{-# LANGUAGE DeriveGeneric #-} {-# LANGUAGE DuplicateRecordFields #-} {-# LANGUAGE NamedFieldPuns #-} {-# LANGUAGE OverloadedStrings #-} {-# LANGUAGE RecordWildCards #-} {-# LANGUAGE StrictData #-} {-# LANGUAGE TypeFamilies #-} {-# LANGUAGE NoImplicitPrelude #-} {-# OPTIONS_GHC -fno-warn-unused-binds #-} {-# OPTIONS_GHC -fno-warn-unused-imports #-} {-# OPTIONS_GHC -fno-warn-unused-matches #-} -- Derived from AWS service descriptions, licensed under Apache 2.0. -- | -- Module : Amazonka.SageMaker.CreateAlgorithm -- Copyright : (c) 2013-2023 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated -- Portability : non-portable (GHC extensions) -- -- Create a machine learning algorithm that you can use in SageMaker and -- list in the Amazon Web Services Marketplace. module Amazonka.SageMaker.CreateAlgorithm ( -- * Creating a Request CreateAlgorithm (..), newCreateAlgorithm, -- * Request Lenses createAlgorithm_algorithmDescription, createAlgorithm_certifyForMarketplace, createAlgorithm_inferenceSpecification, createAlgorithm_tags, createAlgorithm_validationSpecification, createAlgorithm_algorithmName, createAlgorithm_trainingSpecification, -- * Destructuring the Response CreateAlgorithmResponse (..), newCreateAlgorithmResponse, -- * Response Lenses createAlgorithmResponse_httpStatus, createAlgorithmResponse_algorithmArn, ) where import qualified Amazonka.Core as Core import qualified Amazonka.Core.Lens.Internal as Lens import qualified Amazonka.Data as Data import qualified Amazonka.Prelude as Prelude import qualified Amazonka.Request as Request import qualified Amazonka.Response as Response import Amazonka.SageMaker.Types -- | /See:/ 'newCreateAlgorithm' smart constructor. data CreateAlgorithm = CreateAlgorithm' { -- | A description of the algorithm. algorithmDescription :: Prelude.Maybe Prelude.Text, -- | Whether to certify the algorithm so that it can be listed in Amazon Web -- Services Marketplace. certifyForMarketplace :: Prelude.Maybe Prelude.Bool, -- | 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. inferenceSpecification :: Prelude.Maybe InferenceSpecification, -- | 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 -- . tags :: Prelude.Maybe [Tag], -- | 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. validationSpecification :: Prelude.Maybe AlgorithmValidationSpecification, -- | The name of the algorithm. algorithmName :: Prelude.Text, -- | 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. trainingSpecification :: TrainingSpecification } deriving (Prelude.Eq, Prelude.Read, Prelude.Show, Prelude.Generic) -- | -- Create a value of 'CreateAlgorithm' with all optional fields omitted. -- -- Use or to modify other optional fields. -- -- The following record fields are available, with the corresponding lenses provided -- for backwards compatibility: -- -- 'algorithmDescription', 'createAlgorithm_algorithmDescription' - A description of the algorithm. -- -- 'certifyForMarketplace', 'createAlgorithm_certifyForMarketplace' - Whether to certify the algorithm so that it can be listed in Amazon Web -- Services Marketplace. -- -- 'inferenceSpecification', '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. -- -- 'tags', '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 -- . -- -- 'validationSpecification', '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. -- -- 'algorithmName', 'createAlgorithm_algorithmName' - The name of the algorithm. -- -- 'trainingSpecification', '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. newCreateAlgorithm :: -- | 'algorithmName' Prelude.Text -> -- | 'trainingSpecification' TrainingSpecification -> CreateAlgorithm newCreateAlgorithm pAlgorithmName_ pTrainingSpecification_ = CreateAlgorithm' { algorithmDescription = Prelude.Nothing, certifyForMarketplace = Prelude.Nothing, inferenceSpecification = Prelude.Nothing, tags = Prelude.Nothing, validationSpecification = Prelude.Nothing, algorithmName = pAlgorithmName_, trainingSpecification = pTrainingSpecification_ } -- | A description of the algorithm. createAlgorithm_algorithmDescription :: Lens.Lens' CreateAlgorithm (Prelude.Maybe Prelude.Text) createAlgorithm_algorithmDescription = Lens.lens (\CreateAlgorithm' {algorithmDescription} -> algorithmDescription) (\s@CreateAlgorithm' {} a -> s {algorithmDescription = a} :: CreateAlgorithm) -- | Whether to certify the algorithm so that it can be listed in Amazon Web -- Services Marketplace. createAlgorithm_certifyForMarketplace :: Lens.Lens' CreateAlgorithm (Prelude.Maybe Prelude.Bool) createAlgorithm_certifyForMarketplace = Lens.lens (\CreateAlgorithm' {certifyForMarketplace} -> certifyForMarketplace) (\s@CreateAlgorithm' {} a -> s {certifyForMarketplace = a} :: CreateAlgorithm) -- | 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_inferenceSpecification :: Lens.Lens' CreateAlgorithm (Prelude.Maybe InferenceSpecification) createAlgorithm_inferenceSpecification = Lens.lens (\CreateAlgorithm' {inferenceSpecification} -> inferenceSpecification) (\s@CreateAlgorithm' {} a -> s {inferenceSpecification = a} :: CreateAlgorithm) -- | 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 -- . createAlgorithm_tags :: Lens.Lens' CreateAlgorithm (Prelude.Maybe [Tag]) createAlgorithm_tags = Lens.lens (\CreateAlgorithm' {tags} -> tags) (\s@CreateAlgorithm' {} a -> s {tags = a} :: CreateAlgorithm) Prelude.. Lens.mapping Lens.coerced -- | 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_validationSpecification :: Lens.Lens' CreateAlgorithm (Prelude.Maybe AlgorithmValidationSpecification) createAlgorithm_validationSpecification = Lens.lens (\CreateAlgorithm' {validationSpecification} -> validationSpecification) (\s@CreateAlgorithm' {} a -> s {validationSpecification = a} :: CreateAlgorithm) -- | The name of the algorithm. createAlgorithm_algorithmName :: Lens.Lens' CreateAlgorithm Prelude.Text createAlgorithm_algorithmName = Lens.lens (\CreateAlgorithm' {algorithmName} -> algorithmName) (\s@CreateAlgorithm' {} a -> s {algorithmName = a} :: CreateAlgorithm) -- | 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. createAlgorithm_trainingSpecification :: Lens.Lens' CreateAlgorithm TrainingSpecification createAlgorithm_trainingSpecification = Lens.lens (\CreateAlgorithm' {trainingSpecification} -> trainingSpecification) (\s@CreateAlgorithm' {} a -> s {trainingSpecification = a} :: CreateAlgorithm) instance Core.AWSRequest CreateAlgorithm where type AWSResponse CreateAlgorithm = CreateAlgorithmResponse request overrides = Request.postJSON (overrides defaultService) response = Response.receiveJSON ( \s h x -> CreateAlgorithmResponse' Prelude.<$> (Prelude.pure (Prelude.fromEnum s)) Prelude.<*> (x Data..:> "AlgorithmArn") ) instance Prelude.Hashable CreateAlgorithm where hashWithSalt _salt CreateAlgorithm' {..} = _salt `Prelude.hashWithSalt` algorithmDescription `Prelude.hashWithSalt` certifyForMarketplace `Prelude.hashWithSalt` inferenceSpecification `Prelude.hashWithSalt` tags `Prelude.hashWithSalt` validationSpecification `Prelude.hashWithSalt` algorithmName `Prelude.hashWithSalt` trainingSpecification instance Prelude.NFData CreateAlgorithm where rnf CreateAlgorithm' {..} = Prelude.rnf algorithmDescription `Prelude.seq` Prelude.rnf certifyForMarketplace `Prelude.seq` Prelude.rnf inferenceSpecification `Prelude.seq` Prelude.rnf tags `Prelude.seq` Prelude.rnf validationSpecification `Prelude.seq` Prelude.rnf algorithmName `Prelude.seq` Prelude.rnf trainingSpecification instance Data.ToHeaders CreateAlgorithm where toHeaders = Prelude.const ( Prelude.mconcat [ "X-Amz-Target" Data.=# ("SageMaker.CreateAlgorithm" :: Prelude.ByteString), "Content-Type" Data.=# ( "application/x-amz-json-1.1" :: Prelude.ByteString ) ] ) instance Data.ToJSON CreateAlgorithm where toJSON CreateAlgorithm' {..} = Data.object ( Prelude.catMaybes [ ("AlgorithmDescription" Data..=) Prelude.<$> algorithmDescription, ("CertifyForMarketplace" Data..=) Prelude.<$> certifyForMarketplace, ("InferenceSpecification" Data..=) Prelude.<$> inferenceSpecification, ("Tags" Data..=) Prelude.<$> tags, ("ValidationSpecification" Data..=) Prelude.<$> validationSpecification, Prelude.Just ("AlgorithmName" Data..= algorithmName), Prelude.Just ( "TrainingSpecification" Data..= trainingSpecification ) ] ) instance Data.ToPath CreateAlgorithm where toPath = Prelude.const "/" instance Data.ToQuery CreateAlgorithm where toQuery = Prelude.const Prelude.mempty -- | /See:/ 'newCreateAlgorithmResponse' smart constructor. data CreateAlgorithmResponse = CreateAlgorithmResponse' { -- | The response's http status code. httpStatus :: Prelude.Int, -- | The Amazon Resource Name (ARN) of the new algorithm. algorithmArn :: Prelude.Text } deriving (Prelude.Eq, Prelude.Read, Prelude.Show, Prelude.Generic) -- | -- Create a value of 'CreateAlgorithmResponse' with all optional fields omitted. -- -- Use or to modify other optional fields. -- -- The following record fields are available, with the corresponding lenses provided -- for backwards compatibility: -- -- 'httpStatus', 'createAlgorithmResponse_httpStatus' - The response's http status code. -- -- 'algorithmArn', 'createAlgorithmResponse_algorithmArn' - The Amazon Resource Name (ARN) of the new algorithm. newCreateAlgorithmResponse :: -- | 'httpStatus' Prelude.Int -> -- | 'algorithmArn' Prelude.Text -> CreateAlgorithmResponse newCreateAlgorithmResponse pHttpStatus_ pAlgorithmArn_ = CreateAlgorithmResponse' { httpStatus = pHttpStatus_, algorithmArn = pAlgorithmArn_ } -- | The response's http status code. createAlgorithmResponse_httpStatus :: Lens.Lens' CreateAlgorithmResponse Prelude.Int createAlgorithmResponse_httpStatus = Lens.lens (\CreateAlgorithmResponse' {httpStatus} -> httpStatus) (\s@CreateAlgorithmResponse' {} a -> s {httpStatus = a} :: CreateAlgorithmResponse) -- | The Amazon Resource Name (ARN) of the new algorithm. createAlgorithmResponse_algorithmArn :: Lens.Lens' CreateAlgorithmResponse Prelude.Text createAlgorithmResponse_algorithmArn = Lens.lens (\CreateAlgorithmResponse' {algorithmArn} -> algorithmArn) (\s@CreateAlgorithmResponse' {} a -> s {algorithmArn = a} :: CreateAlgorithmResponse) instance Prelude.NFData CreateAlgorithmResponse where rnf CreateAlgorithmResponse' {..} = Prelude.rnf httpStatus `Prelude.seq` Prelude.rnf algorithmArn