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feat(client-sagemaker): Amazon Sagemaker Autopilot releases CreateAutoMLJobV2 and DescribeAutoMLJobV2 for Autopilot customers with ImageClassification, TextClassification and Tabular problem type config support.
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clients/client-sagemaker/src/commands/CreateAutoMLJobCommand.ts

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@@ -36,10 +36,17 @@ export interface CreateAutoMLJobCommandOutput extends CreateAutoMLJobResponse, _
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/**
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* @public
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* <p>Creates an Autopilot job.</p>
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* <p>Find the best-performing model after you run an Autopilot job by calling <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DescribeAutoMLJob.html">DescribeAutoMLJob</a>.</p>
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* <p>For information about how to use Autopilot, see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development.html">Automate Model
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* Development with Amazon SageMaker Autopilot</a>.</p>
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* <p>Creates an Autopilot job also referred to as Autopilot experiment or AutoML job.</p>
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* <p>Find the best-performing model after you run an AutoML job by calling <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DescribeAutoMLJobV2.html">DescribeAutoMLJobV2</a> (recommended) or <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DescribeAutoMLJob.html">DescribeAutoMLJob</a>.</p>
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* <note>
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* <p>
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* <code>CreateAutoMLJob</code> only accepts tabular input data. We recommend using
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* <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateAutoMLJobV2.html">CreateAutoMLJobV2</a> for all problem types. <code>CreateAutoMLJobV2</code> can
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* process the same tabular data as its previous version <code>CreateAutoMLJob</code>, as
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* well as non-tabular data for problem types such as image or text classification.</p>
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* <p>Find guidelines about how to migrate <code>CreateAutoMLJob</code> to
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* <code>CreateAutoMLJobV2</code> in <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development-create-experiment-api.html#autopilot-create-experiment-api-migrate-v1-v2">Migrate a CreateAutoMLJob to CreateAutoMLJobV2</a>.</p>
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* </note>
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* @example
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* Use a bare-bones client and the command you need to make an API call.
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* ```javascript

clients/client-sagemaker/src/commands/CreateAutoMLJobV2Command.ts

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@@ -36,14 +36,17 @@ export interface CreateAutoMLJobV2CommandOutput extends CreateAutoMLJobV2Respons
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/**
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* @public
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* <p>Creates an Amazon SageMaker AutoML job that uses non-tabular data such as images or text for
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* Computer Vision or Natural Language Processing problems.</p>
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* <p>Find the resulting model after you run an AutoML job V2 by calling <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DescribeAutoMLJobV2.html">DescribeAutoMLJobV2</a>.</p>
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* <p>To create an <code>AutoMLJob</code> using tabular data, see <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateAutoMLJob.html">CreateAutoMLJob</a>.</p>
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* <note>
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* <p>This API action is callable through SageMaker Canvas only. Calling it directly from the CLI
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* or an SDK results in an error.</p>
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* </note>
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* <p>Creates an Autopilot job also referred to as Autopilot experiment or AutoML job V2.</p>
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* <p>We recommend using <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateAutoMLJobV2.html">CreateAutoMLJobV2</a>
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* for all problem types. <code>CreateAutoMLJobV2</code> can process the same tabular data as
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* its previous version <code>CreateAutoMLJob</code>, as well as non-tabular data for problem
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* types such as image or text classification.</p>
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* <p>Find guidelines about how to migrate <code>CreateAutoMLJob</code> to
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* <code>CreateAutoMLJobV2</code> in <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development-create-experiment-api.html#autopilot-create-experiment-api-migrate-v1-v2">Migrate a CreateAutoMLJob to CreateAutoMLJobV2</a>.</p>
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* <p>For the list of available problem types supported by <code>CreateAutoMLJobV2</code>, see
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* <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_AutoMLProblemTypeConfig.html">AutoMLProblemTypeConfig</a>.</p>
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* <p>Find the best-performing model after you run an AutoML job V2 by calling <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DescribeAutoMLJobV2.html">DescribeAutoMLJobV2</a>. Calling <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DescribeAutoMLJob.html">DescribeAutoMLJob</a>
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* on a AutoML job V2 results in an error.</p>
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* @example
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* Use a bare-bones client and the command you need to make an API call.
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* ```javascript
@@ -86,6 +89,28 @@ export interface CreateAutoMLJobV2CommandOutput extends CreateAutoMLJobV2Respons
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* ContentColumn: "STRING_VALUE",
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* TargetLabelColumn: "STRING_VALUE",
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* },
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* TabularJobConfig: { // TabularJobConfig
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* CandidateGenerationConfig: { // CandidateGenerationConfig
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* AlgorithmsConfig: [ // AutoMLAlgorithmsConfig
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* { // AutoMLAlgorithmConfig
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* AutoMLAlgorithms: [ // AutoMLAlgorithms // required
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* "xgboost" || "linear-learner" || "mlp" || "lightgbm" || "catboost" || "randomforest" || "extra-trees" || "nn-torch" || "fastai",
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* ],
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* },
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* ],
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* },
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* CompletionCriteria: {
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* MaxCandidates: Number("int"),
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* MaxRuntimePerTrainingJobInSeconds: Number("int"),
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* MaxAutoMLJobRuntimeInSeconds: Number("int"),
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* },
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* FeatureSpecificationS3Uri: "STRING_VALUE",
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* Mode: "AUTO" || "ENSEMBLING" || "HYPERPARAMETER_TUNING",
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* GenerateCandidateDefinitionsOnly: true || false,
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* ProblemType: "BinaryClassification" || "MulticlassClassification" || "Regression",
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* TargetAttributeName: "STRING_VALUE", // required
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* SampleWeightAttributeName: "STRING_VALUE",
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* },
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* },
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* RoleArn: "STRING_VALUE", // required
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* Tags: [ // TagList

clients/client-sagemaker/src/commands/DeleteModelQualityJobDefinitionCommand.ts

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@@ -13,7 +13,7 @@ import {
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import { HttpRequest as __HttpRequest, HttpResponse as __HttpResponse } from "@smithy/protocol-http";
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import { SerdeContext as __SerdeContext } from "@smithy/types";
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import { DeleteModelQualityJobDefinitionRequest } from "../models/models_1";
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import { DeleteModelQualityJobDefinitionRequest } from "../models/models_2";
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import {
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de_DeleteModelQualityJobDefinitionCommand,
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se_DeleteModelQualityJobDefinitionCommand,

clients/client-sagemaker/src/commands/DeleteMonitoringScheduleCommand.ts

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@@ -13,7 +13,7 @@ import {
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import { HttpRequest as __HttpRequest, HttpResponse as __HttpResponse } from "@smithy/protocol-http";
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import { SerdeContext as __SerdeContext } from "@smithy/types";
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import { DeleteMonitoringScheduleRequest } from "../models/models_1";
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import { DeleteMonitoringScheduleRequest } from "../models/models_2";
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import { de_DeleteMonitoringScheduleCommand, se_DeleteMonitoringScheduleCommand } from "../protocols/Aws_json1_1";
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import { SageMakerClientResolvedConfig, ServiceInputTypes, ServiceOutputTypes } from "../SageMakerClient";
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clients/client-sagemaker/src/commands/DeleteNotebookInstanceCommand.ts

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@@ -13,7 +13,7 @@ import {
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import { HttpRequest as __HttpRequest, HttpResponse as __HttpResponse } from "@smithy/protocol-http";
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import { SerdeContext as __SerdeContext } from "@smithy/types";
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import { DeleteNotebookInstanceInput } from "../models/models_1";
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import { DeleteNotebookInstanceInput } from "../models/models_2";
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import { de_DeleteNotebookInstanceCommand, se_DeleteNotebookInstanceCommand } from "../protocols/Aws_json1_1";
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import { SageMakerClientResolvedConfig, ServiceInputTypes, ServiceOutputTypes } from "../SageMakerClient";
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clients/client-sagemaker/src/commands/DeleteNotebookInstanceLifecycleConfigCommand.ts

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@@ -13,7 +13,7 @@ import {
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import { HttpRequest as __HttpRequest, HttpResponse as __HttpResponse } from "@smithy/protocol-http";
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import { SerdeContext as __SerdeContext } from "@smithy/types";
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import { DeleteNotebookInstanceLifecycleConfigInput } from "../models/models_1";
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import { DeleteNotebookInstanceLifecycleConfigInput } from "../models/models_2";
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import {
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de_DeleteNotebookInstanceLifecycleConfigCommand,
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se_DeleteNotebookInstanceLifecycleConfigCommand,

clients/client-sagemaker/src/commands/DeletePipelineCommand.ts

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@@ -13,7 +13,7 @@ import {
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import { HttpRequest as __HttpRequest, HttpResponse as __HttpResponse } from "@smithy/protocol-http";
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import { SerdeContext as __SerdeContext } from "@smithy/types";
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import { DeletePipelineRequest, DeletePipelineResponse } from "../models/models_1";
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import { DeletePipelineRequest, DeletePipelineResponse } from "../models/models_2";
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import { de_DeletePipelineCommand, se_DeletePipelineCommand } from "../protocols/Aws_json1_1";
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import { SageMakerClientResolvedConfig, ServiceInputTypes, ServiceOutputTypes } from "../SageMakerClient";
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clients/client-sagemaker/src/commands/DescribeAutoMLJobCommand.ts

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@@ -36,7 +36,7 @@ export interface DescribeAutoMLJobCommandOutput extends DescribeAutoMLJobRespons
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/**
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* @public
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* <p>Returns information about an Amazon SageMaker AutoML job.</p>
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* <p>Returns information about an AutoML job created by calling <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateAutoMLJob.html">CreateAutoMLJob</a>.</p>
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* @example
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* Use a bare-bones client and the command you need to make an API call.
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* ```javascript

clients/client-sagemaker/src/commands/DescribeAutoMLJobV2Command.ts

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@@ -36,11 +36,7 @@ export interface DescribeAutoMLJobV2CommandOutput extends DescribeAutoMLJobV2Res
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/**
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* @public
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* <p>Returns information about an Amazon SageMaker AutoML V2 job.</p>
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* <note>
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* <p>This API action is callable through SageMaker Canvas only. Calling it directly from the CLI
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* or an SDK results in an error.</p>
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* </note>
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* <p>Returns information about an AutoML job V2 created by calling <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateAutoMLJobV2.html">CreateAutoMLJobV2</a>.</p>
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* @example
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* Use a bare-bones client and the command you need to make an API call.
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* ```javascript
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* // ContentColumn: "STRING_VALUE",
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* // TargetLabelColumn: "STRING_VALUE",
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* // },
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* // TabularJobConfig: { // TabularJobConfig
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* // CandidateGenerationConfig: { // CandidateGenerationConfig
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* // AlgorithmsConfig: [ // AutoMLAlgorithmsConfig
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* // { // AutoMLAlgorithmConfig
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* // AutoMLAlgorithms: [ // AutoMLAlgorithms // required
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* // "xgboost" || "linear-learner" || "mlp" || "lightgbm" || "catboost" || "randomforest" || "extra-trees" || "nn-torch" || "fastai",
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* // ],
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* // },
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* // ],
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* // },
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* // CompletionCriteria: {
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* // MaxCandidates: Number("int"),
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* // MaxRuntimePerTrainingJobInSeconds: Number("int"),
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* // MaxAutoMLJobRuntimeInSeconds: Number("int"),
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* // },
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* // FeatureSpecificationS3Uri: "STRING_VALUE",
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* // Mode: "AUTO" || "ENSEMBLING" || "HYPERPARAMETER_TUNING",
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* // GenerateCandidateDefinitionsOnly: true || false,
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* // ProblemType: "BinaryClassification" || "MulticlassClassification" || "Regression",
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* // TargetAttributeName: "STRING_VALUE", // required
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* // SampleWeightAttributeName: "STRING_VALUE",
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* // },
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* // },
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* // CreationTime: new Date("TIMESTAMP"), // required
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* // EndTime: new Date("TIMESTAMP"),
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* // ],
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* // },
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* // },
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* // AutoMLJobArtifacts: { // AutoMLJobArtifacts
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* // CandidateDefinitionNotebookLocation: "STRING_VALUE",
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* // DataExplorationNotebookLocation: "STRING_VALUE",
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* // },
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* // ResolvedAttributes: { // AutoMLResolvedAttributes
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* // AutoMLJobObjective: {
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* // MetricName: "Accuracy" || "MSE" || "F1" || "F1macro" || "AUC" || "RMSE" || "MAE" || "R2" || "BalancedAccuracy" || "Precision" || "PrecisionMacro" || "Recall" || "RecallMacro", // required
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* // },
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* // CompletionCriteria: {
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* // MaxCandidates: Number("int"),
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* // MaxRuntimePerTrainingJobInSeconds: Number("int"),
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* // MaxAutoMLJobRuntimeInSeconds: Number("int"),
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* // },
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* // AutoMLProblemTypeResolvedAttributes: { // AutoMLProblemTypeResolvedAttributes Union: only one key present
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* // TabularResolvedAttributes: { // TabularResolvedAttributes
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* // ProblemType: "BinaryClassification" || "MulticlassClassification" || "Regression",
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* // },
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* // },
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* // },
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* // AutoMLProblemTypeConfigName: "ImageClassification" || "TextClassification" || "Tabular",
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* // };
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*
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* ```

clients/client-sagemaker/src/commands/StopCompilationJobCommand.ts

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import { HttpRequest as __HttpRequest, HttpResponse as __HttpResponse } from "@smithy/protocol-http";
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import { SerdeContext as __SerdeContext } from "@smithy/types";
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import { StopCompilationJobRequest } from "../models/models_3";
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import { StopCompilationJobRequest } from "../models/models_4";
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import { de_StopCompilationJobCommand, se_StopCompilationJobCommand } from "../protocols/Aws_json1_1";
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import { SageMakerClientResolvedConfig, ServiceInputTypes, ServiceOutputTypes } from "../SageMakerClient";
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