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feat(client-sagemaker): This release provides support in SageMaker fo…
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…r output files in training jobs to be uploaded without compression and enable customer to deploy uncompressed model from S3 to real-time inference Endpoints. In addition, ml.trn1n.32xlarge is added to supported instance type list in training job.
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awstools committed Jun 21, 2023
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7 changes: 4 additions & 3 deletions clients/client-sagemaker/src/commands/CreateAlgorithmCommand.ts
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Expand Up @@ -75,7 +75,7 @@ export interface CreateAlgorithmCommandOutput extends CreateAlgorithmOutput, __M
* },
* ],
* SupportedTrainingInstanceTypes: [ // TrainingInstanceTypes // required
* "ml.m4.xlarge" || "ml.m4.2xlarge" || "ml.m4.4xlarge" || "ml.m4.10xlarge" || "ml.m4.16xlarge" || "ml.g4dn.xlarge" || "ml.g4dn.2xlarge" || "ml.g4dn.4xlarge" || "ml.g4dn.8xlarge" || "ml.g4dn.12xlarge" || "ml.g4dn.16xlarge" || "ml.m5.large" || "ml.m5.xlarge" || "ml.m5.2xlarge" || "ml.m5.4xlarge" || "ml.m5.12xlarge" || "ml.m5.24xlarge" || "ml.c4.xlarge" || "ml.c4.2xlarge" || "ml.c4.4xlarge" || "ml.c4.8xlarge" || "ml.p2.xlarge" || "ml.p2.8xlarge" || "ml.p2.16xlarge" || "ml.p3.2xlarge" || "ml.p3.8xlarge" || "ml.p3.16xlarge" || "ml.p3dn.24xlarge" || "ml.p4d.24xlarge" || "ml.c5.xlarge" || "ml.c5.2xlarge" || "ml.c5.4xlarge" || "ml.c5.9xlarge" || "ml.c5.18xlarge" || "ml.c5n.xlarge" || "ml.c5n.2xlarge" || "ml.c5n.4xlarge" || "ml.c5n.9xlarge" || "ml.c5n.18xlarge" || "ml.g5.xlarge" || "ml.g5.2xlarge" || "ml.g5.4xlarge" || "ml.g5.8xlarge" || "ml.g5.16xlarge" || "ml.g5.12xlarge" || "ml.g5.24xlarge" || "ml.g5.48xlarge" || "ml.trn1.2xlarge" || "ml.trn1.32xlarge",
* "ml.m4.xlarge" || "ml.m4.2xlarge" || "ml.m4.4xlarge" || "ml.m4.10xlarge" || "ml.m4.16xlarge" || "ml.g4dn.xlarge" || "ml.g4dn.2xlarge" || "ml.g4dn.4xlarge" || "ml.g4dn.8xlarge" || "ml.g4dn.12xlarge" || "ml.g4dn.16xlarge" || "ml.m5.large" || "ml.m5.xlarge" || "ml.m5.2xlarge" || "ml.m5.4xlarge" || "ml.m5.12xlarge" || "ml.m5.24xlarge" || "ml.c4.xlarge" || "ml.c4.2xlarge" || "ml.c4.4xlarge" || "ml.c4.8xlarge" || "ml.p2.xlarge" || "ml.p2.8xlarge" || "ml.p2.16xlarge" || "ml.p3.2xlarge" || "ml.p3.8xlarge" || "ml.p3.16xlarge" || "ml.p3dn.24xlarge" || "ml.p4d.24xlarge" || "ml.c5.xlarge" || "ml.c5.2xlarge" || "ml.c5.4xlarge" || "ml.c5.9xlarge" || "ml.c5.18xlarge" || "ml.c5n.xlarge" || "ml.c5n.2xlarge" || "ml.c5n.4xlarge" || "ml.c5n.9xlarge" || "ml.c5n.18xlarge" || "ml.g5.xlarge" || "ml.g5.2xlarge" || "ml.g5.4xlarge" || "ml.g5.8xlarge" || "ml.g5.16xlarge" || "ml.g5.12xlarge" || "ml.g5.24xlarge" || "ml.g5.48xlarge" || "ml.trn1.2xlarge" || "ml.trn1.32xlarge" || "ml.trn1n.32xlarge",
* ],
* SupportsDistributedTraining: true || false,
* MetricDefinitions: [ // MetricDefinitionList
Expand Down Expand Up @@ -183,15 +183,16 @@ export interface CreateAlgorithmCommandOutput extends CreateAlgorithmOutput, __M
* OutputDataConfig: { // OutputDataConfig
* KmsKeyId: "STRING_VALUE",
* S3OutputPath: "STRING_VALUE", // required
* CompressionType: "GZIP" || "NONE",
* },
* ResourceConfig: { // ResourceConfig
* InstanceType: "ml.m4.xlarge" || "ml.m4.2xlarge" || "ml.m4.4xlarge" || "ml.m4.10xlarge" || "ml.m4.16xlarge" || "ml.g4dn.xlarge" || "ml.g4dn.2xlarge" || "ml.g4dn.4xlarge" || "ml.g4dn.8xlarge" || "ml.g4dn.12xlarge" || "ml.g4dn.16xlarge" || "ml.m5.large" || "ml.m5.xlarge" || "ml.m5.2xlarge" || "ml.m5.4xlarge" || "ml.m5.12xlarge" || "ml.m5.24xlarge" || "ml.c4.xlarge" || "ml.c4.2xlarge" || "ml.c4.4xlarge" || "ml.c4.8xlarge" || "ml.p2.xlarge" || "ml.p2.8xlarge" || "ml.p2.16xlarge" || "ml.p3.2xlarge" || "ml.p3.8xlarge" || "ml.p3.16xlarge" || "ml.p3dn.24xlarge" || "ml.p4d.24xlarge" || "ml.c5.xlarge" || "ml.c5.2xlarge" || "ml.c5.4xlarge" || "ml.c5.9xlarge" || "ml.c5.18xlarge" || "ml.c5n.xlarge" || "ml.c5n.2xlarge" || "ml.c5n.4xlarge" || "ml.c5n.9xlarge" || "ml.c5n.18xlarge" || "ml.g5.xlarge" || "ml.g5.2xlarge" || "ml.g5.4xlarge" || "ml.g5.8xlarge" || "ml.g5.16xlarge" || "ml.g5.12xlarge" || "ml.g5.24xlarge" || "ml.g5.48xlarge" || "ml.trn1.2xlarge" || "ml.trn1.32xlarge",
* InstanceType: "ml.m4.xlarge" || "ml.m4.2xlarge" || "ml.m4.4xlarge" || "ml.m4.10xlarge" || "ml.m4.16xlarge" || "ml.g4dn.xlarge" || "ml.g4dn.2xlarge" || "ml.g4dn.4xlarge" || "ml.g4dn.8xlarge" || "ml.g4dn.12xlarge" || "ml.g4dn.16xlarge" || "ml.m5.large" || "ml.m5.xlarge" || "ml.m5.2xlarge" || "ml.m5.4xlarge" || "ml.m5.12xlarge" || "ml.m5.24xlarge" || "ml.c4.xlarge" || "ml.c4.2xlarge" || "ml.c4.4xlarge" || "ml.c4.8xlarge" || "ml.p2.xlarge" || "ml.p2.8xlarge" || "ml.p2.16xlarge" || "ml.p3.2xlarge" || "ml.p3.8xlarge" || "ml.p3.16xlarge" || "ml.p3dn.24xlarge" || "ml.p4d.24xlarge" || "ml.c5.xlarge" || "ml.c5.2xlarge" || "ml.c5.4xlarge" || "ml.c5.9xlarge" || "ml.c5.18xlarge" || "ml.c5n.xlarge" || "ml.c5n.2xlarge" || "ml.c5n.4xlarge" || "ml.c5n.9xlarge" || "ml.c5n.18xlarge" || "ml.g5.xlarge" || "ml.g5.2xlarge" || "ml.g5.4xlarge" || "ml.g5.8xlarge" || "ml.g5.16xlarge" || "ml.g5.12xlarge" || "ml.g5.24xlarge" || "ml.g5.48xlarge" || "ml.trn1.2xlarge" || "ml.trn1.32xlarge" || "ml.trn1n.32xlarge",
* InstanceCount: Number("int"),
* VolumeSizeInGB: Number("int"), // required
* VolumeKmsKeyId: "STRING_VALUE",
* InstanceGroups: [ // InstanceGroups
* { // InstanceGroup
* InstanceType: "ml.m4.xlarge" || "ml.m4.2xlarge" || "ml.m4.4xlarge" || "ml.m4.10xlarge" || "ml.m4.16xlarge" || "ml.g4dn.xlarge" || "ml.g4dn.2xlarge" || "ml.g4dn.4xlarge" || "ml.g4dn.8xlarge" || "ml.g4dn.12xlarge" || "ml.g4dn.16xlarge" || "ml.m5.large" || "ml.m5.xlarge" || "ml.m5.2xlarge" || "ml.m5.4xlarge" || "ml.m5.12xlarge" || "ml.m5.24xlarge" || "ml.c4.xlarge" || "ml.c4.2xlarge" || "ml.c4.4xlarge" || "ml.c4.8xlarge" || "ml.p2.xlarge" || "ml.p2.8xlarge" || "ml.p2.16xlarge" || "ml.p3.2xlarge" || "ml.p3.8xlarge" || "ml.p3.16xlarge" || "ml.p3dn.24xlarge" || "ml.p4d.24xlarge" || "ml.c5.xlarge" || "ml.c5.2xlarge" || "ml.c5.4xlarge" || "ml.c5.9xlarge" || "ml.c5.18xlarge" || "ml.c5n.xlarge" || "ml.c5n.2xlarge" || "ml.c5n.4xlarge" || "ml.c5n.9xlarge" || "ml.c5n.18xlarge" || "ml.g5.xlarge" || "ml.g5.2xlarge" || "ml.g5.4xlarge" || "ml.g5.8xlarge" || "ml.g5.16xlarge" || "ml.g5.12xlarge" || "ml.g5.24xlarge" || "ml.g5.48xlarge" || "ml.trn1.2xlarge" || "ml.trn1.32xlarge", // required
* InstanceType: "ml.m4.xlarge" || "ml.m4.2xlarge" || "ml.m4.4xlarge" || "ml.m4.10xlarge" || "ml.m4.16xlarge" || "ml.g4dn.xlarge" || "ml.g4dn.2xlarge" || "ml.g4dn.4xlarge" || "ml.g4dn.8xlarge" || "ml.g4dn.12xlarge" || "ml.g4dn.16xlarge" || "ml.m5.large" || "ml.m5.xlarge" || "ml.m5.2xlarge" || "ml.m5.4xlarge" || "ml.m5.12xlarge" || "ml.m5.24xlarge" || "ml.c4.xlarge" || "ml.c4.2xlarge" || "ml.c4.4xlarge" || "ml.c4.8xlarge" || "ml.p2.xlarge" || "ml.p2.8xlarge" || "ml.p2.16xlarge" || "ml.p3.2xlarge" || "ml.p3.8xlarge" || "ml.p3.16xlarge" || "ml.p3dn.24xlarge" || "ml.p4d.24xlarge" || "ml.c5.xlarge" || "ml.c5.2xlarge" || "ml.c5.4xlarge" || "ml.c5.9xlarge" || "ml.c5.18xlarge" || "ml.c5n.xlarge" || "ml.c5n.2xlarge" || "ml.c5n.4xlarge" || "ml.c5n.9xlarge" || "ml.c5n.18xlarge" || "ml.g5.xlarge" || "ml.g5.2xlarge" || "ml.g5.4xlarge" || "ml.g5.8xlarge" || "ml.g5.16xlarge" || "ml.g5.12xlarge" || "ml.g5.24xlarge" || "ml.g5.48xlarge" || "ml.trn1.2xlarge" || "ml.trn1.32xlarge" || "ml.trn1n.32xlarge", // required
* InstanceCount: Number("int"), // required
* InstanceGroupName: "STRING_VALUE", // required
* },
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12 changes: 6 additions & 6 deletions clients/client-sagemaker/src/commands/CreateAutoMLJobCommand.ts
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Expand Up @@ -37,16 +37,16 @@ export interface CreateAutoMLJobCommandOutput extends CreateAutoMLJobResponse, _
/**
* @public
* <p>Creates an Autopilot job also referred to as Autopilot experiment or AutoML job.</p>
* <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>
* <note>
* <p>We recommend using the new versions <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateAutoMLJobV2.html">CreateAutoMLJobV2</a> and <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DescribeAutoMLJobV2.html">DescribeAutoMLJobV2</a>, which offer backward compatibility.</p>
* <p>
* <code>CreateAutoMLJob</code> only accepts tabular input data. We recommend using
* <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateAutoMLJobV2.html">CreateAutoMLJobV2</a> for all problem types. <code>CreateAutoMLJobV2</code> can
* process the same tabular data as its previous version <code>CreateAutoMLJob</code>, as
* well as non-tabular data for problem types such as image or text classification.</p>
* <p>Find guidelines about how to migrate <code>CreateAutoMLJob</code> to
* <code>CreateAutoMLJobV2</code> can manage tabular problem types identical to those of
* its previous version <code>CreateAutoMLJob</code>, as well as non-tabular problem types
* such as image or text classification.</p>
* <p>Find guidelines about how to migrate a <code>CreateAutoMLJob</code> to
* <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>
* </note>
* <p>You can 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>
* @example
* Use a bare-bones client and the command you need to make an API call.
* ```javascript
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20 changes: 12 additions & 8 deletions clients/client-sagemaker/src/commands/CreateAutoMLJobV2Command.ts
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Expand Up @@ -37,16 +37,20 @@ export interface CreateAutoMLJobV2CommandOutput extends CreateAutoMLJobV2Respons
/**
* @public
* <p>Creates an Autopilot job also referred to as Autopilot experiment or AutoML job V2.</p>
* <p>We recommend using <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateAutoMLJobV2.html">CreateAutoMLJobV2</a>
* for all problem types. <code>CreateAutoMLJobV2</code> can process the same tabular data as
* its previous version <code>CreateAutoMLJob</code>, as well as non-tabular data for problem
* types such as image or text classification.</p>
* <p>Find guidelines about how to migrate <code>CreateAutoMLJob</code> to
* <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>
* <note>
* <p>
* <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateAutoMLJobV2.html">CreateAutoMLJobV2</a> and <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DescribeAutoMLJobV2.html">DescribeAutoMLJobV2</a> are new versions of <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateAutoMLJob.html">CreateAutoMLJob</a>
* and <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DescribeAutoMLJob.html">DescribeAutoMLJob</a> which offer backward compatibility.</p>
* <p>
* <code>CreateAutoMLJobV2</code> can manage tabular problem types identical to those of its previous version
* <code>CreateAutoMLJob</code>, as well as non-tabular problem types such as
* image or text classification.</p>
* <p>Find guidelines about how to migrate a <code>CreateAutoMLJob</code> to
* <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>
* </note>
* <p>For the list of available problem types supported by <code>CreateAutoMLJobV2</code>, see
* <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_AutoMLProblemTypeConfig.html">AutoMLProblemTypeConfig</a>.</p>
* <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>
* on a AutoML job V2 results in an error.</p>
* <p>You can 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>.</p>
* @example
* Use a bare-bones client and the command you need to make an API call.
* ```javascript
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2 changes: 1 addition & 1 deletion clients/client-sagemaker/src/commands/CreateDomainCommand.ts
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Expand Up @@ -13,7 +13,7 @@ import {
import { HttpRequest as __HttpRequest, HttpResponse as __HttpResponse } from "@smithy/protocol-http";
import { SerdeContext as __SerdeContext } from "@smithy/types";

import { CreateDomainRequest, CreateDomainResponse } from "../models/models_0";
import { CreateDomainRequest, CreateDomainResponse } from "../models/models_1";
import { de_CreateDomainCommand, se_CreateDomainCommand } from "../protocols/Aws_json1_1";
import { SageMakerClientResolvedConfig, ServiceInputTypes, ServiceOutputTypes } from "../SageMakerClient";

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