amazonka-ml-1.6.0: Amazon Machine Learning SDK.

Copyright(c) 2013-2018 Brendan Hay
LicenseMozilla Public License, v. 2.0.
MaintainerBrendan Hay <brendan.g.hay+amazonka@gmail.com>
Stabilityauto-generated
Portabilitynon-portable (GHC extensions)
Safe HaskellNone
LanguageHaskell2010

Network.AWS.MachineLearning.DeleteMLModel

Contents

Description

Assigns the DELETED status to an MLModel , rendering it unusable.

After using the DeleteMLModel operation, you can use the GetMLModel operation to verify that the status of the MLModel changed to DELETED.

Caution: The result of the DeleteMLModel operation is irreversible.

Synopsis

Creating a Request

deleteMLModel Source #

Creates a value of DeleteMLModel with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

  • dmlmMLModelId - A user-supplied ID that uniquely identifies the MLModel .

data DeleteMLModel Source #

See: deleteMLModel smart constructor.

Instances

Eq DeleteMLModel Source # 
Data DeleteMLModel Source # 

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> DeleteMLModel -> c DeleteMLModel #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c DeleteMLModel #

toConstr :: DeleteMLModel -> Constr #

dataTypeOf :: DeleteMLModel -> DataType #

dataCast1 :: Typeable (* -> *) t => (forall d. Data d => c (t d)) -> Maybe (c DeleteMLModel) #

dataCast2 :: Typeable (* -> * -> *) t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c DeleteMLModel) #

gmapT :: (forall b. Data b => b -> b) -> DeleteMLModel -> DeleteMLModel #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> DeleteMLModel -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> DeleteMLModel -> r #

gmapQ :: (forall d. Data d => d -> u) -> DeleteMLModel -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> DeleteMLModel -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> DeleteMLModel -> m DeleteMLModel #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> DeleteMLModel -> m DeleteMLModel #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> DeleteMLModel -> m DeleteMLModel #

Read DeleteMLModel Source # 
Show DeleteMLModel Source # 
Generic DeleteMLModel Source # 

Associated Types

type Rep DeleteMLModel :: * -> * #

Hashable DeleteMLModel Source # 
ToJSON DeleteMLModel Source # 
NFData DeleteMLModel Source # 

Methods

rnf :: DeleteMLModel -> () #

AWSRequest DeleteMLModel Source # 
ToHeaders DeleteMLModel Source # 
ToPath DeleteMLModel Source # 
ToQuery DeleteMLModel Source # 
type Rep DeleteMLModel Source # 
type Rep DeleteMLModel = D1 * (MetaData "DeleteMLModel" "Network.AWS.MachineLearning.DeleteMLModel" "amazonka-ml-1.6.0-Ieesuz5Kri8FW4cNPxVPkB" True) (C1 * (MetaCons "DeleteMLModel'" PrefixI True) (S1 * (MetaSel (Just Symbol "_dmlmMLModelId") NoSourceUnpackedness NoSourceStrictness DecidedLazy) (Rec0 * Text)))
type Rs DeleteMLModel Source # 

Request Lenses

dmlmMLModelId :: Lens' DeleteMLModel Text Source #

A user-supplied ID that uniquely identifies the MLModel .

Destructuring the Response

deleteMLModelResponse Source #

Creates a value of DeleteMLModelResponse with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

  • dmlmrsMLModelId - A user-supplied ID that uniquely identifies the MLModel . This value should be identical to the value of the MLModelID in the request.
  • dmlmrsResponseStatus - -- | The response status code.

data DeleteMLModelResponse Source #

Represents the output of a DeleteMLModel operation.

You can use the GetMLModel operation and check the value of the Status parameter to see whether an MLModel is marked as DELETED .

See: deleteMLModelResponse smart constructor.

Instances

Eq DeleteMLModelResponse Source # 
Data DeleteMLModelResponse Source # 

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> DeleteMLModelResponse -> c DeleteMLModelResponse #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c DeleteMLModelResponse #

toConstr :: DeleteMLModelResponse -> Constr #

dataTypeOf :: DeleteMLModelResponse -> DataType #

dataCast1 :: Typeable (* -> *) t => (forall d. Data d => c (t d)) -> Maybe (c DeleteMLModelResponse) #

dataCast2 :: Typeable (* -> * -> *) t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c DeleteMLModelResponse) #

gmapT :: (forall b. Data b => b -> b) -> DeleteMLModelResponse -> DeleteMLModelResponse #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> DeleteMLModelResponse -> r #

gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> DeleteMLModelResponse -> r #

gmapQ :: (forall d. Data d => d -> u) -> DeleteMLModelResponse -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> DeleteMLModelResponse -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> DeleteMLModelResponse -> m DeleteMLModelResponse #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> DeleteMLModelResponse -> m DeleteMLModelResponse #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> DeleteMLModelResponse -> m DeleteMLModelResponse #

Read DeleteMLModelResponse Source # 
Show DeleteMLModelResponse Source # 
Generic DeleteMLModelResponse Source # 
NFData DeleteMLModelResponse Source # 

Methods

rnf :: DeleteMLModelResponse -> () #

type Rep DeleteMLModelResponse Source # 
type Rep DeleteMLModelResponse = D1 * (MetaData "DeleteMLModelResponse" "Network.AWS.MachineLearning.DeleteMLModel" "amazonka-ml-1.6.0-Ieesuz5Kri8FW4cNPxVPkB" False) (C1 * (MetaCons "DeleteMLModelResponse'" PrefixI True) ((:*:) * (S1 * (MetaSel (Just Symbol "_dmlmrsMLModelId") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 * (Maybe Text))) (S1 * (MetaSel (Just Symbol "_dmlmrsResponseStatus") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 * Int))))

Response Lenses

dmlmrsMLModelId :: Lens' DeleteMLModelResponse (Maybe Text) Source #

A user-supplied ID that uniquely identifies the MLModel . This value should be identical to the value of the MLModelID in the request.