Amazonka.SageMaker.Types.TrainingSpecification

Documentation

data TrainingSpecification

Defines how the algorithm is used for a training job.

See: newTrainingSpecification smart constructor.

Constructors

TrainingSpecification'

Fields

• metricDefinitions :: Maybe [MetricDefinition]

  A list of MetricDefinition objects, which are used for parsing metrics generated by the algorithm.

• supportedHyperParameters :: Maybe [HyperParameterSpecification]

  A list of the HyperParameterSpecification objects, that define the supported hyperparameters. This is required if the algorithm supports automatic model tuning.>

• supportedTuningJobObjectiveMetrics :: Maybe [HyperParameterTuningJobObjective]

  A list of the metrics that the algorithm emits that can be used as the objective metric in a hyperparameter tuning job.

• supportsDistributedTraining :: Maybe Bool

  Indicates whether the algorithm supports distributed training. If set to false, buyers can't request more than one instance during training.

• trainingImageDigest :: Maybe Text

  An MD5 hash of the training algorithm that identifies the Docker image used for training.

• trainingImage :: Text

  The Amazon ECR registry path of the Docker image that contains the training algorithm.

• supportedTrainingInstanceTypes :: [TrainingInstanceType]

  A list of the instance types that this algorithm can use for training.

• trainingChannels :: NonEmpty ChannelSpecification

  A list of ChannelSpecification objects, which specify the input sources to be used by the algorithm.

Instances

FromJSON TrainingSpecification

Defined in Amazonka.SageMaker.Types.TrainingSpecification

Methods

parseJSON :: Value -> Parser TrainingSpecification

parseJSONList :: Value -> Parser [TrainingSpecification]

ToJSON TrainingSpecification

Defined in Amazonka.SageMaker.Types.TrainingSpecification

Methods

toJSON :: TrainingSpecification -> Value

toEncoding :: TrainingSpecification -> Encoding

toJSONList :: [TrainingSpecification] -> Value

toEncodingList :: [TrainingSpecification] -> Encoding

Generic TrainingSpecification

Defined in Amazonka.SageMaker.Types.TrainingSpecification

Associated Types

type Rep TrainingSpecification :: Type -> Type

Methods

from :: TrainingSpecification -> Rep TrainingSpecification x

to :: Rep TrainingSpecification x -> TrainingSpecification

Read TrainingSpecification

Defined in Amazonka.SageMaker.Types.TrainingSpecification

Methods

readsPrec :: Int -> ReadS TrainingSpecification

readList :: ReadS [TrainingSpecification]

readPrec :: ReadPrec TrainingSpecification

readListPrec :: ReadPrec [TrainingSpecification]

Show TrainingSpecification

Defined in Amazonka.SageMaker.Types.TrainingSpecification

Methods

showsPrec :: Int -> TrainingSpecification -> ShowS

show :: TrainingSpecification -> String

showList :: [TrainingSpecification] -> ShowS

NFData TrainingSpecification

Defined in Amazonka.SageMaker.Types.TrainingSpecification

Methods

rnf :: TrainingSpecification -> ()

Eq TrainingSpecification

Defined in Amazonka.SageMaker.Types.TrainingSpecification

Methods

(==) :: TrainingSpecification -> TrainingSpecification -> Bool

(/=) :: TrainingSpecification -> TrainingSpecification -> Bool

Hashable TrainingSpecification

Defined in Amazonka.SageMaker.Types.TrainingSpecification

Methods

hashWithSalt :: Int -> TrainingSpecification -> Int

hash :: TrainingSpecification -> Int

type Rep TrainingSpecification

Defined in Amazonka.SageMaker.Types.TrainingSpecification

type Rep TrainingSpecification = D1 ('MetaData "TrainingSpecification" "Amazonka.SageMaker.Types.TrainingSpecification" "amazonka-sagemaker-2.0-9SyrKZ4KqhsL1qX9u3ILA3" 'False) (C1 ('MetaCons "TrainingSpecification'" 'PrefixI 'True) (((S1 ('MetaSel ('Just "metricDefinitions") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe [MetricDefinition])) :*: S1 ('MetaSel ('Just "supportedHyperParameters") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe [HyperParameterSpecification]))) :*: (S1 ('MetaSel ('Just "supportedTuningJobObjectiveMetrics") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe [HyperParameterTuningJobObjective])) :*: S1 ('MetaSel ('Just "supportsDistributedTraining") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Bool)))) :*: ((S1 ('MetaSel ('Just "trainingImageDigest") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)) :*: S1 ('MetaSel ('Just "trainingImage") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 Text)) :*: (S1 ('MetaSel ('Just "supportedTrainingInstanceTypes") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 [TrainingInstanceType]) :*: S1 ('MetaSel ('Just "trainingChannels") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (NonEmpty ChannelSpecification))))))

newTrainingSpecification

Arguments

:: Text

$sel:trainingImage:TrainingSpecification'

-> NonEmpty ChannelSpecification

$sel:trainingChannels:TrainingSpecification'

-> TrainingSpecification

Create a value of TrainingSpecification with all optional fields omitted.

Use generic-lens or optics to modify other optional fields.

The following record fields are available, with the corresponding lenses provided for backwards compatibility:

$sel:metricDefinitions:TrainingSpecification', trainingSpecification_metricDefinitions - A list of MetricDefinition objects, which are used for parsing metrics generated by the algorithm.

$sel:supportedHyperParameters:TrainingSpecification', trainingSpecification_supportedHyperParameters - A list of the HyperParameterSpecification objects, that define the supported hyperparameters. This is required if the algorithm supports automatic model tuning.>

$sel:supportedTuningJobObjectiveMetrics:TrainingSpecification', trainingSpecification_supportedTuningJobObjectiveMetrics - A list of the metrics that the algorithm emits that can be used as the objective metric in a hyperparameter tuning job.

$sel:supportsDistributedTraining:TrainingSpecification', trainingSpecification_supportsDistributedTraining - Indicates whether the algorithm supports distributed training. If set to false, buyers can't request more than one instance during training.

$sel:trainingImageDigest:TrainingSpecification', trainingSpecification_trainingImageDigest - An MD5 hash of the training algorithm that identifies the Docker image used for training.

$sel:trainingImage:TrainingSpecification', trainingSpecification_trainingImage - The Amazon ECR registry path of the Docker image that contains the training algorithm.

$sel:supportedTrainingInstanceTypes:TrainingSpecification', trainingSpecification_supportedTrainingInstanceTypes - A list of the instance types that this algorithm can use for training.

$sel:trainingChannels:TrainingSpecification', trainingSpecification_trainingChannels - A list of ChannelSpecification objects, which specify the input sources to be used by the algorithm.

trainingSpecification_metricDefinitions :: Lens' TrainingSpecification (Maybe [MetricDefinition])

A list of MetricDefinition objects, which are used for parsing metrics generated by the algorithm.

trainingSpecification_supportedHyperParameters :: Lens' TrainingSpecification (Maybe [HyperParameterSpecification])

A list of the HyperParameterSpecification objects, that define the supported hyperparameters. This is required if the algorithm supports automatic model tuning.>

trainingSpecification_supportedTuningJobObjectiveMetrics :: Lens' TrainingSpecification (Maybe [HyperParameterTuningJobObjective])

A list of the metrics that the algorithm emits that can be used as the objective metric in a hyperparameter tuning job.

trainingSpecification_supportsDistributedTraining :: Lens' TrainingSpecification (Maybe Bool)

Indicates whether the algorithm supports distributed training. If set to false, buyers can't request more than one instance during training.

trainingSpecification_trainingImageDigest :: Lens' TrainingSpecification (Maybe Text)

An MD5 hash of the training algorithm that identifies the Docker image used for training.

trainingSpecification_trainingImage :: Lens' TrainingSpecification Text

The Amazon ECR registry path of the Docker image that contains the training algorithm.

trainingSpecification_supportedTrainingInstanceTypes :: Lens' TrainingSpecification [TrainingInstanceType]

A list of the instance types that this algorithm can use for training.

trainingSpecification_trainingChannels :: Lens' TrainingSpecification (NonEmpty ChannelSpecification)

A list of ChannelSpecification objects, which specify the input sources to be used by the algorithm.