amazonka-sagemaker-2.0: Amazon SageMaker Service SDK.
Copyright(c) 2013-2023 Brendan Hay
LicenseMozilla Public License, v. 2.0.
MaintainerBrendan Hay
Stabilityauto-generated
Portabilitynon-portable (GHC extensions)
Safe HaskellSafe-Inferred
LanguageHaskell2010

Amazonka.SageMaker.CreateAlgorithm

Description

Create a machine learning algorithm that you can use in SageMaker and list in the Amazon Web Services Marketplace.

Synopsis

Creating a Request

data CreateAlgorithm Source #

See: newCreateAlgorithm smart constructor.

Constructors

CreateAlgorithm' 

Fields

  • algorithmDescription :: Maybe Text

    A description of the algorithm.

  • certifyForMarketplace :: Maybe Bool

    Whether to certify the algorithm so that it can be listed in Amazon Web Services Marketplace.

  • inferenceSpecification :: Maybe InferenceSpecification

    Specifies 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.
  • tags :: Maybe [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 Tagging Amazon Web Services Resources.

  • validationSpecification :: Maybe AlgorithmValidationSpecification

    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.

  • algorithmName :: Text

    The name of the algorithm.

  • trainingSpecification :: TrainingSpecification

    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.
    • The hyperparameters that the algorithm supports.
    • The instance types that the algorithm supports for training.
    • Whether the algorithm supports distributed training.
    • The metrics that the algorithm emits to Amazon CloudWatch.
    • Which metrics that the algorithm emits can be used as the objective metric for hyperparameter tuning jobs.
    • The input channels that the algorithm supports for training data. For example, an algorithm might support train, validation, and test channels.

Instances

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ToJSON CreateAlgorithm Source # 
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ToHeaders CreateAlgorithm Source # 
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ToPath CreateAlgorithm Source # 
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ToQuery CreateAlgorithm Source # 
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AWSRequest CreateAlgorithm Source # 
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Associated Types

type AWSResponse CreateAlgorithm #

Generic CreateAlgorithm Source # 
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Associated Types

type Rep CreateAlgorithm :: Type -> Type #

Read CreateAlgorithm Source # 
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Show CreateAlgorithm Source # 
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NFData CreateAlgorithm Source # 
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Methods

rnf :: CreateAlgorithm -> () #

Eq CreateAlgorithm Source # 
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Hashable CreateAlgorithm Source # 
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type AWSResponse CreateAlgorithm Source # 
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type Rep CreateAlgorithm Source # 
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type Rep CreateAlgorithm = D1 ('MetaData "CreateAlgorithm" "Amazonka.SageMaker.CreateAlgorithm" "amazonka-sagemaker-2.0-9SyrKZ4KqhsL1qX9u3ILA3" 'False) (C1 ('MetaCons "CreateAlgorithm'" 'PrefixI 'True) ((S1 ('MetaSel ('Just "algorithmDescription") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)) :*: (S1 ('MetaSel ('Just "certifyForMarketplace") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Bool)) :*: S1 ('MetaSel ('Just "inferenceSpecification") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe InferenceSpecification)))) :*: ((S1 ('MetaSel ('Just "tags") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe [Tag])) :*: S1 ('MetaSel ('Just "validationSpecification") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe AlgorithmValidationSpecification))) :*: (S1 ('MetaSel ('Just "algorithmName") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 Text) :*: S1 ('MetaSel ('Just "trainingSpecification") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 TrainingSpecification)))))

newCreateAlgorithm Source #

Create a value of CreateAlgorithm 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:

CreateAlgorithm, createAlgorithm_algorithmDescription - A description of the algorithm.

CreateAlgorithm, createAlgorithm_certifyForMarketplace - Whether to certify the algorithm so that it can be listed in Amazon Web Services Marketplace.

CreateAlgorithm, createAlgorithm_inferenceSpecification - Specifies 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.

CreateAlgorithm, createAlgorithm_tags - 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 Tagging Amazon Web Services Resources.

CreateAlgorithm, createAlgorithm_validationSpecification - 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.

CreateAlgorithm, createAlgorithm_algorithmName - The name of the algorithm.

$sel:trainingSpecification:CreateAlgorithm', createAlgorithm_trainingSpecification - 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.
  • The hyperparameters that the algorithm supports.
  • The instance types that the algorithm supports for training.
  • Whether the algorithm supports distributed training.
  • The metrics that the algorithm emits to Amazon CloudWatch.
  • Which metrics that the algorithm emits can be used as the objective metric for hyperparameter tuning jobs.
  • The input channels that the algorithm supports for training data. For example, an algorithm might support train, validation, and test channels.

Request Lenses

createAlgorithm_certifyForMarketplace :: Lens' CreateAlgorithm (Maybe Bool) Source #

Whether to certify the algorithm so that it can be listed in Amazon Web Services Marketplace.

createAlgorithm_inferenceSpecification :: Lens' CreateAlgorithm (Maybe InferenceSpecification) Source #

Specifies 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.

createAlgorithm_tags :: Lens' CreateAlgorithm (Maybe [Tag]) Source #

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 Tagging Amazon Web Services Resources.

createAlgorithm_validationSpecification :: Lens' CreateAlgorithm (Maybe AlgorithmValidationSpecification) Source #

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.

createAlgorithm_trainingSpecification :: Lens' CreateAlgorithm TrainingSpecification Source #

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.
  • The hyperparameters that the algorithm supports.
  • The instance types that the algorithm supports for training.
  • Whether the algorithm supports distributed training.
  • The metrics that the algorithm emits to Amazon CloudWatch.
  • Which metrics that the algorithm emits can be used as the objective metric for hyperparameter tuning jobs.
  • The input channels that the algorithm supports for training data. For example, an algorithm might support train, validation, and test channels.

Destructuring the Response

data CreateAlgorithmResponse Source #

See: newCreateAlgorithmResponse smart constructor.

Constructors

CreateAlgorithmResponse' 

Fields

Instances

Instances details
Generic CreateAlgorithmResponse Source # 
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Associated Types

type Rep CreateAlgorithmResponse :: Type -> Type #

Read CreateAlgorithmResponse Source # 
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Show CreateAlgorithmResponse Source # 
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NFData CreateAlgorithmResponse Source # 
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Methods

rnf :: CreateAlgorithmResponse -> () #

Eq CreateAlgorithmResponse Source # 
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type Rep CreateAlgorithmResponse Source # 
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type Rep CreateAlgorithmResponse = D1 ('MetaData "CreateAlgorithmResponse" "Amazonka.SageMaker.CreateAlgorithm" "amazonka-sagemaker-2.0-9SyrKZ4KqhsL1qX9u3ILA3" 'False) (C1 ('MetaCons "CreateAlgorithmResponse'" 'PrefixI 'True) (S1 ('MetaSel ('Just "httpStatus") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 Int) :*: S1 ('MetaSel ('Just "algorithmArn") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 Text)))

newCreateAlgorithmResponse Source #

Create a value of CreateAlgorithmResponse 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:httpStatus:CreateAlgorithmResponse', createAlgorithmResponse_httpStatus - The response's http status code.

CreateAlgorithmResponse, createAlgorithmResponse_algorithmArn - The Amazon Resource Name (ARN) of the new algorithm.

Response Lenses

createAlgorithmResponse_algorithmArn :: Lens' CreateAlgorithmResponse Text Source #

The Amazon Resource Name (ARN) of the new algorithm.