteam%$fAWSPagerListLabelingJobsForWorkteam+$fNFDataListLabelingJobsForWorkteamResponse'$fAWSRequestListLabelingJobsForWorkteam'$fEqListLabelingJobsForWorkteamResponse)$fReadListLabelingJobsForWorkteamResponse)$fShowListLabelingJobsForWorkteamResponse,$fGenericListLabelingJobsForWorkteamResponse$fEqListLabelingJobsForWorkteam!$fReadListLabelingJobsForWorkteam!$fShowListLabelingJobsForWorkteam$$fGenericListLabelingJobsForWorkteamListLabelingJobsResponseListLabelingJobsResponse'5$sel:labelingJobSummaryList:ListLabelingJobsResponse'($sel:nextToken:ListLabelingJobsResponse')$sel:httpStatus:ListLabelingJobsResponse'ListLabelingJobsListLabelingJobs'($sel:creationTimeAfter:ListLabelingJobs')$sel:creationTimeBefore:ListLabelingJobs',$sel:lastModifiedTimeAfter:ListLabelingJobs'-$sel:lastModifiedTimeBefore:ListLabelingJobs'!$sel:maxResults:ListLabelingJobs'#$sel:nameContains:ListLabelingJobs' $sel:nextToken:ListLabelingJobs'$sel:sortBy:ListLabelingJobs' $sel:sortOrder:ListLabelingJobs'#$sel:statusEquals:ListLabelingJobs'newListLabelingJobs"listLabelingJobs_creationTimeAfter#listLabelingJobs_creationTimeBefore&listLabelingJobs_lastModifiedTimeAfter'listLabelingJobs_lastModifiedTimeBeforelistLabelingJobs_maxResultslistLabelingJobs_nameContainslistLabelingJobs_nextTokenlistLabelingJobs_sortBylistLabelingJobs_sortOrderlistLabelingJobs_statusEqualsnewListLabelingJobsResponse/listLabelingJobsResponse_labelingJobSummaryList"listLabelingJobsResponse_nextToken#listLabelingJobsResponse_httpStatus$fToQueryListLabelingJobs$fToPathListLabelingJobs$fToJSONListLabelingJobs$fToHeadersListLabelingJobs$fNFDataListLabelingJobs$fHashableListLabelingJobs$fAWSPagerListLabelingJobs $fNFDataListLabelingJobsResponse$fAWSRequestListLabelingJobs$fEqListLabelingJobsResponse$fReadListLabelingJobsResponse$fShowListLabelingJobsResponse!$fGenericListLabelingJobsResponse$fEqListLabelingJobs$fReadListLabelingJobs$fShowListLabelingJobs$fGenericListLabelingJobs(ListInferenceRecommendationsJobsResponse)ListInferenceRecommendationsJobsResponse'8$sel:nextToken:ListInferenceRecommendationsJobsResponse'9$sel:httpStatus:ListInferenceRecommendationsJobsResponse'$sel:inferenceRecommendationsJobs:ListInferenceRecommendationsJobsResponse' ListInferenceRecommendationsJobs!ListInferenceRecommendationsJobs'8$sel:creationTimeAfter:ListInferenceRecommendationsJobs'9$sel:creationTimeBefore:ListInferenceRecommendationsJobs'<$sel:lastModifiedTimeAfter:ListInferenceRecommendationsJobs'=$sel:lastModifiedTimeBefore:ListInferenceRecommendationsJobs'1$sel:maxResults:ListInferenceRecommendationsJobs'3$sel:nameContains:ListInferenceRecommendationsJobs'0$sel:nextToken:ListInferenceRecommendationsJobs'-$sel:sortBy:ListInferenceRecommendationsJobs'0$sel:sortOrder:ListInferenceRecommendationsJobs'3$sel:statusEquals:ListInferenceRecommendationsJobs'#newListInferenceRecommendationsJobs2listInferenceRecommendationsJobs_creationTimeAfter3listInferenceRecommendationsJobs_creationTimeBefore6listInferenceRecommendationsJobs_lastModifiedTimeAfter7listInferenceRecommendationsJobs_lastModifiedTimeBefore+listInferenceRecommendationsJobs_maxResults-listInferenceRecommendationsJobs_nameContains*listInferenceRecommendationsJobs_nextToken'listInferenceRecommendationsJobs_sortBy*listInferenceRecommendationsJobs_sortOrder-listInferenceRecommendationsJobs_statusEquals+newListInferenceRecommendationsJobsResponse2listInferenceRecommendationsJobsResponse_nextToken3listInferenceRecommendationsJobsResponse_httpStatuslistInferenceRecommendationsJobsResponse_inferenceRecommendationsJobs)$fToQueryListInferenceRecommendationsJobs($fToPathListInferenceRecommendationsJobs($fToJSONListInferenceRecommendationsJobs+$fToHeadersListInferenceRecommendationsJobs($fNFDataListInferenceRecommendationsJobs*$fHashableListInferenceRecommendationsJobs*$fAWSPagerListInferenceRecommendationsJobs0$fNFDataListInferenceRecommendationsJobsResponse,$fAWSRequestListInferenceRecommendationsJobs,$fEqListInferenceRecommendationsJobsResponse.$fReadListInferenceRecommendationsJobsResponse.$fShowListInferenceRecommendationsJobsResponse1$fGenericListInferenceRecommendationsJobsResponse$$fEqListInferenceRecommendationsJobs&$fReadListInferenceRecommendationsJobs&$fShowListInferenceRecommendationsJobs)$fGenericListInferenceRecommendationsJobs,ListInferenceRecommendationsJobStepsResponse-ListInferenceRecommendationsJobStepsResponse'<$sel:nextToken:ListInferenceRecommendationsJobStepsResponse'8$sel:steps:ListInferenceRecommendationsJobStepsResponse'=$sel:httpStatus:ListInferenceRecommendationsJobStepsResponse'$ListInferenceRecommendationsJobSteps%ListInferenceRecommendationsJobSteps'5$sel:maxResults:ListInferenceRecommendationsJobSteps'4$sel:nextToken:ListInferenceRecommendationsJobSteps'1$sel:status:ListInferenceRecommendationsJobSteps'3$sel:stepType:ListInferenceRecommendationsJobSteps'2$sel:jobName:ListInferenceRecommendationsJobSteps''newListInferenceRecommendationsJobSteps/listInferenceRecommendationsJobSteps_maxResults.listInferenceRecommendationsJobSteps_nextToken+listInferenceRecommendationsJobSteps_status-listInferenceRecommendationsJobSteps_stepType,listInferenceRecommendationsJobSteps_jobName/newListInferenceRecommendationsJobStepsResponse6listInferenceRecommendationsJobStepsResponse_nextToken2listInferenceRecommendationsJobStepsResponse_steps7listInferenceRecommendationsJobStepsResponse_httpStatus-$fToQueryListInferenceRecommendationsJobSteps,$fToPathListInferenceRecommendationsJobSteps,$fToJSONListInferenceRecommendationsJobSteps/$fToHeadersListInferenceRecommendationsJobSteps,$fNFDataListInferenceRecommendationsJobSteps.$fHashableListInferenceRecommendationsJobSteps.$fAWSPagerListInferenceRecommendationsJobSteps4$fNFDataListInferenceRecommendationsJobStepsResponse0$fAWSRequestListInferenceRecommendationsJobSteps0$fEqListInferenceRecommendationsJobStepsResponse2$fReadListInferenceRecommendationsJobStepsResponse2$fShowListInferenceRecommendationsJobStepsResponse5$fGenericListInferenceRecommendationsJobStepsResponse($fEqListInferenceRecommendationsJobSteps*$fReadListInferenceRecommendationsJobSteps*$fShowListInferenceRecommendationsJobSteps-$fGenericListInferenceRecommendationsJobSteps ListInferenceExperimentsResponse!ListInferenceExperimentsResponse';$sel:inferenceExperiments:ListInferenceExperimentsResponse'0$sel:nextToken:ListInferenceExperimentsResponse'1$sel:httpStatus:ListInferenceExperimentsResponse'ListInferenceExperimentsListInferenceExperiments'0$sel:creationTimeAfter:ListInferenceExperiments'1$sel:creationTimeBefore:ListInferenceExperiments'4$sel:lastModifiedTimeAfter:ListInferenceExperiments'5$sel:lastModifiedTimeBefore:ListInferenceExperiments')$sel:maxResults:ListInferenceExperiments'+$sel:nameContains:ListInferenceExperiments'($sel:nextToken:ListInferenceExperiments'%$sel:sortBy:ListInferenceExperiments'($sel:sortOrder:ListInferenceExperiments'+$sel:statusEquals:ListInferenceExperiments'$$sel:type':ListInferenceExperiments'newListInferenceExperiments*listInferenceExperiments_creationTimeAfter+listInferenceExperiments_creationTimeBefore.listInferenceExperiments_lastModifiedTimeAfter/listInferenceExperiments_lastModifiedTimeBefore#listInferenceExperiments_maxResults%listInferenceExperiments_nameContains"listInferenceExperiments_nextTokenlistInferenceExperiments_sortBy"listInferenceExperiments_sortOrder%listInferenceExperiments_statusEqualslistInferenceExperiments_type#newListInferenceExperimentsResponse5listInferenceExperimentsResponse_inferenceExperiments*listInferenceExperimentsResponse_nextToken+listInferenceExperimentsResponse_httpStatus!$fToQueryListInferenceExperiments $fToPathListInferenceExperiments $fToJSONListInferenceExperiments#$fToHeadersListInferenceExperiments $fNFDataListInferenceExperiments"$fHashableListInferenceExperiments"$fAWSPagerListInferenceExperiments($fNFDataListInferenceExperimentsResponse$$fAWSRequestListInferenceExperiments$$fEqListInferenceExperimentsResponse&$fReadListInferenceExperimentsResponse&$fShowListInferenceExperimentsResponse)$fGenericListInferenceExperimentsResponse$fEqListInferenceExperiments$fReadListInferenceExperiments$fShowListInferenceExperiments!$fGenericListInferenceExperimentsListImagesResponseListImagesResponse'$sel:images:ListImagesResponse'"$sel:nextToken:ListImagesResponse'#$sel:httpStatus:ListImagesResponse' ListImages ListImages'"$sel:creationTimeAfter:ListImages'#$sel:creationTimeBefore:ListImages'&$sel:lastModifiedTimeAfter:ListImages''$sel:lastModifiedTimeBefore:ListImages'$sel:maxResults:ListImages'$sel:nameContains:ListImages'$sel:nextToken:ListImages'$sel:sortBy:ListImages'$sel:sortOrder:ListImages' newListImageslistImages_creationTimeAfterlistImages_creationTimeBefore listImages_lastModifiedTimeAfter!listImages_lastModifiedTimeBeforelistImages_maxResultslistImages_nameContainslistImages_nextTokenlistImages_sortBylistImages_sortOrdernewListImagesResponselistImagesResponse_imageslistImagesResponse_nextTokenlistImagesResponse_httpStatus$fToQueryListImages$fToPathListImages$fToJSONListImages$fToHeadersListImages$fNFDataListImages$fHashableListImages$fAWSPagerListImages$fNFDataListImagesResponse$fAWSRequestListImages$fEqListImagesResponse$fReadListImagesResponse$fShowListImagesResponse$fGenericListImagesResponse$fEqListImages$fReadListImages$fShowListImages$fGenericListImagesListImageVersionsResponseListImageVersionsResponse'-$sel:imageVersions:ListImageVersionsResponse')$sel:nextToken:ListImageVersionsResponse'*$sel:httpStatus:ListImageVersionsResponse'ListImageVersionsListImageVersions')$sel:creationTimeAfter:ListImageVersions'*$sel:creationTimeBefore:ListImageVersions'-$sel:lastModifiedTimeAfter:ListImageVersions'.$sel:lastModifiedTimeBefore:ListImageVersions'"$sel:maxResults:ListImageVersions'!$sel:nextToken:ListImageVersions'$sel:sortBy:ListImageVersions'!$sel:sortOrder:ListImageVersions'!$sel:imageName:ListImageVersions'newListImageVersions#listImageVersions_creationTimeAfter$listImageVersions_creationTimeBefore'listImageVersions_lastModifiedTimeAfter(listImageVersions_lastModifiedTimeBeforelistImageVersions_maxResultslistImageVersions_nextTokenlistImageVersions_sortBylistImageVersions_sortOrderlistImageVersions_imageNamenewListImageVersionsResponse'listImageVersionsResponse_imageVersions#listImageVersionsResponse_nextToken$listImageVersionsResponse_httpStatus$fToQueryListImageVersions$fToPathListImageVersions$fToJSONListImageVersions$fToHeadersListImageVersions$fNFDataListImageVersions$fHashableListImageVersions$fAWSPagerListImageVersions!$fNFDataListImageVersionsResponse$fAWSRequestListImageVersions$fEqListImageVersionsResponse$fReadListImageVersionsResponse$fShowListImageVersionsResponse"$fGenericListImageVersionsResponse$fEqListImageVersions$fReadListImageVersions$fShowListImageVersions$fGenericListImageVersions$ListHyperParameterTuningJobsResponse%ListHyperParameterTuningJobsResponse'4$sel:nextToken:ListHyperParameterTuningJobsResponse'5$sel:httpStatus:ListHyperParameterTuningJobsResponse'$sel:hyperParameterTuningJobSummaries:ListHyperParameterTuningJobsResponse'ListHyperParameterTuningJobsListHyperParameterTuningJobs'4$sel:creationTimeAfter:ListHyperParameterTuningJobs'5$sel:creationTimeBefore:ListHyperParameterTuningJobs'8$sel:lastModifiedTimeAfter:ListHyperParameterTuningJobs'9$sel:lastModifiedTimeBefore:ListHyperParameterTuningJobs'-$sel:maxResults:ListHyperParameterTuningJobs'/$sel:nameContains:ListHyperParameterTuningJobs',$sel:nextToken:ListHyperParameterTuningJobs')$sel:sortBy:ListHyperParameterTuningJobs',$sel:sortOrder:ListHyperParameterTuningJobs'/$sel:statusEquals:ListHyperParameterTuningJobs'newListHyperParameterTuningJobs.listHyperParameterTuningJobs_creationTimeAfter/listHyperParameterTuningJobs_creationTimeBefore2listHyperParameterTuningJobs_lastModifiedTimeAfter3listHyperParameterTuningJobs_lastModifiedTimeBefore'listHyperParameterTuningJobs_maxResults)listHyperParameterTuningJobs_nameContains&listHyperParameterTuningJobs_nextToken#listHyperParameterTuningJobs_sortBy&listHyperParameterTuningJobs_sortOrder)listHyperParameterTuningJobs_statusEquals'newListHyperParameterTuningJobsResponse.listHyperParameterTuningJobsResponse_nextToken/listHyperParameterTuningJobsResponse_httpStatuslistHyperParameterTuningJobsResponse_hyperParameterTuningJobSummaries%$fToQueryListHyperParameterTuningJobs$$fToPathListHyperParameterTuningJobs$$fToJSONListHyperParameterTuningJobs'$fToHeadersListHyperParameterTuningJobs$$fNFDataListHyperParameterTuningJobs&$fHashableListHyperParameterTuningJobs&$fAWSPagerListHyperParameterTuningJobs,$fNFDataListHyperParameterTuningJobsResponse($fAWSRequestListHyperParameterTuningJobs($fEqListHyperParameterTuningJobsResponse*$fReadListHyperParameterTuningJobsResponse*$fShowListHyperParameterTuningJobsResponse-$fGenericListHyperParameterTuningJobsResponse $fEqListHyperParameterTuningJobs"$fReadListHyperParameterTuningJobs"$fShowListHyperParameterTuningJobs%$fGenericListHyperParameterTuningJobsListHumanTaskUisResponseListHumanTaskUisResponse'($sel:nextToken:ListHumanTaskUisResponse')$sel:httpStatus:ListHumanTaskUisResponse'3$sel:humanTaskUiSummaries:ListHumanTaskUisResponse'ListHumanTaskUisListHumanTaskUis'($sel:creationTimeAfter:ListHumanTaskUis')$sel:creationTimeBefore:ListHumanTaskUis'!$sel:maxResults:ListHumanTaskUis' $sel:nextToken:ListHumanTaskUis' $sel:sortOrder:ListHumanTaskUis'newListHumanTaskUis"listHumanTaskUis_creationTimeAfter#listHumanTaskUis_creationTimeBeforelistHumanTaskUis_maxResultslistHumanTaskUis_nextTokenlistHumanTaskUis_sortOrdernewListHumanTaskUisResponse"listHumanTaskUisResponse_nextToken#listHumanTaskUisResponse_httpStatus-listHumanTaskUisResponse_humanTaskUiSummaries$fToQueryListHumanTaskUis$fToPathListHumanTaskUis$fToJSONListHumanTaskUis$fToHeadersListHumanTaskUis$fNFDataListHumanTaskUis$fHashableListHumanTaskUis$fAWSPagerListHumanTaskUis $fNFDataListHumanTaskUisResponse$fAWSRequestListHumanTaskUis$fEqListHumanTaskUisResponse$fReadListHumanTaskUisResponse$fShowListHumanTaskUisResponse!$fGenericListHumanTaskUisResponse$fEqListHumanTaskUis$fReadListHumanTaskUis$fShowListHumanTaskUis$fGenericListHumanTaskUisListHubsResponseListHubsResponse' $sel:nextToken:ListHubsResponse'!$sel:httpStatus:ListHubsResponse'#$sel:hubSummaries:ListHubsResponse'ListHubs ListHubs' $sel:creationTimeAfter:ListHubs'!$sel:creationTimeBefore:ListHubs'$$sel:lastModifiedTimeAfter:ListHubs'%$sel:lastModifiedTimeBefore:ListHubs'$sel:maxResults:ListHubs'$sel:nameContains:ListHubs'$sel:nextToken:ListHubs'$sel:sortBy:ListHubs'$sel:sortOrder:ListHubs' newListHubslistHubs_creationTimeAfterlistHubs_creationTimeBeforelistHubs_lastModifiedTimeAfterlistHubs_lastModifiedTimeBeforelistHubs_maxResultslistHubs_nameContainslistHubs_nextTokenlistHubs_sortBylistHubs_sortOrdernewListHubsResponselistHubsResponse_nextTokenlistHubsResponse_httpStatuslistHubsResponse_hubSummaries$fToQueryListHubs$fToPathListHubs$fToJSONListHubs$fToHeadersListHubs$fNFDataListHubs$fHashableListHubs$fNFDataListHubsResponse$fAWSRequestListHubs$fEqListHubsResponse$fReadListHubsResponse$fShowListHubsResponse$fGenericListHubsResponse $fEqListHubs$fReadListHubs$fShowListHubs$fGenericListHubsListHubContentsResponseListHubContentsResponse''$sel:nextToken:ListHubContentsResponse'($sel:httpStatus:ListHubContentsResponse'1$sel:hubContentSummaries:ListHubContentsResponse'ListHubContentsListHubContents''$sel:creationTimeAfter:ListHubContents'($sel:creationTimeBefore:ListHubContents' $sel:maxResults:ListHubContents'&$sel:maxSchemaVersion:ListHubContents'"$sel:nameContains:ListHubContents'$sel:nextToken:ListHubContents'$sel:sortBy:ListHubContents'$sel:sortOrder:ListHubContents'$sel:hubName:ListHubContents'$$sel:hubContentType:ListHubContents'newListHubContents!listHubContents_creationTimeAfter"listHubContents_creationTimeBeforelistHubContents_maxResults listHubContents_maxSchemaVersionlistHubContents_nameContainslistHubContents_nextTokenlistHubContents_sortBylistHubContents_sortOrderlistHubContents_hubNamelistHubContents_hubContentTypenewListHubContentsResponse!listHubContentsResponse_nextToken"listHubContentsResponse_httpStatus+listHubContentsResponse_hubContentSummaries$fToQueryListHubContents$fToPathListHubContents$fToJSONListHubContents$fToHeadersListHubContents$fNFDataListHubContents$fHashableListHubContents$fNFDataListHubContentsResponse$fAWSRequestListHubContents$fEqListHubContentsResponse$fReadListHubContentsResponse$fShowListHubContentsResponse $fGenericListHubContentsResponse$fEqListHubContents$fReadListHubContents$fShowListHubContents$fGenericListHubContentsListHubContentVersionsResponseListHubContentVersionsResponse'.$sel:nextToken:ListHubContentVersionsResponse'/$sel:httpStatus:ListHubContentVersionsResponse'8$sel:hubContentSummaries:ListHubContentVersionsResponse'ListHubContentVersionsListHubContentVersions'.$sel:creationTimeAfter:ListHubContentVersions'/$sel:creationTimeBefore:ListHubContentVersions''$sel:maxResults:ListHubContentVersions'-$sel:maxSchemaVersion:ListHubContentVersions''$sel:minVersion:ListHubContentVersions'&$sel:nextToken:ListHubContentVersions'#$sel:sortBy:ListHubContentVersions'&$sel:sortOrder:ListHubContentVersions'$$sel:hubName:ListHubContentVersions'+$sel:hubContentType:ListHubContentVersions'+$sel:hubContentName:ListHubContentVersions'newListHubContentVersions(listHubContentVersions_creationTimeAfter)listHubContentVersions_creationTimeBefore!listHubContentVersions_maxResults'listHubContentVersions_maxSchemaVersion!listHubContentVersions_minVersion listHubContentVersions_nextTokenlistHubContentVersions_sortBy listHubContentVersions_sortOrderlistHubContentVersions_hubName%listHubContentVersions_hubContentType%listHubContentVersions_hubContentName!newListHubContentVersionsResponse(listHubContentVersionsResponse_nextToken)listHubContentVersionsResponse_httpStatus2listHubContentVersionsResponse_hubContentSummaries$fToQueryListHubContentVersions$fToPathListHubContentVersions$fToJSONListHubContentVersions!$fToHeadersListHubContentVersions$fNFDataListHubContentVersions $fHashableListHubContentVersions&$fNFDataListHubContentVersionsResponse"$fAWSRequestListHubContentVersions"$fEqListHubContentVersionsResponse$$fReadListHubContentVersionsResponse$$fShowListHubContentVersionsResponse'$fGenericListHubContentVersionsResponse$fEqListHubContentVersions$fReadListHubContentVersions$fShowListHubContentVersions$fGenericListHubContentVersionsListFlowDefinitionsResponseListFlowDefinitionsResponse'+$sel:nextToken:ListFlowDefinitionsResponse',$sel:httpStatus:ListFlowDefinitionsResponse'9$sel:flowDefinitionSummaries:ListFlowDefinitionsResponse'ListFlowDefinitionsListFlowDefinitions'+$sel:creationTimeAfter:ListFlowDefinitions',$sel:creationTimeBefore:ListFlowDefinitions'$$sel:maxResults:ListFlowDefinitions'#$sel:nextToken:ListFlowDefinitions'#$sel:sortOrder:ListFlowDefinitions'newListFlowDefinitions%listFlowDefinitions_creationTimeAfter&listFlowDefinitions_creationTimeBeforelistFlowDefinitions_maxResultslistFlowDefinitions_nextTokenlistFlowDefinitions_sortOrdernewListFlowDefinitionsResponse%listFlowDefinitionsResponse_nextToken&listFlowDefinitionsResponse_httpStatus3listFlowDefinitionsResponse_flowDefinitionSummaries$fToQueryListFlowDefinitions$fToPathListFlowDefinitions$fToJSONListFlowDefinitions$fToHeadersListFlowDefinitions$fNFDataListFlowDefinitions$fHashableListFlowDefinitions$fAWSPagerListFlowDefinitions#$fNFDataListFlowDefinitionsResponse$fAWSRequestListFlowDefinitions$fEqListFlowDefinitionsResponse!$fReadListFlowDefinitionsResponse!$fShowListFlowDefinitionsResponse$$fGenericListFlowDefinitionsResponse$fEqListFlowDefinitions$fReadListFlowDefinitions$fShowListFlowDefinitions$fGenericListFlowDefinitionsListFeatureGroupsResponseListFeatureGroupsResponse')$sel:nextToken:ListFeatureGroupsResponse'*$sel:httpStatus:ListFeatureGroupsResponse'5$sel:featureGroupSummaries:ListFeatureGroupsResponse'ListFeatureGroupsListFeatureGroups')$sel:creationTimeAfter:ListFeatureGroups'*$sel:creationTimeBefore:ListFeatureGroups'0$sel:featureGroupStatusEquals:ListFeatureGroups'"$sel:maxResults:ListFeatureGroups'$$sel:nameContains:ListFeatureGroups'!$sel:nextToken:ListFeatureGroups'0$sel:offlineStoreStatusEquals:ListFeatureGroups'$sel:sortBy:ListFeatureGroups'!$sel:sortOrder:ListFeatureGroups'newListFeatureGroups#listFeatureGroups_creationTimeAfter$listFeatureGroups_creationTimeBefore*listFeatureGroups_featureGroupStatusEqualslistFeatureGroups_maxResultslistFeatureGroups_nameContainslistFeatureGroups_nextToken*listFeatureGroups_offlineStoreStatusEqualslistFeatureGroups_sortBylistFeatureGroups_sortOrdernewListFeatureGroupsResponse#listFeatureGroupsResponse_nextToken$listFeatureGroupsResponse_httpStatus/listFeatureGroupsResponse_featureGroupSummaries$fToQueryListFeatureGroups$fToPathListFeatureGroups$fToJSONListFeatureGroups$fToHeadersListFeatureGroups$fNFDataListFeatureGroups$fHashableListFeatureGroups$fAWSPagerListFeatureGroups!$fNFDataListFeatureGroupsResponse$fAWSRequestListFeatureGroups$fEqListFeatureGroupsResponse$fReadListFeatureGroupsResponse$fShowListFeatureGroupsResponse"$fGenericListFeatureGroupsResponse$fEqListFeatureGroups$fReadListFeatureGroups$fShowListFeatureGroups$fGenericListFeatureGroupsListExperimentsResponseListExperimentsResponse'1$sel:experimentSummaries:ListExperimentsResponse''$sel:nextToken:ListExperimentsResponse'($sel:httpStatus:ListExperimentsResponse'ListExperimentsListExperiments'"$sel:createdAfter:ListExperiments'#$sel:createdBefore:ListExperiments' $sel:maxResults:ListExperiments'$sel:nextToken:ListExperiments'$sel:sortBy:ListExperiments'$sel:sortOrder:ListExperiments'newListExperimentslistExperiments_createdAfterlistExperiments_createdBeforelistExperiments_maxResultslistExperiments_nextTokenlistExperiments_sortBylistExperiments_sortOrdernewListExperimentsResponse+listExperimentsResponse_experimentSummaries!listExperimentsResponse_nextToken"listExperimentsResponse_httpStatus$fToQueryListExperiments$fToPathListExperiments$fToJSONListExperiments$fToHeadersListExperiments$fNFDataListExperiments$fHashableListExperiments$fAWSPagerListExperiments$fNFDataListExperimentsResponse$fAWSRequestListExperiments$fEqListExperimentsResponse$fReadListExperimentsResponse$fShowListExperimentsResponse $fGenericListExperimentsResponse$fEqListExperiments$fReadListExperiments$fShowListExperiments$fGenericListExperimentsListEndpointsResponseListEndpointsResponse'%$sel:nextToken:ListEndpointsResponse'&$sel:httpStatus:ListEndpointsResponse'%$sel:endpoints:ListEndpointsResponse' ListEndpointsListEndpoints'%$sel:creationTimeAfter:ListEndpoints'&$sel:creationTimeBefore:ListEndpoints')$sel:lastModifiedTimeAfter:ListEndpoints'*$sel:lastModifiedTimeBefore:ListEndpoints'$sel:maxResults:ListEndpoints' $sel:nameContains:ListEndpoints'$sel:nextToken:ListEndpoints'$sel:sortBy:ListEndpoints'$sel:sortOrder:ListEndpoints' $sel:statusEquals:ListEndpoints'newListEndpointslistEndpoints_creationTimeAfter listEndpoints_creationTimeBefore#listEndpoints_lastModifiedTimeAfter$listEndpoints_lastModifiedTimeBeforelistEndpoints_maxResultslistEndpoints_nameContainslistEndpoints_nextTokenlistEndpoints_sortBylistEndpoints_sortOrderlistEndpoints_statusEqualsnewListEndpointsResponselistEndpointsResponse_nextToken listEndpointsResponse_httpStatuslistEndpointsResponse_endpoints$fToQueryListEndpoints$fToPathListEndpoints$fToJSONListEndpoints$fToHeadersListEndpoints$fNFDataListEndpoints$fHashableListEndpoints$fAWSPagerListEndpoints$fNFDataListEndpointsResponse$fAWSRequestListEndpoints$fEqListEndpointsResponse$fReadListEndpointsResponse$fShowListEndpointsResponse$fGenericListEndpointsResponse$fEqListEndpoints$fReadListEndpoints$fShowListEndpoints$fGenericListEndpointsListEndpointConfigsResponseListEndpointConfigsResponse'+$sel:nextToken:ListEndpointConfigsResponse',$sel:httpStatus:ListEndpointConfigsResponse'1$sel:endpointConfigs:ListEndpointConfigsResponse'ListEndpointConfigsListEndpointConfigs'+$sel:creationTimeAfter:ListEndpointConfigs',$sel:creationTimeBefore:ListEndpointConfigs'$$sel:maxResults:ListEndpointConfigs'&$sel:nameContains:ListEndpointConfigs'#$sel:nextToken:ListEndpointConfigs' $sel:sortBy:ListEndpointConfigs'#$sel:sortOrder:ListEndpointConfigs'newListEndpointConfigs%listEndpointConfigs_creationTimeAfter&listEndpointConfigs_creationTimeBeforelistEndpointConfigs_maxResults listEndpointConfigs_nameContainslistEndpointConfigs_nextTokenlistEndpointConfigs_sortBylistEndpointConfigs_sortOrdernewListEndpointConfigsResponse%listEndpointConfigsResponse_nextToken&listEndpointConfigsResponse_httpStatus+listEndpointConfigsResponse_endpointConfigs$fToQueryListEndpointConfigs$fToPathListEndpointConfigs$fToJSONListEndpointConfigs$fToHeadersListEndpointConfigs$fNFDataListEndpointConfigs$fHashableListEndpointConfigs$fAWSPagerListEndpointConfigs#$fNFDataListEndpointConfigsResponse$fAWSRequestListEndpointConfigs$fEqListEndpointConfigsResponse!$fReadListEndpointConfigsResponse!$fShowListEndpointConfigsResponse$$fGenericListEndpointConfigsResponse$fEqListEndpointConfigs$fReadListEndpointConfigs$fShowListEndpointConfigs$fGenericListEndpointConfigsListEdgePackagingJobsResponseListEdgePackagingJobsResponse'-$sel:nextToken:ListEdgePackagingJobsResponse'.$sel:httpStatus:ListEdgePackagingJobsResponse'=$sel:edgePackagingJobSummaries:ListEdgePackagingJobsResponse'ListEdgePackagingJobsListEdgePackagingJobs'-$sel:creationTimeAfter:ListEdgePackagingJobs'.$sel:creationTimeBefore:ListEdgePackagingJobs'1$sel:lastModifiedTimeAfter:ListEdgePackagingJobs'2$sel:lastModifiedTimeBefore:ListEdgePackagingJobs'&$sel:maxResults:ListEdgePackagingJobs'-$sel:modelNameContains:ListEdgePackagingJobs'($sel:nameContains:ListEdgePackagingJobs'%$sel:nextToken:ListEdgePackagingJobs'"$sel:sortBy:ListEdgePackagingJobs'%$sel:sortOrder:ListEdgePackagingJobs'($sel:statusEquals:ListEdgePackagingJobs'newListEdgePackagingJobs'listEdgePackagingJobs_creationTimeAfter(listEdgePackagingJobs_creationTimeBefore+listEdgePackagingJobs_lastModifiedTimeAfter,listEdgePackagingJobs_lastModifiedTimeBefore listEdgePackagingJobs_maxResults'listEdgePackagingJobs_modelNameContains"listEdgePackagingJobs_nameContainslistEdgePackagingJobs_nextTokenlistEdgePackagingJobs_sortBylistEdgePackagingJobs_sortOrder"listEdgePackagingJobs_statusEquals newListEdgePackagingJobsResponse'listEdgePackagingJobsResponse_nextToken(listEdgePackagingJobsResponse_httpStatus7listEdgePackagingJobsResponse_edgePackagingJobSummaries$fToQueryListEdgePackagingJobs$fToPathListEdgePackagingJobs$fToJSONListEdgePackagingJobs $fToHeadersListEdgePackagingJobs$fNFDataListEdgePackagingJobs$fHashableListEdgePackagingJobs$fAWSPagerListEdgePackagingJobs%$fNFDataListEdgePackagingJobsResponse!$fAWSRequestListEdgePackagingJobs!$fEqListEdgePackagingJobsResponse#$fReadListEdgePackagingJobsResponse#$fShowListEdgePackagingJobsResponse&$fGenericListEdgePackagingJobsResponse$fEqListEdgePackagingJobs$fReadListEdgePackagingJobs$fShowListEdgePackagingJobs$fGenericListEdgePackagingJobsListEdgeDeploymentPlansResponse ListEdgeDeploymentPlansResponse'/$sel:nextToken:ListEdgeDeploymentPlansResponse'0$sel:httpStatus:ListEdgeDeploymentPlansResponse'$sel:edgeDeploymentPlanSummaries:ListEdgeDeploymentPlansResponse'ListEdgeDeploymentPlansListEdgeDeploymentPlans'/$sel:creationTimeAfter:ListEdgeDeploymentPlans'0$sel:creationTimeBefore:ListEdgeDeploymentPlans'5$sel:deviceFleetNameContains:ListEdgeDeploymentPlans'3$sel:lastModifiedTimeAfter:ListEdgeDeploymentPlans'4$sel:lastModifiedTimeBefore:ListEdgeDeploymentPlans'($sel:maxResults:ListEdgeDeploymentPlans'*$sel:nameContains:ListEdgeDeploymentPlans''$sel:nextToken:ListEdgeDeploymentPlans'$$sel:sortBy:ListEdgeDeploymentPlans''$sel:sortOrder:ListEdgeDeploymentPlans'newListEdgeDeploymentPlans)listEdgeDeploymentPlans_creationTimeAfter*listEdgeDeploymentPlans_creationTimeBefore/listEdgeDeploymentPlans_deviceFleetNameContains-listEdgeDeploymentPlans_lastModifiedTimeAfter.listEdgeDeploymentPlans_lastModifiedTimeBefore"listEdgeDeploymentPlans_maxResults$listEdgeDeploymentPlans_nameContains!listEdgeDeploymentPlans_nextTokenlistEdgeDeploymentPlans_sortBy!listEdgeDeploymentPlans_sortOrder"newListEdgeDeploymentPlansResponse)listEdgeDeploymentPlansResponse_nextToken*listEdgeDeploymentPlansResponse_httpStatus;listEdgeDeploymentPlansResponse_edgeDeploymentPlanSummaries $fToQueryListEdgeDeploymentPlans$fToPathListEdgeDeploymentPlans$fToJSONListEdgeDeploymentPlans"$fToHeadersListEdgeDeploymentPlans$fNFDataListEdgeDeploymentPlans!$fHashableListEdgeDeploymentPlans!$fAWSPagerListEdgeDeploymentPlans'$fNFDataListEdgeDeploymentPlansResponse#$fAWSRequestListEdgeDeploymentPlans#$fEqListEdgeDeploymentPlansResponse%$fReadListEdgeDeploymentPlansResponse%$fShowListEdgeDeploymentPlansResponse($fGenericListEdgeDeploymentPlansResponse$fEqListEdgeDeploymentPlans$fReadListEdgeDeploymentPlans$fShowListEdgeDeploymentPlans $fGenericListEdgeDeploymentPlansListDomainsResponseListDomainsResponse'!$sel:domains:ListDomainsResponse'#$sel:nextToken:ListDomainsResponse'$$sel:httpStatus:ListDomainsResponse' ListDomains ListDomains'$sel:maxResults:ListDomains'$sel:nextToken:ListDomains'newListDomainslistDomains_maxResultslistDomains_nextTokennewListDomainsResponselistDomainsResponse_domainslistDomainsResponse_nextTokenlistDomainsResponse_httpStatus$fToQueryListDomains$fToPathListDomains$fToJSONListDomains$fToHeadersListDomains$fNFDataListDomains$fHashableListDomains$fAWSPagerListDomains$fNFDataListDomainsResponse$fAWSRequestListDomains$fEqListDomainsResponse$fReadListDomainsResponse$fShowListDomainsResponse$fGenericListDomainsResponse$fEqListDomains$fReadListDomains$fShowListDomains$fGenericListDomainsListDevicesResponseListDevicesResponse'#$sel:nextToken:ListDevicesResponse'$$sel:httpStatus:ListDevicesResponse')$sel:deviceSummaries:ListDevicesResponse' ListDevices ListDevices'!$sel:deviceFleetName:ListDevices'&$sel:latestHeartbeatAfter:ListDevices'$sel:maxResults:ListDevices'$sel:modelName:ListDevices'$sel:nextToken:ListDevices'newListDeviceslistDevices_deviceFleetName listDevices_latestHeartbeatAfterlistDevices_maxResultslistDevices_modelNamelistDevices_nextTokennewListDevicesResponselistDevicesResponse_nextTokenlistDevicesResponse_httpStatus#listDevicesResponse_deviceSummaries$fToQueryListDevices$fToPathListDevices$fToJSONListDevices$fToHeadersListDevices$fNFDataListDevices$fHashableListDevices$fAWSPagerListDevices$fNFDataListDevicesResponse$fAWSRequestListDevices$fEqListDevicesResponse$fReadListDevicesResponse$fShowListDevicesResponse$fGenericListDevicesResponse$fEqListDevices$fReadListDevices$fShowListDevices$fGenericListDevicesListDeviceFleetsResponseListDeviceFleetsResponse'($sel:nextToken:ListDeviceFleetsResponse')$sel:httpStatus:ListDeviceFleetsResponse'3$sel:deviceFleetSummaries:ListDeviceFleetsResponse'ListDeviceFleetsListDeviceFleets'($sel:creationTimeAfter:ListDeviceFleets')$sel:creationTimeBefore:ListDeviceFleets',$sel:lastModifiedTimeAfter:ListDeviceFleets'-$sel:lastModifiedTimeBefore:ListDeviceFleets'!$sel:maxResults:ListDeviceFleets'#$sel:nameContains:ListDeviceFleets' $sel:nextToken:ListDeviceFleets'$sel:sortBy:ListDeviceFleets' $sel:sortOrder:ListDeviceFleets'newListDeviceFleets"listDeviceFleets_creationTimeAfter#listDeviceFleets_creationTimeBefore&listDeviceFleets_lastModifiedTimeAfter'listDeviceFleets_lastModifiedTimeBeforelistDeviceFleets_maxResultslistDeviceFleets_nameContainslistDeviceFleets_nextTokenlistDeviceFleets_sortBylistDeviceFleets_sortOrdernewListDeviceFleetsResponse"listDeviceFleetsResponse_nextToken#listDeviceFleetsResponse_httpStatus-listDeviceFleetsResponse_deviceFleetSummaries$fToQueryListDeviceFleets$fToPathListDeviceFleets$fToJSONListDeviceFleets$fToHeadersListDeviceFleets$fNFDataListDeviceFleets$fHashableListDeviceFleets$fAWSPagerListDeviceFleets $fNFDataListDeviceFleetsResponse$fAWSRequestListDeviceFleets$fEqListDeviceFleetsResponse$fReadListDeviceFleetsResponse$fShowListDeviceFleetsResponse!$fGenericListDeviceFleetsResponse$fEqListDeviceFleets$fReadListDeviceFleets$fShowListDeviceFleets$fGenericListDeviceFleets%ListDataQualityJobDefinitionsResponse&ListDataQualityJobDefinitionsResponse'5$sel:nextToken:ListDataQualityJobDefinitionsResponse'6$sel:httpStatus:ListDataQualityJobDefinitionsResponse'$sel:jobDefinitionSummaries:ListDataQualityJobDefinitionsResponse'ListDataQualityJobDefinitionsListDataQualityJobDefinitions'5$sel:creationTimeAfter:ListDataQualityJobDefinitions'6$sel:creationTimeBefore:ListDataQualityJobDefinitions'0$sel:endpointName:ListDataQualityJobDefinitions'.$sel:maxResults:ListDataQualityJobDefinitions'0$sel:nameContains:ListDataQualityJobDefinitions'-$sel:nextToken:ListDataQualityJobDefinitions'*$sel:sortBy:ListDataQualityJobDefinitions'-$sel:sortOrder:ListDataQualityJobDefinitions' newListDataQualityJobDefinitions/listDataQualityJobDefinitions_creationTimeAfter0listDataQualityJobDefinitions_creationTimeBefore*listDataQualityJobDefinitions_endpointName(listDataQualityJobDefinitions_maxResults*listDataQualityJobDefinitions_nameContains'listDataQualityJobDefinitions_nextToken$listDataQualityJobDefinitions_sortBy'listDataQualityJobDefinitions_sortOrder(newListDataQualityJobDefinitionsResponse/listDataQualityJobDefinitionsResponse_nextToken0listDataQualityJobDefinitionsResponse_httpStatus$sel:status:GetSagemakerServicecatalogPortfolioStatusResponse'$sel:httpStatus:GetSagemakerServicecatalogPortfolioStatusResponse')GetSagemakerServicecatalogPortfolioStatus*GetSagemakerServicecatalogPortfolioStatus',newGetSagemakerServicecatalogPortfolioStatus4newGetSagemakerServicecatalogPortfolioStatusResponse8getSagemakerServicecatalogPortfolioStatusResponse_statusdescribeStudioLifecycleConfigResponse_studioLifecycleConfigArndescribeStudioLifecycleConfigResponse_studioLifecycleConfigContent?describeStudioLifecycleConfigResponse_studioLifecycleConfigName0describeStudioLifecycleConfigResponse_httpStatus&$fToQueryDescribeStudioLifecycleConfig%$fToPathDescribeStudioLifecycleConfig%$fToJSONDescribeStudioLifecycleConfig($fToHeadersDescribeStudioLifecycleConfig%$fNFDataDescribeStudioLifecycleConfig'$fHashableDescribeStudioLifecycleConfig-$fNFDataDescribeStudioLifecycleConfigResponse)$fAWSRequestDescribeStudioLifecycleConfig)$fEqDescribeStudioLifecycleConfigResponse+$fReadDescribeStudioLifecycleConfigResponse+$fShowDescribeStudioLifecycleConfigResponse.$fGenericDescribeStudioLifecycleConfigResponse!$fEqDescribeStudioLifecycleConfig#$fReadDescribeStudioLifecycleConfig#$fShowDescribeStudioLifecycleConfig&$fGenericDescribeStudioLifecycleConfigDescribeSpaceResponseDescribeSpaceResponse'($sel:creationTime:DescribeSpaceResponse'$$sel:domainId:DescribeSpaceResponse')$sel:failureReason:DescribeSpaceResponse'0$sel:homeEfsFileSystemUid:DescribeSpaceResponse',$sel:lastModifiedTime:DescribeSpaceResponse'$$sel:spaceArn:DescribeSpaceResponse'%$sel:spaceName:DescribeSpaceResponse')$sel:spaceSettings:DescribeSpaceResponse'"$sel:status:DescribeSpaceResponse'&$sel:httpStatus:DescribeSpaceResponse' DescribeSpaceDescribeSpace'$sel:domainId:DescribeSpace'$sel:spaceName:DescribeSpace'newDescribeSpacedescribeSpace_domainIddescribeSpace_spaceNamenewDescribeSpaceResponse"describeSpaceResponse_creationTimedescribeSpaceResponse_domainId#describeSpaceResponse_failureReason*describeSpaceResponse_homeEfsFileSystemUid&describeSpaceResponse_lastModifiedTimedescribeSpaceResponse_spaceArndescribeSpaceResponse_spaceName#describeSpaceResponse_spaceSettingsdescribeSpaceResponse_status describeSpaceResponse_httpStatus$fToQueryDescribeSpace$fToPathDescribeSpace$fToJSONDescribeSpace$fToHeadersDescribeSpace$fNFDataDescribeSpace$fHashableDescribeSpace$fNFDataDescribeSpaceResponse$fAWSRequestDescribeSpace$fEqDescribeSpaceResponse$fReadDescribeSpaceResponse$fShowDescribeSpaceResponse$fGenericDescribeSpaceResponse$fEqDescribeSpace$fReadDescribeSpace$fShowDescribeSpace$fGenericDescribeSpaceDescribeProjectResponseDescribeProjectResponse''$sel:createdBy:DescribeProjectResponse',$sel:lastModifiedBy:DescribeProjectResponse'.$sel:lastModifiedTime:DescribeProjectResponse'0$sel:projectDescription:DescribeProjectResponse'$sel:serviceCatalogProvisionedProductDetails:DescribeProjectResponse'($sel:httpStatus:DescribeProjectResponse'($sel:projectArn:DescribeProjectResponse')$sel:projectName:DescribeProjectResponse''$sel:projectId:DescribeProjectResponse'?$sel:serviceCatalogProvisioningDetails:DescribeProjectResponse'+$sel:projectStatus:DescribeProjectResponse'*$sel:creationTime:DescribeProjectResponse'DescribeProjectDescribeProject'!$sel:projectName:DescribeProject'newDescribeProjectdescribeProject_projectNamenewDescribeProjectResponse!describeProjectResponse_createdBy&describeProjectResponse_lastModifiedBy(describeProjectResponse_lastModifiedTime*describeProjectResponse_projectDescription?describeProjectResponse_serviceCatalogProvisionedProductDetails"describeProjectResponse_httpStatus"describeProjectResponse_projectArn#describeProjectResponse_projectName!describeProjectResponse_projectId9describeProjectResponse_serviceCatalogProvisioningDetails%describeProjectResponse_projectStatus$describeProjectResponse_creationTime$fToQueryDescribeProject$fToPathDescribeProject$fToJSONDescribeProject$fToHeadersDescribeProject$fNFDataDescribeProject$fHashableDescribeProject$fNFDataDescribeProjectResponse$fAWSRequestDescribeProject$fEqDescribeProjectResponse$fReadDescribeProjectResponse$fShowDescribeProjectResponse $fGenericDescribeProjectResponse$fEqDescribeProject$fReadDescribeProject$fShowDescribeProject$fGenericDescribeProjectDescribeProcessingJobResponseDescribeProcessingJobResponse'0$sel:autoMLJobArn:DescribeProcessingJobResponse'/$sel:environment:DescribeProcessingJobResponse'/$sel:exitMessage:DescribeProcessingJobResponse'4$sel:experimentConfig:DescribeProcessingJobResponse'1$sel:failureReason:DescribeProcessingJobResponse'4$sel:lastModifiedTime:DescribeProcessingJobResponse'9$sel:monitoringScheduleArn:DescribeProcessingJobResponse'1$sel:networkConfig:DescribeProcessingJobResponse'5$sel:processingEndTime:DescribeProcessingJobResponse'4$sel:processingInputs:DescribeProcessingJobResponse':$sel:processingOutputConfig:DescribeProcessingJobResponse'7$sel:processingStartTime:DescribeProcessingJobResponse'+$sel:roleArn:DescribeProcessingJobResponse'5$sel:stoppingCondition:DescribeProcessingJobResponse'2$sel:trainingJobArn:DescribeProcessingJobResponse'.$sel:httpStatus:DescribeProcessingJobResponse'5$sel:processingJobName:DescribeProcessingJobResponse'7$sel:processingResources:DescribeProcessingJobResponse'4$sel:appSpecification:DescribeProcessingJobResponse'4$sel:processingJobArn:DescribeProcessingJobResponse'7$sel:processingJobStatus:DescribeProcessingJobResponse'0$sel:creationTime:DescribeProcessingJobResponse'DescribeProcessingJob'-$sel:processingJobName:DescribeProcessingJob'newDescribeProcessingJob'describeProcessingJob_processingJobName newDescribeProcessingJobResponse*describeProcessingJobResponse_autoMLJobArn)describeProcessingJobResponse_environment)describeProcessingJobResponse_exitMessage.describeProcessingJobResponse_experimentConfig+describeProcessingJobResponse_failureReason.describeProcessingJobResponse_lastModifiedTime3describeProcessingJobResponse_monitoringScheduleArn+describeProcessingJobResponse_networkConfig/describeProcessingJobResponse_processingEndTime.describeProcessingJobResponse_processingInputs4describeProcessingJobResponse_processingOutputConfig1describeProcessingJobResponse_processingStartTime%describeProcessingJobResponse_roleArn/describeProcessingJobResponse_stoppingCondition,describeProcessingJobResponse_trainingJobArn(describeProcessingJobResponse_httpStatus/describeProcessingJobResponse_processingJobName1describeProcessingJobResponse_processingResources.describeProcessingJobResponse_appSpecification.describeProcessingJobResponse_processingJobArn1describeProcessingJobResponse_processingJobStatus*describeProcessingJobResponse_creationTime$fToQueryDescribeProcessingJob$fToPathDescribeProcessingJob$fToJSONDescribeProcessingJob $fToHeadersDescribeProcessingJob$fNFDataDescribeProcessingJob$fHashableDescribeProcessingJob%$fNFDataDescribeProcessingJobResponse!$fAWSRequestDescribeProcessingJob!$fEqDescribeProcessingJobResponse#$fReadDescribeProcessingJobResponse#$fShowDescribeProcessingJobResponse&$fGenericDescribeProcessingJobResponse$fEqDescribeProcessingJob$fReadDescribeProcessingJob$fShowDescribeProcessingJob$fGenericDescribeProcessingJob!DescribePipelineExecutionResponse"DescribePipelineExecutionResponse'1$sel:createdBy:DescribePipelineExecutionResponse'4$sel:creationTime:DescribePipelineExecutionResponse'5$sel:failureReason:DescribePipelineExecutionResponse'6$sel:lastModifiedBy:DescribePipelineExecutionResponse'8$sel:lastModifiedTime:DescribePipelineExecutionResponse'$sel:parallelismConfiguration:DescribePipelineExecutionResponse'3$sel:pipelineArn:DescribePipelineExecutionResponse'<$sel:pipelineExecutionArn:DescribePipelineExecutionResponse'$sel:pipelineExecutionDescription:DescribePipelineExecutionResponse'$sel:pipelineExecutionDisplayName:DescribePipelineExecutionResponse'?$sel:pipelineExecutionStatus:DescribePipelineExecutionResponse'$sel:pipelineExperimentConfig:DescribePipelineExecutionResponse'2$sel:httpStatus:DescribePipelineExecutionResponse'DescribePipelineExecutionDescribePipelineExecution'4$sel:pipelineExecutionArn:DescribePipelineExecution'newDescribePipelineExecution.describePipelineExecution_pipelineExecutionArn$newDescribePipelineExecutionResponse+describePipelineExecutionResponse_createdBy.describePipelineExecutionResponse_creationTime/describePipelineExecutionResponse_failureReason0describePipelineExecutionResponse_lastModifiedBy2describePipelineExecutionResponse_lastModifiedTime:describePipelineExecutionResponse_parallelismConfiguration-describePipelineExecutionResponse_pipelineArn6describePipelineExecutionResponse_pipelineExecutionArn>describePipelineExecutionResponse_pipelineExecutionDescription>describePipelineExecutionResponse_pipelineExecutionDisplayName9describePipelineExecutionResponse_pipelineExecutionStatus:describePipelineExecutionResponse_pipelineExperimentConfig,describePipelineExecutionResponse_httpStatus"$fToQueryDescribePipelineExecution!$fToPathDescribePipelineExecution!$fToJSONDescribePipelineExecution$$fToHeadersDescribePipelineExecution!$fNFDataDescribePipelineExecution#$fHashableDescribePipelineExecution)$fNFDataDescribePipelineExecutionResponse%$fAWSRequestDescribePipelineExecution%$fEqDescribePipelineExecutionResponse'$fReadDescribePipelineExecutionResponse'$fShowDescribePipelineExecutionResponse*$fGenericDescribePipelineExecutionResponse$fEqDescribePipelineExecution$fReadDescribePipelineExecution$fShowDescribePipelineExecution"$fGenericDescribePipelineExecution.DescribePipelineDefinitionForExecutionResponse/DescribePipelineDefinitionForExecutionResponse'$sel:creationTime:DescribePipelineDefinitionForExecutionResponse'$sel:pipelineDefinition:DescribePipelineDefinitionForExecutionResponse'?$sel:httpStatus:DescribePipelineDefinitionForExecutionResponse'&DescribePipelineDefinitionForExecution'DescribePipelineDefinitionForExecution'$sel:pipelineExecutionArn:DescribePipelineDefinitionForExecution')newDescribePipelineDefinitionForExecution;describePipelineDefinitionForExecution_pipelineExecutionArn1newDescribePipelineDefinitionForExecutionResponse;describePipelineDefinitionForExecutionResponse_creationTimedescribePipelineDefinitionForExecutionResponse_pipelineDefinition9describePipelineDefinitionForExecutionResponse_httpStatus/$fToQueryDescribePipelineDefinitionForExecution.$fToPathDescribePipelineDefinitionForExecution.$fToJSONDescribePipelineDefinitionForExecution1$fToHeadersDescribePipelineDefinitionForExecution.$fNFDataDescribePipelineDefinitionForExecution0$fHashableDescribePipelineDefinitionForExecution6$fNFDataDescribePipelineDefinitionForExecutionResponse2$fAWSRequestDescribePipelineDefinitionForExecution2$fEqDescribePipelineDefinitionForExecutionResponse4$fReadDescribePipelineDefinitionForExecutionResponse4$fShowDescribePipelineDefinitionForExecutionResponse7$fGenericDescribePipelineDefinitionForExecutionResponse*$fEqDescribePipelineDefinitionForExecution,$fReadDescribePipelineDefinitionForExecution,$fShowDescribePipelineDefinitionForExecution/$fGenericDescribePipelineDefinitionForExecutionDescribePipelineResponseDescribePipelineResponse'($sel:createdBy:DescribePipelineResponse'+$sel:creationTime:DescribePipelineResponse'-$sel:lastModifiedBy:DescribePipelineResponse'/$sel:lastModifiedTime:DescribePipelineResponse'*$sel:lastRunTime:DescribePipelineResponse'7$sel:parallelismConfiguration:DescribePipelineResponse'*$sel:pipelineArn:DescribePipelineResponse'1$sel:pipelineDefinition:DescribePipelineResponse'2$sel:pipelineDescription:DescribePipelineResponse'2$sel:pipelineDisplayName:DescribePipelineResponse'+$sel:pipelineName:DescribePipelineResponse'-$sel:pipelineStatus:DescribePipelineResponse'&$sel:roleArn:DescribePipelineResponse')$sel:httpStatus:DescribePipelineResponse'DescribePipelineDescribePipeline'#$sel:pipelineName:DescribePipeline'newDescribePipelinedescribePipeline_pipelineNamenewDescribePipelineResponse"describePipelineResponse_createdBy%describePipelineResponse_creationTime'describePipelineResponse_lastModifiedBy)describePipelineResponse_lastModifiedTime$describePipelineResponse_lastRunTime1describePipelineResponse_parallelismConfiguration$describePipelineResponse_pipelineArn+describePipelineResponse_pipelineDefinition,describePipelineResponse_pipelineDescription,describePipelineResponse_pipelineDisplayName%describePipelineResponse_pipelineName'describePipelineResponse_pipelineStatus describePipelineResponse_roleArn#describePipelineResponse_httpStatus$fToQueryDescribePipeline$fToPathDescribePipeline$fToJSONDescribePipeline$fToHeadersDescribePipeline$fNFDataDescribePipeline$fHashableDescribePipeline $fNFDataDescribePipelineResponse$fAWSRequestDescribePipeline$fEqDescribePipelineResponse$fReadDescribePipelineResponse$fShowDescribePipelineResponse!$fGenericDescribePipelineResponse$fEqDescribePipeline$fReadDescribePipeline$fShowDescribePipeline$fGenericDescribePipeline/DescribeNotebookInstanceLifecycleConfigResponse0DescribeNotebookInstanceLifecycleConfigResponse'$sel:creationTime:DescribeNotebookInstanceLifecycleConfigResponse'$sel:lastModifiedTime:DescribeNotebookInstanceLifecycleConfigResponse'$sel:notebookInstanceLifecycleConfigArn:DescribeNotebookInstanceLifecycleConfigResponse'$sel:notebookInstanceLifecycleConfigName:DescribeNotebookInstanceLifecycleConfigResponse'>$sel:onCreate:DescribeNotebookInstanceLifecycleConfigResponse'=$sel:onStart:DescribeNotebookInstanceLifecycleConfigResponse'$sel:httpStatus:DescribeNotebookInstanceLifecycleConfigResponse''DescribeNotebookInstanceLifecycleConfig(DescribeNotebookInstanceLifecycleConfig'$sel:notebookInstanceLifecycleConfigName:DescribeNotebookInstanceLifecycleConfig'*newDescribeNotebookInstanceLifecycleConfigdescribeNotebookInstanceLifecycleConfig_notebookInstanceLifecycleConfigName2newDescribeNotebookInstanceLifecycleConfigResponse$sel:monitoringScheduleArn:DescribeMonitoringScheduleResponse'?$sel:monitoringScheduleName:DescribeMonitoringScheduleResponse'$sel:monitoringScheduleStatus:DescribeMonitoringScheduleResponse'5$sel:creationTime:DescribeMonitoringScheduleResponse'9$sel:lastModifiedTime:DescribeMonitoringScheduleResponse'$sel:monitoringScheduleConfig:DescribeMonitoringScheduleResponse'DescribeMonitoringScheduleDescribeMonitoringSchedule'7$sel:monitoringScheduleName:DescribeMonitoringSchedule'newDescribeMonitoringSchedule1describeMonitoringSchedule_monitoringScheduleName%newDescribeMonitoringScheduleResponse/describeMonitoringScheduleResponse_endpointName0describeMonitoringScheduleResponse_failureReasondescribeMonitoringScheduleResponse_lastMonitoringExecutionSummary1describeMonitoringScheduleResponse_monitoringType-describeMonitoringScheduleResponse_httpStatus8describeMonitoringScheduleResponse_monitoringScheduleArn9describeMonitoringScheduleResponse_monitoringScheduleName;describeMonitoringScheduleResponse_monitoringScheduleStatus/describeMonitoringScheduleResponse_creationTime3describeMonitoringScheduleResponse_lastModifiedTime;describeMonitoringScheduleResponse_monitoringScheduleConfig#$fToQueryDescribeMonitoringSchedule"$fToPathDescribeMonitoringSchedule"$fToJSONDescribeMonitoringSchedule%$fToHeadersDescribeMonitoringSchedule"$fNFDataDescribeMonitoringSchedule$$fHashableDescribeMonitoringSchedule*$fNFDataDescribeMonitoringScheduleResponse&$fAWSRequestDescribeMonitoringSchedule&$fEqDescribeMonitoringScheduleResponse($fReadDescribeMonitoringScheduleResponse($fShowDescribeMonitoringScheduleResponse+$fGenericDescribeMonitoringScheduleResponse$fEqDescribeMonitoringSchedule $fReadDescribeMonitoringSchedule $fShowDescribeMonitoringSchedule#$fGenericDescribeMonitoringSchedule)DescribeModelQualityJobDefinitionResponse*DescribeModelQualityJobDefinitionResponse'$sel:modelQualityBaselineConfig:DescribeModelQualityJobDefinitionResponse'=$sel:networkConfig:DescribeModelQualityJobDefinitionResponse'$sel:stoppingCondition:DescribeModelQualityJobDefinitionResponse':$sel:httpStatus:DescribeModelQualityJobDefinitionResponse'$sel:jobDefinitionArn:DescribeModelQualityJobDefinitionResponse'$sel:jobDefinitionName:DescribeModelQualityJobDefinitionResponse'<$sel:creationTime:DescribeModelQualityJobDefinitionResponse'$sel:modelQualityAppSpecification:DescribeModelQualityJobDefinitionResponse'$sel:modelQualityJobInput:DescribeModelQualityJobDefinitionResponse'$sel:modelQualityJobOutputConfig:DescribeModelQualityJobDefinitionResponse'<$sel:jobResources:DescribeModelQualityJobDefinitionResponse'7$sel:roleArn:DescribeModelQualityJobDefinitionResponse'!DescribeModelQualityJobDefinition"DescribeModelQualityJobDefinition'9$sel:jobDefinitionName:DescribeModelQualityJobDefinition'$newDescribeModelQualityJobDefinition3describeModelQualityJobDefinition_jobDefinitionName,newDescribeModelQualityJobDefinitionResponsedescribeModelQualityJobDefinitionResponse_modelQualityBaselineConfig7describeModelQualityJobDefinitionResponse_networkConfig;describeModelQualityJobDefinitionResponse_stoppingCondition4describeModelQualityJobDefinitionResponse_httpStatus:describeModelQualityJobDefinitionResponse_jobDefinitionArn;describeModelQualityJobDefinitionResponse_jobDefinitionName6describeModelQualityJobDefinitionResponse_creationTimedescribeModelQualityJobDefinitionResponse_modelQualityAppSpecification>describeModelQualityJobDefinitionResponse_modelQualityJobInputdescribeModelQualityJobDefinitionResponse_modelQualityJobOutputConfig6describeModelQualityJobDefinitionResponse_jobResources1describeModelQualityJobDefinitionResponse_roleArn*$fToQueryDescribeModelQualityJobDefinition)$fToPathDescribeModelQualityJobDefinition)$fToJSONDescribeModelQualityJobDefinition,$fToHeadersDescribeModelQualityJobDefinition)$fNFDataDescribeModelQualityJobDefinition+$fHashableDescribeModelQualityJobDefinition1$fNFDataDescribeModelQualityJobDefinitionResponse-$fAWSRequestDescribeModelQualityJobDefinition-$fEqDescribeModelQualityJobDefinitionResponse/$fReadDescribeModelQualityJobDefinitionResponse/$fShowDescribeModelQualityJobDefinitionResponse2$fGenericDescribeModelQualityJobDefinitionResponse%$fEqDescribeModelQualityJobDefinition'$fReadDescribeModelQualityJobDefinition'$fShowDescribeModelQualityJobDefinition*$fGenericDescribeModelQualityJobDefinition!DescribeModelPackageGroupResponse"DescribeModelPackageGroupResponse'$sel:modelPackageGroupDescription:DescribeModelPackageGroupResponse'2$sel:httpStatus:DescribeModelPackageGroupResponse'=$sel:modelPackageGroupName:DescribeModelPackageGroupResponse'<$sel:modelPackageGroupArn:DescribeModelPackageGroupResponse'4$sel:creationTime:DescribeModelPackageGroupResponse'1$sel:createdBy:DescribeModelPackageGroupResponse'?$sel:modelPackageGroupStatus:DescribeModelPackageGroupResponse'DescribeModelPackageGroupDescribeModelPackageGroup'5$sel:modelPackageGroupName:DescribeModelPackageGroup'newDescribeModelPackageGroup/describeModelPackageGroup_modelPackageGroupName$newDescribeModelPackageGroupResponse>describeModelPackageGroupResponse_modelPackageGroupDescription,describeModelPackageGroupResponse_httpStatus7describeModelPackageGroupResponse_modelPackageGroupName6describeModelPackageGroupResponse_modelPackageGroupArn.describeModelPackageGroupResponse_creationTime+describeModelPackageGroupResponse_createdBy9describeModelPackageGroupResponse_modelPackageGroupStatus"$fToQueryDescribeModelPackageGroup!$fToPathDescribeModelPackageGroup!$fToJSONDescribeModelPackageGroup$$fToHeadersDescribeModelPackageGroup!$fNFDataDescribeModelPackageGroup#$fHashableDescribeModelPackageGroup)$fNFDataDescribeModelPackageGroupResponse%$fAWSRequestDescribeModelPackageGroup%$fEqDescribeModelPackageGroupResponse'$fReadDescribeModelPackageGroupResponse'$fShowDescribeModelPackageGroupResponse*$fGenericDescribeModelPackageGroupResponse$fEqDescribeModelPackageGroup$fReadDescribeModelPackageGroup$fShowDescribeModelPackageGroup"$fGenericDescribeModelPackageGroupDescribeModelPackageResponseDescribeModelPackageResponse'$sel:additionalInferenceSpecifications:DescribeModelPackageResponse'6$sel:approvalDescription:DescribeModelPackageResponse'8$sel:certifyForMarketplace:DescribeModelPackageResponse',$sel:createdBy:DescribeModelPackageResponse'=$sel:customerMetadataProperties:DescribeModelPackageResponse')$sel:domain:DescribeModelPackageResponse'6$sel:driftCheckBaselines:DescribeModelPackageResponse'9$sel:inferenceSpecification:DescribeModelPackageResponse'1$sel:lastModifiedBy:DescribeModelPackageResponse'3$sel:lastModifiedTime:DescribeModelPackageResponse'5$sel:metadataProperties:DescribeModelPackageResponse'6$sel:modelApprovalStatus:DescribeModelPackageResponse'/$sel:modelMetrics:DescribeModelPackageResponse':$sel:modelPackageDescription:DescribeModelPackageResponse'8$sel:modelPackageGroupName:DescribeModelPackageResponse'6$sel:modelPackageVersion:DescribeModelPackageResponse'3$sel:samplePayloadUrl:DescribeModelPackageResponse'?$sel:sourceAlgorithmSpecification:DescribeModelPackageResponse''$sel:task:DescribeModelPackageResponse':$sel:validationSpecification:DescribeModelPackageResponse'-$sel:httpStatus:DescribeModelPackageResponse'3$sel:modelPackageName:DescribeModelPackageResponse'2$sel:modelPackageArn:DescribeModelPackageResponse'/$sel:creationTime:DescribeModelPackageResponse'5$sel:modelPackageStatus:DescribeModelPackageResponse'<$sel:modelPackageStatusDetails:DescribeModelPackageResponse'DescribeModelPackageDescribeModelPackage'+$sel:modelPackageName:DescribeModelPackage'newDescribeModelPackage%describeModelPackage_modelPackageNamenewDescribeModelPackageResponse>describeModelPackageResponse_additionalInferenceSpecifications0describeModelPackageResponse_approvalDescription2describeModelPackageResponse_certifyForMarketplace&describeModelPackageResponse_createdBy7describeModelPackageResponse_customerMetadataProperties#describeModelPackageResponse_domain0describeModelPackageResponse_driftCheckBaselines3describeModelPackageResponse_inferenceSpecification+describeModelPackageResponse_lastModifiedBy-describeModelPackageResponse_lastModifiedTime/describeModelPackageResponse_metadataProperties0describeModelPackageResponse_modelApprovalStatus)describeModelPackageResponse_modelMetrics4describeModelPackageResponse_modelPackageDescription2describeModelPackageResponse_modelPackageGroupName0describeModelPackageResponse_modelPackageVersion-describeModelPackageResponse_samplePayloadUrl9describeModelPackageResponse_sourceAlgorithmSpecification!describeModelPackageResponse_task4describeModelPackageResponse_validationSpecification'describeModelPackageResponse_httpStatus-describeModelPackageResponse_modelPackageName,describeModelPackageResponse_modelPackageArn)describeModelPackageResponse_creationTime/describeModelPackageResponse_modelPackageStatus6describeModelPackageResponse_modelPackageStatusDetails$fToQueryDescribeModelPackage$fToPathDescribeModelPackage$fToJSONDescribeModelPackage$fToHeadersDescribeModelPackage$fNFDataDescribeModelPackage$fHashableDescribeModelPackage$$fNFDataDescribeModelPackageResponse $fAWSRequestDescribeModelPackage $fEqDescribeModelPackageResponse"$fReadDescribeModelPackageResponse"$fShowDescribeModelPackageResponse%$fGenericDescribeModelPackageResponse$fEqDescribeModelPackage$fReadDescribeModelPackage$fShowDescribeModelPackage$fGenericDescribeModelPackage0DescribeModelExplainabilityJobDefinitionResponse1DescribeModelExplainabilityJobDefinitionResponse'$sel:modelExplainabilityBaselineConfig:DescribeModelExplainabilityJobDefinitionResponse'$sel:networkConfig:DescribeModelExplainabilityJobDefinitionResponse'$sel:stoppingCondition:DescribeModelExplainabilityJobDefinitionResponse'$sel:httpStatus:DescribeModelExplainabilityJobDefinitionResponse'$sel:jobDefinitionArn:DescribeModelExplainabilityJobDefinitionResponse'$sel:jobDefinitionName:DescribeModelExplainabilityJobDefinitionResponse'$sel:creationTime:DescribeModelExplainabilityJobDefinitionResponse'$sel:modelExplainabilityAppSpecification:DescribeModelExplainabilityJobDefinitionResponse'$sel:modelExplainabilityJobInput:DescribeModelExplainabilityJobDefinitionResponse'$sel:modelExplainabilityJobOutputConfig:DescribeModelExplainabilityJobDefinitionResponse'$sel:jobResources:DescribeModelExplainabilityJobDefinitionResponse'>$sel:roleArn:DescribeModelExplainabilityJobDefinitionResponse'(DescribeModelExplainabilityJobDefinition)DescribeModelExplainabilityJobDefinition'$sel:jobDefinitionName:DescribeModelExplainabilityJobDefinition'+newDescribeModelExplainabilityJobDefinition:describeModelExplainabilityJobDefinition_jobDefinitionName3newDescribeModelExplainabilityJobDefinitionResponsedescribeModelExplainabilityJobDefinitionResponse_modelExplainabilityBaselineConfig>describeModelExplainabilityJobDefinitionResponse_networkConfigdescribeModelExplainabilityJobDefinitionResponse_stoppingCondition;describeModelExplainabilityJobDefinitionResponse_httpStatusdescribeModelExplainabilityJobDefinitionResponse_jobDefinitionArndescribeModelExplainabilityJobDefinitionResponse_jobDefinitionName=describeModelExplainabilityJobDefinitionResponse_creationTimedescribeModelExplainabilityJobDefinitionResponse_modelExplainabilityAppSpecificationdescribeModelExplainabilityJobDefinitionResponse_modelExplainabilityJobInputdescribeModelExplainabilityJobDefinitionResponse_modelExplainabilityJobOutputConfig=describeModelExplainabilityJobDefinitionResponse_jobResources8describeModelExplainabilityJobDefinitionResponse_roleArn1$fToQueryDescribeModelExplainabilityJobDefinition0$fToPathDescribeModelExplainabilityJobDefinition0$fToJSONDescribeModelExplainabilityJobDefinition3$fToHeadersDescribeModelExplainabilityJobDefinition0$fNFDataDescribeModelExplainabilityJobDefinition2$fHashableDescribeModelExplainabilityJobDefinition8$fNFDataDescribeModelExplainabilityJobDefinitionResponse4$fAWSRequestDescribeModelExplainabilityJobDefinition4$fEqDescribeModelExplainabilityJobDefinitionResponse6$fReadDescribeModelExplainabilityJobDefinitionResponse6$fShowDescribeModelExplainabilityJobDefinitionResponse9$fGenericDescribeModelExplainabilityJobDefinitionResponse,$fEqDescribeModelExplainabilityJobDefinition.$fReadDescribeModelExplainabilityJobDefinition.$fShowDescribeModelExplainabilityJobDefinition1$fGenericDescribeModelExplainabilityJobDefinition"DescribeModelCardExportJobResponse#DescribeModelCardExportJobResponse'8$sel:exportArtifacts:DescribeModelCardExportJobResponse'6$sel:failureReason:DescribeModelCardExportJobResponse'3$sel:httpStatus:DescribeModelCardExportJobResponse'?$sel:modelCardExportJobName:DescribeModelCardExportJobResponse'>$sel:modelCardExportJobArn:DescribeModelCardExportJobResponse'/$sel:status:DescribeModelCardExportJobResponse'6$sel:modelCardName:DescribeModelCardExportJobResponse'9$sel:modelCardVersion:DescribeModelCardExportJobResponse'5$sel:outputConfig:DescribeModelCardExportJobResponse'2$sel:createdAt:DescribeModelCardExportJobResponse'7$sel:lastModifiedAt:DescribeModelCardExportJobResponse'DescribeModelCardExportJobDescribeModelCardExportJob'6$sel:modelCardExportJobArn:DescribeModelCardExportJob'newDescribeModelCardExportJob0describeModelCardExportJob_modelCardExportJobArn%newDescribeModelCardExportJobResponse2describeModelCardExportJobResponse_exportArtifacts0describeModelCardExportJobResponse_failureReason-describeModelCardExportJobResponse_httpStatus9describeModelCardExportJobResponse_modelCardExportJobName8describeModelCardExportJobResponse_modelCardExportJobArn)describeModelCardExportJobResponse_status0describeModelCardExportJobResponse_modelCardName3describeModelCardExportJobResponse_modelCardVersion/describeModelCardExportJobResponse_outputConfig,describeModelCardExportJobResponse_createdAt1describeModelCardExportJobResponse_lastModifiedAt#$fToQueryDescribeModelCardExportJob"$fToPathDescribeModelCardExportJob"$fToJSONDescribeModelCardExportJob%$fToHeadersDescribeModelCardExportJob"$fNFDataDescribeModelCardExportJob$$fHashableDescribeModelCardExportJob*$fNFDataDescribeModelCardExportJobResponse&$fAWSRequestDescribeModelCardExportJob&$fEqDescribeModelCardExportJobResponse($fReadDescribeModelCardExportJobResponse($fShowDescribeModelCardExportJobResponse+$fGenericDescribeModelCardExportJobResponse$fEqDescribeModelCardExportJob $fReadDescribeModelCardExportJob $fShowDescribeModelCardExportJob#$fGenericDescribeModelCardExportJobDescribeModelCardResponseDescribeModelCardResponse'.$sel:lastModifiedBy:DescribeModelCardResponse'0$sel:lastModifiedTime:DescribeModelCardResponse'9$sel:modelCardProcessingStatus:DescribeModelCardResponse'.$sel:securityConfig:DescribeModelCardResponse'*$sel:httpStatus:DescribeModelCardResponse',$sel:modelCardArn:DescribeModelCardResponse'-$sel:modelCardName:DescribeModelCardResponse'0$sel:modelCardVersion:DescribeModelCardResponse''$sel:content:DescribeModelCardResponse'/$sel:modelCardStatus:DescribeModelCardResponse',$sel:creationTime:DescribeModelCardResponse')$sel:createdBy:DescribeModelCardResponse'DescribeModelCardDescribeModelCard'($sel:modelCardVersion:DescribeModelCard'%$sel:modelCardName:DescribeModelCard'newDescribeModelCard"describeModelCard_modelCardVersiondescribeModelCard_modelCardNamenewDescribeModelCardResponse(describeModelCardResponse_lastModifiedBy*describeModelCardResponse_lastModifiedTime3describeModelCardResponse_modelCardProcessingStatus(describeModelCardResponse_securityConfig$describeModelCardResponse_httpStatus&describeModelCardResponse_modelCardArn'describeModelCardResponse_modelCardName*describeModelCardResponse_modelCardVersion!describeModelCardResponse_content)describeModelCardResponse_modelCardStatus&describeModelCardResponse_creationTime#describeModelCardResponse_createdBy$fToQueryDescribeModelCard$fToPathDescribeModelCard$fToJSONDescribeModelCard$fToHeadersDescribeModelCard$fNFDataDescribeModelCard$fHashableDescribeModelCard!$fNFDataDescribeModelCardResponse$fAWSRequestDescribeModelCard$fEqDescribeModelCardResponse$fShowDescribeModelCardResponse"$fGenericDescribeModelCardResponse$fEqDescribeModelCard$fReadDescribeModelCard$fShowDescribeModelCard$fGenericDescribeModelCard&DescribeModelBiasJobDefinitionResponse'DescribeModelBiasJobDefinitionResponse'$sel:modelBiasBaselineConfig:DescribeModelBiasJobDefinitionResponse':$sel:networkConfig:DescribeModelBiasJobDefinitionResponse'>$sel:stoppingCondition:DescribeModelBiasJobDefinitionResponse'7$sel:httpStatus:DescribeModelBiasJobDefinitionResponse'=$sel:jobDefinitionArn:DescribeModelBiasJobDefinitionResponse'>$sel:jobDefinitionName:DescribeModelBiasJobDefinitionResponse'9$sel:creationTime:DescribeModelBiasJobDefinitionResponse'$sel:modelBiasAppSpecification:DescribeModelBiasJobDefinitionResponse'>$sel:modelBiasJobInput:DescribeModelBiasJobDefinitionResponse'$sel:modelBiasJobOutputConfig:DescribeModelBiasJobDefinitionResponse'9$sel:jobResources:DescribeModelBiasJobDefinitionResponse'4$sel:roleArn:DescribeModelBiasJobDefinitionResponse'DescribeModelBiasJobDefinitionDescribeModelBiasJobDefinition'6$sel:jobDefinitionName:DescribeModelBiasJobDefinition'!newDescribeModelBiasJobDefinition0describeModelBiasJobDefinition_jobDefinitionName)newDescribeModelBiasJobDefinitionResponse>describeModelBiasJobDefinitionResponse_modelBiasBaselineConfig4describeModelBiasJobDefinitionResponse_networkConfig8describeModelBiasJobDefinitionResponse_stoppingCondition1describeModelBiasJobDefinitionResponse_httpStatus7describeModelBiasJobDefinitionResponse_jobDefinitionArn8describeModelBiasJobDefinitionResponse_jobDefinitionName3describeModelBiasJobDefinitionResponse_creationTimedescribeModelBiasJobDefinitionResponse_modelBiasAppSpecification8describeModelBiasJobDefinitionResponse_modelBiasJobInput?describeModelBiasJobDefinitionResponse_modelBiasJobOutputConfig3describeModelBiasJobDefinitionResponse_jobResources.describeModelBiasJobDefinitionResponse_roleArn'$fToQueryDescribeModelBiasJobDefinition&$fToPathDescribeModelBiasJobDefinition&$fToJSONDescribeModelBiasJobDefinition)$fToHeadersDescribeModelBiasJobDefinition&$fNFDataDescribeModelBiasJobDefinition($fHashableDescribeModelBiasJobDefinition.$fNFDataDescribeModelBiasJobDefinitionResponse*$fAWSRequestDescribeModelBiasJobDefinition*$fEqDescribeModelBiasJobDefinitionResponse,$fReadDescribeModelBiasJobDefinitionResponse,$fShowDescribeModelBiasJobDefinitionResponse/$fGenericDescribeModelBiasJobDefinitionResponse"$fEqDescribeModelBiasJobDefinition$$fReadDescribeModelBiasJobDefinition$$fShowDescribeModelBiasJobDefinition'$fGenericDescribeModelBiasJobDefinitionDescribeModelResponseDescribeModelResponse'&$sel:containers:DescribeModelResponse'2$sel:enableNetworkIsolation:DescribeModelResponse'4$sel:inferenceExecutionConfig:DescribeModelResponse',$sel:primaryContainer:DescribeModelResponse'%$sel:vpcConfig:DescribeModelResponse'&$sel:httpStatus:DescribeModelResponse'%$sel:modelName:DescribeModelResponse',$sel:executionRoleArn:DescribeModelResponse'($sel:creationTime:DescribeModelResponse'$$sel:modelArn:DescribeModelResponse' DescribeModelDescribeModel'$sel:modelName:DescribeModel'newDescribeModeldescribeModel_modelNamenewDescribeModelResponse describeModelResponse_containers,describeModelResponse_enableNetworkIsolation.describeModelResponse_inferenceExecutionConfig&describeModelResponse_primaryContainerdescribeModelResponse_vpcConfig describeModelResponse_httpStatusdescribeModelResponse_modelName&describeModelResponse_executionRoleArn"describeModelResponse_creationTimedescribeModelResponse_modelArn$fToQueryDescribeModel$fToPathDescribeModel$fToJSONDescribeModel$fToHeadersDescribeModel$fNFDataDescribeModel$fHashableDescribeModel$fNFDataDescribeModelResponse$fAWSRequestDescribeModel$fEqDescribeModelResponse$fReadDescribeModelResponse$fShowDescribeModelResponse$fGenericDescribeModelResponse$fEqDescribeModel$fReadDescribeModel$fShowDescribeModel$fGenericDescribeModelDescribeLineageGroupResponseDescribeLineageGroupResponse',$sel:createdBy:DescribeLineageGroupResponse'/$sel:creationTime:DescribeLineageGroupResponse'.$sel:description:DescribeLineageGroupResponse'.$sel:displayName:DescribeLineageGroupResponse'1$sel:lastModifiedBy:DescribeLineageGroupResponse'3$sel:lastModifiedTime:DescribeLineageGroupResponse'2$sel:lineageGroupArn:DescribeLineageGroupResponse'3$sel:lineageGroupName:DescribeLineageGroupResponse'-$sel:httpStatus:DescribeLineageGroupResponse'DescribeLineageGroupDescribeLineageGroup'+$sel:lineageGroupName:DescribeLineageGroup'newDescribeLineageGroup%describeLineageGroup_lineageGroupNamenewDescribeLineageGroupResponse&describeLineageGroupResponse_createdBy)describeLineageGroupResponse_creationTime(describeLineageGroupResponse_description(describeLineageGroupResponse_displayName+describeLineageGroupResponse_lastModifiedBy-describeLineageGroupResponse_lastModifiedTime,describeLineageGroupResponse_lineageGroupArn-describeLineageGroupResponse_lineageGroupName'describeLineageGroupResponse_httpStatus$fToQueryDescribeLineageGroup$fToPathDescribeLineageGroup$fToJSONDescribeLineageGroup$fToHeadersDescribeLineageGroup$fNFDataDescribeLineageGroup$fHashableDescribeLineageGroup$$fNFDataDescribeLineageGroupResponse $fAWSRequestDescribeLineageGroup $fEqDescribeLineageGroupResponse"$fReadDescribeLineageGroupResponse"$fShowDescribeLineageGroupResponse%$fGenericDescribeLineageGroupResponse$fEqDescribeLineageGroup$fReadDescribeLineageGroup$fShowDescribeLineageGroup$fGenericDescribeLineageGroupDescribeLabelingJobResponseDescribeLabelingJobResponse'/$sel:failureReason:DescribeLabelingJobResponse'4$sel:labelAttributeName:DescribeLabelingJobResponse':$sel:labelCategoryConfigS3Uri:DescribeLabelingJobResponse'=$sel:labelingJobAlgorithmsConfig:DescribeLabelingJobResponse'3$sel:labelingJobOutput:DescribeLabelingJobResponse'4$sel:stoppingConditions:DescribeLabelingJobResponse'&$sel:tags:DescribeLabelingJobResponse',$sel:httpStatus:DescribeLabelingJobResponse'3$sel:labelingJobStatus:DescribeLabelingJobResponse'/$sel:labelCounters:DescribeLabelingJobResponse'.$sel:creationTime:DescribeLabelingJobResponse'2$sel:lastModifiedTime:DescribeLabelingJobResponse'2$sel:jobReferenceCode:DescribeLabelingJobResponse'1$sel:labelingJobName:DescribeLabelingJobResponse'0$sel:labelingJobArn:DescribeLabelingJobResponse'-$sel:inputConfig:DescribeLabelingJobResponse'.$sel:outputConfig:DescribeLabelingJobResponse')$sel:roleArn:DescribeLabelingJobResponse'1$sel:humanTaskConfig:DescribeLabelingJobResponse'DescribeLabelingJobDescribeLabelingJob')$sel:labelingJobName:DescribeLabelingJob'newDescribeLabelingJob#describeLabelingJob_labelingJobNamenewDescribeLabelingJobResponse)describeLabelingJobResponse_failureReason.describeLabelingJobResponse_labelAttributeName4describeLabelingJobResponse_labelCategoryConfigS3Uri7describeLabelingJobResponse_labelingJobAlgorithmsConfig-describeLabelingJobResponse_labelingJobOutput.describeLabelingJobResponse_stoppingConditions describeLabelingJobResponse_tags&describeLabelingJobResponse_httpStatus-describeLabelingJobResponse_labelingJobStatus)describeLabelingJobResponse_labelCounters(describeLabelingJobResponse_creationTime,describeLabelingJobResponse_lastModifiedTime,describeLabelingJobResponse_jobReferenceCode+describeLabelingJobResponse_labelingJobName*describeLabelingJobResponse_labelingJobArn'describeLabelingJobResponse_inputConfig(describeLabelingJobResponse_outputConfig#describeLabelingJobResponse_roleArn+describeLabelingJobResponse_humanTaskConfig$fToQueryDescribeLabelingJob$fToPathDescribeLabelingJob$fToJSONDescribeLabelingJob$fToHeadersDescribeLabelingJob$fNFDataDescribeLabelingJob$fHashableDescribeLabelingJob#$fNFDataDescribeLabelingJobResponse$fAWSRequestDescribeLabelingJob$fEqDescribeLabelingJobResponse!$fReadDescribeLabelingJobResponse!$fShowDescribeLabelingJobResponse$$fGenericDescribeLabelingJobResponse$fEqDescribeLabelingJob$fReadDescribeLabelingJob$fShowDescribeLabelingJob$fGenericDescribeLabelingJob+DescribeInferenceRecommendationsJobResponse,DescribeInferenceRecommendationsJobResponse'$sel:completionTime:DescribeInferenceRecommendationsJobResponse'$sel:endpointPerformances:DescribeInferenceRecommendationsJobResponse'?$sel:failureReason:DescribeInferenceRecommendationsJobResponse'$sel:inferenceRecommendations:DescribeInferenceRecommendationsJobResponse'$sel:jobDescription:DescribeInferenceRecommendationsJobResponse'$sel:stoppingConditions:DescribeInferenceRecommendationsJobResponse'<$sel:httpStatus:DescribeInferenceRecommendationsJobResponse'9$sel:jobName:DescribeInferenceRecommendationsJobResponse'9$sel:jobType:DescribeInferenceRecommendationsJobResponse'8$sel:jobArn:DescribeInferenceRecommendationsJobResponse'9$sel:roleArn:DescribeInferenceRecommendationsJobResponse'8$sel:status:DescribeInferenceRecommendationsJobResponse'>$sel:creationTime:DescribeInferenceRecommendationsJobResponse'$sel:lastModifiedTime:DescribeInferenceRecommendationsJobResponse'=$sel:inputConfig:DescribeInferenceRecommendationsJobResponse'#DescribeInferenceRecommendationsJob$DescribeInferenceRecommendationsJob'1$sel:jobName:DescribeInferenceRecommendationsJob'&newDescribeInferenceRecommendationsJob+describeInferenceRecommendationsJob_jobName.newDescribeInferenceRecommendationsJobResponse:describeInferenceRecommendationsJobResponse_completionTimedescribeInferenceRecommendationsJobResponse_endpointPerformances9describeInferenceRecommendationsJobResponse_failureReasondescribeInferenceRecommendationsJobResponse_inferenceRecommendations:describeInferenceRecommendationsJobResponse_jobDescription>describeInferenceRecommendationsJobResponse_stoppingConditions6describeInferenceRecommendationsJobResponse_httpStatus3describeInferenceRecommendationsJobResponse_jobName3describeInferenceRecommendationsJobResponse_jobType2describeInferenceRecommendationsJobResponse_jobArn3describeInferenceRecommendationsJobResponse_roleArn2describeInferenceRecommendationsJobResponse_status8describeInferenceRecommendationsJobResponse_creationTime$sel:lastModifiedTime:DescribeHyperParameterTuningJobResponse'$sel:overallBestTrainingJob:DescribeHyperParameterTuningJobResponse'$sel:trainingJobDefinition:DescribeHyperParameterTuningJobResponse'$sel:trainingJobDefinitions:DescribeHyperParameterTuningJobResponse'=$sel:warmStartConfig:DescribeHyperParameterTuningJobResponse'8$sel:httpStatus:DescribeHyperParameterTuningJobResponse'$sel:hyperParameterTuningJobName:DescribeHyperParameterTuningJobResponse'$sel:hyperParameterTuningJobArn:DescribeHyperParameterTuningJobResponse'$sel:hyperParameterTuningJobConfig:DescribeHyperParameterTuningJobResponse'$sel:hyperParameterTuningJobStatus:DescribeHyperParameterTuningJobResponse':$sel:creationTime:DescribeHyperParameterTuningJobResponse'$sel:trainingJobStatusCounters:DescribeHyperParameterTuningJobResponse'$sel:objectiveStatusCounters:DescribeHyperParameterTuningJobResponse'DescribeHyperParameterTuningJob DescribeHyperParameterTuningJob'$sel:hyperParameterTuningJobName:DescribeHyperParameterTuningJob'"newDescribeHyperParameterTuningJob;describeHyperParameterTuningJob_hyperParameterTuningJobName*newDescribeHyperParameterTuningJobResponse7describeHyperParameterTuningJobResponse_bestTrainingJob5describeHyperParameterTuningJobResponse_failureReasondescribeHyperParameterTuningJobResponse_hyperParameterTuningEndTime8describeHyperParameterTuningJobResponse_lastModifiedTime>describeHyperParameterTuningJobResponse_overallBestTrainingJob=describeHyperParameterTuningJobResponse_trainingJobDefinition>describeHyperParameterTuningJobResponse_trainingJobDefinitions7describeHyperParameterTuningJobResponse_warmStartConfig2describeHyperParameterTuningJobResponse_httpStatusdescribeHyperParameterTuningJobResponse_hyperParameterTuningJobNamedescribeHyperParameterTuningJobResponse_hyperParameterTuningJobArndescribeHyperParameterTuningJobResponse_hyperParameterTuningJobConfigdescribeHyperParameterTuningJobResponse_hyperParameterTuningJobStatus4describeHyperParameterTuningJobResponse_creationTimedescribeHyperParameterTuningJobResponse_trainingJobStatusCounters?describeHyperParameterTuningJobResponse_objectiveStatusCounters($fToQueryDescribeHyperParameterTuningJob'$fToPathDescribeHyperParameterTuningJob'$fToJSONDescribeHyperParameterTuningJob*$fToHeadersDescribeHyperParameterTuningJob'$fNFDataDescribeHyperParameterTuningJob)$fHashableDescribeHyperParameterTuningJob/$fNFDataDescribeHyperParameterTuningJobResponse+$fAWSRequestDescribeHyperParameterTuningJob+$fEqDescribeHyperParameterTuningJobResponse-$fReadDescribeHyperParameterTuningJobResponse-$fShowDescribeHyperParameterTuningJobResponse0$fGenericDescribeHyperParameterTuningJobResponse#$fEqDescribeHyperParameterTuningJob%$fReadDescribeHyperParameterTuningJob%$fShowDescribeHyperParameterTuningJob($fGenericDescribeHyperParameterTuningJobDescribeHumanTaskUiResponseDescribeHumanTaskUiResponse'3$sel:humanTaskUiStatus:DescribeHumanTaskUiResponse',$sel:httpStatus:DescribeHumanTaskUiResponse'0$sel:humanTaskUiArn:DescribeHumanTaskUiResponse'1$sel:humanTaskUiName:DescribeHumanTaskUiResponse'.$sel:creationTime:DescribeHumanTaskUiResponse',$sel:uiTemplate:DescribeHumanTaskUiResponse'DescribeHumanTaskUiDescribeHumanTaskUi')$sel:humanTaskUiName:DescribeHumanTaskUi'newDescribeHumanTaskUi#describeHumanTaskUi_humanTaskUiNamenewDescribeHumanTaskUiResponse-describeHumanTaskUiResponse_humanTaskUiStatus&describeHumanTaskUiResponse_httpStatus*describeHumanTaskUiResponse_humanTaskUiArn+describeHumanTaskUiResponse_humanTaskUiName(describeHumanTaskUiResponse_creationTime&describeHumanTaskUiResponse_uiTemplate$fToQueryDescribeHumanTaskUi$fToPathDescribeHumanTaskUi$fToJSONDescribeHumanTaskUi$fToHeadersDescribeHumanTaskUi$fNFDataDescribeHumanTaskUi$fHashableDescribeHumanTaskUi#$fNFDataDescribeHumanTaskUiResponse$fAWSRequestDescribeHumanTaskUi$fEqDescribeHumanTaskUiResponse!$fReadDescribeHumanTaskUiResponse!$fShowDescribeHumanTaskUiResponse$$fGenericDescribeHumanTaskUiResponse$fEqDescribeHumanTaskUi$fReadDescribeHumanTaskUi$fShowDescribeHumanTaskUi$fGenericDescribeHumanTaskUiDescribeHubContentResponseDescribeHubContentResponse'.$sel:failureReason:DescribeHubContentResponse'7$sel:hubContentDependencies:DescribeHubContentResponse'6$sel:hubContentDescription:DescribeHubContentResponse'6$sel:hubContentDisplayName:DescribeHubContentResponse'3$sel:hubContentMarkdown:DescribeHubContentResponse'9$sel:hubContentSearchKeywords:DescribeHubContentResponse'+$sel:httpStatus:DescribeHubContentResponse'/$sel:hubContentName:DescribeHubContentResponse'.$sel:hubContentArn:DescribeHubContentResponse'2$sel:hubContentVersion:DescribeHubContentResponse'/$sel:hubContentType:DescribeHubContentResponse'6$sel:documentSchemaVersion:DescribeHubContentResponse'($sel:hubName:DescribeHubContentResponse''$sel:hubArn:DescribeHubContentResponse'3$sel:hubContentDocument:DescribeHubContentResponse'1$sel:hubContentStatus:DescribeHubContentResponse'-$sel:creationTime:DescribeHubContentResponse'DescribeHubContentDescribeHubContent'*$sel:hubContentVersion:DescribeHubContent' $sel:hubName:DescribeHubContent''$sel:hubContentType:DescribeHubContent''$sel:hubContentName:DescribeHubContent'newDescribeHubContent$describeHubContent_hubContentVersiondescribeHubContent_hubName!describeHubContent_hubContentType!describeHubContent_hubContentNamenewDescribeHubContentResponse(describeHubContentResponse_failureReason1describeHubContentResponse_hubContentDependencies0describeHubContentResponse_hubContentDescription0describeHubContentResponse_hubContentDisplayName-describeHubContentResponse_hubContentMarkdown3describeHubContentResponse_hubContentSearchKeywords%describeHubContentResponse_httpStatus)describeHubContentResponse_hubContentName(describeHubContentResponse_hubContentArn,describeHubContentResponse_hubContentVersion)describeHubContentResponse_hubContentType0describeHubContentResponse_documentSchemaVersion"describeHubContentResponse_hubName!describeHubContentResponse_hubArn-describeHubContentResponse_hubContentDocument+describeHubContentResponse_hubContentStatus'describeHubContentResponse_creationTime$fToQueryDescribeHubContent$fToPathDescribeHubContent$fToJSONDescribeHubContent$fToHeadersDescribeHubContent$fNFDataDescribeHubContent$fHashableDescribeHubContent"$fNFDataDescribeHubContentResponse$fAWSRequestDescribeHubContent$fEqDescribeHubContentResponse $fReadDescribeHubContentResponse $fShowDescribeHubContentResponse#$fGenericDescribeHubContentResponse$fEqDescribeHubContent$fReadDescribeHubContent$fShowDescribeHubContent$fGenericDescribeHubContentDescribeHubResponseDescribeHubResponse''$sel:failureReason:DescribeHubResponse'($sel:hubDescription:DescribeHubResponse'($sel:hubDisplayName:DescribeHubResponse'+$sel:hubSearchKeywords:DescribeHubResponse')$sel:s3StorageConfig:DescribeHubResponse'$$sel:httpStatus:DescribeHubResponse'!$sel:hubName:DescribeHubResponse' $sel:hubArn:DescribeHubResponse'#$sel:hubStatus:DescribeHubResponse'&$sel:creationTime:DescribeHubResponse'*$sel:lastModifiedTime:DescribeHubResponse' DescribeHub DescribeHub'$sel:hubName:DescribeHub'newDescribeHubdescribeHub_hubNamenewDescribeHubResponse!describeHubResponse_failureReason"describeHubResponse_hubDescription"describeHubResponse_hubDisplayName%describeHubResponse_hubSearchKeywords#describeHubResponse_s3StorageConfigdescribeHubResponse_httpStatusdescribeHubResponse_hubNamedescribeHubResponse_hubArndescribeHubResponse_hubStatus describeHubResponse_creationTime$describeHubResponse_lastModifiedTime$fToQueryDescribeHub$fToPathDescribeHub$fToJSONDescribeHub$fToHeadersDescribeHub$fNFDataDescribeHub$fHashableDescribeHub$fNFDataDescribeHubResponse$fAWSRequestDescribeHub$fEqDescribeHubResponse$fReadDescribeHubResponse$fShowDescribeHubResponse$fGenericDescribeHubResponse$fEqDescribeHub$fReadDescribeHub$fShowDescribeHub$fGenericDescribeHubDescribeFlowDefinitionResponseDescribeFlowDefinitionResponse'2$sel:failureReason:DescribeFlowDefinitionResponse'>$sel:humanLoopActivationConfig:DescribeFlowDefinitionResponse';$sel:humanLoopRequestSource:DescribeFlowDefinitionResponse'/$sel:httpStatus:DescribeFlowDefinitionResponse'6$sel:flowDefinitionArn:DescribeFlowDefinitionResponse'7$sel:flowDefinitionName:DescribeFlowDefinitionResponse'9$sel:flowDefinitionStatus:DescribeFlowDefinitionResponse'1$sel:creationTime:DescribeFlowDefinitionResponse'4$sel:humanLoopConfig:DescribeFlowDefinitionResponse'1$sel:outputConfig:DescribeFlowDefinitionResponse',$sel:roleArn:DescribeFlowDefinitionResponse'DescribeFlowDefinitionDescribeFlowDefinition'/$sel:flowDefinitionName:DescribeFlowDefinition'newDescribeFlowDefinition)describeFlowDefinition_flowDefinitionName!newDescribeFlowDefinitionResponse,describeFlowDefinitionResponse_failureReason8describeFlowDefinitionResponse_humanLoopActivationConfig5describeFlowDefinitionResponse_humanLoopRequestSource)describeFlowDefinitionResponse_httpStatus0describeFlowDefinitionResponse_flowDefinitionArn1describeFlowDefinitionResponse_flowDefinitionName3describeFlowDefinitionResponse_flowDefinitionStatus+describeFlowDefinitionResponse_creationTime.describeFlowDefinitionResponse_humanLoopConfig+describeFlowDefinitionResponse_outputConfig&describeFlowDefinitionResponse_roleArn$fToQueryDescribeFlowDefinition$fToPathDescribeFlowDefinition$fToJSONDescribeFlowDefinition!$fToHeadersDescribeFlowDefinition$fNFDataDescribeFlowDefinition $fHashableDescribeFlowDefinition&$fNFDataDescribeFlowDefinitionResponse"$fAWSRequestDescribeFlowDefinition"$fEqDescribeFlowDefinitionResponse$$fReadDescribeFlowDefinitionResponse$$fShowDescribeFlowDefinitionResponse'$fGenericDescribeFlowDefinitionResponse$fEqDescribeFlowDefinition$fReadDescribeFlowDefinition$fShowDescribeFlowDefinition$fGenericDescribeFlowDefinitionDescribeFeatureMetadataResponse DescribeFeatureMetadataResponse'1$sel:description:DescribeFeatureMetadataResponse'0$sel:parameters:DescribeFeatureMetadataResponse'0$sel:httpStatus:DescribeFeatureMetadataResponse'5$sel:featureGroupArn:DescribeFeatureMetadataResponse'6$sel:featureGroupName:DescribeFeatureMetadataResponse'1$sel:featureName:DescribeFeatureMetadataResponse'1$sel:featureType:DescribeFeatureMetadataResponse'2$sel:creationTime:DescribeFeatureMetadataResponse'6$sel:lastModifiedTime:DescribeFeatureMetadataResponse'DescribeFeatureMetadataDescribeFeatureMetadata'.$sel:featureGroupName:DescribeFeatureMetadata')$sel:featureName:DescribeFeatureMetadata'newDescribeFeatureMetadata(describeFeatureMetadata_featureGroupName#describeFeatureMetadata_featureName"newDescribeFeatureMetadataResponse+describeFeatureMetadataResponse_description*describeFeatureMetadataResponse_parameters*describeFeatureMetadataResponse_httpStatus/describeFeatureMetadataResponse_featureGroupArn0describeFeatureMetadataResponse_featureGroupName+describeFeatureMetadataResponse_featureName+describeFeatureMetadataResponse_featureType,describeFeatureMetadataResponse_creationTime0describeFeatureMetadataResponse_lastModifiedTime $fToQueryDescribeFeatureMetadata$fToPathDescribeFeatureMetadata$fToJSONDescribeFeatureMetadata"$fToHeadersDescribeFeatureMetadata$fNFDataDescribeFeatureMetadata!$fHashableDescribeFeatureMetadata'$fNFDataDescribeFeatureMetadataResponse#$fAWSRequestDescribeFeatureMetadata#$fEqDescribeFeatureMetadataResponse%$fReadDescribeFeatureMetadataResponse%$fShowDescribeFeatureMetadataResponse($fGenericDescribeFeatureMetadataResponse$fEqDescribeFeatureMetadata$fReadDescribeFeatureMetadata$fShowDescribeFeatureMetadata $fGenericDescribeFeatureMetadataDescribeFeatureGroupResponseDescribeFeatureGroupResponse'.$sel:description:DescribeFeatureGroupResponse'0$sel:failureReason:DescribeFeatureGroupResponse'5$sel:featureGroupStatus:DescribeFeatureGroupResponse'3$sel:lastModifiedTime:DescribeFeatureGroupResponse'3$sel:lastUpdateStatus:DescribeFeatureGroupResponse'5$sel:offlineStoreConfig:DescribeFeatureGroupResponse'5$sel:offlineStoreStatus:DescribeFeatureGroupResponse'4$sel:onlineStoreConfig:DescribeFeatureGroupResponse'<$sel:onlineStoreTotalSizeBytes:DescribeFeatureGroupResponse'*$sel:roleArn:DescribeFeatureGroupResponse'-$sel:httpStatus:DescribeFeatureGroupResponse'2$sel:featureGroupArn:DescribeFeatureGroupResponse'3$sel:featureGroupName:DescribeFeatureGroupResponse'>$sel:recordIdentifierFeatureName:DescribeFeatureGroupResponse'7$sel:eventTimeFeatureName:DescribeFeatureGroupResponse'5$sel:featureDefinitions:DescribeFeatureGroupResponse'/$sel:creationTime:DescribeFeatureGroupResponse',$sel:nextToken:DescribeFeatureGroupResponse'DescribeFeatureGroupDescribeFeatureGroup'$$sel:nextToken:DescribeFeatureGroup'+$sel:featureGroupName:DescribeFeatureGroup'newDescribeFeatureGroupdescribeFeatureGroup_nextToken%describeFeatureGroup_featureGroupNamenewDescribeFeatureGroupResponse(describeFeatureGroupResponse_description*describeFeatureGroupResponse_failureReason/describeFeatureGroupResponse_featureGroupStatus-describeFeatureGroupResponse_lastModifiedTime-describeFeatureGroupResponse_lastUpdateStatus/describeFeatureGroupResponse_offlineStoreConfig/describeFeatureGroupResponse_offlineStoreStatus.describeFeatureGroupResponse_onlineStoreConfig6describeFeatureGroupResponse_onlineStoreTotalSizeBytes$describeFeatureGroupResponse_roleArn'describeFeatureGroupResponse_httpStatus,describeFeatureGroupResponse_featureGroupArn-describeFeatureGroupResponse_featureGroupName8describeFeatureGroupResponse_recordIdentifierFeatureName1describeFeatureGroupResponse_eventTimeFeatureName/describeFeatureGroupResponse_featureDefinitions)describeFeatureGroupResponse_creationTime&describeFeatureGroupResponse_nextToken$fToQueryDescribeFeatureGroup$fToPathDescribeFeatureGroup$fToJSONDescribeFeatureGroup$fToHeadersDescribeFeatureGroup$fNFDataDescribeFeatureGroup$fHashableDescribeFeatureGroup$$fNFDataDescribeFeatureGroupResponse $fAWSRequestDescribeFeatureGroup $fEqDescribeFeatureGroupResponse"$fReadDescribeFeatureGroupResponse"$fShowDescribeFeatureGroupResponse%$fGenericDescribeFeatureGroupResponse$fEqDescribeFeatureGroup$fReadDescribeFeatureGroup$fShowDescribeFeatureGroup$fGenericDescribeFeatureGroupDescribeExperimentResponseDescribeExperimentResponse'*$sel:createdBy:DescribeExperimentResponse'-$sel:creationTime:DescribeExperimentResponse',$sel:description:DescribeExperimentResponse',$sel:displayName:DescribeExperimentResponse'.$sel:experimentArn:DescribeExperimentResponse'/$sel:experimentName:DescribeExperimentResponse'/$sel:lastModifiedBy:DescribeExperimentResponse'1$sel:lastModifiedTime:DescribeExperimentResponse''$sel:source:DescribeExperimentResponse'+$sel:httpStatus:DescribeExperimentResponse'DescribeExperimentDescribeExperiment''$sel:experimentName:DescribeExperiment'newDescribeExperiment!describeExperiment_experimentNamenewDescribeExperimentResponse$describeExperimentResponse_createdBy'describeExperimentResponse_creationTime&describeExperimentResponse_description&describeExperimentResponse_displayName(describeExperimentResponse_experimentArn)describeExperimentResponse_experimentName)describeExperimentResponse_lastModifiedBy+describeExperimentResponse_lastModifiedTime!describeExperimentResponse_source%describeExperimentResponse_httpStatus$fToQueryDescribeExperiment$fToPathDescribeExperiment$fToJSONDescribeExperiment$fToHeadersDescribeExperiment$fNFDataDescribeExperiment$fHashableDescribeExperiment"$fNFDataDescribeExperimentResponse$fAWSRequestDescribeExperiment$fEqDescribeExperimentResponse $fReadDescribeExperimentResponse $fShowDescribeExperimentResponse#$fGenericDescribeExperimentResponse$fEqDescribeExperiment$fReadDescribeExperiment$fShowDescribeExperiment$fGenericDescribeExperimentDescribeEndpointConfigResponseDescribeEndpointConfigResponse'9$sel:asyncInferenceConfig:DescribeEndpointConfigResponse'6$sel:dataCaptureConfig:DescribeEndpointConfigResponse'4$sel:explainerConfig:DescribeEndpointConfigResponse'-$sel:kmsKeyId:DescribeEndpointConfigResponse'=$sel:shadowProductionVariants:DescribeEndpointConfigResponse'/$sel:httpStatus:DescribeEndpointConfigResponse'7$sel:endpointConfigName:DescribeEndpointConfigResponse'6$sel:endpointConfigArn:DescribeEndpointConfigResponse'7$sel:productionVariants:DescribeEndpointConfigResponse'1$sel:creationTime:DescribeEndpointConfigResponse'DescribeEndpointConfigDescribeEndpointConfig'/$sel:endpointConfigName:DescribeEndpointConfig'newDescribeEndpointConfig)describeEndpointConfig_endpointConfigName!newDescribeEndpointConfigResponse3describeEndpointConfigResponse_asyncInferenceConfig0describeEndpointConfigResponse_dataCaptureConfig.describeEndpointConfigResponse_explainerConfig'describeEndpointConfigResponse_kmsKeyId7describeEndpointConfigResponse_shadowProductionVariants)describeEndpointConfigResponse_httpStatus1describeEndpointConfigResponse_endpointConfigName0describeEndpointConfigResponse_endpointConfigArn1describeEndpointConfigResponse_productionVariants+describeEndpointConfigResponse_creationTime$fToQueryDescribeEndpointConfig$fToPathDescribeEndpointConfig$fToJSONDescribeEndpointConfig!$fToHeadersDescribeEndpointConfig$fNFDataDescribeEndpointConfig $fHashableDescribeEndpointConfig&$fNFDataDescribeEndpointConfigResponse"$fAWSRequestDescribeEndpointConfig"$fEqDescribeEndpointConfigResponse$$fReadDescribeEndpointConfigResponse$$fShowDescribeEndpointConfigResponse'$fGenericDescribeEndpointConfigResponse$fEqDescribeEndpointConfig$fReadDescribeEndpointConfig$fShowDescribeEndpointConfig$fGenericDescribeEndpointConfigDescribeEndpointResponseDescribeEndpointResponse'3$sel:asyncInferenceConfig:DescribeEndpointResponse'0$sel:dataCaptureConfig:DescribeEndpointResponse'.$sel:explainerConfig:DescribeEndpointResponse',$sel:failureReason:DescribeEndpointResponse'3$sel:lastDeploymentConfig:DescribeEndpointResponse'7$sel:pendingDeploymentSummary:DescribeEndpointResponse'1$sel:productionVariants:DescribeEndpointResponse'7$sel:shadowProductionVariants:DescribeEndpointResponse')$sel:httpStatus:DescribeEndpointResponse'+$sel:endpointName:DescribeEndpointResponse'*$sel:endpointArn:DescribeEndpointResponse'1$sel:endpointConfigName:DescribeEndpointResponse'-$sel:endpointStatus:DescribeEndpointResponse'+$sel:creationTime:DescribeEndpointResponse'/$sel:lastModifiedTime:DescribeEndpointResponse'DescribeEndpoint'#$sel:endpointName:DescribeEndpoint'newDescribeEndpointdescribeEndpoint_endpointNamenewDescribeEndpointResponse-describeEndpointResponse_asyncInferenceConfig*describeEndpointResponse_dataCaptureConfig(describeEndpointResponse_explainerConfig&describeEndpointResponse_failureReason-describeEndpointResponse_lastDeploymentConfig1describeEndpointResponse_pendingDeploymentSummary+describeEndpointResponse_productionVariants1describeEndpointResponse_shadowProductionVariants#describeEndpointResponse_httpStatus%describeEndpointResponse_endpointName$describeEndpointResponse_endpointArn+describeEndpointResponse_endpointConfigName'describeEndpointResponse_endpointStatus%describeEndpointResponse_creationTime)describeEndpointResponse_lastModifiedTime$fToQueryDescribeEndpoint$fToPathDescribeEndpoint$fToJSONDescribeEndpoint$fToHeadersDescribeEndpoint$fNFDataDescribeEndpoint$fHashableDescribeEndpoint $fNFDataDescribeEndpointResponse$fAWSRequestDescribeEndpoint$fEqDescribeEndpointResponse$fReadDescribeEndpointResponse$fShowDescribeEndpointResponse!$fGenericDescribeEndpointResponse$fEqDescribeEndpoint$fReadDescribeEndpoint$fShowDescribeEndpoint$fGenericDescribeEndpoint DescribeEdgePackagingJobResponse!DescribeEdgePackagingJobResponse'9$sel:compilationJobName:DescribeEdgePackagingJobResponse'3$sel:creationTime:DescribeEdgePackagingJobResponse'$sel:edgePackagingJobStatusMessage:DescribeEdgePackagingJobResponse'7$sel:lastModifiedTime:DescribeEdgePackagingJobResponse'4$sel:modelArtifact:DescribeEdgePackagingJobResponse'0$sel:modelName:DescribeEdgePackagingJobResponse'5$sel:modelSignature:DescribeEdgePackagingJobResponse'3$sel:modelVersion:DescribeEdgePackagingJobResponse'3$sel:outputConfig:DescribeEdgePackagingJobResponse'=$sel:presetDeploymentOutput:DescribeEdgePackagingJobResponse'2$sel:resourceKey:DescribeEdgePackagingJobResponse'.$sel:roleArn:DescribeEdgePackagingJobResponse'1$sel:httpStatus:DescribeEdgePackagingJobResponse':$sel:edgePackagingJobArn:DescribeEdgePackagingJobResponse';$sel:edgePackagingJobName:DescribeEdgePackagingJobResponse'=$sel:edgePackagingJobStatus:DescribeEdgePackagingJobResponse'DescribeEdgePackagingJobDescribeEdgePackagingJob'3$sel:edgePackagingJobName:DescribeEdgePackagingJob'newDescribeEdgePackagingJob-describeEdgePackagingJob_edgePackagingJobName#newDescribeEdgePackagingJobResponse3describeEdgePackagingJobResponse_compilationJobName-describeEdgePackagingJobResponse_creationTime>describeEdgePackagingJobResponse_edgePackagingJobStatusMessage1describeEdgePackagingJobResponse_lastModifiedTime.describeEdgePackagingJobResponse_modelArtifact*describeEdgePackagingJobResponse_modelName/describeEdgePackagingJobResponse_modelSignature-describeEdgePackagingJobResponse_modelVersion-describeEdgePackagingJobResponse_outputConfig7describeEdgePackagingJobResponse_presetDeploymentOutput,describeEdgePackagingJobResponse_resourceKey(describeEdgePackagingJobResponse_roleArn+describeEdgePackagingJobResponse_httpStatus4describeEdgePackagingJobResponse_edgePackagingJobArn5describeEdgePackagingJobResponse_edgePackagingJobName7describeEdgePackagingJobResponse_edgePackagingJobStatus!$fToQueryDescribeEdgePackagingJob $fToPathDescribeEdgePackagingJob $fToJSONDescribeEdgePackagingJob#$fToHeadersDescribeEdgePackagingJob $fNFDataDescribeEdgePackagingJob"$fHashableDescribeEdgePackagingJob($fNFDataDescribeEdgePackagingJobResponse$$fAWSRequestDescribeEdgePackagingJob$$fEqDescribeEdgePackagingJobResponse&$fReadDescribeEdgePackagingJobResponse&$fShowDescribeEdgePackagingJobResponse)$fGenericDescribeEdgePackagingJobResponse$fEqDescribeEdgePackagingJob$fReadDescribeEdgePackagingJob$fShowDescribeEdgePackagingJob!$fGenericDescribeEdgePackagingJob"DescribeEdgeDeploymentPlanResponse#DescribeEdgeDeploymentPlanResponse'5$sel:creationTime:DescribeEdgeDeploymentPlanResponse'=$sel:edgeDeploymentFailed:DescribeEdgeDeploymentPlanResponse'>$sel:edgeDeploymentPending:DescribeEdgeDeploymentPlanResponse'>$sel:edgeDeploymentSuccess:DescribeEdgeDeploymentPlanResponse'9$sel:lastModifiedTime:DescribeEdgeDeploymentPlanResponse'2$sel:nextToken:DescribeEdgeDeploymentPlanResponse'3$sel:httpStatus:DescribeEdgeDeploymentPlanResponse'>$sel:edgeDeploymentPlanArn:DescribeEdgeDeploymentPlanResponse'?$sel:edgeDeploymentPlanName:DescribeEdgeDeploymentPlanResponse'5$sel:modelConfigs:DescribeEdgeDeploymentPlanResponse'8$sel:deviceFleetName:DescribeEdgeDeploymentPlanResponse'/$sel:stages:DescribeEdgeDeploymentPlanResponse'DescribeEdgeDeploymentPlanDescribeEdgeDeploymentPlan'+$sel:maxResults:DescribeEdgeDeploymentPlan'*$sel:nextToken:DescribeEdgeDeploymentPlan'7$sel:edgeDeploymentPlanName:DescribeEdgeDeploymentPlan'newDescribeEdgeDeploymentPlan%describeEdgeDeploymentPlan_maxResults$describeEdgeDeploymentPlan_nextToken1describeEdgeDeploymentPlan_edgeDeploymentPlanName%newDescribeEdgeDeploymentPlanResponse/describeEdgeDeploymentPlanResponse_creationTime7describeEdgeDeploymentPlanResponse_edgeDeploymentFailed8describeEdgeDeploymentPlanResponse_edgeDeploymentPending8describeEdgeDeploymentPlanResponse_edgeDeploymentSuccess3describeEdgeDeploymentPlanResponse_lastModifiedTime,describeEdgeDeploymentPlanResponse_nextToken-describeEdgeDeploymentPlanResponse_httpStatus8describeEdgeDeploymentPlanResponse_edgeDeploymentPlanArn9describeEdgeDeploymentPlanResponse_edgeDeploymentPlanName/describeEdgeDeploymentPlanResponse_modelConfigs2describeEdgeDeploymentPlanResponse_deviceFleetName)describeEdgeDeploymentPlanResponse_stages#$fToQueryDescribeEdgeDeploymentPlan"$fToPathDescribeEdgeDeploymentPlan"$fToJSONDescribeEdgeDeploymentPlan%$fToHeadersDescribeEdgeDeploymentPlan"$fNFDataDescribeEdgeDeploymentPlan$$fHashableDescribeEdgeDeploymentPlan*$fNFDataDescribeEdgeDeploymentPlanResponse&$fAWSRequestDescribeEdgeDeploymentPlan&$fEqDescribeEdgeDeploymentPlanResponse($fReadDescribeEdgeDeploymentPlanResponse($fShowDescribeEdgeDeploymentPlanResponse+$fGenericDescribeEdgeDeploymentPlanResponse$fEqDescribeEdgeDeploymentPlan $fReadDescribeEdgeDeploymentPlan $fShowDescribeEdgeDeploymentPlan#$fGenericDescribeEdgeDeploymentPlanDescribeDomainResponseDescribeDomainResponse'1$sel:appNetworkAccessType:DescribeDomainResponse'7$sel:appSecurityGroupManagement:DescribeDomainResponse'%$sel:authMode:DescribeDomainResponse')$sel:creationTime:DescribeDomainResponse'1$sel:defaultSpaceSettings:DescribeDomainResponse'0$sel:defaultUserSettings:DescribeDomainResponse'&$sel:domainArn:DescribeDomainResponse'%$sel:domainId:DescribeDomainResponse''$sel:domainName:DescribeDomainResponse'+$sel:domainSettings:DescribeDomainResponse'*$sel:failureReason:DescribeDomainResponse'0$sel:homeEfsFileSystemId:DescribeDomainResponse'6$sel:homeEfsFileSystemKmsKeyId:DescribeDomainResponse'%$sel:kmsKeyId:DescribeDomainResponse'-$sel:lastModifiedTime:DescribeDomainResponse'=$sel:securityGroupIdForDomainBoundary:DescribeDomainResponse'$sel:singleSignOnManagedApplicationInstanceId:DescribeDomainResponse'#$sel:status:DescribeDomainResponse'&$sel:subnetIds:DescribeDomainResponse' $sel:url:DescribeDomainResponse'"$sel:vpcId:DescribeDomainResponse''$sel:httpStatus:DescribeDomainResponse'DescribeDomainDescribeDomain'$sel:domainId:DescribeDomain'newDescribeDomaindescribeDomain_domainIdnewDescribeDomainResponse+describeDomainResponse_appNetworkAccessType1describeDomainResponse_appSecurityGroupManagementdescribeDomainResponse_authMode#describeDomainResponse_creationTime+describeDomainResponse_defaultSpaceSettings*describeDomainResponse_defaultUserSettings describeDomainResponse_domainArndescribeDomainResponse_domainId!describeDomainResponse_domainName%describeDomainResponse_domainSettings$describeDomainResponse_failureReason*describeDomainResponse_homeEfsFileSystemId0describeDomainResponse_homeEfsFileSystemKmsKeyIddescribeDomainResponse_kmsKeyId'describeDomainResponse_lastModifiedTime7describeDomainResponse_securityGroupIdForDomainBoundary?describeDomainResponse_singleSignOnManagedApplicationInstanceIddescribeDomainResponse_status describeDomainResponse_subnetIdsdescribeDomainResponse_urldescribeDomainResponse_vpcId!describeDomainResponse_httpStatus$fToQueryDescribeDomain$fToPathDescribeDomain$fToJSONDescribeDomain$fToHeadersDescribeDomain$fNFDataDescribeDomain$fHashableDescribeDomain$fNFDataDescribeDomainResponse$fAWSRequestDescribeDomain$fEqDescribeDomainResponse$fReadDescribeDomainResponse$fShowDescribeDomainResponse$fGenericDescribeDomainResponse$fEqDescribeDomain$fReadDescribeDomain$fShowDescribeDomain$fGenericDescribeDomainDescribeDeviceFleetResponseDescribeDeviceFleetResponse'-$sel:description:DescribeDeviceFleetResponse'.$sel:iotRoleAlias:DescribeDeviceFleetResponse')$sel:roleArn:DescribeDeviceFleetResponse',$sel:httpStatus:DescribeDeviceFleetResponse'1$sel:deviceFleetName:DescribeDeviceFleetResponse'0$sel:deviceFleetArn:DescribeDeviceFleetResponse'.$sel:outputConfig:DescribeDeviceFleetResponse'.$sel:creationTime:DescribeDeviceFleetResponse'2$sel:lastModifiedTime:DescribeDeviceFleetResponse'DescribeDeviceFleetDescribeDeviceFleet')$sel:deviceFleetName:DescribeDeviceFleet'newDescribeDeviceFleet#describeDeviceFleet_deviceFleetNamenewDescribeDeviceFleetResponse'describeDeviceFleetResponse_description(describeDeviceFleetResponse_iotRoleAlias#describeDeviceFleetResponse_roleArn&describeDeviceFleetResponse_httpStatus+describeDeviceFleetResponse_deviceFleetName*describeDeviceFleetResponse_deviceFleetArn(describeDeviceFleetResponse_outputConfig(describeDeviceFleetResponse_creationTime,describeDeviceFleetResponse_lastModifiedTime$fToQueryDescribeDeviceFleet$fToPathDescribeDeviceFleet$fToJSONDescribeDeviceFleet$fToHeadersDescribeDeviceFleet$fNFDataDescribeDeviceFleet$fHashableDescribeDeviceFleet#$fNFDataDescribeDeviceFleetResponse$fAWSRequestDescribeDeviceFleet$fEqDescribeDeviceFleetResponse!$fReadDescribeDeviceFleetResponse!$fShowDescribeDeviceFleetResponse$$fGenericDescribeDeviceFleetResponse$fEqDescribeDeviceFleet$fReadDescribeDeviceFleet$fShowDescribeDeviceFleet$fGenericDescribeDeviceFleetDescribeDeviceResponseDescribeDeviceResponse')$sel:agentVersion:DescribeDeviceResponse'($sel:description:DescribeDeviceResponse'&$sel:deviceArn:DescribeDeviceResponse')$sel:iotThingName:DescribeDeviceResponse',$sel:latestHeartbeat:DescribeDeviceResponse'&$sel:maxModels:DescribeDeviceResponse'#$sel:models:DescribeDeviceResponse'&$sel:nextToken:DescribeDeviceResponse''$sel:httpStatus:DescribeDeviceResponse''$sel:deviceName:DescribeDeviceResponse',$sel:deviceFleetName:DescribeDeviceResponse'-$sel:registrationTime:DescribeDeviceResponse'DescribeDeviceDescribeDevice'$sel:nextToken:DescribeDevice'$sel:deviceName:DescribeDevice'$$sel:deviceFleetName:DescribeDevice'newDescribeDevicedescribeDevice_nextTokendescribeDevice_deviceNamedescribeDevice_deviceFleetNamenewDescribeDeviceResponse#describeDeviceResponse_agentVersion"describeDeviceResponse_description describeDeviceResponse_deviceArn#describeDeviceResponse_iotThingName&describeDeviceResponse_latestHeartbeat describeDeviceResponse_maxModelsdescribeDeviceResponse_models describeDeviceResponse_nextToken!describeDeviceResponse_httpStatus!describeDeviceResponse_deviceName&describeDeviceResponse_deviceFleetName'describeDeviceResponse_registrationTime$fToQueryDescribeDevice$fToPathDescribeDevice$fToJSONDescribeDevice$fToHeadersDescribeDevice$fNFDataDescribeDevice$fHashableDescribeDevice$fNFDataDescribeDeviceResponse$fAWSRequestDescribeDevice$fEqDescribeDeviceResponse$fReadDescribeDeviceResponse$fShowDescribeDeviceResponse$fGenericDescribeDeviceResponse$fEqDescribeDevice$fReadDescribeDevice$fShowDescribeDevice$fGenericDescribeDevice(DescribeDataQualityJobDefinitionResponse)DescribeDataQualityJobDefinitionResponse'$sel:dataQualityBaselineConfig:DescribeDataQualityJobDefinitionResponse'<$sel:networkConfig:DescribeDataQualityJobDefinitionResponse'$sel:stoppingCondition:DescribeDataQualityJobDefinitionResponse'9$sel:httpStatus:DescribeDataQualityJobDefinitionResponse'?$sel:jobDefinitionArn:DescribeDataQualityJobDefinitionResponse'$sel:jobDefinitionName:DescribeDataQualityJobDefinitionResponse';$sel:creationTime:DescribeDataQualityJobDefinitionResponse'$sel:dataQualityAppSpecification:DescribeDataQualityJobDefinitionResponse'$sel:dataQualityJobInput:DescribeDataQualityJobDefinitionResponse'$sel:dataQualityJobOutputConfig:DescribeDataQualityJobDefinitionResponse';$sel:jobResources:DescribeDataQualityJobDefinitionResponse'6$sel:roleArn:DescribeDataQualityJobDefinitionResponse' DescribeDataQualityJobDefinition!DescribeDataQualityJobDefinition'8$sel:jobDefinitionName:DescribeDataQualityJobDefinition'#newDescribeDataQualityJobDefinition2describeDataQualityJobDefinition_jobDefinitionName+newDescribeDataQualityJobDefinitionResponsedescribeDataQualityJobDefinitionResponse_dataQualityBaselineConfig6describeDataQualityJobDefinitionResponse_networkConfig:describeDataQualityJobDefinitionResponse_stoppingCondition3describeDataQualityJobDefinitionResponse_httpStatus9describeDataQualityJobDefinitionResponse_jobDefinitionArn:describeDataQualityJobDefinitionResponse_jobDefinitionName5describeDataQualityJobDefinitionResponse_creationTimedescribeDataQualityJobDefinitionResponse_dataQualityAppSpecification$sel:jobDefinitionName:DeleteModelExplainabilityJobDefinition')newDeleteModelExplainabilityJobDefinition8deleteModelExplainabilityJobDefinition_jobDefinitionName1newDeleteModelExplainabilityJobDefinitionResponse/$fToQueryDeleteModelExplainabilityJobDefinition.$fToPathDeleteModelExplainabilityJobDefinition.$fToJSONDeleteModelExplainabilityJobDefinition1$fToHeadersDeleteModelExplainabilityJobDefinition.$fNFDataDeleteModelExplainabilityJobDefinition0$fHashableDeleteModelExplainabilityJobDefinition6$fNFDataDeleteModelExplainabilityJobDefinitionResponse2$fAWSRequestDeleteModelExplainabilityJobDefinition2$fEqDeleteModelExplainabilityJobDefinitionResponse4$fReadDeleteModelExplainabilityJobDefinitionResponse4$fShowDeleteModelExplainabilityJobDefinitionResponse7$fGenericDeleteModelExplainabilityJobDefinitionResponse*$fEqDeleteModelExplainabilityJobDefinition,$fReadDeleteModelExplainabilityJobDefinition,$fShowDeleteModelExplainabilityJobDefinition/$fGenericDeleteModelExplainabilityJobDefinitionDeleteModelCardResponseDeleteModelCardResponse'DeleteModelCardDeleteModelCard'#$sel:modelCardName:DeleteModelCard'newDeleteModelCarddeleteModelCard_modelCardNamenewDeleteModelCardResponse$fToQueryDeleteModelCard$fToPathDeleteModelCard$fToJSONDeleteModelCard$fToHeadersDeleteModelCard$fNFDataDeleteModelCard$fHashableDeleteModelCard$fNFDataDeleteModelCardResponse$fAWSRequestDeleteModelCard$fEqDeleteModelCardResponse$fReadDeleteModelCardResponse$fShowDeleteModelCardResponse $fGenericDeleteModelCardResponse$fEqDeleteModelCard$fReadDeleteModelCard$fShowDeleteModelCard$fGenericDeleteModelCard$DeleteModelBiasJobDefinitionResponse%DeleteModelBiasJobDefinitionResponse'DeleteModelBiasJobDefinitionDeleteModelBiasJobDefinition'4$sel:jobDefinitionName:DeleteModelBiasJobDefinition'newDeleteModelBiasJobDefinition.deleteModelBiasJobDefinition_jobDefinitionName'newDeleteModelBiasJobDefinitionResponse%$fToQueryDeleteModelBiasJobDefinition$$fToPathDeleteModelBiasJobDefinition$$fToJSONDeleteModelBiasJobDefinition'$fToHeadersDeleteModelBiasJobDefinition$$fNFDataDeleteModelBiasJobDefinition&$fHashableDeleteModelBiasJobDefinition,$fNFDataDeleteModelBiasJobDefinitionResponse($fAWSRequestDeleteModelBiasJobDefinition($fEqDeleteModelBiasJobDefinitionResponse*$fReadDeleteModelBiasJobDefinitionResponse*$fShowDeleteModelBiasJobDefinitionResponse-$fGenericDeleteModelBiasJobDefinitionResponse $fEqDeleteModelBiasJobDefinition"$fReadDeleteModelBiasJobDefinition"$fShowDeleteModelBiasJobDefinition%$fGenericDeleteModelBiasJobDefinitionDeleteModelResponseDeleteModelResponse' DeleteModel DeleteModel'$sel:modelName:DeleteModel'newDeleteModeldeleteModel_modelNamenewDeleteModelResponse$fToQueryDeleteModel$fToPathDeleteModel$fToJSONDeleteModel$fToHeadersDeleteModel$fNFDataDeleteModel$fHashableDeleteModel$fNFDataDeleteModelResponse$fAWSRequestDeleteModel$fEqDeleteModelResponse$fReadDeleteModelResponse$fShowDeleteModelResponse$fGenericDeleteModelResponse$fEqDeleteModel$fReadDeleteModel$fShowDeleteModel$fGenericDeleteModel!DeleteInferenceExperimentResponse"DeleteInferenceExperimentResponse'2$sel:httpStatus:DeleteInferenceExperimentResponse'>$sel:inferenceExperimentArn:DeleteInferenceExperimentResponse'DeleteInferenceExperimentDeleteInferenceExperiment'$$sel:name:DeleteInferenceExperiment'newDeleteInferenceExperimentdeleteInferenceExperiment_name$newDeleteInferenceExperimentResponse,deleteInferenceExperimentResponse_httpStatus8deleteInferenceExperimentResponse_inferenceExperimentArn"$fToQueryDeleteInferenceExperiment!$fToPathDeleteInferenceExperiment!$fToJSONDeleteInferenceExperiment$$fToHeadersDeleteInferenceExperiment!$fNFDataDeleteInferenceExperiment#$fHashableDeleteInferenceExperiment)$fNFDataDeleteInferenceExperimentResponse%$fAWSRequestDeleteInferenceExperiment%$fEqDeleteInferenceExperimentResponse'$fReadDeleteInferenceExperimentResponse'$fShowDeleteInferenceExperimentResponse*$fGenericDeleteInferenceExperimentResponse$fEqDeleteInferenceExperiment$fReadDeleteInferenceExperiment$fShowDeleteInferenceExperiment"$fGenericDeleteInferenceExperimentDeleteImageVersionResponseDeleteImageVersionResponse'+$sel:httpStatus:DeleteImageVersionResponse'DeleteImageVersionDeleteImageVersion'$sel:alias:DeleteImageVersion' $sel:version:DeleteImageVersion'"$sel:imageName:DeleteImageVersion'newDeleteImageVersiondeleteImageVersion_aliasdeleteImageVersion_versiondeleteImageVersion_imageNamenewDeleteImageVersionResponse%deleteImageVersionResponse_httpStatus$fToQueryDeleteImageVersion$fToPathDeleteImageVersion$fToJSONDeleteImageVersion$fToHeadersDeleteImageVersion$fNFDataDeleteImageVersion$fHashableDeleteImageVersion"$fNFDataDeleteImageVersionResponse$fAWSRequestDeleteImageVersion$fEqDeleteImageVersionResponse $fReadDeleteImageVersionResponse $fShowDeleteImageVersionResponse#$fGenericDeleteImageVersionResponse$fEqDeleteImageVersion$fReadDeleteImageVersion$fShowDeleteImageVersion$fGenericDeleteImageVersionDeleteImageResponseDeleteImageResponse'$$sel:httpStatus:DeleteImageResponse' DeleteImage DeleteImage'$sel:imageName:DeleteImage'newDeleteImagedeleteImage_imageNamenewDeleteImageResponsedeleteImageResponse_httpStatus$fToQueryDeleteImage$fToPathDeleteImage$fToJSONDeleteImage$fToHeadersDeleteImage$fNFDataDeleteImage$fHashableDeleteImage$fNFDataDeleteImageResponse$fAWSRequestDeleteImage$fEqDeleteImageResponse$fReadDeleteImageResponse$fShowDeleteImageResponse$fGenericDeleteImageResponse$fEqDeleteImage$fReadDeleteImage$fShowDeleteImage$fGenericDeleteImageDeleteHumanTaskUiResponseDeleteHumanTaskUiResponse'*$sel:httpStatus:DeleteHumanTaskUiResponse'DeleteHumanTaskUiDeleteHumanTaskUi''$sel:humanTaskUiName:DeleteHumanTaskUi'newDeleteHumanTaskUi!deleteHumanTaskUi_humanTaskUiNamenewDeleteHumanTaskUiResponse$deleteHumanTaskUiResponse_httpStatus$fToQueryDeleteHumanTaskUi$fToPathDeleteHumanTaskUi$fToJSONDeleteHumanTaskUi$fToHeadersDeleteHumanTaskUi$fNFDataDeleteHumanTaskUi$fHashableDeleteHumanTaskUi!$fNFDataDeleteHumanTaskUiResponse$fAWSRequestDeleteHumanTaskUi$fEqDeleteHumanTaskUiResponse$fReadDeleteHumanTaskUiResponse$fShowDeleteHumanTaskUiResponse"$fGenericDeleteHumanTaskUiResponse$fEqDeleteHumanTaskUi$fReadDeleteHumanTaskUi$fShowDeleteHumanTaskUi$fGenericDeleteHumanTaskUiDeleteHubContentResponseDeleteHubContentResponse'DeleteHubContentDeleteHubContent'$sel:hubName:DeleteHubContent'%$sel:hubContentType:DeleteHubContent'%$sel:hubContentName:DeleteHubContent'($sel:hubContentVersion:DeleteHubContent'newDeleteHubContentdeleteHubContent_hubNamedeleteHubContent_hubContentTypedeleteHubContent_hubContentName"deleteHubContent_hubContentVersionnewDeleteHubContentResponse$fToQueryDeleteHubContent$fToPathDeleteHubContent$fToJSONDeleteHubContent$fToHeadersDeleteHubContent$fNFDataDeleteHubContent$fHashableDeleteHubContent $fNFDataDeleteHubContentResponse$fAWSRequestDeleteHubContent$fEqDeleteHubContentResponse$fReadDeleteHubContentResponse$fShowDeleteHubContentResponse!$fGenericDeleteHubContentResponse$fEqDeleteHubContent$fReadDeleteHubContent$fShowDeleteHubContent$fGenericDeleteHubContentDeleteHubResponseDeleteHubResponse' DeleteHub DeleteHub'$sel:hubName:DeleteHub' newDeleteHubdeleteHub_hubNamenewDeleteHubResponse$fToQueryDeleteHub$fToPathDeleteHub$fToJSONDeleteHub$fToHeadersDeleteHub$fNFDataDeleteHub$fHashableDeleteHub$fNFDataDeleteHubResponse$fAWSRequestDeleteHub$fEqDeleteHubResponse$fReadDeleteHubResponse$fShowDeleteHubResponse$fGenericDeleteHubResponse $fEqDeleteHub$fReadDeleteHub$fShowDeleteHub$fGenericDeleteHubDeleteFlowDefinitionResponseDeleteFlowDefinitionResponse'-$sel:httpStatus:DeleteFlowDefinitionResponse'DeleteFlowDefinitionDeleteFlowDefinition'-$sel:flowDefinitionName:DeleteFlowDefinition'newDeleteFlowDefinition'deleteFlowDefinition_flowDefinitionNamenewDeleteFlowDefinitionResponse'deleteFlowDefinitionResponse_httpStatus$fToQueryDeleteFlowDefinition$fToPathDeleteFlowDefinition$fToJSONDeleteFlowDefinition$fToHeadersDeleteFlowDefinition$fNFDataDeleteFlowDefinition$fHashableDeleteFlowDefinition$$fNFDataDeleteFlowDefinitionResponse $fAWSRequestDeleteFlowDefinition $fEqDeleteFlowDefinitionResponse"$fReadDeleteFlowDefinitionResponse"$fShowDeleteFlowDefinitionResponse%$fGenericDeleteFlowDefinitionResponse$fEqDeleteFlowDefinition$fReadDeleteFlowDefinition$fShowDeleteFlowDefinition$fGenericDeleteFlowDefinitionDeleteFeatureGroupResponseDeleteFeatureGroupResponse'DeleteFeatureGroupDeleteFeatureGroup')$sel:featureGroupName:DeleteFeatureGroup'newDeleteFeatureGroup#deleteFeatureGroup_featureGroupNamenewDeleteFeatureGroupResponse$fToQueryDeleteFeatureGroup$fToPathDeleteFeatureGroup$fToJSONDeleteFeatureGroup$fToHeadersDeleteFeatureGroup$fNFDataDeleteFeatureGroup$fHashableDeleteFeatureGroup"$fNFDataDeleteFeatureGroupResponse$fAWSRequestDeleteFeatureGroup$fEqDeleteFeatureGroupResponse $fReadDeleteFeatureGroupResponse $fShowDeleteFeatureGroupResponse#$fGenericDeleteFeatureGroupResponse$fEqDeleteFeatureGroup$fReadDeleteFeatureGroup$fShowDeleteFeatureGroup$fGenericDeleteFeatureGroupDeleteExperimentResponseDeleteExperimentResponse',$sel:experimentArn:DeleteExperimentResponse')$sel:httpStatus:DeleteExperimentResponse'DeleteExperimentDeleteExperiment'%$sel:experimentName:DeleteExperiment'newDeleteExperimentdeleteExperiment_experimentNamenewDeleteExperimentResponse&deleteExperimentResponse_experimentArn#deleteExperimentResponse_httpStatus$fToQueryDeleteExperiment$fToPathDeleteExperiment$fToJSONDeleteExperiment$fToHeadersDeleteExperiment$fNFDataDeleteExperiment$fHashableDeleteExperiment $fNFDataDeleteExperimentResponse$fAWSRequestDeleteExperiment$fEqDeleteExperimentResponse$fReadDeleteExperimentResponse$fShowDeleteExperimentResponse!$fGenericDeleteExperimentResponse$fEqDeleteExperiment$fReadDeleteExperiment$fShowDeleteExperiment$fGenericDeleteExperimentDeleteEndpointConfigResponseDeleteEndpointConfigResponse'DeleteEndpointConfigDeleteEndpointConfig'-$sel:endpointConfigName:DeleteEndpointConfig'newDeleteEndpointConfig'deleteEndpointConfig_endpointConfigNamenewDeleteEndpointConfigResponse$fToQueryDeleteEndpointConfig$fToPathDeleteEndpointConfig$fToJSONDeleteEndpointConfig$fToHeadersDeleteEndpointConfig$fNFDataDeleteEndpointConfig$fHashableDeleteEndpointConfig$$fNFDataDeleteEndpointConfigResponse $fAWSRequestDeleteEndpointConfig $fEqDeleteEndpointConfigResponse"$fReadDeleteEndpointConfigResponse"$fShowDeleteEndpointConfigResponse%$fGenericDeleteEndpointConfigResponse$fEqDeleteEndpointConfig$fReadDeleteEndpointConfig$fShowDeleteEndpointConfig$fGenericDeleteEndpointConfigDeleteEndpointResponseDeleteEndpointResponse'DeleteEndpointDeleteEndpoint'!$sel:endpointName:DeleteEndpoint'newDeleteEndpointdeleteEndpoint_endpointNamenewDeleteEndpointResponse$fToQueryDeleteEndpoint$fToPathDeleteEndpoint$fToJSONDeleteEndpoint$fToHeadersDeleteEndpoint$fNFDataDeleteEndpoint$fHashableDeleteEndpoint$fNFDataDeleteEndpointResponse$fAWSRequestDeleteEndpoint$fEqDeleteEndpointResponse$fReadDeleteEndpointResponse$fShowDeleteEndpointResponse$fGenericDeleteEndpointResponse$fEqDeleteEndpoint$fReadDeleteEndpoint$fShowDeleteEndpoint$fGenericDeleteEndpoint!DeleteEdgeDeploymentStageResponse"DeleteEdgeDeploymentStageResponse'DeleteEdgeDeploymentStageDeleteEdgeDeploymentStage'6$sel:edgeDeploymentPlanName:DeleteEdgeDeploymentStage')$sel:stageName:DeleteEdgeDeploymentStage'newDeleteEdgeDeploymentStage0deleteEdgeDeploymentStage_edgeDeploymentPlanName#deleteEdgeDeploymentStage_stageName$newDeleteEdgeDeploymentStageResponse"$fToQueryDeleteEdgeDeploymentStage!$fToPathDeleteEdgeDeploymentStage!$fToJSONDeleteEdgeDeploymentStage$$fToHeadersDeleteEdgeDeploymentStage!$fNFDataDeleteEdgeDeploymentStage#$fHashableDeleteEdgeDeploymentStage)$fNFDataDeleteEdgeDeploymentStageResponse%$fAWSRequestDeleteEdgeDeploymentStage%$fEqDeleteEdgeDeploymentStageResponse'$fReadDeleteEdgeDeploymentStageResponse'$fShowDeleteEdgeDeploymentStageResponse*$fGenericDeleteEdgeDeploymentStageResponse$fEqDeleteEdgeDeploymentStage$fReadDeleteEdgeDeploymentStage$fShowDeleteEdgeDeploymentStage"$fGenericDeleteEdgeDeploymentStage DeleteEdgeDeploymentPlanResponse!DeleteEdgeDeploymentPlanResponse'DeleteEdgeDeploymentPlanDeleteEdgeDeploymentPlan'5$sel:edgeDeploymentPlanName:DeleteEdgeDeploymentPlan'newDeleteEdgeDeploymentPlan/deleteEdgeDeploymentPlan_edgeDeploymentPlanName#newDeleteEdgeDeploymentPlanResponse!$fToQueryDeleteEdgeDeploymentPlan $fToPathDeleteEdgeDeploymentPlan $fToJSONDeleteEdgeDeploymentPlan#$fToHeadersDeleteEdgeDeploymentPlan $fNFDataDeleteEdgeDeploymentPlan"$fHashableDeleteEdgeDeploymentPlan($fNFDataDeleteEdgeDeploymentPlanResponse$$fAWSRequestDeleteEdgeDeploymentPlan$$fEqDeleteEdgeDeploymentPlanResponse&$fReadDeleteEdgeDeploymentPlanResponse&$fShowDeleteEdgeDeploymentPlanResponse)$fGenericDeleteEdgeDeploymentPlanResponse$fEqDeleteEdgeDeploymentPlan$fReadDeleteEdgeDeploymentPlan$fShowDeleteEdgeDeploymentPlan!$fGenericDeleteEdgeDeploymentPlanDeleteDomainResponseDeleteDomainResponse' DeleteDomain DeleteDomain'"$sel:retentionPolicy:DeleteDomain'$sel:domainId:DeleteDomain'newDeleteDomaindeleteDomain_retentionPolicydeleteDomain_domainIdnewDeleteDomainResponse$fToQueryDeleteDomain$fToPathDeleteDomain$fToJSONDeleteDomain$fToHeadersDeleteDomain$fNFDataDeleteDomain$fHashableDeleteDomain$fNFDataDeleteDomainResponse$fAWSRequestDeleteDomain$fEqDeleteDomainResponse$fReadDeleteDomainResponse$fShowDeleteDomainResponse$fGenericDeleteDomainResponse$fEqDeleteDomain$fReadDeleteDomain$fShowDeleteDomain$fGenericDeleteDomainDeleteDeviceFleetResponseDeleteDeviceFleetResponse'DeleteDeviceFleetDeleteDeviceFleet''$sel:deviceFleetName:DeleteDeviceFleet'newDeleteDeviceFleet!deleteDeviceFleet_deviceFleetNamenewDeleteDeviceFleetResponse$fToQueryDeleteDeviceFleet$fToPathDeleteDeviceFleet$fToJSONDeleteDeviceFleet$fToHeadersDeleteDeviceFleet$fNFDataDeleteDeviceFleet$fHashableDeleteDeviceFleet!$fNFDataDeleteDeviceFleetResponse$fAWSRequestDeleteDeviceFleet$fEqDeleteDeviceFleetResponse$fReadDeleteDeviceFleetResponse$fShowDeleteDeviceFleetResponse"$fGenericDeleteDeviceFleetResponse$fEqDeleteDeviceFleet$fReadDeleteDeviceFleet$fShowDeleteDeviceFleet$fGenericDeleteDeviceFleet&DeleteDataQualityJobDefinitionResponse'DeleteDataQualityJobDefinitionResponse'DeleteDataQualityJobDefinitionDeleteDataQualityJobDefinition'6$sel:jobDefinitionName:DeleteDataQualityJobDefinition'!newDeleteDataQualityJobDefinition0deleteDataQualityJobDefinition_jobDefinitionName)newDeleteDataQualityJobDefinitionResponse'$fToQueryDeleteDataQualityJobDefinition&$fToPathDeleteDataQualityJobDefinition&$fToJSONDeleteDataQualityJobDefinition)$fToHeadersDeleteDataQualityJobDefinition&$fNFDataDeleteDataQualityJobDefinition($fHashableDeleteDataQualityJobDefinition.$fNFDataDeleteDataQualityJobDefinitionResponse*$fAWSRequestDeleteDataQualityJobDefinition*$fEqDeleteDataQualityJobDefinitionResponse,$fReadDeleteDataQualityJobDefinitionResponse,$fShowDeleteDataQualityJobDefinitionResponse/$fGenericDeleteDataQualityJobDefinitionResponse"$fEqDeleteDataQualityJobDefinition$$fReadDeleteDataQualityJobDefinition$$fShowDeleteDataQualityJobDefinition'$fGenericDeleteDataQualityJobDefinitionDeleteContextResponseDeleteContextResponse'&$sel:contextArn:DeleteContextResponse'&$sel:httpStatus:DeleteContextResponse' DeleteContextDeleteContext'$sel:contextName:DeleteContext'newDeleteContextdeleteContext_contextNamenewDeleteContextResponse deleteContextResponse_contextArn deleteContextResponse_httpStatus$fToQueryDeleteContext$fToPathDeleteContext$fToJSONDeleteContext$fToHeadersDeleteContext$fNFDataDeleteContext$fHashableDeleteContext$fNFDataDeleteContextResponse$fAWSRequestDeleteContext$fEqDeleteContextResponse$fReadDeleteContextResponse$fShowDeleteContextResponse$fGenericDeleteContextResponse$fEqDeleteContext$fReadDeleteContext$fShowDeleteContext$fGenericDeleteContextDeleteCodeRepositoryResponseDeleteCodeRepositoryResponse'DeleteCodeRepositoryDeleteCodeRepository'-$sel:codeRepositoryName:DeleteCodeRepository'newDeleteCodeRepository'deleteCodeRepository_codeRepositoryNamenewDeleteCodeRepositoryResponse$fToQueryDeleteCodeRepository$fToPathDeleteCodeRepository$fToJSONDeleteCodeRepository$fToHeadersDeleteCodeRepository$fNFDataDeleteCodeRepository$fHashableDeleteCodeRepository$$fNFDataDeleteCodeRepositoryResponse $fAWSRequestDeleteCodeRepository $fEqDeleteCodeRepositoryResponse"$fReadDeleteCodeRepositoryResponse"$fShowDeleteCodeRepositoryResponse%$fGenericDeleteCodeRepositoryResponse$fEqDeleteCodeRepository$fReadDeleteCodeRepository$fShowDeleteCodeRepository$fGenericDeleteCodeRepositoryDeleteAssociationResponseDeleteAssociationResponse'.$sel:destinationArn:DeleteAssociationResponse')$sel:sourceArn:DeleteAssociationResponse'*$sel:httpStatus:DeleteAssociationResponse'DeleteAssociationDeleteAssociation'!$sel:sourceArn:DeleteAssociation'&$sel:destinationArn:DeleteAssociation'newDeleteAssociationdeleteAssociation_sourceArn deleteAssociation_destinationArnnewDeleteAssociationResponse(deleteAssociationResponse_destinationArn#deleteAssociationResponse_sourceArn$deleteAssociationResponse_httpStatus$fToQueryDeleteAssociation$fToPathDeleteAssociation$fToJSONDeleteAssociation$fToHeadersDeleteAssociation$fNFDataDeleteAssociation$fHashableDeleteAssociation!$fNFDataDeleteAssociationResponse$fAWSRequestDeleteAssociation$fEqDeleteAssociationResponse$fReadDeleteAssociationResponse$fShowDeleteAssociationResponse"$fGenericDeleteAssociationResponse$fEqDeleteAssociation$fReadDeleteAssociation$fShowDeleteAssociation$fGenericDeleteAssociationDeleteArtifactResponseDeleteArtifactResponse'($sel:artifactArn:DeleteArtifactResponse''$sel:httpStatus:DeleteArtifactResponse'DeleteArtifactDeleteArtifact' $sel:artifactArn:DeleteArtifact'$sel:source:DeleteArtifact'newDeleteArtifactdeleteArtifact_artifactArndeleteArtifact_sourcenewDeleteArtifactResponse"deleteArtifactResponse_artifactArn!deleteArtifactResponse_httpStatus$fToQueryDeleteArtifact$fToPathDeleteArtifact$fToJSONDeleteArtifact$fToHeadersDeleteArtifact$fNFDataDeleteArtifact$fHashableDeleteArtifact$fNFDataDeleteArtifactResponse$fAWSRequestDeleteArtifact$fEqDeleteArtifactResponse$fReadDeleteArtifactResponse$fShowDeleteArtifactResponse$fGenericDeleteArtifactResponse$fEqDeleteArtifact$fReadDeleteArtifact$fShowDeleteArtifact$fGenericDeleteArtifactDeleteAppImageConfigResponseDeleteAppImageConfigResponse'DeleteAppImageConfigDeleteAppImageConfig'-$sel:appImageConfigName:DeleteAppImageConfig'newDeleteAppImageConfig'deleteAppImageConfig_appImageConfigNamenewDeleteAppImageConfigResponse$fToQueryDeleteAppImageConfig$fToPathDeleteAppImageConfig$fToJSONDeleteAppImageConfig$fToHeadersDeleteAppImageConfig$fNFDataDeleteAppImageConfig$fHashableDeleteAppImageConfig$$fNFDataDeleteAppImageConfigResponse $fAWSRequestDeleteAppImageConfig $fEqDeleteAppImageConfigResponse"$fReadDeleteAppImageConfigResponse"$fShowDeleteAppImageConfigResponse%$fGenericDeleteAppImageConfigResponse$fEqDeleteAppImageConfig$fReadDeleteAppImageConfig$fShowDeleteAppImageConfig$fGenericDeleteAppImageConfigDeleteAppResponseDeleteAppResponse' DeleteApp DeleteApp'$sel:spaceName:DeleteApp'$sel:userProfileName:DeleteApp'$sel:domainId:DeleteApp'$sel:appType:DeleteApp'$sel:appName:DeleteApp' newDeleteAppdeleteApp_spaceNamedeleteApp_userProfileNamedeleteApp_domainIddeleteApp_appTypedeleteApp_appNamenewDeleteAppResponse$fToQueryDeleteApp$fToPathDeleteApp$fToJSONDeleteApp$fToHeadersDeleteApp$fNFDataDeleteApp$fHashableDeleteApp$fNFDataDeleteAppResponse$fAWSRequestDeleteApp$fEqDeleteAppResponse$fReadDeleteAppResponse$fShowDeleteAppResponse$fGenericDeleteAppResponse $fEqDeleteApp$fReadDeleteApp$fShowDeleteApp$fGenericDeleteAppDeleteAlgorithmResponseDeleteAlgorithmResponse'DeleteAlgorithmDeleteAlgorithm'#$sel:algorithmName:DeleteAlgorithm'newDeleteAlgorithmdeleteAlgorithm_algorithmNamenewDeleteAlgorithmResponse$fToQueryDeleteAlgorithm$fToPathDeleteAlgorithm$fToJSONDeleteAlgorithm$fToHeadersDeleteAlgorithm$fNFDataDeleteAlgorithm$fHashableDeleteAlgorithm$fNFDataDeleteAlgorithmResponse$fAWSRequestDeleteAlgorithm$fEqDeleteAlgorithmResponse$fReadDeleteAlgorithmResponse$fShowDeleteAlgorithmResponse $fGenericDeleteAlgorithmResponse$fEqDeleteAlgorithm$fReadDeleteAlgorithm$fShowDeleteAlgorithm$fGenericDeleteAlgorithmDeleteActionResponseDeleteActionResponse'$$sel:actionArn:DeleteActionResponse'%$sel:httpStatus:DeleteActionResponse' DeleteAction DeleteAction'$sel:actionName:DeleteAction'newDeleteActiondeleteAction_actionNamenewDeleteActionResponsedeleteActionResponse_actionArndeleteActionResponse_httpStatus$fToQueryDeleteAction$fToPathDeleteAction$fToJSONDeleteAction$fToHeadersDeleteAction$fNFDataDeleteAction$fHashableDeleteAction$fNFDataDeleteActionResponse$fAWSRequestDeleteAction$fEqDeleteActionResponse$fReadDeleteActionResponse$fShowDeleteActionResponse$fGenericDeleteActionResponse$fEqDeleteAction$fReadDeleteAction$fShowDeleteAction$fGenericDeleteActionCreateWorkteamResponseCreateWorkteamResponse'($sel:workteamArn:CreateWorkteamResponse''$sel:httpStatus:CreateWorkteamResponse'CreateWorkteamCreateWorkteam'.$sel:notificationConfiguration:CreateWorkteam'$sel:tags:CreateWorkteam'"$sel:workforceName:CreateWorkteam'!$sel:workteamName:CreateWorkteam'&$sel:memberDefinitions:CreateWorkteam' $sel:description:CreateWorkteam'newCreateWorkteam(createWorkteam_notificationConfigurationcreateWorkteam_tagscreateWorkteam_workforceNamecreateWorkteam_workteamName createWorkteam_memberDefinitionscreateWorkteam_descriptionnewCreateWorkteamResponse"createWorkteamResponse_workteamArn!createWorkteamResponse_httpStatus$fToQueryCreateWorkteam$fToPathCreateWorkteam$fToJSONCreateWorkteam$fToHeadersCreateWorkteam$fNFDataCreateWorkteam$fHashableCreateWorkteam$fNFDataCreateWorkteamResponse$fAWSRequestCreateWorkteam$fEqCreateWorkteamResponse$fReadCreateWorkteamResponse$fShowCreateWorkteamResponse$fGenericCreateWorkteamResponse$fEqCreateWorkteam$fReadCreateWorkteam$fShowCreateWorkteam$fGenericCreateWorkteamCreateWorkforceResponseCreateWorkforceResponse'($sel:httpStatus:CreateWorkforceResponse'*$sel:workforceArn:CreateWorkforceResponse'CreateWorkforceCreateWorkforce'#$sel:cognitoConfig:CreateWorkforce' $sel:oidcConfig:CreateWorkforce'$$sel:sourceIpConfig:CreateWorkforce'$sel:tags:CreateWorkforce'($sel:workforceVpcConfig:CreateWorkforce'#$sel:workforceName:CreateWorkforce'newCreateWorkforcecreateWorkforce_cognitoConfigcreateWorkforce_oidcConfigcreateWorkforce_sourceIpConfigcreateWorkforce_tags"createWorkforce_workforceVpcConfigcreateWorkforce_workforceNamenewCreateWorkforceResponse"createWorkforceResponse_httpStatus$createWorkforceResponse_workforceArn$fToQueryCreateWorkforce$fToPathCreateWorkforce$fToJSONCreateWorkforce$fToHeadersCreateWorkforce$fNFDataCreateWorkforce$fHashableCreateWorkforce$fNFDataCreateWorkforceResponse$fAWSRequestCreateWorkforce$fEqCreateWorkforceResponse$fReadCreateWorkforceResponse$fShowCreateWorkforceResponse $fGenericCreateWorkforceResponse$fEqCreateWorkforce$fShowCreateWorkforce$fGenericCreateWorkforceCreateUserProfileResponseCreateUserProfileResponse'.$sel:userProfileArn:CreateUserProfileResponse'*$sel:httpStatus:CreateUserProfileResponse'CreateUserProfileCreateUserProfile'2$sel:singleSignOnUserIdentifier:CreateUserProfile'-$sel:singleSignOnUserValue:CreateUserProfile'$sel:tags:CreateUserProfile'$$sel:userSettings:CreateUserProfile' $sel:domainId:CreateUserProfile''$sel:userProfileName:CreateUserProfile'newCreateUserProfile,createUserProfile_singleSignOnUserIdentifier'createUserProfile_singleSignOnUserValuecreateUserProfile_tagscreateUserProfile_userSettingscreateUserProfile_domainId!createUserProfile_userProfileNamenewCreateUserProfileResponse(createUserProfileResponse_userProfileArn$createUserProfileResponse_httpStatus$fToQueryCreateUserProfile$fToPathCreateUserProfile$fToJSONCreateUserProfile$fToHeadersCreateUserProfile$fNFDataCreateUserProfile$fHashableCreateUserProfile!$fNFDataCreateUserProfileResponse$fAWSRequestCreateUserProfile$fEqCreateUserProfileResponse$fReadCreateUserProfileResponse$fShowCreateUserProfileResponse"$fGenericCreateUserProfileResponse$fEqCreateUserProfile$fReadCreateUserProfile$fShowCreateUserProfile$fGenericCreateUserProfileCreateTrialComponentResponseCreateTrialComponentResponse'4$sel:trialComponentArn:CreateTrialComponentResponse'-$sel:httpStatus:CreateTrialComponentResponse'CreateTrialComponentCreateTrialComponent'&$sel:displayName:CreateTrialComponent'"$sel:endTime:CreateTrialComponent')$sel:inputArtifacts:CreateTrialComponent'-$sel:metadataProperties:CreateTrialComponent'*$sel:outputArtifacts:CreateTrialComponent'%$sel:parameters:CreateTrialComponent'$$sel:startTime:CreateTrialComponent'!$sel:status:CreateTrialComponent'$sel:tags:CreateTrialComponent'-$sel:trialComponentName:CreateTrialComponent'newCreateTrialComponent createTrialComponent_displayNamecreateTrialComponent_endTime#createTrialComponent_inputArtifacts'createTrialComponent_metadataProperties$createTrialComponent_outputArtifactscreateTrialComponent_parameterscreateTrialComponent_startTimecreateTrialComponent_statuscreateTrialComponent_tags'createTrialComponent_trialComponentNamenewCreateTrialComponentResponse.createTrialComponentResponse_trialComponentArn'createTrialComponentResponse_httpStatus$fToQueryCreateTrialComponent$fToPathCreateTrialComponent$fToJSONCreateTrialComponent$fToHeadersCreateTrialComponent$fNFDataCreateTrialComponent$fHashableCreateTrialComponent$$fNFDataCreateTrialComponentResponse $fAWSRequestCreateTrialComponent $fEqCreateTrialComponentResponse"$fReadCreateTrialComponentResponse"$fShowCreateTrialComponentResponse%$fGenericCreateTrialComponentResponse$fEqCreateTrialComponent$fReadCreateTrialComponent$fShowCreateTrialComponent$fGenericCreateTrialComponentCreateTrialResponseCreateTrialResponse'"$sel:trialArn:CreateTrialResponse'$$sel:httpStatus:CreateTrialResponse' CreateTrial CreateTrial'$sel:displayName:CreateTrial'$$sel:metadataProperties:CreateTrial'$sel:tags:CreateTrial'$sel:trialName:CreateTrial' $sel:experimentName:CreateTrial'newCreateTrialcreateTrial_displayNamecreateTrial_metadataPropertiescreateTrial_tagscreateTrial_trialNamecreateTrial_experimentNamenewCreateTrialResponsecreateTrialResponse_trialArncreateTrialResponse_httpStatus$fToQueryCreateTrial$fToPathCreateTrial$fToJSONCreateTrial$fToHeadersCreateTrial$fNFDataCreateTrial$fHashableCreateTrial$fNFDataCreateTrialResponse$fAWSRequestCreateTrial$fEqCreateTrialResponse$fReadCreateTrialResponse$fShowCreateTrialResponse$fGenericCreateTrialResponse$fEqCreateTrial$fReadCreateTrial$fShowCreateTrial$fGenericCreateTrialCreateTransformJobResponseCreateTransformJobResponse'+$sel:httpStatus:CreateTransformJobResponse'0$sel:transformJobArn:CreateTransformJobResponse'CreateTransformJobCreateTransformJob'&$sel:batchStrategy:CreateTransformJob'*$sel:dataCaptureConfig:CreateTransformJob''$sel:dataProcessing:CreateTransformJob'$$sel:environment:CreateTransformJob')$sel:experimentConfig:CreateTransformJob'0$sel:maxConcurrentTransforms:CreateTransformJob''$sel:maxPayloadInMB:CreateTransformJob'*$sel:modelClientConfig:CreateTransformJob'$sel:tags:CreateTransformJob')$sel:transformJobName:CreateTransformJob'"$sel:modelName:CreateTransformJob''$sel:transformInput:CreateTransformJob'($sel:transformOutput:CreateTransformJob'+$sel:transformResources:CreateTransformJob'newCreateTransformJob createTransformJob_batchStrategy$createTransformJob_dataCaptureConfig!createTransformJob_dataProcessingcreateTransformJob_environment#createTransformJob_experimentConfig*createTransformJob_maxConcurrentTransforms!createTransformJob_maxPayloadInMB$createTransformJob_modelClientConfigcreateTransformJob_tags#createTransformJob_transformJobNamecreateTransformJob_modelName!createTransformJob_transformInput"createTransformJob_transformOutput%createTransformJob_transformResourcesnewCreateTransformJobResponse%createTransformJobResponse_httpStatus*createTransformJobResponse_transformJobArn$fToQueryCreateTransformJob$fToPathCreateTransformJob$fToJSONCreateTransformJob$fToHeadersCreateTransformJob$fNFDataCreateTransformJob$fHashableCreateTransformJob"$fNFDataCreateTransformJobResponse$fAWSRequestCreateTransformJob$fEqCreateTransformJobResponse $fReadCreateTransformJobResponse $fShowCreateTransformJobResponse#$fGenericCreateTransformJobResponse$fEqCreateTransformJob$fReadCreateTransformJob$fShowCreateTransformJob$fGenericCreateTransformJobCreateTrainingJobResponseCreateTrainingJobResponse'*$sel:httpStatus:CreateTrainingJobResponse'.$sel:trainingJobArn:CreateTrainingJobResponse'CreateTrainingJobCreateTrainingJob'($sel:checkpointConfig:CreateTrainingJob''$sel:debugHookConfig:CreateTrainingJob'/$sel:debugRuleConfigurations:CreateTrainingJob'=$sel:enableInterContainerTrafficEncryption:CreateTrainingJob'1$sel:enableManagedSpotTraining:CreateTrainingJob'.$sel:enableNetworkIsolation:CreateTrainingJob'#$sel:environment:CreateTrainingJob'($sel:experimentConfig:CreateTrainingJob''$sel:hyperParameters:CreateTrainingJob''$sel:inputDataConfig:CreateTrainingJob'&$sel:profilerConfig:CreateTrainingJob'2$sel:profilerRuleConfigurations:CreateTrainingJob'%$sel:retryStrategy:CreateTrainingJob'$sel:tags:CreateTrainingJob'/$sel:tensorBoardOutputConfig:CreateTrainingJob'!$sel:vpcConfig:CreateTrainingJob''$sel:trainingJobName:CreateTrainingJob'.$sel:algorithmSpecification:CreateTrainingJob'$sel:roleArn:CreateTrainingJob'($sel:outputDataConfig:CreateTrainingJob'&$sel:resourceConfig:CreateTrainingJob')$sel:stoppingCondition:CreateTrainingJob'newCreateTrainingJob"createTrainingJob_checkpointConfig!createTrainingJob_debugHookConfig)createTrainingJob_debugRuleConfigurations7createTrainingJob_enableInterContainerTrafficEncryption+createTrainingJob_enableManagedSpotTraining(createTrainingJob_enableNetworkIsolationcreateTrainingJob_environment"createTrainingJob_experimentConfig!createTrainingJob_hyperParameters!createTrainingJob_inputDataConfig createTrainingJob_profilerConfig,createTrainingJob_profilerRuleConfigurationscreateTrainingJob_retryStrategycreateTrainingJob_tags)createTrainingJob_tensorBoardOutputConfigcreateTrainingJob_vpcConfig!createTrainingJob_trainingJobName(createTrainingJob_algorithmSpecificationcreateTrainingJob_roleArn"createTrainingJob_outputDataConfig createTrainingJob_resourceConfig#createTrainingJob_stoppingConditionnewCreateTrainingJobResponse$createTrainingJobResponse_httpStatus(createTrainingJobResponse_trainingJobArn$fToQueryCreateTrainingJob$fToPathCreateTrainingJob$fToJSONCreateTrainingJob$fToHeadersCreateTrainingJob$fNFDataCreateTrainingJob$fHashableCreateTrainingJob!$fNFDataCreateTrainingJobResponse$fAWSRequestCreateTrainingJob$fEqCreateTrainingJobResponse$fReadCreateTrainingJobResponse$fShowCreateTrainingJobResponse"$fGenericCreateTrainingJobResponse$fEqCreateTrainingJob$fReadCreateTrainingJob$fShowCreateTrainingJob$fGenericCreateTrainingJob#CreateStudioLifecycleConfigResponse$CreateStudioLifecycleConfigResponse'$sel:studioLifecycleConfigArn:CreateStudioLifecycleConfigResponse'4$sel:httpStatus:CreateStudioLifecycleConfigResponse'CreateStudioLifecycleConfigCreateStudioLifecycleConfig'&$sel:tags:CreateStudioLifecycleConfig';$sel:studioLifecycleConfigName:CreateStudioLifecycleConfig'>$sel:studioLifecycleConfigContent:CreateStudioLifecycleConfig'>$sel:studioLifecycleConfigAppType:CreateStudioLifecycleConfig'newCreateStudioLifecycleConfig createStudioLifecycleConfig_tags5createStudioLifecycleConfig_studioLifecycleConfigName8createStudioLifecycleConfig_studioLifecycleConfigContent8createStudioLifecycleConfig_studioLifecycleConfigAppType&newCreateStudioLifecycleConfigResponse$sel:authorizedUrl:CreatePresignedNotebookInstanceUrlResponse';$sel:httpStatus:CreatePresignedNotebookInstanceUrlResponse'"CreatePresignedNotebookInstanceUrl#CreatePresignedNotebookInstanceUrl'$sel:sessionExpirationDurationInSeconds:CreatePresignedNotebookInstanceUrl'=$sel:notebookInstanceName:CreatePresignedNotebookInstanceUrl'%newCreatePresignedNotebookInstanceUrlcreatePresignedNotebookInstanceUrl_sessionExpirationDurationInSeconds7createPresignedNotebookInstanceUrl_notebookInstanceName-newCreatePresignedNotebookInstanceUrlResponse8createPresignedNotebookInstanceUrlResponse_authorizedUrl5createPresignedNotebookInstanceUrlResponse_httpStatus+$fToQueryCreatePresignedNotebookInstanceUrl*$fToPathCreatePresignedNotebookInstanceUrl*$fToJSONCreatePresignedNotebookInstanceUrl-$fToHeadersCreatePresignedNotebookInstanceUrl*$fNFDataCreatePresignedNotebookInstanceUrl,$fHashableCreatePresignedNotebookInstanceUrl2$fNFDataCreatePresignedNotebookInstanceUrlResponse.$fAWSRequestCreatePresignedNotebookInstanceUrl.$fEqCreatePresignedNotebookInstanceUrlResponse0$fReadCreatePresignedNotebookInstanceUrlResponse0$fShowCreatePresignedNotebookInstanceUrlResponse3$fGenericCreatePresignedNotebookInstanceUrlResponse&$fEqCreatePresignedNotebookInstanceUrl($fReadCreatePresignedNotebookInstanceUrl($fShowCreatePresignedNotebookInstanceUrl+$fGenericCreatePresignedNotebookInstanceUrl CreatePresignedDomainUrlResponse!CreatePresignedDomainUrlResponse'4$sel:authorizedUrl:CreatePresignedDomainUrlResponse'1$sel:httpStatus:CreatePresignedDomainUrlResponse'CreatePresignedDomainUrlCreatePresignedDomainUrl'/$sel:expiresInSeconds:CreatePresignedDomainUrl'$sel:sessionExpirationDurationInSeconds:CreatePresignedDomainUrl'($sel:spaceName:CreatePresignedDomainUrl''$sel:domainId:CreatePresignedDomainUrl'.$sel:userProfileName:CreatePresignedDomainUrl'newCreatePresignedDomainUrl)createPresignedDomainUrl_expiresInSeconds;createPresignedDomainUrl_sessionExpirationDurationInSeconds"createPresignedDomainUrl_spaceName!createPresignedDomainUrl_domainId(createPresignedDomainUrl_userProfileName#newCreatePresignedDomainUrlResponse.createPresignedDomainUrlResponse_authorizedUrl+createPresignedDomainUrlResponse_httpStatus!$fToQueryCreatePresignedDomainUrl $fToPathCreatePresignedDomainUrl $fToJSONCreatePresignedDomainUrl#$fToHeadersCreatePresignedDomainUrl $fNFDataCreatePresignedDomainUrl"$fHashableCreatePresignedDomainUrl($fNFDataCreatePresignedDomainUrlResponse$$fAWSRequestCreatePresignedDomainUrl$$fEqCreatePresignedDomainUrlResponse&$fReadCreatePresignedDomainUrlResponse&$fShowCreatePresignedDomainUrlResponse)$fGenericCreatePresignedDomainUrlResponse$fEqCreatePresignedDomainUrl$fReadCreatePresignedDomainUrl$fShowCreatePresignedDomainUrl!$fGenericCreatePresignedDomainUrlCreatePipelineResponseCreatePipelineResponse'($sel:pipelineArn:CreatePipelineResponse''$sel:httpStatus:CreatePipelineResponse'CreatePipelineCreatePipeline'-$sel:parallelismConfiguration:CreatePipeline''$sel:pipelineDefinition:CreatePipeline'1$sel:pipelineDefinitionS3Location:CreatePipeline'($sel:pipelineDescription:CreatePipeline'($sel:pipelineDisplayName:CreatePipeline'$sel:tags:CreatePipeline'!$sel:pipelineName:CreatePipeline''$sel:clientRequestToken:CreatePipeline'$sel:roleArn:CreatePipeline'newCreatePipeline'createPipeline_parallelismConfiguration!createPipeline_pipelineDefinition+createPipeline_pipelineDefinitionS3Location"createPipeline_pipelineDescription"createPipeline_pipelineDisplayNamecreatePipeline_tagscreatePipeline_pipelineName!createPipeline_clientRequestTokencreatePipeline_roleArnnewCreatePipelineResponse"createPipelineResponse_pipelineArn!createPipelineResponse_httpStatus$fToQueryCreatePipeline$fToPathCreatePipeline$fToJSONCreatePipeline$fToHeadersCreatePipeline$fNFDataCreatePipeline$fHashableCreatePipeline$fNFDataCreatePipelineResponse$fAWSRequestCreatePipeline$fEqCreatePipelineResponse$fReadCreatePipelineResponse$fShowCreatePipelineResponse$fGenericCreatePipelineResponse$fEqCreatePipeline$fReadCreatePipeline$fShowCreatePipeline$fGenericCreatePipeline-CreateNotebookInstanceLifecycleConfigResponse.CreateNotebookInstanceLifecycleConfigResponse'$sel:notebookInstanceLifecycleConfigArn:CreateNotebookInstanceLifecycleConfigResponse'>$sel:httpStatus:CreateNotebookInstanceLifecycleConfigResponse'%CreateNotebookInstanceLifecycleConfig&CreateNotebookInstanceLifecycleConfig'4$sel:onCreate:CreateNotebookInstanceLifecycleConfig'3$sel:onStart:CreateNotebookInstanceLifecycleConfig'$sel:notebookInstanceLifecycleConfigName:CreateNotebookInstanceLifecycleConfig'(newCreateNotebookInstanceLifecycleConfig.createNotebookInstanceLifecycleConfig_onCreate-createNotebookInstanceLifecycleConfig_onStartcreateNotebookInstanceLifecycleConfig_notebookInstanceLifecycleConfigName0newCreateNotebookInstanceLifecycleConfigResponsecreateNotebookInstanceLifecycleConfigResponse_notebookInstanceLifecycleConfigArn8createNotebookInstanceLifecycleConfigResponse_httpStatus.$fToQueryCreateNotebookInstanceLifecycleConfig-$fToPathCreateNotebookInstanceLifecycleConfig-$fToJSONCreateNotebookInstanceLifecycleConfig0$fToHeadersCreateNotebookInstanceLifecycleConfig-$fNFDataCreateNotebookInstanceLifecycleConfig/$fHashableCreateNotebookInstanceLifecycleConfig5$fNFDataCreateNotebookInstanceLifecycleConfigResponse1$fAWSRequestCreateNotebookInstanceLifecycleConfig1$fEqCreateNotebookInstanceLifecycleConfigResponse3$fReadCreateNotebookInstanceLifecycleConfigResponse3$fShowCreateNotebookInstanceLifecycleConfigResponse6$fGenericCreateNotebookInstanceLifecycleConfigResponse)$fEqCreateNotebookInstanceLifecycleConfig+$fReadCreateNotebookInstanceLifecycleConfig+$fShowCreateNotebookInstanceLifecycleConfig.$fGenericCreateNotebookInstanceLifecycleConfigCreateNotebookInstanceResponseCreateNotebookInstanceResponse'8$sel:notebookInstanceArn:CreateNotebookInstanceResponse'/$sel:httpStatus:CreateNotebookInstanceResponse'CreateNotebookInstanceCreateNotebookInstance'-$sel:acceleratorTypes:CreateNotebookInstance'7$sel:additionalCodeRepositories:CreateNotebookInstance'2$sel:defaultCodeRepository:CreateNotebookInstance'1$sel:directInternetAccess:CreateNotebookInstance'$sel:instanceMetadataServiceConfiguration:CreateNotebookInstance'%$sel:kmsKeyId:CreateNotebookInstance'0$sel:lifecycleConfigName:CreateNotebookInstance'/$sel:platformIdentifier:CreateNotebookInstance''$sel:rootAccess:CreateNotebookInstance'-$sel:securityGroupIds:CreateNotebookInstance'%$sel:subnetId:CreateNotebookInstance'!$sel:tags:CreateNotebookInstance'+$sel:volumeSizeInGB:CreateNotebookInstance'1$sel:notebookInstanceName:CreateNotebookInstance')$sel:instanceType:CreateNotebookInstance'$$sel:roleArn:CreateNotebookInstance'newCreateNotebookInstance'createNotebookInstance_acceleratorTypes1createNotebookInstance_additionalCodeRepositories,createNotebookInstance_defaultCodeRepository+createNotebookInstance_directInternetAccess;createNotebookInstance_instanceMetadataServiceConfigurationcreateNotebookInstance_kmsKeyId*createNotebookInstance_lifecycleConfigName)createNotebookInstance_platformIdentifier!createNotebookInstance_rootAccess'createNotebookInstance_securityGroupIdscreateNotebookInstance_subnetIdcreateNotebookInstance_tags%createNotebookInstance_volumeSizeInGB+createNotebookInstance_notebookInstanceName#createNotebookInstance_instanceTypecreateNotebookInstance_roleArn!newCreateNotebookInstanceResponse2createNotebookInstanceResponse_notebookInstanceArn)createNotebookInstanceResponse_httpStatus$fToQueryCreateNotebookInstance$fToPathCreateNotebookInstance$fToJSONCreateNotebookInstance!$fToHeadersCreateNotebookInstance$fNFDataCreateNotebookInstance $fHashableCreateNotebookInstance&$fNFDataCreateNotebookInstanceResponse"$fAWSRequestCreateNotebookInstance"$fEqCreateNotebookInstanceResponse$$fReadCreateNotebookInstanceResponse$$fShowCreateNotebookInstanceResponse'$fGenericCreateNotebookInstanceResponse$fEqCreateNotebookInstance$fReadCreateNotebookInstance$fShowCreateNotebookInstance$fGenericCreateNotebookInstance CreateMonitoringScheduleResponse!CreateMonitoringScheduleResponse'1$sel:httpStatus:CreateMonitoringScheduleResponse'<$sel:monitoringScheduleArn:CreateMonitoringScheduleResponse'CreateMonitoringScheduleCreateMonitoringSchedule'#$sel:tags:CreateMonitoringSchedule'5$sel:monitoringScheduleName:CreateMonitoringSchedule'7$sel:monitoringScheduleConfig:CreateMonitoringSchedule'newCreateMonitoringSchedulecreateMonitoringSchedule_tags/createMonitoringSchedule_monitoringScheduleName1createMonitoringSchedule_monitoringScheduleConfig#newCreateMonitoringScheduleResponse+createMonitoringScheduleResponse_httpStatus6createMonitoringScheduleResponse_monitoringScheduleArn!$fToQueryCreateMonitoringSchedule $fToPathCreateMonitoringSchedule $fToJSONCreateMonitoringSchedule#$fToHeadersCreateMonitoringSchedule $fNFDataCreateMonitoringSchedule"$fHashableCreateMonitoringSchedule($fNFDataCreateMonitoringScheduleResponse$$fAWSRequestCreateMonitoringSchedule$$fEqCreateMonitoringScheduleResponse&$fReadCreateMonitoringScheduleResponse&$fShowCreateMonitoringScheduleResponse)$fGenericCreateMonitoringScheduleResponse$fEqCreateMonitoringSchedule$fReadCreateMonitoringSchedule$fShowCreateMonitoringSchedule!$fGenericCreateMonitoringSchedule'CreateModelQualityJobDefinitionResponse(CreateModelQualityJobDefinitionResponse'8$sel:httpStatus:CreateModelQualityJobDefinitionResponse'>$sel:jobDefinitionArn:CreateModelQualityJobDefinitionResponse'CreateModelQualityJobDefinition CreateModelQualityJobDefinition'$sel:modelQualityBaselineConfig:CreateModelQualityJobDefinition'3$sel:networkConfig:CreateModelQualityJobDefinition'7$sel:stoppingCondition:CreateModelQualityJobDefinition'*$sel:tags:CreateModelQualityJobDefinition'7$sel:jobDefinitionName:CreateModelQualityJobDefinition'$sel:modelQualityAppSpecification:CreateModelQualityJobDefinition':$sel:modelQualityJobInput:CreateModelQualityJobDefinition'$sel:modelQualityJobOutputConfig:CreateModelQualityJobDefinition'2$sel:jobResources:CreateModelQualityJobDefinition'-$sel:roleArn:CreateModelQualityJobDefinition'"newCreateModelQualityJobDefinition:createModelQualityJobDefinition_modelQualityBaselineConfig-createModelQualityJobDefinition_networkConfig1createModelQualityJobDefinition_stoppingCondition$createModelQualityJobDefinition_tags1createModelQualityJobDefinition_jobDefinitionName$sel:stoppingCondition:CreateModelExplainabilityJobDefinition'1$sel:tags:CreateModelExplainabilityJobDefinition'>$sel:jobDefinitionName:CreateModelExplainabilityJobDefinition'$sel:modelExplainabilityAppSpecification:CreateModelExplainabilityJobDefinition'$sel:modelExplainabilityJobInput:CreateModelExplainabilityJobDefinition'$sel:modelExplainabilityJobOutputConfig:CreateModelExplainabilityJobDefinition'9$sel:jobResources:CreateModelExplainabilityJobDefinition'4$sel:roleArn:CreateModelExplainabilityJobDefinition')newCreateModelExplainabilityJobDefinitioncreateModelExplainabilityJobDefinition_modelExplainabilityBaselineConfig4createModelExplainabilityJobDefinition_networkConfig8createModelExplainabilityJobDefinition_stoppingCondition+createModelExplainabilityJobDefinition_tags8createModelExplainabilityJobDefinition_jobDefinitionNamecreateModelExplainabilityJobDefinition_modelExplainabilityAppSpecificationcreateModelExplainabilityJobDefinition_modelExplainabilityJobInputcreateModelExplainabilityJobDefinition_modelExplainabilityJobOutputConfig3createModelExplainabilityJobDefinition_jobResources.createModelExplainabilityJobDefinition_roleArn1newCreateModelExplainabilityJobDefinitionResponse9createModelExplainabilityJobDefinitionResponse_httpStatus?createModelExplainabilityJobDefinitionResponse_jobDefinitionArn/$fToQueryCreateModelExplainabilityJobDefinition.$fToPathCreateModelExplainabilityJobDefinition.$fToJSONCreateModelExplainabilityJobDefinition1$fToHeadersCreateModelExplainabilityJobDefinition.$fNFDataCreateModelExplainabilityJobDefinition0$fHashableCreateModelExplainabilityJobDefinition6$fNFDataCreateModelExplainabilityJobDefinitionResponse2$fAWSRequestCreateModelExplainabilityJobDefinition2$fEqCreateModelExplainabilityJobDefinitionResponse4$fReadCreateModelExplainabilityJobDefinitionResponse4$fShowCreateModelExplainabilityJobDefinitionResponse7$fGenericCreateModelExplainabilityJobDefinitionResponse*$fEqCreateModelExplainabilityJobDefinition,$fReadCreateModelExplainabilityJobDefinition,$fShowCreateModelExplainabilityJobDefinition/$fGenericCreateModelExplainabilityJobDefinition CreateModelCardExportJobResponse!CreateModelCardExportJobResponse'1$sel:httpStatus:CreateModelCardExportJobResponse'<$sel:modelCardExportJobArn:CreateModelCardExportJobResponse'CreateModelCardExportJobCreateModelCardExportJob'/$sel:modelCardVersion:CreateModelCardExportJob',$sel:modelCardName:CreateModelCardExportJob'5$sel:modelCardExportJobName:CreateModelCardExportJob'+$sel:outputConfig:CreateModelCardExportJob'newCreateModelCardExportJob)createModelCardExportJob_modelCardVersion&createModelCardExportJob_modelCardName/createModelCardExportJob_modelCardExportJobName%createModelCardExportJob_outputConfig#newCreateModelCardExportJobResponse+createModelCardExportJobResponse_httpStatus6createModelCardExportJobResponse_modelCardExportJobArn!$fToQueryCreateModelCardExportJob $fToPathCreateModelCardExportJob $fToJSONCreateModelCardExportJob#$fToHeadersCreateModelCardExportJob $fNFDataCreateModelCardExportJob"$fHashableCreateModelCardExportJob($fNFDataCreateModelCardExportJobResponse$$fAWSRequestCreateModelCardExportJob$$fEqCreateModelCardExportJobResponse&$fReadCreateModelCardExportJobResponse&$fShowCreateModelCardExportJobResponse)$fGenericCreateModelCardExportJobResponse$fEqCreateModelCardExportJob$fReadCreateModelCardExportJob$fShowCreateModelCardExportJob!$fGenericCreateModelCardExportJobCreateModelCardResponseCreateModelCardResponse'($sel:httpStatus:CreateModelCardResponse'*$sel:modelCardArn:CreateModelCardResponse'CreateModelCardCreateModelCard'$$sel:securityConfig:CreateModelCard'$sel:tags:CreateModelCard'#$sel:modelCardName:CreateModelCard'$sel:content:CreateModelCard'%$sel:modelCardStatus:CreateModelCard'newCreateModelCardcreateModelCard_securityConfigcreateModelCard_tagscreateModelCard_modelCardNamecreateModelCard_contentcreateModelCard_modelCardStatusnewCreateModelCardResponse"createModelCardResponse_httpStatus$createModelCardResponse_modelCardArn$fToQueryCreateModelCard$fToPathCreateModelCard$fToJSONCreateModelCard$fToHeadersCreateModelCard$fNFDataCreateModelCard$fHashableCreateModelCard$fNFDataCreateModelCardResponse$fAWSRequestCreateModelCard$fEqCreateModelCardResponse$fReadCreateModelCardResponse$fShowCreateModelCardResponse $fGenericCreateModelCardResponse$fEqCreateModelCard$fShowCreateModelCard$fGenericCreateModelCard$CreateModelBiasJobDefinitionResponse%CreateModelBiasJobDefinitionResponse'5$sel:httpStatus:CreateModelBiasJobDefinitionResponse';$sel:jobDefinitionArn:CreateModelBiasJobDefinitionResponse'CreateModelBiasJobDefinitionCreateModelBiasJobDefinition':$sel:modelBiasBaselineConfig:CreateModelBiasJobDefinition'0$sel:networkConfig:CreateModelBiasJobDefinition'4$sel:stoppingCondition:CreateModelBiasJobDefinition''$sel:tags:CreateModelBiasJobDefinition'4$sel:jobDefinitionName:CreateModelBiasJobDefinition'<$sel:modelBiasAppSpecification:CreateModelBiasJobDefinition'4$sel:modelBiasJobInput:CreateModelBiasJobDefinition';$sel:modelBiasJobOutputConfig:CreateModelBiasJobDefinition'/$sel:jobResources:CreateModelBiasJobDefinition'*$sel:roleArn:CreateModelBiasJobDefinition'newCreateModelBiasJobDefinition4createModelBiasJobDefinition_modelBiasBaselineConfig*createModelBiasJobDefinition_networkConfig.createModelBiasJobDefinition_stoppingCondition!createModelBiasJobDefinition_tags.createModelBiasJobDefinition_jobDefinitionName6createModelBiasJobDefinition_modelBiasAppSpecification.createModelBiasJobDefinition_modelBiasJobInput5createModelBiasJobDefinition_modelBiasJobOutputConfig)createModelBiasJobDefinition_jobResources$createModelBiasJobDefinition_roleArn'newCreateModelBiasJobDefinitionResponse/createModelBiasJobDefinitionResponse_httpStatus5createModelBiasJobDefinitionResponse_jobDefinitionArn%$fToQueryCreateModelBiasJobDefinition$$fToPathCreateModelBiasJobDefinition$$fToJSONCreateModelBiasJobDefinition'$fToHeadersCreateModelBiasJobDefinition$$fNFDataCreateModelBiasJobDefinition&$fHashableCreateModelBiasJobDefinition,$fNFDataCreateModelBiasJobDefinitionResponse($fAWSRequestCreateModelBiasJobDefinition($fEqCreateModelBiasJobDefinitionResponse*$fReadCreateModelBiasJobDefinitionResponse*$fShowCreateModelBiasJobDefinitionResponse-$fGenericCreateModelBiasJobDefinitionResponse $fEqCreateModelBiasJobDefinition"$fReadCreateModelBiasJobDefinition"$fShowCreateModelBiasJobDefinition%$fGenericCreateModelBiasJobDefinitionCreateModelResponseCreateModelResponse'$$sel:httpStatus:CreateModelResponse'"$sel:modelArn:CreateModelResponse' CreateModel CreateModel'$sel:containers:CreateModel'($sel:enableNetworkIsolation:CreateModel'*$sel:inferenceExecutionConfig:CreateModel'"$sel:primaryContainer:CreateModel'$sel:tags:CreateModel'$sel:vpcConfig:CreateModel'$sel:modelName:CreateModel'"$sel:executionRoleArn:CreateModel'newCreateModelcreateModel_containers"createModel_enableNetworkIsolation$createModel_inferenceExecutionConfigcreateModel_primaryContainercreateModel_tagscreateModel_vpcConfigcreateModel_modelNamecreateModel_executionRoleArnnewCreateModelResponsecreateModelResponse_httpStatuscreateModelResponse_modelArn$fToQueryCreateModel$fToPathCreateModel$fToJSONCreateModel$fToHeadersCreateModel$fNFDataCreateModel$fHashableCreateModel$fNFDataCreateModelResponse$fAWSRequestCreateModel$fEqCreateModelResponse$fReadCreateModelResponse$fShowCreateModelResponse$fGenericCreateModelResponse$fEqCreateModel$fReadCreateModel$fShowCreateModel$fGenericCreateModelCreateLabelingJobResponseCreateLabelingJobResponse'*$sel:httpStatus:CreateLabelingJobResponse'.$sel:labelingJobArn:CreateLabelingJobResponse'CreateLabelingJobCreateLabelingJob'0$sel:labelCategoryConfigS3Uri:CreateLabelingJob'3$sel:labelingJobAlgorithmsConfig:CreateLabelingJob'*$sel:stoppingConditions:CreateLabelingJob'$sel:tags:CreateLabelingJob''$sel:labelingJobName:CreateLabelingJob'*$sel:labelAttributeName:CreateLabelingJob'#$sel:inputConfig:CreateLabelingJob'$$sel:outputConfig:CreateLabelingJob'$sel:roleArn:CreateLabelingJob''$sel:humanTaskConfig:CreateLabelingJob'newCreateLabelingJob*createLabelingJob_labelCategoryConfigS3Uri-createLabelingJob_labelingJobAlgorithmsConfig$createLabelingJob_stoppingConditionscreateLabelingJob_tags!createLabelingJob_labelingJobName$createLabelingJob_labelAttributeNamecreateLabelingJob_inputConfigcreateLabelingJob_outputConfigcreateLabelingJob_roleArn!createLabelingJob_humanTaskConfignewCreateLabelingJobResponse$createLabelingJobResponse_httpStatus(createLabelingJobResponse_labelingJobArn$fToQueryCreateLabelingJob$fToPathCreateLabelingJob$fToJSONCreateLabelingJob$fToHeadersCreateLabelingJob$fNFDataCreateLabelingJob$fHashableCreateLabelingJob!$fNFDataCreateLabelingJobResponse$fAWSRequestCreateLabelingJob$fEqCreateLabelingJobResponse$fReadCreateLabelingJobResponse$fShowCreateLabelingJobResponse"$fGenericCreateLabelingJobResponse$fEqCreateLabelingJob$fReadCreateLabelingJob$fShowCreateLabelingJob$fGenericCreateLabelingJob)CreateInferenceRecommendationsJobResponse*CreateInferenceRecommendationsJobResponse':$sel:httpStatus:CreateInferenceRecommendationsJobResponse'6$sel:jobArn:CreateInferenceRecommendationsJobResponse'!CreateInferenceRecommendationsJob"CreateInferenceRecommendationsJob'6$sel:jobDescription:CreateInferenceRecommendationsJob'4$sel:outputConfig:CreateInferenceRecommendationsJob':$sel:stoppingConditions:CreateInferenceRecommendationsJob',$sel:tags:CreateInferenceRecommendationsJob'/$sel:jobName:CreateInferenceRecommendationsJob'/$sel:jobType:CreateInferenceRecommendationsJob'/$sel:roleArn:CreateInferenceRecommendationsJob'3$sel:inputConfig:CreateInferenceRecommendationsJob'$newCreateInferenceRecommendationsJob0createInferenceRecommendationsJob_jobDescription.createInferenceRecommendationsJob_outputConfig4createInferenceRecommendationsJob_stoppingConditions&createInferenceRecommendationsJob_tags)createInferenceRecommendationsJob_jobName)createInferenceRecommendationsJob_jobType)createInferenceRecommendationsJob_roleArn-createInferenceRecommendationsJob_inputConfig,newCreateInferenceRecommendationsJobResponse4createInferenceRecommendationsJobResponse_httpStatus0createInferenceRecommendationsJobResponse_jobArn*$fToQueryCreateInferenceRecommendationsJob)$fToPathCreateInferenceRecommendationsJob)$fToJSONCreateInferenceRecommendationsJob,$fToHeadersCreateInferenceRecommendationsJob)$fNFDataCreateInferenceRecommendationsJob+$fHashableCreateInferenceRecommendationsJob1$fNFDataCreateInferenceRecommendationsJobResponse-$fAWSRequestCreateInferenceRecommendationsJob-$fEqCreateInferenceRecommendationsJobResponse/$fReadCreateInferenceRecommendationsJobResponse/$fShowCreateInferenceRecommendationsJobResponse2$fGenericCreateInferenceRecommendationsJobResponse%$fEqCreateInferenceRecommendationsJob'$fReadCreateInferenceRecommendationsJob'$fShowCreateInferenceRecommendationsJob*$fGenericCreateInferenceRecommendationsJob!CreateInferenceExperimentResponse"CreateInferenceExperimentResponse'2$sel:httpStatus:CreateInferenceExperimentResponse'>$sel:inferenceExperimentArn:CreateInferenceExperimentResponse'CreateInferenceExperimentCreateInferenceExperiment'1$sel:dataStorageConfig:CreateInferenceExperiment'+$sel:description:CreateInferenceExperiment'&$sel:kmsKey:CreateInferenceExperiment'($sel:schedule:CreateInferenceExperiment'$$sel:tags:CreateInferenceExperiment'$$sel:name:CreateInferenceExperiment'%$sel:type':CreateInferenceExperiment''$sel:roleArn:CreateInferenceExperiment',$sel:endpointName:CreateInferenceExperiment'-$sel:modelVariants:CreateInferenceExperiment'0$sel:shadowModeConfig:CreateInferenceExperiment'newCreateInferenceExperiment+createInferenceExperiment_dataStorageConfig%createInferenceExperiment_description createInferenceExperiment_kmsKey"createInferenceExperiment_schedulecreateInferenceExperiment_tagscreateInferenceExperiment_namecreateInferenceExperiment_type!createInferenceExperiment_roleArn&createInferenceExperiment_endpointName'createInferenceExperiment_modelVariants*createInferenceExperiment_shadowModeConfig$newCreateInferenceExperimentResponse,createInferenceExperimentResponse_httpStatus8createInferenceExperimentResponse_inferenceExperimentArn"$fToQueryCreateInferenceExperiment!$fToPathCreateInferenceExperiment!$fToJSONCreateInferenceExperiment$$fToHeadersCreateInferenceExperiment!$fNFDataCreateInferenceExperiment#$fHashableCreateInferenceExperiment)$fNFDataCreateInferenceExperimentResponse%$fAWSRequestCreateInferenceExperiment%$fEqCreateInferenceExperimentResponse'$fReadCreateInferenceExperimentResponse'$fShowCreateInferenceExperimentResponse*$fGenericCreateInferenceExperimentResponse$fEqCreateInferenceExperiment$fReadCreateInferenceExperiment$fShowCreateInferenceExperiment"$fGenericCreateInferenceExperimentCreateImageVersionResponseCreateImageVersionResponse'0$sel:imageVersionArn:CreateImageVersionResponse'+$sel:httpStatus:CreateImageVersionResponse'CreateImageVersionCreateImageVersion' $sel:aliases:CreateImageVersion' $sel:horovod:CreateImageVersion' $sel:jobType:CreateImageVersion'$$sel:mLFramework:CreateImageVersion'"$sel:processor:CreateImageVersion'($sel:programmingLang:CreateImageVersion'%$sel:releaseNotes:CreateImageVersion''$sel:vendorGuidance:CreateImageVersion'"$sel:baseImage:CreateImageVersion'$$sel:clientToken:CreateImageVersion'"$sel:imageName:CreateImageVersion'newCreateImageVersioncreateImageVersion_aliasescreateImageVersion_horovodcreateImageVersion_jobTypecreateImageVersion_mLFrameworkcreateImageVersion_processor"createImageVersion_programmingLangcreateImageVersion_releaseNotes!createImageVersion_vendorGuidancecreateImageVersion_baseImagecreateImageVersion_clientTokencreateImageVersion_imageNamenewCreateImageVersionResponse*createImageVersionResponse_imageVersionArn%createImageVersionResponse_httpStatus$fToQueryCreateImageVersion$fToPathCreateImageVersion$fToJSONCreateImageVersion$fToHeadersCreateImageVersion$fNFDataCreateImageVersion$fHashableCreateImageVersion"$fNFDataCreateImageVersionResponse$fAWSRequestCreateImageVersion$fEqCreateImageVersionResponse $fReadCreateImageVersionResponse $fShowCreateImageVersionResponse#$fGenericCreateImageVersionResponse$fEqCreateImageVersion$fReadCreateImageVersion$fShowCreateImageVersion$fGenericCreateImageVersionCreateImageResponseCreateImageResponse'"$sel:imageArn:CreateImageResponse'$$sel:httpStatus:CreateImageResponse' CreateImage CreateImage'$sel:description:CreateImage'$sel:displayName:CreateImage'$sel:tags:CreateImage'$sel:imageName:CreateImage'$sel:roleArn:CreateImage'newCreateImagecreateImage_descriptioncreateImage_displayNamecreateImage_tagscreateImage_imageNamecreateImage_roleArnnewCreateImageResponsecreateImageResponse_imageArncreateImageResponse_httpStatus$fToQueryCreateImage$fToPathCreateImage$fToJSONCreateImage$fToHeadersCreateImage$fNFDataCreateImage$fHashableCreateImage$fNFDataCreateImageResponse$fAWSRequestCreateImage$fEqCreateImageResponse$fReadCreateImageResponse$fShowCreateImageResponse$fGenericCreateImageResponse$fEqCreateImage$fReadCreateImage$fShowCreateImage$fGenericCreateImage%CreateHyperParameterTuningJobResponse&CreateHyperParameterTuningJobResponse'6$sel:httpStatus:CreateHyperParameterTuningJobResponse'$sel:hyperParameterTuningJobArn:CreateHyperParameterTuningJobResponse'CreateHyperParameterTuningJobCreateHyperParameterTuningJob'($sel:tags:CreateHyperParameterTuningJob'9$sel:trainingJobDefinition:CreateHyperParameterTuningJob':$sel:trainingJobDefinitions:CreateHyperParameterTuningJob'3$sel:warmStartConfig:CreateHyperParameterTuningJob'?$sel:hyperParameterTuningJobName:CreateHyperParameterTuningJob'$sel:hyperParameterTuningJobConfig:CreateHyperParameterTuningJob' newCreateHyperParameterTuningJob"createHyperParameterTuningJob_tags3createHyperParameterTuningJob_trainingJobDefinition4createHyperParameterTuningJob_trainingJobDefinitions-createHyperParameterTuningJob_warmStartConfig9createHyperParameterTuningJob_hyperParameterTuningJobName;createHyperParameterTuningJob_hyperParameterTuningJobConfig(newCreateHyperParameterTuningJobResponse0createHyperParameterTuningJobResponse_httpStatuscreateHyperParameterTuningJobResponse_hyperParameterTuningJobArn&$fToQueryCreateHyperParameterTuningJob%$fToPathCreateHyperParameterTuningJob%$fToJSONCreateHyperParameterTuningJob($fToHeadersCreateHyperParameterTuningJob%$fNFDataCreateHyperParameterTuningJob'$fHashableCreateHyperParameterTuningJob-$fNFDataCreateHyperParameterTuningJobResponse)$fAWSRequestCreateHyperParameterTuningJob)$fEqCreateHyperParameterTuningJobResponse+$fReadCreateHyperParameterTuningJobResponse+$fShowCreateHyperParameterTuningJobResponse.$fGenericCreateHyperParameterTuningJobResponse!$fEqCreateHyperParameterTuningJob#$fReadCreateHyperParameterTuningJob#$fShowCreateHyperParameterTuningJob&$fGenericCreateHyperParameterTuningJobCreateHumanTaskUiResponseCreateHumanTaskUiResponse'*$sel:httpStatus:CreateHumanTaskUiResponse'.$sel:humanTaskUiArn:CreateHumanTaskUiResponse'CreateHumanTaskUiCreateHumanTaskUi'$sel:tags:CreateHumanTaskUi''$sel:humanTaskUiName:CreateHumanTaskUi'"$sel:uiTemplate:CreateHumanTaskUi'newCreateHumanTaskUicreateHumanTaskUi_tags!createHumanTaskUi_humanTaskUiNamecreateHumanTaskUi_uiTemplatenewCreateHumanTaskUiResponse$createHumanTaskUiResponse_httpStatus(createHumanTaskUiResponse_humanTaskUiArn$fToQueryCreateHumanTaskUi$fToPathCreateHumanTaskUi$fToJSONCreateHumanTaskUi$fToHeadersCreateHumanTaskUi$fNFDataCreateHumanTaskUi$fHashableCreateHumanTaskUi!$fNFDataCreateHumanTaskUiResponse$fAWSRequestCreateHumanTaskUi$fEqCreateHumanTaskUiResponse$fReadCreateHumanTaskUiResponse$fShowCreateHumanTaskUiResponse"$fGenericCreateHumanTaskUiResponse$fEqCreateHumanTaskUi$fReadCreateHumanTaskUi$fShowCreateHumanTaskUi$fGenericCreateHumanTaskUiCreateHubResponseCreateHubResponse'"$sel:httpStatus:CreateHubResponse'$sel:hubArn:CreateHubResponse' CreateHub CreateHub'$sel:hubDisplayName:CreateHub'!$sel:hubSearchKeywords:CreateHub'$sel:s3StorageConfig:CreateHub'$sel:tags:CreateHub'$sel:hubName:CreateHub'$sel:hubDescription:CreateHub' newCreateHubcreateHub_hubDisplayNamecreateHub_hubSearchKeywordscreateHub_s3StorageConfigcreateHub_tagscreateHub_hubNamecreateHub_hubDescriptionnewCreateHubResponsecreateHubResponse_httpStatuscreateHubResponse_hubArn$fToQueryCreateHub$fToPathCreateHub$fToJSONCreateHub$fToHeadersCreateHub$fNFDataCreateHub$fHashableCreateHub$fNFDataCreateHubResponse$fAWSRequestCreateHub$fEqCreateHubResponse$fReadCreateHubResponse$fShowCreateHubResponse$fGenericCreateHubResponse $fEqCreateHub$fReadCreateHub$fShowCreateHub$fGenericCreateHubCreateFlowDefinitionResponseCreateFlowDefinitionResponse'-$sel:httpStatus:CreateFlowDefinitionResponse'4$sel:flowDefinitionArn:CreateFlowDefinitionResponse'CreateFlowDefinitionCreateFlowDefinition'4$sel:humanLoopActivationConfig:CreateFlowDefinition'1$sel:humanLoopRequestSource:CreateFlowDefinition'$sel:tags:CreateFlowDefinition'-$sel:flowDefinitionName:CreateFlowDefinition'*$sel:humanLoopConfig:CreateFlowDefinition''$sel:outputConfig:CreateFlowDefinition'"$sel:roleArn:CreateFlowDefinition'newCreateFlowDefinition.createFlowDefinition_humanLoopActivationConfig+createFlowDefinition_humanLoopRequestSourcecreateFlowDefinition_tags'createFlowDefinition_flowDefinitionName$createFlowDefinition_humanLoopConfig!createFlowDefinition_outputConfigcreateFlowDefinition_roleArnnewCreateFlowDefinitionResponse'createFlowDefinitionResponse_httpStatus.createFlowDefinitionResponse_flowDefinitionArn$fToQueryCreateFlowDefinition$fToPathCreateFlowDefinition$fToJSONCreateFlowDefinition$fToHeadersCreateFlowDefinition$fNFDataCreateFlowDefinition$fHashableCreateFlowDefinition$$fNFDataCreateFlowDefinitionResponse $fAWSRequestCreateFlowDefinition $fEqCreateFlowDefinitionResponse"$fReadCreateFlowDefinitionResponse"$fShowCreateFlowDefinitionResponse%$fGenericCreateFlowDefinitionResponse$fEqCreateFlowDefinition$fReadCreateFlowDefinition$fShowCreateFlowDefinition$fGenericCreateFlowDefinitionCreateFeatureGroupResponseCreateFeatureGroupResponse'+$sel:httpStatus:CreateFeatureGroupResponse'0$sel:featureGroupArn:CreateFeatureGroupResponse'CreateFeatureGroupCreateFeatureGroup'$$sel:description:CreateFeatureGroup'+$sel:offlineStoreConfig:CreateFeatureGroup'*$sel:onlineStoreConfig:CreateFeatureGroup' $sel:roleArn:CreateFeatureGroup'$sel:tags:CreateFeatureGroup')$sel:featureGroupName:CreateFeatureGroup'4$sel:recordIdentifierFeatureName:CreateFeatureGroup'-$sel:eventTimeFeatureName:CreateFeatureGroup'+$sel:featureDefinitions:CreateFeatureGroup'newCreateFeatureGroupcreateFeatureGroup_description%createFeatureGroup_offlineStoreConfig$createFeatureGroup_onlineStoreConfigcreateFeatureGroup_roleArncreateFeatureGroup_tags#createFeatureGroup_featureGroupName.createFeatureGroup_recordIdentifierFeatureName'createFeatureGroup_eventTimeFeatureName%createFeatureGroup_featureDefinitionsnewCreateFeatureGroupResponse%createFeatureGroupResponse_httpStatus*createFeatureGroupResponse_featureGroupArn$fToQueryCreateFeatureGroup$fToPathCreateFeatureGroup$fToJSONCreateFeatureGroup$fToHeadersCreateFeatureGroup$fNFDataCreateFeatureGroup$fHashableCreateFeatureGroup"$fNFDataCreateFeatureGroupResponse$fAWSRequestCreateFeatureGroup$fEqCreateFeatureGroupResponse $fReadCreateFeatureGroupResponse $fShowCreateFeatureGroupResponse#$fGenericCreateFeatureGroupResponse$fEqCreateFeatureGroup$fReadCreateFeatureGroup$fShowCreateFeatureGroup$fGenericCreateFeatureGroupCreateExperimentResponseCreateExperimentResponse',$sel:experimentArn:CreateExperimentResponse')$sel:httpStatus:CreateExperimentResponse'CreateExperimentCreateExperiment'"$sel:description:CreateExperiment'"$sel:displayName:CreateExperiment'$sel:tags:CreateExperiment'%$sel:experimentName:CreateExperiment'newCreateExperimentcreateExperiment_descriptioncreateExperiment_displayNamecreateExperiment_tagscreateExperiment_experimentNamenewCreateExperimentResponse&createExperimentResponse_experimentArn#createExperimentResponse_httpStatus$fToQueryCreateExperiment$fToPathCreateExperiment$fToJSONCreateExperiment$fToHeadersCreateExperiment$fNFDataCreateExperiment$fHashableCreateExperiment $fNFDataCreateExperimentResponse$fAWSRequestCreateExperiment$fEqCreateExperimentResponse$fReadCreateExperimentResponse$fShowCreateExperimentResponse!$fGenericCreateExperimentResponse$fEqCreateExperiment$fReadCreateExperiment$fShowCreateExperiment$fGenericCreateExperimentCreateEndpointConfigResponseCreateEndpointConfigResponse'-$sel:httpStatus:CreateEndpointConfigResponse'4$sel:endpointConfigArn:CreateEndpointConfigResponse'CreateEndpointConfigCreateEndpointConfig'/$sel:asyncInferenceConfig:CreateEndpointConfig',$sel:dataCaptureConfig:CreateEndpointConfig'*$sel:explainerConfig:CreateEndpointConfig'#$sel:kmsKeyId:CreateEndpointConfig'3$sel:shadowProductionVariants:CreateEndpointConfig'$sel:tags:CreateEndpointConfig'-$sel:endpointConfigName:CreateEndpointConfig'-$sel:productionVariants:CreateEndpointConfig'newCreateEndpointConfig)createEndpointConfig_asyncInferenceConfig&createEndpointConfig_dataCaptureConfig$createEndpointConfig_explainerConfigcreateEndpointConfig_kmsKeyId-createEndpointConfig_shadowProductionVariantscreateEndpointConfig_tags'createEndpointConfig_endpointConfigName'createEndpointConfig_productionVariantsnewCreateEndpointConfigResponse'createEndpointConfigResponse_httpStatus.createEndpointConfigResponse_endpointConfigArn$fToQueryCreateEndpointConfig$fToPathCreateEndpointConfig$fToJSONCreateEndpointConfig$fToHeadersCreateEndpointConfig$fNFDataCreateEndpointConfig$fHashableCreateEndpointConfig$$fNFDataCreateEndpointConfigResponse $fAWSRequestCreateEndpointConfig $fEqCreateEndpointConfigResponse"$fReadCreateEndpointConfigResponse"$fShowCreateEndpointConfigResponse%$fGenericCreateEndpointConfigResponse$fEqCreateEndpointConfig$fReadCreateEndpointConfig$fShowCreateEndpointConfig$fGenericCreateEndpointConfigCreateEndpointResponseCreateEndpointResponse''$sel:httpStatus:CreateEndpointResponse'($sel:endpointArn:CreateEndpointResponse'CreateEndpointCreateEndpoint'%$sel:deploymentConfig:CreateEndpoint'$sel:tags:CreateEndpoint'!$sel:endpointName:CreateEndpoint''$sel:endpointConfigName:CreateEndpoint'newCreateEndpointcreateEndpoint_deploymentConfigcreateEndpoint_tagscreateEndpoint_endpointName!createEndpoint_endpointConfigNamenewCreateEndpointResponse!createEndpointResponse_httpStatus"createEndpointResponse_endpointArn$fToQueryCreateEndpoint$fToPathCreateEndpoint$fToJSONCreateEndpoint$fToHeadersCreateEndpoint$fNFDataCreateEndpoint$fHashableCreateEndpoint$fNFDataCreateEndpointResponse$fAWSRequestCreateEndpoint$fEqCreateEndpointResponse$fReadCreateEndpointResponse$fShowCreateEndpointResponse$fGenericCreateEndpointResponse$fEqCreateEndpoint$fReadCreateEndpoint$fShowCreateEndpoint$fGenericCreateEndpointCreateEdgePackagingJobResponseCreateEdgePackagingJobResponse'CreateEdgePackagingJobCreateEdgePackagingJob'($sel:resourceKey:CreateEdgePackagingJob'!$sel:tags:CreateEdgePackagingJob'1$sel:edgePackagingJobName:CreateEdgePackagingJob'/$sel:compilationJobName:CreateEdgePackagingJob'&$sel:modelName:CreateEdgePackagingJob')$sel:modelVersion:CreateEdgePackagingJob'$$sel:roleArn:CreateEdgePackagingJob')$sel:outputConfig:CreateEdgePackagingJob'newCreateEdgePackagingJob"createEdgePackagingJob_resourceKeycreateEdgePackagingJob_tags+createEdgePackagingJob_edgePackagingJobName)createEdgePackagingJob_compilationJobName createEdgePackagingJob_modelName#createEdgePackagingJob_modelVersioncreateEdgePackagingJob_roleArn#createEdgePackagingJob_outputConfig!newCreateEdgePackagingJobResponse$fToQueryCreateEdgePackagingJob$fToPathCreateEdgePackagingJob$fToJSONCreateEdgePackagingJob!$fToHeadersCreateEdgePackagingJob$fNFDataCreateEdgePackagingJob $fHashableCreateEdgePackagingJob&$fNFDataCreateEdgePackagingJobResponse"$fAWSRequestCreateEdgePackagingJob"$fEqCreateEdgePackagingJobResponse$$fReadCreateEdgePackagingJobResponse$$fShowCreateEdgePackagingJobResponse'$fGenericCreateEdgePackagingJobResponse$fEqCreateEdgePackagingJob$fReadCreateEdgePackagingJob$fShowCreateEdgePackagingJob$fGenericCreateEdgePackagingJob!CreateEdgeDeploymentStageResponse"CreateEdgeDeploymentStageResponse'CreateEdgeDeploymentStageCreateEdgeDeploymentStage'6$sel:edgeDeploymentPlanName:CreateEdgeDeploymentStage'&$sel:stages:CreateEdgeDeploymentStage'newCreateEdgeDeploymentStage0createEdgeDeploymentStage_edgeDeploymentPlanName createEdgeDeploymentStage_stages$newCreateEdgeDeploymentStageResponse"$fToQueryCreateEdgeDeploymentStage!$fToPathCreateEdgeDeploymentStage!$fToJSONCreateEdgeDeploymentStage$$fToHeadersCreateEdgeDeploymentStage!$fNFDataCreateEdgeDeploymentStage#$fHashableCreateEdgeDeploymentStage)$fNFDataCreateEdgeDeploymentStageResponse%$fAWSRequestCreateEdgeDeploymentStage%$fEqCreateEdgeDeploymentStageResponse'$fReadCreateEdgeDeploymentStageResponse'$fShowCreateEdgeDeploymentStageResponse*$fGenericCreateEdgeDeploymentStageResponse$fEqCreateEdgeDeploymentStage$fReadCreateEdgeDeploymentStage$fShowCreateEdgeDeploymentStage"$fGenericCreateEdgeDeploymentStage CreateEdgeDeploymentPlanResponse!CreateEdgeDeploymentPlanResponse'1$sel:httpStatus:CreateEdgeDeploymentPlanResponse'<$sel:edgeDeploymentPlanArn:CreateEdgeDeploymentPlanResponse'CreateEdgeDeploymentPlanCreateEdgeDeploymentPlan'%$sel:stages:CreateEdgeDeploymentPlan'#$sel:tags:CreateEdgeDeploymentPlan'5$sel:edgeDeploymentPlanName:CreateEdgeDeploymentPlan'+$sel:modelConfigs:CreateEdgeDeploymentPlan'.$sel:deviceFleetName:CreateEdgeDeploymentPlan'newCreateEdgeDeploymentPlancreateEdgeDeploymentPlan_stagescreateEdgeDeploymentPlan_tags/createEdgeDeploymentPlan_edgeDeploymentPlanName%createEdgeDeploymentPlan_modelConfigs(createEdgeDeploymentPlan_deviceFleetName#newCreateEdgeDeploymentPlanResponse+createEdgeDeploymentPlanResponse_httpStatus6createEdgeDeploymentPlanResponse_edgeDeploymentPlanArn!$fToQueryCreateEdgeDeploymentPlan $fToPathCreateEdgeDeploymentPlan $fToJSONCreateEdgeDeploymentPlan#$fToHeadersCreateEdgeDeploymentPlan $fNFDataCreateEdgeDeploymentPlan"$fHashableCreateEdgeDeploymentPlan($fNFDataCreateEdgeDeploymentPlanResponse$$fAWSRequestCreateEdgeDeploymentPlan$$fEqCreateEdgeDeploymentPlanResponse&$fReadCreateEdgeDeploymentPlanResponse&$fShowCreateEdgeDeploymentPlanResponse)$fGenericCreateEdgeDeploymentPlanResponse$fEqCreateEdgeDeploymentPlan$fReadCreateEdgeDeploymentPlan$fShowCreateEdgeDeploymentPlan!$fGenericCreateEdgeDeploymentPlanCreateDomainResponseCreateDomainResponse'$$sel:domainArn:CreateDomainResponse'$sel:url:CreateDomainResponse'%$sel:httpStatus:CreateDomainResponse' CreateDomain CreateDomain''$sel:appNetworkAccessType:CreateDomain'-$sel:appSecurityGroupManagement:CreateDomain''$sel:defaultSpaceSettings:CreateDomain'!$sel:domainSettings:CreateDomain',$sel:homeEfsFileSystemKmsKeyId:CreateDomain'$sel:kmsKeyId:CreateDomain'$sel:tags:CreateDomain'$sel:domainName:CreateDomain'$sel:authMode:CreateDomain'&$sel:defaultUserSettings:CreateDomain'$sel:subnetIds:CreateDomain'$sel:vpcId:CreateDomain'newCreateDomain!createDomain_appNetworkAccessType'createDomain_appSecurityGroupManagement!createDomain_defaultSpaceSettingscreateDomain_domainSettings&createDomain_homeEfsFileSystemKmsKeyIdcreateDomain_kmsKeyIdcreateDomain_tagscreateDomain_domainNamecreateDomain_authMode createDomain_defaultUserSettingscreateDomain_subnetIdscreateDomain_vpcIdnewCreateDomainResponsecreateDomainResponse_domainArncreateDomainResponse_urlcreateDomainResponse_httpStatus$fToQueryCreateDomain$fToPathCreateDomain$fToJSONCreateDomain$fToHeadersCreateDomain$fNFDataCreateDomain$fHashableCreateDomain$fNFDataCreateDomainResponse$fAWSRequestCreateDomain$fEqCreateDomainResponse$fReadCreateDomainResponse$fShowCreateDomainResponse$fGenericCreateDomainResponse$fEqCreateDomain$fReadCreateDomain$fShowCreateDomain$fGenericCreateDomainCreateDeviceFleetResponseCreateDeviceFleetResponse'CreateDeviceFleetCreateDeviceFleet'#$sel:description:CreateDeviceFleet'*$sel:enableIotRoleAlias:CreateDeviceFleet'$sel:roleArn:CreateDeviceFleet'$sel:tags:CreateDeviceFleet''$sel:deviceFleetName:CreateDeviceFleet'$$sel:outputConfig:CreateDeviceFleet'newCreateDeviceFleetcreateDeviceFleet_description$createDeviceFleet_enableIotRoleAliascreateDeviceFleet_roleArncreateDeviceFleet_tags!createDeviceFleet_deviceFleetNamecreateDeviceFleet_outputConfignewCreateDeviceFleetResponse$fToQueryCreateDeviceFleet$fToPathCreateDeviceFleet$fToJSONCreateDeviceFleet$fToHeadersCreateDeviceFleet$fNFDataCreateDeviceFleet$fHashableCreateDeviceFleet!$fNFDataCreateDeviceFleetResponse$fAWSRequestCreateDeviceFleet$fEqCreateDeviceFleetResponse$fReadCreateDeviceFleetResponse$fShowCreateDeviceFleetResponse"$fGenericCreateDeviceFleetResponse$fEqCreateDeviceFleet$fReadCreateDeviceFleet$fShowCreateDeviceFleet$fGenericCreateDeviceFleet&CreateDataQualityJobDefinitionResponse'CreateDataQualityJobDefinitionResponse'7$sel:httpStatus:CreateDataQualityJobDefinitionResponse'=$sel:jobDefinitionArn:CreateDataQualityJobDefinitionResponse'CreateDataQualityJobDefinitionCreateDataQualityJobDefinition'>$sel:dataQualityBaselineConfig:CreateDataQualityJobDefinition'2$sel:networkConfig:CreateDataQualityJobDefinition'6$sel:stoppingCondition:CreateDataQualityJobDefinition')$sel:tags:CreateDataQualityJobDefinition'6$sel:jobDefinitionName:CreateDataQualityJobDefinition'$sel:dataQualityAppSpecification:CreateDataQualityJobDefinition'8$sel:dataQualityJobInput:CreateDataQualityJobDefinition'?$sel:dataQualityJobOutputConfig:CreateDataQualityJobDefinition'1$sel:jobResources:CreateDataQualityJobDefinition',$sel:roleArn:CreateDataQualityJobDefinition'!newCreateDataQualityJobDefinition8createDataQualityJobDefinition_dataQualityBaselineConfig,createDataQualityJobDefinition_networkConfig0createDataQualityJobDefinition_stoppingCondition#createDataQualityJobDefinition_tags0createDataQualityJobDefinition_jobDefinitionName:createDataQualityJobDefinition_dataQualityAppSpecification2createDataQualityJobDefinition_dataQualityJobInput9createDataQualityJobDefinition_dataQualityJobOutputConfig+createDataQualityJobDefinition_jobResources&createDataQualityJobDefinition_roleArn)newCreateDataQualityJobDefinitionResponse1createDataQualityJobDefinitionResponse_httpStatus7createDataQualityJobDefinitionResponse_jobDefinitionArn'$fToQueryCreateDataQualityJobDefinition&$fToPathCreateDataQualityJobDefinition&$fToJSONCreateDataQualityJobDefinition)$fToHeadersCreateDataQualityJobDefinition&$fNFDataCreateDataQualityJobDefinition($fHashableCreateDataQualityJobDefinition.$fNFDataCreateDataQualityJobDefinitionResponse*$fAWSRequestCreateDataQualityJobDefinition*$fEqCreateDataQualityJobDefinitionResponse,$fReadCreateDataQualityJobDefinitionResponse,$fShowCreateDataQualityJobDefinitionResponse/$fGenericCreateDataQualityJobDefinitionResponse"$fEqCreateDataQualityJobDefinition$$fReadCreateDataQualityJobDefinition$$fShowCreateDataQualityJobDefinition'$fGenericCreateDataQualityJobDefinitionCreateContextResponseCreateContextResponse'&$sel:contextArn:CreateContextResponse'&$sel:httpStatus:CreateContextResponse' CreateContextCreateContext'$sel:description:CreateContext'$sel:properties:CreateContext'$sel:tags:CreateContext'$sel:contextName:CreateContext'$sel:source:CreateContext'$sel:contextType:CreateContext'newCreateContextcreateContext_descriptioncreateContext_propertiescreateContext_tagscreateContext_contextNamecreateContext_sourcecreateContext_contextTypenewCreateContextResponse createContextResponse_contextArn createContextResponse_httpStatus$fToQueryCreateContext$fToPathCreateContext$fToJSONCreateContext$fToHeadersCreateContext$fNFDataCreateContext$fHashableCreateContext$fNFDataCreateContextResponse$fAWSRequestCreateContext$fEqCreateContextResponse$fReadCreateContextResponse$fShowCreateContextResponse$fGenericCreateContextResponse$fEqCreateContext$fReadCreateContext$fShowCreateContext$fGenericCreateContextCreateCompilationJobResponseCreateCompilationJobResponse'-$sel:httpStatus:CreateCompilationJobResponse'4$sel:compilationJobArn:CreateCompilationJobResponse'CreateCompilationJobCreateCompilationJob'&$sel:inputConfig:CreateCompilationJob'1$sel:modelPackageVersionArn:CreateCompilationJob'$sel:tags:CreateCompilationJob'$$sel:vpcConfig:CreateCompilationJob'-$sel:compilationJobName:CreateCompilationJob'"$sel:roleArn:CreateCompilationJob''$sel:outputConfig:CreateCompilationJob',$sel:stoppingCondition:CreateCompilationJob'newCreateCompilationJob createCompilationJob_inputConfig+createCompilationJob_modelPackageVersionArncreateCompilationJob_tagscreateCompilationJob_vpcConfig'createCompilationJob_compilationJobNamecreateCompilationJob_roleArn!createCompilationJob_outputConfig&createCompilationJob_stoppingConditionnewCreateCompilationJobResponse'createCompilationJobResponse_httpStatus.createCompilationJobResponse_compilationJobArn$fToQueryCreateCompilationJob$fToPathCreateCompilationJob$fToJSONCreateCompilationJob$fToHeadersCreateCompilationJob$fNFDataCreateCompilationJob$fHashableCreateCompilationJob$$fNFDataCreateCompilationJobResponse $fAWSRequestCreateCompilationJob $fEqCreateCompilationJobResponse"$fReadCreateCompilationJobResponse"$fShowCreateCompilationJobResponse%$fGenericCreateCompilationJobResponse$fEqCreateCompilationJob$fReadCreateCompilationJob$fShowCreateCompilationJob$fGenericCreateCompilationJobCreateCodeRepositoryResponseCreateCodeRepositoryResponse'-$sel:httpStatus:CreateCodeRepositoryResponse'4$sel:codeRepositoryArn:CreateCodeRepositoryResponse'CreateCodeRepositoryCreateCodeRepository'$sel:tags:CreateCodeRepository'-$sel:codeRepositoryName:CreateCodeRepository'$$sel:gitConfig:CreateCodeRepository'newCreateCodeRepositorycreateCodeRepository_tags'createCodeRepository_codeRepositoryNamecreateCodeRepository_gitConfignewCreateCodeRepositoryResponse'createCodeRepositoryResponse_httpStatus.createCodeRepositoryResponse_codeRepositoryArn$fToQueryCreateCodeRepository$fToPathCreateCodeRepository$fToJSONCreateCodeRepository$fToHeadersCreateCodeRepository$fNFDataCreateCodeRepository$fHashableCreateCodeRepository$$fNFDataCreateCodeRepositoryResponse $fAWSRequestCreateCodeRepository $fEqCreateCodeRepositoryResponse"$fReadCreateCodeRepositoryResponse"$fShowCreateCodeRepositoryResponse%$fGenericCreateCodeRepositoryResponse$fEqCreateCodeRepository$fReadCreateCodeRepository$fShowCreateCodeRepository$fGenericCreateCodeRepositoryCreateAutoMLJobResponseCreateAutoMLJobResponse'($sel:httpStatus:CreateAutoMLJobResponse'*$sel:autoMLJobArn:CreateAutoMLJobResponse'CreateAutoMLJobCreateAutoMLJob'%$sel:autoMLJobConfig:CreateAutoMLJob'($sel:autoMLJobObjective:CreateAutoMLJob'6$sel:generateCandidateDefinitionsOnly:CreateAutoMLJob''$sel:modelDeployConfig:CreateAutoMLJob'!$sel:problemType:CreateAutoMLJob'$sel:tags:CreateAutoMLJob'#$sel:autoMLJobName:CreateAutoMLJob'%$sel:inputDataConfig:CreateAutoMLJob'&$sel:outputDataConfig:CreateAutoMLJob'$sel:roleArn:CreateAutoMLJob'newCreateAutoMLJobcreateAutoMLJob_autoMLJobConfig"createAutoMLJob_autoMLJobObjective0createAutoMLJob_generateCandidateDefinitionsOnly!createAutoMLJob_modelDeployConfigcreateAutoMLJob_problemTypecreateAutoMLJob_tagscreateAutoMLJob_autoMLJobNamecreateAutoMLJob_inputDataConfig createAutoMLJob_outputDataConfigcreateAutoMLJob_roleArnnewCreateAutoMLJobResponse"createAutoMLJobResponse_httpStatus$createAutoMLJobResponse_autoMLJobArn$fToQueryCreateAutoMLJob$fToPathCreateAutoMLJob$fToJSONCreateAutoMLJob$fToHeadersCreateAutoMLJob$fNFDataCreateAutoMLJob$fHashableCreateAutoMLJob$fNFDataCreateAutoMLJobResponse$fAWSRequestCreateAutoMLJob$fEqCreateAutoMLJobResponse$fReadCreateAutoMLJobResponse$fShowCreateAutoMLJobResponse $fGenericCreateAutoMLJobResponse$fEqCreateAutoMLJob$fReadCreateAutoMLJob$fShowCreateAutoMLJob$fGenericCreateAutoMLJobCreateArtifactResponseCreateArtifactResponse'($sel:artifactArn:CreateArtifactResponse''$sel:httpStatus:CreateArtifactResponse'CreateArtifactCreateArtifact'!$sel:artifactName:CreateArtifact''$sel:metadataProperties:CreateArtifact'$sel:properties:CreateArtifact'$sel:tags:CreateArtifact'$sel:source:CreateArtifact'!$sel:artifactType:CreateArtifact'newCreateArtifactcreateArtifact_artifactName!createArtifact_metadataPropertiescreateArtifact_propertiescreateArtifact_tagscreateArtifact_sourcecreateArtifact_artifactTypenewCreateArtifactResponse"createArtifactResponse_artifactArn!createArtifactResponse_httpStatus$fToQueryCreateArtifact$fToPathCreateArtifact$fToJSONCreateArtifact$fToHeadersCreateArtifact$fNFDataCreateArtifact$fHashableCreateArtifact$fNFDataCreateArtifactResponse$fAWSRequestCreateArtifact$fEqCreateArtifactResponse$fReadCreateArtifactResponse$fShowCreateArtifactResponse$fGenericCreateArtifactResponse$fEqCreateArtifact$fReadCreateArtifact$fShowCreateArtifact$fGenericCreateArtifactCreateAppImageConfigResponseCreateAppImageConfigResponse'4$sel:appImageConfigArn:CreateAppImageConfigResponse'-$sel:httpStatus:CreateAppImageConfigResponse'CreateAppImageConfigCreateAppImageConfig'3$sel:kernelGatewayImageConfig:CreateAppImageConfig'$sel:tags:CreateAppImageConfig'-$sel:appImageConfigName:CreateAppImageConfig'newCreateAppImageConfig-createAppImageConfig_kernelGatewayImageConfigcreateAppImageConfig_tags'createAppImageConfig_appImageConfigNamenewCreateAppImageConfigResponse.createAppImageConfigResponse_appImageConfigArn'createAppImageConfigResponse_httpStatus$fToQueryCreateAppImageConfig$fToPathCreateAppImageConfig$fToJSONCreateAppImageConfig$fToHeadersCreateAppImageConfig$fNFDataCreateAppImageConfig$fHashableCreateAppImageConfig$$fNFDataCreateAppImageConfigResponse $fAWSRequestCreateAppImageConfig $fEqCreateAppImageConfigResponse"$fReadCreateAppImageConfigResponse"$fShowCreateAppImageConfigResponse%$fGenericCreateAppImageConfigResponse$fEqCreateAppImageConfig$fReadCreateAppImageConfig$fShowCreateAppImageConfig$fGenericCreateAppImageConfigCreateAppResponseCreateAppResponse'$sel:appArn:CreateAppResponse'"$sel:httpStatus:CreateAppResponse' CreateApp CreateApp'$sel:resourceSpec:CreateApp'$sel:spaceName:CreateApp'$sel:tags:CreateApp'$sel:userProfileName:CreateApp'$sel:domainId:CreateApp'$sel:appType:CreateApp'$sel:appName:CreateApp' newCreateAppcreateApp_resourceSpeccreateApp_spaceNamecreateApp_tagscreateApp_userProfileNamecreateApp_domainIdcreateApp_appTypecreateApp_appNamenewCreateAppResponsecreateAppResponse_appArncreateAppResponse_httpStatus$fToQueryCreateApp$fToPathCreateApp$fToJSONCreateApp$fToHeadersCreateApp$fNFDataCreateApp$fHashableCreateApp$fNFDataCreateAppResponse$fAWSRequestCreateApp$fEqCreateAppResponse$fReadCreateAppResponse$fShowCreateAppResponse$fGenericCreateAppResponse $fEqCreateApp$fReadCreateApp$fShowCreateApp$fGenericCreateAppCreateAlgorithmResponseCreateAlgorithmResponse'($sel:httpStatus:CreateAlgorithmResponse'*$sel:algorithmArn:CreateAlgorithmResponse'CreateAlgorithmCreateAlgorithm'*$sel:algorithmDescription:CreateAlgorithm'+$sel:certifyForMarketplace:CreateAlgorithm',$sel:inferenceSpecification:CreateAlgorithm'$sel:tags:CreateAlgorithm'-$sel:validationSpecification:CreateAlgorithm'#$sel:algorithmName:CreateAlgorithm'+$sel:trainingSpecification:CreateAlgorithm'newCreateAlgorithm$createAlgorithm_algorithmDescription%createAlgorithm_certifyForMarketplace&createAlgorithm_inferenceSpecificationcreateAlgorithm_tags'createAlgorithm_validationSpecificationcreateAlgorithm_algorithmName%createAlgorithm_trainingSpecificationnewCreateAlgorithmResponse"createAlgorithmResponse_httpStatus$createAlgorithmResponse_algorithmArn$fToQueryCreateAlgorithm$fToPathCreateAlgorithm$fToJSONCreateAlgorithm$fToHeadersCreateAlgorithm$fNFDataCreateAlgorithm$fHashableCreateAlgorithm$fNFDataCreateAlgorithmResponse$fAWSRequestCreateAlgorithm$fEqCreateAlgorithmResponse$fReadCreateAlgorithmResponse$fShowCreateAlgorithmResponse $fGenericCreateAlgorithmResponse$fEqCreateAlgorithm$fReadCreateAlgorithm$fShowCreateAlgorithm$fGenericCreateAlgorithmCreateActionResponseCreateActionResponse'$$sel:actionArn:CreateActionResponse'%$sel:httpStatus:CreateActionResponse' CreateAction CreateAction'$sel:description:CreateAction'%$sel:metadataProperties:CreateAction'$sel:properties:CreateAction'$sel:status:CreateAction'$sel:tags:CreateAction'$sel:actionName:CreateAction'$sel:source:CreateAction'$sel:actionType:CreateAction'newCreateActioncreateAction_descriptioncreateAction_metadataPropertiescreateAction_propertiescreateAction_statuscreateAction_tagscreateAction_actionNamecreateAction_sourcecreateAction_actionTypenewCreateActionResponsecreateActionResponse_actionArncreateActionResponse_httpStatus$fToQueryCreateAction$fToPathCreateAction$fToJSONCreateAction$fToHeadersCreateAction$fNFDataCreateAction$fHashableCreateAction$fNFDataCreateActionResponse$fAWSRequestCreateAction$fEqCreateActionResponse$fReadCreateActionResponse$fShowCreateActionResponse$fGenericCreateActionResponse$fEqCreateAction$fReadCreateAction$fShowCreateAction$fGenericCreateAction!BatchDescribeModelPackageResponse"BatchDescribeModelPackageResponse'$sel:batchDescribeModelPackageErrorMap:BatchDescribeModelPackageResponse'=$sel:modelPackageSummaries:BatchDescribeModelPackageResponse'2$sel:httpStatus:BatchDescribeModelPackageResponse'BatchDescribeModelPackageBatchDescribeModelPackage'3$sel:modelPackageArnList:BatchDescribeModelPackage'newBatchDescribeModelPackage-batchDescribeModelPackage_modelPackageArnList$newBatchDescribeModelPackageResponsebatchDescribeModelPackageResponse_batchDescribeModelPackageErrorMap7batchDescribeModelPackageResponse_modelPackageSummaries,batchDescribeModelPackageResponse_httpStatus"$fToQueryBatchDescribeModelPackage!$fToPathBatchDescribeModelPackage!$fToJSONBatchDescribeModelPackage$$fToHeadersBatchDescribeModelPackage!$fNFDataBatchDescribeModelPackage#$fHashableBatchDescribeModelPackage)$fNFDataBatchDescribeModelPackageResponse%$fAWSRequestBatchDescribeModelPackage%$fEqBatchDescribeModelPackageResponse'$fReadBatchDescribeModelPackageResponse'$fShowBatchDescribeModelPackageResponse*$fGenericBatchDescribeModelPackageResponse$fEqBatchDescribeModelPackage$fReadBatchDescribeModelPackage$fShowBatchDescribeModelPackage"$fGenericBatchDescribeModelPackageAssociateTrialComponentResponse AssociateTrialComponentResponse'.$sel:trialArn:AssociateTrialComponentResponse'7$sel:trialComponentArn:AssociateTrialComponentResponse'0$sel:httpStatus:AssociateTrialComponentResponse'AssociateTrialComponentAssociateTrialComponent'0$sel:trialComponentName:AssociateTrialComponent''$sel:trialName:AssociateTrialComponent'newAssociateTrialComponent*associateTrialComponent_trialComponentName!associateTrialComponent_trialName"newAssociateTrialComponentResponse(associateTrialComponentResponse_trialArn1associateTrialComponentResponse_trialComponentArn*associateTrialComponentResponse_httpStatus $fToQueryAssociateTrialComponent$fToPathAssociateTrialComponent$fToJSONAssociateTrialComponent"$fToHeadersAssociateTrialComponent$fNFDataAssociateTrialComponent!$fHashableAssociateTrialComponent'$fNFDataAssociateTrialComponentResponse#$fAWSRequestAssociateTrialComponent#$fEqAssociateTrialComponentResponse%$fReadAssociateTrialComponentResponse%$fShowAssociateTrialComponentResponse($fGenericAssociateTrialComponentResponse$fEqAssociateTrialComponent$fReadAssociateTrialComponent$fShowAssociateTrialComponent $fGenericAssociateTrialComponentAddTagsResponseAddTagsResponse'$sel:tags:AddTagsResponse' $sel:httpStatus:AddTagsResponse'AddTagsAddTags'$sel:resourceArn:AddTags'$sel:tags:AddTags' newAddTagsaddTags_resourceArn addTags_tagsnewAddTagsResponseaddTagsResponse_tagsaddTagsResponse_httpStatus$fToQueryAddTags$fToPathAddTags$fToJSONAddTags$fToHeadersAddTags$fNFDataAddTags$fHashableAddTags$fNFDataAddTagsResponse$fAWSRequestAddTags$fEqAddTagsResponse$fReadAddTagsResponse$fShowAddTagsResponse$fGenericAddTagsResponse $fEqAddTags $fReadAddTags $fShowAddTags$fGenericAddTagsAddAssociationResponseAddAssociationResponse'+$sel:destinationArn:AddAssociationResponse'&$sel:sourceArn:AddAssociationResponse''$sel:httpStatus:AddAssociationResponse'AddAssociationAddAssociation'$$sel:associationType:AddAssociation'$sel:sourceArn:AddAssociation'#$sel:destinationArn:AddAssociation'newAddAssociationaddAssociation_associationTypeaddAssociation_sourceArnaddAssociation_destinationArnnewAddAssociationResponse%addAssociationResponse_destinationArn addAssociationResponse_sourceArn!addAssociationResponse_httpStatus$fToQueryAddAssociation$fToPathAddAssociation$fToJSONAddAssociation$fToHeadersAddAssociation$fNFDataAddAssociation$fHashableAddAssociation$fNFDataAddAssociationResponse$fAWSRequestAddAssociation$fEqAddAssociationResponse$fReadAddAssociationResponse$fShowAddAssociationResponse$fGenericAddAssociationResponse$fEqAddAssociation$fReadAddAssociation$fShowAddAssociation$fGenericAddAssociationUpdateActionResponseUpdateActionResponse'$$sel:actionArn:UpdateActionResponse'%$sel:httpStatus:UpdateActionResponse' UpdateAction UpdateAction'$sel:description:UpdateAction'$sel:properties:UpdateAction'%$sel:propertiesToRemove:UpdateAction'$sel:status:UpdateAction'$sel:actionName:UpdateAction'newUpdateActionupdateAction_descriptionupdateAction_propertiesupdateAction_propertiesToRemoveupdateAction_statusupdateAction_actionNamenewUpdateActionResponseupdateActionResponse_actionArnupdateActionResponse_httpStatus$fToQueryUpdateAction$fToPathUpdateAction$fToJSONUpdateAction$fToHeadersUpdateAction$fNFDataUpdateAction$fHashableUpdateAction$fNFDataUpdateActionResponse$fAWSRequestUpdateAction$fEqUpdateActionResponse$fReadUpdateActionResponse$fShowUpdateActionResponse$fGenericUpdateActionResponse$fEqUpdateAction$fReadUpdateAction$fShowUpdateAction$fGenericUpdateActionUpdateAppImageConfigResponseUpdateAppImageConfigResponse'4$sel:appImageConfigArn:UpdateAppImageConfigResponse'-$sel:httpStatus:UpdateAppImageConfigResponse'UpdateAppImageConfigUpdateAppImageConfig'3$sel:kernelGatewayImageConfig:UpdateAppImageConfig'-$sel:appImageConfigName:UpdateAppImageConfig'newUpdateAppImageConfig-updateAppImageConfig_kernelGatewayImageConfig'updateAppImageConfig_appImageConfigNamenewUpdateAppImageConfigResponse.updateAppImageConfigResponse_appImageConfigArn'updateAppImageConfigResponse_httpStatus$fToQueryUpdateAppImageConfig$fToPathUpdateAppImageConfig$fToJSONUpdateAppImageConfig$fToHeadersUpdateAppImageConfig$fNFDataUpdateAppImageConfig$fHashableUpdateAppImageConfig$$fNFDataUpdateAppImageConfigResponse $fAWSRequestUpdateAppImageConfig $fEqUpdateAppImageConfigResponse"$fReadUpdateAppImageConfigResponse"$fShowUpdateAppImageConfigResponse%$fGenericUpdateAppImageConfigResponse$fEqUpdateAppImageConfig$fReadUpdateAppImageConfig$fShowUpdateAppImageConfig$fGenericUpdateAppImageConfigUpdateArtifactResponseUpdateArtifactResponse'($sel:artifactArn:UpdateArtifactResponse''$sel:httpStatus:UpdateArtifactResponse'UpdateArtifactUpdateArtifact'!$sel:artifactName:UpdateArtifact'$sel:properties:UpdateArtifact''$sel:propertiesToRemove:UpdateArtifact' $sel:artifactArn:UpdateArtifact'newUpdateArtifactupdateArtifact_artifactNameupdateArtifact_properties!updateArtifact_propertiesToRemoveupdateArtifact_artifactArnnewUpdateArtifactResponse"updateArtifactResponse_artifactArn!updateArtifactResponse_httpStatus$fToQueryUpdateArtifact$fToPathUpdateArtifact$fToJSONUpdateArtifact$fToHeadersUpdateArtifact$fNFDataUpdateArtifact$fHashableUpdateArtifact$fNFDataUpdateArtifactResponse$fAWSRequestUpdateArtifact$fEqUpdateArtifactResponse$fReadUpdateArtifactResponse$fShowUpdateArtifactResponse$fGenericUpdateArtifactResponse$fEqUpdateArtifact$fReadUpdateArtifact$fShowUpdateArtifact$fGenericUpdateArtifactUpdateCodeRepositoryResponseUpdateCodeRepositoryResponse'-$sel:httpStatus:UpdateCodeRepositoryResponse'4$sel:codeRepositoryArn:UpdateCodeRepositoryResponse'UpdateCodeRepositoryUpdateCodeRepository'$$sel:gitConfig:UpdateCodeRepository'-$sel:codeRepositoryName:UpdateCodeRepository'newUpdateCodeRepositoryupdateCodeRepository_gitConfig'updateCodeRepository_codeRepositoryNamenewUpdateCodeRepositoryResponse'updateCodeRepositoryResponse_httpStatus.updateCodeRepositoryResponse_codeRepositoryArn$fToQueryUpdateCodeRepository$fToPathUpdateCodeRepository$fToJSONUpdateCodeRepository$fToHeadersUpdateCodeRepository$fNFDataUpdateCodeRepository$fHashableUpdateCodeRepository$$fNFDataUpdateCodeRepositoryResponse $fAWSRequestUpdateCodeRepository $fEqUpdateCodeRepositoryResponse"$fReadUpdateCodeRepositoryResponse"$fShowUpdateCodeRepositoryResponse%$fGenericUpdateCodeRepositoryResponse$fEqUpdateCodeRepository$fReadUpdateCodeRepository$fShowUpdateCodeRepository$fGenericUpdateCodeRepositoryUpdateContextResponseUpdateContextResponse'&$sel:contextArn:UpdateContextResponse'&$sel:httpStatus:UpdateContextResponse' UpdateContextUpdateContext'$sel:description:UpdateContext'$sel:properties:UpdateContext'&$sel:propertiesToRemove:UpdateContext'$sel:contextName:UpdateContext'newUpdateContextupdateContext_descriptionupdateContext_properties updateContext_propertiesToRemoveupdateContext_contextNamenewUpdateContextResponse updateContextResponse_contextArn updateContextResponse_httpStatus$fToQueryUpdateContext$fToPathUpdateContext$fToJSONUpdateContext$fToHeadersUpdateContext$fNFDataUpdateContext$fHashableUpdateContext$fNFDataUpdateContextResponse$fAWSRequestUpdateContext$fEqUpdateContextResponse$fReadUpdateContextResponse$fShowUpdateContextResponse$fGenericUpdateContextResponse$fEqUpdateContext$fReadUpdateContext$fShowUpdateContext$fGenericUpdateContextUpdateDeviceFleetResponseUpdateDeviceFleetResponse'UpdateDeviceFleetUpdateDeviceFleet'#$sel:description:UpdateDeviceFleet'*$sel:enableIotRoleAlias:UpdateDeviceFleet'$sel:roleArn:UpdateDeviceFleet''$sel:deviceFleetName:UpdateDeviceFleet'$$sel:outputConfig:UpdateDeviceFleet'newUpdateDeviceFleetupdateDeviceFleet_description$updateDeviceFleet_enableIotRoleAliasupdateDeviceFleet_roleArn!updateDeviceFleet_deviceFleetNameupdateDeviceFleet_outputConfignewUpdateDeviceFleetResponse$fToQueryUpdateDeviceFleet$fToPathUpdateDeviceFleet$fToJSONUpdateDeviceFleet$fToHeadersUpdateDeviceFleet$fNFDataUpdateDeviceFleet$fHashableUpdateDeviceFleet!$fNFDataUpdateDeviceFleetResponse$fAWSRequestUpdateDeviceFleet$fEqUpdateDeviceFleetResponse$fReadUpdateDeviceFleetResponse$fShowUpdateDeviceFleetResponse"$fGenericUpdateDeviceFleetResponse$fEqUpdateDeviceFleet$fReadUpdateDeviceFleet$fShowUpdateDeviceFleet$fGenericUpdateDeviceFleetUpdateDevicesResponseUpdateDevicesResponse' UpdateDevicesUpdateDevices'#$sel:deviceFleetName:UpdateDevices'$sel:devices:UpdateDevices'newUpdateDevicesupdateDevices_deviceFleetNameupdateDevices_devicesnewUpdateDevicesResponse$fToQueryUpdateDevices$fToPathUpdateDevices$fToJSONUpdateDevices$fToHeadersUpdateDevices$fNFDataUpdateDevices$fHashableUpdateDevices$fNFDataUpdateDevicesResponse$fAWSRequestUpdateDevices$fEqUpdateDevicesResponse$fReadUpdateDevicesResponse$fShowUpdateDevicesResponse$fGenericUpdateDevicesResponse$fEqUpdateDevices$fReadUpdateDevices$fShowUpdateDevices$fGenericUpdateDevicesUpdateDomainResponseUpdateDomainResponse'$$sel:domainArn:UpdateDomainResponse'%$sel:httpStatus:UpdateDomainResponse' UpdateDomain UpdateDomain'-$sel:appSecurityGroupManagement:UpdateDomain''$sel:defaultSpaceSettings:UpdateDomain'&$sel:defaultUserSettings:UpdateDomain'*$sel:domainSettingsForUpdate:UpdateDomain'$sel:domainId:UpdateDomain'newUpdateDomain'updateDomain_appSecurityGroupManagement!updateDomain_defaultSpaceSettings updateDomain_defaultUserSettings$updateDomain_domainSettingsForUpdateupdateDomain_domainIdnewUpdateDomainResponseupdateDomainResponse_domainArnupdateDomainResponse_httpStatus$fToQueryUpdateDomain$fToPathUpdateDomain$fToJSONUpdateDomain$fToHeadersUpdateDomain$fNFDataUpdateDomain$fHashableUpdateDomain$fNFDataUpdateDomainResponse$fAWSRequestUpdateDomain$fEqUpdateDomainResponse$fReadUpdateDomainResponse$fShowUpdateDomainResponse$fGenericUpdateDomainResponse$fEqUpdateDomain$fReadUpdateDomain$fShowUpdateDomain$fGenericUpdateDomainUpdateEndpointResponseUpdateEndpointResponse''$sel:httpStatus:UpdateEndpointResponse'($sel:endpointArn:UpdateEndpointResponse'UpdateEndpointUpdateEndpoint'%$sel:deploymentConfig:UpdateEndpoint'5$sel:excludeRetainedVariantProperties:UpdateEndpoint'/$sel:retainAllVariantProperties:UpdateEndpoint'+$sel:retainDeploymentConfig:UpdateEndpoint'!$sel:endpointName:UpdateEndpoint''$sel:endpointConfigName:UpdateEndpoint'newUpdateEndpointupdateEndpoint_deploymentConfig/updateEndpoint_excludeRetainedVariantProperties)updateEndpoint_retainAllVariantProperties%updateEndpoint_retainDeploymentConfigupdateEndpoint_endpointName!updateEndpoint_endpointConfigNamenewUpdateEndpointResponse!updateEndpointResponse_httpStatus"updateEndpointResponse_endpointArn$fToQueryUpdateEndpoint$fToPathUpdateEndpoint$fToJSONUpdateEndpoint$fToHeadersUpdateEndpoint$fNFDataUpdateEndpoint$fHashableUpdateEndpoint$fNFDataUpdateEndpointResponse$fAWSRequestUpdateEndpoint$fEqUpdateEndpointResponse$fReadUpdateEndpointResponse$fShowUpdateEndpointResponse$fGenericUpdateEndpointResponse$fEqUpdateEndpoint$fReadUpdateEndpoint$fShowUpdateEndpoint$fGenericUpdateEndpoint*UpdateEndpointWeightsAndCapacitiesResponse+UpdateEndpointWeightsAndCapacitiesResponse';$sel:httpStatus:UpdateEndpointWeightsAndCapacitiesResponse'<$sel:endpointArn:UpdateEndpointWeightsAndCapacitiesResponse'"UpdateEndpointWeightsAndCapacities#UpdateEndpointWeightsAndCapacities'5$sel:endpointName:UpdateEndpointWeightsAndCapacities'$sel:desiredWeightsAndCapacities:UpdateEndpointWeightsAndCapacities'%newUpdateEndpointWeightsAndCapacities/updateEndpointWeightsAndCapacities_endpointName>updateEndpointWeightsAndCapacities_desiredWeightsAndCapacities-newUpdateEndpointWeightsAndCapacitiesResponse5updateEndpointWeightsAndCapacitiesResponse_httpStatus6updateEndpointWeightsAndCapacitiesResponse_endpointArn+$fToQueryUpdateEndpointWeightsAndCapacities*$fToPathUpdateEndpointWeightsAndCapacities*$fToJSONUpdateEndpointWeightsAndCapacities-$fToHeadersUpdateEndpointWeightsAndCapacities*$fNFDataUpdateEndpointWeightsAndCapacities,$fHashableUpdateEndpointWeightsAndCapacities2$fNFDataUpdateEndpointWeightsAndCapacitiesResponse.$fAWSRequestUpdateEndpointWeightsAndCapacities.$fEqUpdateEndpointWeightsAndCapacitiesResponse0$fReadUpdateEndpointWeightsAndCapacitiesResponse0$fShowUpdateEndpointWeightsAndCapacitiesResponse3$fGenericUpdateEndpointWeightsAndCapacitiesResponse&$fEqUpdateEndpointWeightsAndCapacities($fReadUpdateEndpointWeightsAndCapacities($fShowUpdateEndpointWeightsAndCapacities+$fGenericUpdateEndpointWeightsAndCapacitiesUpdateExperimentResponseUpdateExperimentResponse',$sel:experimentArn:UpdateExperimentResponse')$sel:httpStatus:UpdateExperimentResponse'UpdateExperimentUpdateExperiment'"$sel:description:UpdateExperiment'"$sel:displayName:UpdateExperiment'%$sel:experimentName:UpdateExperiment'newUpdateExperimentupdateExperiment_descriptionupdateExperiment_displayNameupdateExperiment_experimentNamenewUpdateExperimentResponse&updateExperimentResponse_experimentArn#updateExperimentResponse_httpStatus$fToQueryUpdateExperiment$fToPathUpdateExperiment$fToJSONUpdateExperiment$fToHeadersUpdateExperiment$fNFDataUpdateExperiment$fHashableUpdateExperiment $fNFDataUpdateExperimentResponse$fAWSRequestUpdateExperiment$fEqUpdateExperimentResponse$fReadUpdateExperimentResponse$fShowUpdateExperimentResponse!$fGenericUpdateExperimentResponse$fEqUpdateExperiment$fReadUpdateExperiment$fShowUpdateExperiment$fGenericUpdateExperimentUpdateFeatureGroupResponseUpdateFeatureGroupResponse'+$sel:httpStatus:UpdateFeatureGroupResponse'0$sel:featureGroupArn:UpdateFeatureGroupResponse'UpdateFeatureGroupUpdateFeatureGroup')$sel:featureAdditions:UpdateFeatureGroup')$sel:featureGroupName:UpdateFeatureGroup'newUpdateFeatureGroup#updateFeatureGroup_featureAdditions#updateFeatureGroup_featureGroupNamenewUpdateFeatureGroupResponse%updateFeatureGroupResponse_httpStatus*updateFeatureGroupResponse_featureGroupArn$fToQueryUpdateFeatureGroup$fToPathUpdateFeatureGroup$fToJSONUpdateFeatureGroup$fToHeadersUpdateFeatureGroup$fNFDataUpdateFeatureGroup$fHashableUpdateFeatureGroup"$fNFDataUpdateFeatureGroupResponse$fAWSRequestUpdateFeatureGroup$fEqUpdateFeatureGroupResponse $fReadUpdateFeatureGroupResponse $fShowUpdateFeatureGroupResponse#$fGenericUpdateFeatureGroupResponse$fEqUpdateFeatureGroup$fReadUpdateFeatureGroup$fShowUpdateFeatureGroup$fGenericUpdateFeatureGroupUpdateFeatureMetadataResponseUpdateFeatureMetadataResponse'UpdateFeatureMetadataUpdateFeatureMetadata''$sel:description:UpdateFeatureMetadata'.$sel:parameterAdditions:UpdateFeatureMetadata'-$sel:parameterRemovals:UpdateFeatureMetadata',$sel:featureGroupName:UpdateFeatureMetadata''$sel:featureName:UpdateFeatureMetadata'newUpdateFeatureMetadata!updateFeatureMetadata_description(updateFeatureMetadata_parameterAdditions'updateFeatureMetadata_parameterRemovals&updateFeatureMetadata_featureGroupName!updateFeatureMetadata_featureName newUpdateFeatureMetadataResponse$fToQueryUpdateFeatureMetadata$fToPathUpdateFeatureMetadata$fToJSONUpdateFeatureMetadata $fToHeadersUpdateFeatureMetadata$fNFDataUpdateFeatureMetadata$fHashableUpdateFeatureMetadata%$fNFDataUpdateFeatureMetadataResponse!$fAWSRequestUpdateFeatureMetadata!$fEqUpdateFeatureMetadataResponse#$fReadUpdateFeatureMetadataResponse#$fShowUpdateFeatureMetadataResponse&$fGenericUpdateFeatureMetadataResponse$fEqUpdateFeatureMetadata$fReadUpdateFeatureMetadata$fShowUpdateFeatureMetadata$fGenericUpdateFeatureMetadataUpdateHubResponseUpdateHubResponse'"$sel:httpStatus:UpdateHubResponse'$sel:hubArn:UpdateHubResponse' UpdateHub UpdateHub'$sel:hubDescription:UpdateHub'$sel:hubDisplayName:UpdateHub'!$sel:hubSearchKeywords:UpdateHub'$sel:hubName:UpdateHub' newUpdateHubupdateHub_hubDescriptionupdateHub_hubDisplayNameupdateHub_hubSearchKeywordsupdateHub_hubNamenewUpdateHubResponseupdateHubResponse_httpStatusupdateHubResponse_hubArn$fToQueryUpdateHub$fToPathUpdateHub$fToJSONUpdateHub$fToHeadersUpdateHub$fNFDataUpdateHub$fHashableUpdateHub$fNFDataUpdateHubResponse$fAWSRequestUpdateHub$fEqUpdateHubResponse$fReadUpdateHubResponse$fShowUpdateHubResponse$fGenericUpdateHubResponse $fEqUpdateHub$fReadUpdateHub$fShowUpdateHub$fGenericUpdateHubUpdateImageResponseUpdateImageResponse'"$sel:imageArn:UpdateImageResponse'$$sel:httpStatus:UpdateImageResponse' UpdateImage UpdateImage'"$sel:deleteProperties:UpdateImage'$sel:description:UpdateImage'$sel:displayName:UpdateImage'$sel:roleArn:UpdateImage'$sel:imageName:UpdateImage'newUpdateImageupdateImage_deletePropertiesupdateImage_descriptionupdateImage_displayNameupdateImage_roleArnupdateImage_imageNamenewUpdateImageResponseupdateImageResponse_imageArnupdateImageResponse_httpStatus$fToQueryUpdateImage$fToPathUpdateImage$fToJSONUpdateImage$fToHeadersUpdateImage$fNFDataUpdateImage$fHashableUpdateImage$fNFDataUpdateImageResponse$fAWSRequestUpdateImage$fEqUpdateImageResponse$fReadUpdateImageResponse$fShowUpdateImageResponse$fGenericUpdateImageResponse$fEqUpdateImage$fReadUpdateImage$fShowUpdateImage$fGenericUpdateImageUpdateImageVersionResponseUpdateImageVersionResponse'0$sel:imageVersionArn:UpdateImageVersionResponse'+$sel:httpStatus:UpdateImageVersionResponse'UpdateImageVersionUpdateImageVersion'$sel:alias:UpdateImageVersion'%$sel:aliasesToAdd:UpdateImageVersion'($sel:aliasesToDelete:UpdateImageVersion' $sel:horovod:UpdateImageVersion' $sel:jobType:UpdateImageVersion'$$sel:mLFramework:UpdateImageVersion'"$sel:processor:UpdateImageVersion'($sel:programmingLang:UpdateImageVersion'%$sel:releaseNotes:UpdateImageVersion''$sel:vendorGuidance:UpdateImageVersion' $sel:version:UpdateImageVersion'"$sel:imageName:UpdateImageVersion'newUpdateImageVersionupdateImageVersion_aliasupdateImageVersion_aliasesToAdd"updateImageVersion_aliasesToDeleteupdateImageVersion_horovodupdateImageVersion_jobTypeupdateImageVersion_mLFrameworkupdateImageVersion_processor"updateImageVersion_programmingLangupdateImageVersion_releaseNotes!updateImageVersion_vendorGuidanceupdateImageVersion_versionupdateImageVersion_imageNamenewUpdateImageVersionResponse*updateImageVersionResponse_imageVersionArn%updateImageVersionResponse_httpStatus$fToQueryUpdateImageVersion$fToPathUpdateImageVersion$fToJSONUpdateImageVersion$fToHeadersUpdateImageVersion$fNFDataUpdateImageVersion$fHashableUpdateImageVersion"$fNFDataUpdateImageVersionResponse$fAWSRequestUpdateImageVersion$fEqUpdateImageVersionResponse $fReadUpdateImageVersionResponse $fShowUpdateImageVersionResponse#$fGenericUpdateImageVersionResponse$fEqUpdateImageVersion$fReadUpdateImageVersion$fShowUpdateImageVersion$fGenericUpdateImageVersion!UpdateInferenceExperimentResponse"UpdateInferenceExperimentResponse'2$sel:httpStatus:UpdateInferenceExperimentResponse'>$sel:inferenceExperimentArn:UpdateInferenceExperimentResponse'UpdateInferenceExperimentUpdateInferenceExperiment'1$sel:dataStorageConfig:UpdateInferenceExperiment'+$sel:description:UpdateInferenceExperiment'-$sel:modelVariants:UpdateInferenceExperiment'($sel:schedule:UpdateInferenceExperiment'0$sel:shadowModeConfig:UpdateInferenceExperiment'$$sel:name:UpdateInferenceExperiment'newUpdateInferenceExperiment+updateInferenceExperiment_dataStorageConfig%updateInferenceExperiment_description'updateInferenceExperiment_modelVariants"updateInferenceExperiment_schedule*updateInferenceExperiment_shadowModeConfigupdateInferenceExperiment_name$newUpdateInferenceExperimentResponse,updateInferenceExperimentResponse_httpStatus8updateInferenceExperimentResponse_inferenceExperimentArn"$fToQueryUpdateInferenceExperiment!$fToPathUpdateInferenceExperiment!$fToJSONUpdateInferenceExperiment$$fToHeadersUpdateInferenceExperiment!$fNFDataUpdateInferenceExperiment#$fHashableUpdateInferenceExperiment)$fNFDataUpdateInferenceExperimentResponse%$fAWSRequestUpdateInferenceExperiment%$fEqUpdateInferenceExperimentResponse'$fReadUpdateInferenceExperimentResponse'$fShowUpdateInferenceExperimentResponse*$fGenericUpdateInferenceExperimentResponse$fEqUpdateInferenceExperiment$fReadUpdateInferenceExperiment$fShowUpdateInferenceExperiment"$fGenericUpdateInferenceExperimentUpdateModelCardResponseUpdateModelCardResponse'($sel:httpStatus:UpdateModelCardResponse'*$sel:modelCardArn:UpdateModelCardResponse'UpdateModelCardUpdateModelCard'$sel:content:UpdateModelCard'%$sel:modelCardStatus:UpdateModelCard'#$sel:modelCardName:UpdateModelCard'newUpdateModelCardupdateModelCard_contentupdateModelCard_modelCardStatusupdateModelCard_modelCardNamenewUpdateModelCardResponse"updateModelCardResponse_httpStatus$updateModelCardResponse_modelCardArn$fToQueryUpdateModelCard$fToPathUpdateModelCard$fToJSONUpdateModelCard$fToHeadersUpdateModelCard$fNFDataUpdateModelCard$fHashableUpdateModelCard$fNFDataUpdateModelCardResponse$fAWSRequestUpdateModelCard$fEqUpdateModelCardResponse$fReadUpdateModelCardResponse$fShowUpdateModelCardResponse $fGenericUpdateModelCardResponse$fEqUpdateModelCard$fShowUpdateModelCard$fGenericUpdateModelCardUpdateModelPackageResponseUpdateModelPackageResponse'+$sel:httpStatus:UpdateModelPackageResponse'0$sel:modelPackageArn:UpdateModelPackageResponse'UpdateModelPackageUpdateModelPackage'?$sel:additionalInferenceSpecificationsToAdd:UpdateModelPackage',$sel:approvalDescription:UpdateModelPackage'3$sel:customerMetadataProperties:UpdateModelPackage';$sel:customerMetadataPropertiesToRemove:UpdateModelPackage',$sel:modelApprovalStatus:UpdateModelPackage'($sel:modelPackageArn:UpdateModelPackage'newUpdateModelPackage9updateModelPackage_additionalInferenceSpecificationsToAdd&updateModelPackage_approvalDescription-updateModelPackage_customerMetadataProperties5updateModelPackage_customerMetadataPropertiesToRemove&updateModelPackage_modelApprovalStatus"updateModelPackage_modelPackageArnnewUpdateModelPackageResponse%updateModelPackageResponse_httpStatus*updateModelPackageResponse_modelPackageArn$fToQueryUpdateModelPackage$fToPathUpdateModelPackage$fToJSONUpdateModelPackage$fToHeadersUpdateModelPackage$fNFDataUpdateModelPackage$fHashableUpdateModelPackage"$fNFDataUpdateModelPackageResponse$fAWSRequestUpdateModelPackage$fEqUpdateModelPackageResponse $fReadUpdateModelPackageResponse $fShowUpdateModelPackageResponse#$fGenericUpdateModelPackageResponse$fEqUpdateModelPackage$fReadUpdateModelPackage$fShowUpdateModelPackage$fGenericUpdateModelPackageUpdateMonitoringAlertResponseUpdateMonitoringAlertResponse'7$sel:monitoringAlertName:UpdateMonitoringAlertResponse'.$sel:httpStatus:UpdateMonitoringAlertResponse'9$sel:monitoringScheduleArn:UpdateMonitoringAlertResponse'UpdateMonitoringAlertUpdateMonitoringAlert'2$sel:monitoringScheduleName:UpdateMonitoringAlert'/$sel:monitoringAlertName:UpdateMonitoringAlert'-$sel:datapointsToAlert:UpdateMonitoringAlert',$sel:evaluationPeriod:UpdateMonitoringAlert'newUpdateMonitoringAlert,updateMonitoringAlert_monitoringScheduleName)updateMonitoringAlert_monitoringAlertName'updateMonitoringAlert_datapointsToAlert&updateMonitoringAlert_evaluationPeriod newUpdateMonitoringAlertResponse1updateMonitoringAlertResponse_monitoringAlertName(updateMonitoringAlertResponse_httpStatus3updateMonitoringAlertResponse_monitoringScheduleArn$fToQueryUpdateMonitoringAlert$fToPathUpdateMonitoringAlert$fToJSONUpdateMonitoringAlert $fToHeadersUpdateMonitoringAlert$fNFDataUpdateMonitoringAlert$fHashableUpdateMonitoringAlert%$fNFDataUpdateMonitoringAlertResponse!$fAWSRequestUpdateMonitoringAlert!$fEqUpdateMonitoringAlertResponse#$fReadUpdateMonitoringAlertResponse#$fShowUpdateMonitoringAlertResponse&$fGenericUpdateMonitoringAlertResponse$fEqUpdateMonitoringAlert$fReadUpdateMonitoringAlert$fShowUpdateMonitoringAlert$fGenericUpdateMonitoringAlert UpdateMonitoringScheduleResponse!UpdateMonitoringScheduleResponse'1$sel:httpStatus:UpdateMonitoringScheduleResponse'<$sel:monitoringScheduleArn:UpdateMonitoringScheduleResponse'UpdateMonitoringScheduleUpdateMonitoringSchedule'5$sel:monitoringScheduleName:UpdateMonitoringSchedule'7$sel:monitoringScheduleConfig:UpdateMonitoringSchedule'newUpdateMonitoringSchedule/updateMonitoringSchedule_monitoringScheduleName1updateMonitoringSchedule_monitoringScheduleConfig#newUpdateMonitoringScheduleResponse+updateMonitoringScheduleResponse_httpStatus6updateMonitoringScheduleResponse_monitoringScheduleArn!$fToQueryUpdateMonitoringSchedule $fToPathUpdateMonitoringSchedule $fToJSONUpdateMonitoringSchedule#$fToHeadersUpdateMonitoringSchedule $fNFDataUpdateMonitoringSchedule"$fHashableUpdateMonitoringSchedule($fNFDataUpdateMonitoringScheduleResponse$$fAWSRequestUpdateMonitoringSchedule$$fEqUpdateMonitoringScheduleResponse&$fReadUpdateMonitoringScheduleResponse&$fShowUpdateMonitoringScheduleResponse)$fGenericUpdateMonitoringScheduleResponse$fEqUpdateMonitoringSchedule$fReadUpdateMonitoringSchedule$fShowUpdateMonitoringSchedule!$fGenericUpdateMonitoringScheduleUpdateNotebookInstanceResponseUpdateNotebookInstanceResponse'/$sel:httpStatus:UpdateNotebookInstanceResponse'UpdateNotebookInstanceUpdateNotebookInstance'-$sel:acceleratorTypes:UpdateNotebookInstance'7$sel:additionalCodeRepositories:UpdateNotebookInstance'2$sel:defaultCodeRepository:UpdateNotebookInstance'9$sel:disassociateAcceleratorTypes:UpdateNotebookInstance'$sel:disassociateAdditionalCodeRepositories:UpdateNotebookInstance'>$sel:disassociateDefaultCodeRepository:UpdateNotebookInstance'8$sel:disassociateLifecycleConfig:UpdateNotebookInstance'$sel:instanceMetadataServiceConfiguration:UpdateNotebookInstance')$sel:instanceType:UpdateNotebookInstance'0$sel:lifecycleConfigName:UpdateNotebookInstance'$$sel:roleArn:UpdateNotebookInstance''$sel:rootAccess:UpdateNotebookInstance'+$sel:volumeSizeInGB:UpdateNotebookInstance'1$sel:notebookInstanceName:UpdateNotebookInstance'newUpdateNotebookInstance'updateNotebookInstance_acceleratorTypes1updateNotebookInstance_additionalCodeRepositories,updateNotebookInstance_defaultCodeRepository3updateNotebookInstance_disassociateAcceleratorTypes=updateNotebookInstance_disassociateAdditionalCodeRepositories8updateNotebookInstance_disassociateDefaultCodeRepository2updateNotebookInstance_disassociateLifecycleConfig;updateNotebookInstance_instanceMetadataServiceConfiguration#updateNotebookInstance_instanceType*updateNotebookInstance_lifecycleConfigNameupdateNotebookInstance_roleArn!updateNotebookInstance_rootAccess%updateNotebookInstance_volumeSizeInGB+updateNotebookInstance_notebookInstanceName!newUpdateNotebookInstanceResponse)updateNotebookInstanceResponse_httpStatus$fToQueryUpdateNotebookInstance$fToPathUpdateNotebookInstance$fToJSONUpdateNotebookInstance!$fToHeadersUpdateNotebookInstance$fNFDataUpdateNotebookInstance $fHashableUpdateNotebookInstance&$fNFDataUpdateNotebookInstanceResponse"$fAWSRequestUpdateNotebookInstance"$fEqUpdateNotebookInstanceResponse$$fReadUpdateNotebookInstanceResponse$$fShowUpdateNotebookInstanceResponse'$fGenericUpdateNotebookInstanceResponse$fEqUpdateNotebookInstance$fReadUpdateNotebookInstance$fShowUpdateNotebookInstance$fGenericUpdateNotebookInstance-UpdateNotebookInstanceLifecycleConfigResponse.UpdateNotebookInstanceLifecycleConfigResponse'>$sel:httpStatus:UpdateNotebookInstanceLifecycleConfigResponse'%UpdateNotebookInstanceLifecycleConfig&UpdateNotebookInstanceLifecycleConfig'4$sel:onCreate:UpdateNotebookInstanceLifecycleConfig'3$sel:onStart:UpdateNotebookInstanceLifecycleConfig'$sel:notebookInstanceLifecycleConfigName:UpdateNotebookInstanceLifecycleConfig'(newUpdateNotebookInstanceLifecycleConfig.updateNotebookInstanceLifecycleConfig_onCreate-updateNotebookInstanceLifecycleConfig_onStartupdateNotebookInstanceLifecycleConfig_notebookInstanceLifecycleConfigName0newUpdateNotebookInstanceLifecycleConfigResponse8updateNotebookInstanceLifecycleConfigResponse_httpStatus.$fToQueryUpdateNotebookInstanceLifecycleConfig-$fToPathUpdateNotebookInstanceLifecycleConfig-$fToJSONUpdateNotebookInstanceLifecycleConfig0$fToHeadersUpdateNotebookInstanceLifecycleConfig-$fNFDataUpdateNotebookInstanceLifecycleConfig/$fHashableUpdateNotebookInstanceLifecycleConfig5$fNFDataUpdateNotebookInstanceLifecycleConfigResponse1$fAWSRequestUpdateNotebookInstanceLifecycleConfig1$fEqUpdateNotebookInstanceLifecycleConfigResponse3$fReadUpdateNotebookInstanceLifecycleConfigResponse3$fShowUpdateNotebookInstanceLifecycleConfigResponse6$fGenericUpdateNotebookInstanceLifecycleConfigResponse)$fEqUpdateNotebookInstanceLifecycleConfig+$fReadUpdateNotebookInstanceLifecycleConfig+$fShowUpdateNotebookInstanceLifecycleConfig.$fGenericUpdateNotebookInstanceLifecycleConfigUpdatePipelineResponseUpdatePipelineResponse'($sel:pipelineArn:UpdatePipelineResponse''$sel:httpStatus:UpdatePipelineResponse'UpdatePipelineUpdatePipeline'-$sel:parallelismConfiguration:UpdatePipeline''$sel:pipelineDefinition:UpdatePipeline'1$sel:pipelineDefinitionS3Location:UpdatePipeline'($sel:pipelineDescription:UpdatePipeline'($sel:pipelineDisplayName:UpdatePipeline'$sel:roleArn:UpdatePipeline'!$sel:pipelineName:UpdatePipeline'newUpdatePipeline'updatePipeline_parallelismConfiguration!updatePipeline_pipelineDefinition+updatePipeline_pipelineDefinitionS3Location"updatePipeline_pipelineDescription"updatePipeline_pipelineDisplayNameupdatePipeline_roleArnupdatePipeline_pipelineNamenewUpdatePipelineResponse"updatePipelineResponse_pipelineArn!updatePipelineResponse_httpStatus$fToQueryUpdatePipeline$fToPathUpdatePipeline$fToJSONUpdatePipeline$fToHeadersUpdatePipeline$fNFDataUpdatePipeline$fHashableUpdatePipeline$fNFDataUpdatePipelineResponse$fAWSRequestUpdatePipeline$fEqUpdatePipelineResponse$fReadUpdatePipelineResponse$fShowUpdatePipelineResponse$fGenericUpdatePipelineResponse$fEqUpdatePipeline$fReadUpdatePipeline$fShowUpdatePipeline$fGenericUpdatePipelineUpdatePipelineExecutionResponse UpdatePipelineExecutionResponse':$sel:pipelineExecutionArn:UpdatePipelineExecutionResponse'0$sel:httpStatus:UpdatePipelineExecutionResponse'UpdatePipelineExecutionUpdatePipelineExecution'6$sel:parallelismConfiguration:UpdatePipelineExecution':$sel:pipelineExecutionDescription:UpdatePipelineExecution':$sel:pipelineExecutionDisplayName:UpdatePipelineExecution'2$sel:pipelineExecutionArn:UpdatePipelineExecution'newUpdatePipelineExecution0updatePipelineExecution_parallelismConfiguration4updatePipelineExecution_pipelineExecutionDescription4updatePipelineExecution_pipelineExecutionDisplayName,updatePipelineExecution_pipelineExecutionArn"newUpdatePipelineExecutionResponse4updatePipelineExecutionResponse_pipelineExecutionArn*updatePipelineExecutionResponse_httpStatus $fToQueryUpdatePipelineExecution$fToPathUpdatePipelineExecution$fToJSONUpdatePipelineExecution"$fToHeadersUpdatePipelineExecution$fNFDataUpdatePipelineExecution!$fHashableUpdatePipelineExecution'$fNFDataUpdatePipelineExecutionResponse#$fAWSRequestUpdatePipelineExecution#$fEqUpdatePipelineExecutionResponse%$fReadUpdatePipelineExecutionResponse%$fShowUpdatePipelineExecutionResponse($fGenericUpdatePipelineExecutionResponse$fEqUpdatePipelineExecution$fReadUpdatePipelineExecution$fShowUpdatePipelineExecution $fGenericUpdatePipelineExecutionUpdateProjectResponseUpdateProjectResponse'&$sel:httpStatus:UpdateProjectResponse'&$sel:projectArn:UpdateProjectResponse' UpdateProjectUpdateProject'&$sel:projectDescription:UpdateProject';$sel:serviceCatalogProvisioningUpdateDetails:UpdateProject'$sel:tags:UpdateProject'$sel:projectName:UpdateProject'newUpdateProject updateProject_projectDescription5updateProject_serviceCatalogProvisioningUpdateDetailsupdateProject_tagsupdateProject_projectNamenewUpdateProjectResponse updateProjectResponse_httpStatus updateProjectResponse_projectArn$fToQueryUpdateProject$fToPathUpdateProject$fToJSONUpdateProject$fToHeadersUpdateProject$fNFDataUpdateProject$fHashableUpdateProject$fNFDataUpdateProjectResponse$fAWSRequestUpdateProject$fEqUpdateProjectResponse$fReadUpdateProjectResponse$fShowUpdateProjectResponse$fGenericUpdateProjectResponse$fEqUpdateProject$fReadUpdateProject$fShowUpdateProject$fGenericUpdateProjectUpdateSpaceResponseUpdateSpaceResponse'"$sel:spaceArn:UpdateSpaceResponse'$$sel:httpStatus:UpdateSpaceResponse' UpdateSpace UpdateSpace'$sel:spaceSettings:UpdateSpace'$sel:domainId:UpdateSpace'$sel:spaceName:UpdateSpace'newUpdateSpaceupdateSpace_spaceSettingsupdateSpace_domainIdupdateSpace_spaceNamenewUpdateSpaceResponseupdateSpaceResponse_spaceArnupdateSpaceResponse_httpStatus$fToQueryUpdateSpace$fToPathUpdateSpace$fToJSONUpdateSpace$fToHeadersUpdateSpace$fNFDataUpdateSpace$fHashableUpdateSpace$fNFDataUpdateSpaceResponse$fAWSRequestUpdateSpace$fEqUpdateSpaceResponse$fReadUpdateSpaceResponse$fShowUpdateSpaceResponse$fGenericUpdateSpaceResponse$fEqUpdateSpace$fReadUpdateSpace$fShowUpdateSpace$fGenericUpdateSpaceUpdateTrainingJobResponseUpdateTrainingJobResponse'*$sel:httpStatus:UpdateTrainingJobResponse'.$sel:trainingJobArn:UpdateTrainingJobResponse'UpdateTrainingJobUpdateTrainingJob'&$sel:profilerConfig:UpdateTrainingJob'2$sel:profilerRuleConfigurations:UpdateTrainingJob'&$sel:resourceConfig:UpdateTrainingJob''$sel:trainingJobName:UpdateTrainingJob'newUpdateTrainingJob updateTrainingJob_profilerConfig,updateTrainingJob_profilerRuleConfigurations updateTrainingJob_resourceConfig!updateTrainingJob_trainingJobNamenewUpdateTrainingJobResponse$updateTrainingJobResponse_httpStatus(updateTrainingJobResponse_trainingJobArn$fToQueryUpdateTrainingJob$fToPathUpdateTrainingJob$fToJSONUpdateTrainingJob$fToHeadersUpdateTrainingJob$fNFDataUpdateTrainingJob$fHashableUpdateTrainingJob!$fNFDataUpdateTrainingJobResponse$fAWSRequestUpdateTrainingJob$fEqUpdateTrainingJobResponse$fReadUpdateTrainingJobResponse$fShowUpdateTrainingJobResponse"$fGenericUpdateTrainingJobResponse$fEqUpdateTrainingJob$fReadUpdateTrainingJob$fShowUpdateTrainingJob$fGenericUpdateTrainingJobUpdateTrialResponseUpdateTrialResponse'"$sel:trialArn:UpdateTrialResponse'$$sel:httpStatus:UpdateTrialResponse' UpdateTrial UpdateTrial'$sel:displayName:UpdateTrial'$sel:trialName:UpdateTrial'newUpdateTrialupdateTrial_displayNameupdateTrial_trialNamenewUpdateTrialResponseupdateTrialResponse_trialArnupdateTrialResponse_httpStatus$fToQueryUpdateTrial$fToPathUpdateTrial$fToJSONUpdateTrial$fToHeadersUpdateTrial$fNFDataUpdateTrial$fHashableUpdateTrial$fNFDataUpdateTrialResponse$fAWSRequestUpdateTrial$fEqUpdateTrialResponse$fReadUpdateTrialResponse$fShowUpdateTrialResponse$fGenericUpdateTrialResponse$fEqUpdateTrial$fReadUpdateTrial$fShowUpdateTrial$fGenericUpdateTrialUpdateTrialComponentResponseUpdateTrialComponentResponse'4$sel:trialComponentArn:UpdateTrialComponentResponse'-$sel:httpStatus:UpdateTrialComponentResponse'UpdateTrialComponentUpdateTrialComponent'&$sel:displayName:UpdateTrialComponent'"$sel:endTime:UpdateTrialComponent')$sel:inputArtifacts:UpdateTrialComponent'1$sel:inputArtifactsToRemove:UpdateTrialComponent'*$sel:outputArtifacts:UpdateTrialComponent'2$sel:outputArtifactsToRemove:UpdateTrialComponent'%$sel:parameters:UpdateTrialComponent'-$sel:parametersToRemove:UpdateTrialComponent'$$sel:startTime:UpdateTrialComponent'!$sel:status:UpdateTrialComponent'-$sel:trialComponentName:UpdateTrialComponent'newUpdateTrialComponent updateTrialComponent_displayNameupdateTrialComponent_endTime#updateTrialComponent_inputArtifacts+updateTrialComponent_inputArtifactsToRemove$updateTrialComponent_outputArtifacts,updateTrialComponent_outputArtifactsToRemoveupdateTrialComponent_parameters'updateTrialComponent_parametersToRemoveupdateTrialComponent_startTimeupdateTrialComponent_status'updateTrialComponent_trialComponentNamenewUpdateTrialComponentResponse.updateTrialComponentResponse_trialComponentArn'updateTrialComponentResponse_httpStatus$fToQueryUpdateTrialComponent$fToPathUpdateTrialComponent$fToJSONUpdateTrialComponent$fToHeadersUpdateTrialComponent$fNFDataUpdateTrialComponent$fHashableUpdateTrialComponent$$fNFDataUpdateTrialComponentResponse $fAWSRequestUpdateTrialComponent $fEqUpdateTrialComponentResponse"$fReadUpdateTrialComponentResponse"$fShowUpdateTrialComponentResponse%$fGenericUpdateTrialComponentResponse$fEqUpdateTrialComponent$fReadUpdateTrialComponent$fShowUpdateTrialComponent$fGenericUpdateTrialComponentUpdateUserProfileResponseUpdateUserProfileResponse'.$sel:userProfileArn:UpdateUserProfileResponse'*$sel:httpStatus:UpdateUserProfileResponse'UpdateUserProfileUpdateUserProfile'$$sel:userSettings:UpdateUserProfile' $sel:domainId:UpdateUserProfile''$sel:userProfileName:UpdateUserProfile'newUpdateUserProfileupdateUserProfile_userSettingsupdateUserProfile_domainId!updateUserProfile_userProfileNamenewUpdateUserProfileResponse(updateUserProfileResponse_userProfileArn$updateUserProfileResponse_httpStatus$fToQueryUpdateUserProfile$fToPathUpdateUserProfile$fToJSONUpdateUserProfile$fToHeadersUpdateUserProfile$fNFDataUpdateUserProfile$fHashableUpdateUserProfile!$fNFDataUpdateUserProfileResponse$fAWSRequestUpdateUserProfile$fEqUpdateUserProfileResponse$fReadUpdateUserProfileResponse$fShowUpdateUserProfileResponse"$fGenericUpdateUserProfileResponse$fEqUpdateUserProfile$fReadUpdateUserProfile$fShowUpdateUserProfile$fGenericUpdateUserProfileUpdateWorkforceResponseUpdateWorkforceResponse'($sel:httpStatus:UpdateWorkforceResponse''$sel:workforce:UpdateWorkforceResponse'UpdateWorkforceUpdateWorkforce' $sel:oidcConfig:UpdateWorkforce'$$sel:sourceIpConfig:UpdateWorkforce'($sel:workforceVpcConfig:UpdateWorkforce'#$sel:workforceName:UpdateWorkforce'newUpdateWorkforceupdateWorkforce_oidcConfigupdateWorkforce_sourceIpConfig"updateWorkforce_workforceVpcConfigupdateWorkforce_workforceNamenewUpdateWorkforceResponse"updateWorkforceResponse_httpStatus!updateWorkforceResponse_workforce$fToQueryUpdateWorkforce$fToPathUpdateWorkforce$fToJSONUpdateWorkforce$fToHeadersUpdateWorkforce$fNFDataUpdateWorkforce$fHashableUpdateWorkforce$fNFDataUpdateWorkforceResponse$fAWSRequestUpdateWorkforce$fEqUpdateWorkforceResponse$fReadUpdateWorkforceResponse$fShowUpdateWorkforceResponse $fGenericUpdateWorkforceResponse$fEqUpdateWorkforce$fShowUpdateWorkforce$fGenericUpdateWorkforceUpdateWorkteamResponseUpdateWorkteamResponse''$sel:httpStatus:UpdateWorkteamResponse'%$sel:workteam:UpdateWorkteamResponse'UpdateWorkteamUpdateWorkteam' $sel:description:UpdateWorkteam'&$sel:memberDefinitions:UpdateWorkteam'.$sel:notificationConfiguration:UpdateWorkteam'!$sel:workteamName:UpdateWorkteam'newUpdateWorkteamupdateWorkteam_description updateWorkteam_memberDefinitions(updateWorkteam_notificationConfigurationupdateWorkteam_workteamNamenewUpdateWorkteamResponse!updateWorkteamResponse_httpStatusupdateWorkteamResponse_workteam$fToQueryUpdateWorkteam$fToPathUpdateWorkteam$fToJSONUpdateWorkteam$fToHeadersUpdateWorkteam$fNFDataUpdateWorkteam$fHashableUpdateWorkteam$fNFDataUpdateWorkteamResponse$fAWSRequestUpdateWorkteam$fEqUpdateWorkteamResponse$fReadUpdateWorkteamResponse$fShowUpdateWorkteamResponse$fGenericUpdateWorkteamResponse$fEqUpdateWorkteam$fReadUpdateWorkteam$fShowUpdateWorkteam$fGenericUpdateWorkteamnewEndpointDeletednewEndpointInServicenewImageCreatednewImageDeletednewImageUpdatednewImageVersionCreatednewImageVersionDeletednewNotebookInstanceDeletednewNotebookInstanceInServicenewNotebookInstanceStopped"newProcessingJobCompletedOrStopped newTrainingJobCompletedOrStopped!newTransformJobCompletedOrStopped