From bfe260bffc143ad14d06e8b212c3bc6cc0888494 Mon Sep 17 00:00:00 2001
From: awstools
+UpdateClusterSoftware
+
+
+[Command API Reference](https://docs.aws.amazon.com/AWSJavaScriptSDK/v3/latest/client/sagemaker/command/UpdateClusterSoftwareCommand/) / [Input](https://docs.aws.amazon.com/AWSJavaScriptSDK/v3/latest/Package/-aws-sdk-client-sagemaker/Interface/UpdateClusterSoftwareCommandInput/) / [Output](https://docs.aws.amazon.com/AWSJavaScriptSDK/v3/latest/Package/-aws-sdk-client-sagemaker/Interface/UpdateClusterSoftwareCommandOutput/)
+
diff --git a/clients/client-sagemaker/src/SageMaker.ts b/clients/client-sagemaker/src/SageMaker.ts
index 397ef2b0fc09..5b7a4c369e07 100644
--- a/clients/client-sagemaker/src/SageMaker.ts
+++ b/clients/client-sagemaker/src/SageMaker.ts
@@ -1325,6 +1325,11 @@ import {
UpdateClusterCommandInput,
UpdateClusterCommandOutput,
} from "./commands/UpdateClusterCommand";
+import {
+ UpdateClusterSoftwareCommand,
+ UpdateClusterSoftwareCommandInput,
+ UpdateClusterSoftwareCommandOutput,
+} from "./commands/UpdateClusterSoftwareCommand";
import {
UpdateCodeRepositoryCommand,
UpdateCodeRepositoryCommandInput,
@@ -1759,6 +1764,7 @@ const commands = {
UpdateAppImageConfigCommand,
UpdateArtifactCommand,
UpdateClusterCommand,
+ UpdateClusterSoftwareCommand,
UpdateCodeRepositoryCommand,
UpdateContextCommand,
UpdateDeviceFleetCommand,
@@ -6259,6 +6265,23 @@ export interface SageMaker {
cb: (err: any, data?: UpdateClusterCommandOutput) => void
): void;
+ /**
+ * @see {@link UpdateClusterSoftwareCommand}
+ */
+ updateClusterSoftware(
+ args: UpdateClusterSoftwareCommandInput,
+ options?: __HttpHandlerOptions
+ ): Promise
Tags that you add to a SageMaker Domain or User Profile by calling this API
- * are also added to any Apps that the Domain or User Profile launches after you call
- * this API, but not to Apps that the Domain or User Profile launched before you called
- * this API. To make sure that the tags associated with a Domain or User Profile are
- * also added to all Apps that the Domain or User Profile launches, add the tags when
- * you first create the Domain or User Profile by specifying them in the
- * Tags
parameter of CreateDomain
+ *
Tags that you add to a SageMaker Domain or User Profile by calling this API are
+ * also added to any Apps that the Domain or User Profile launches after you call this
+ * API, but not to Apps that the Domain or User Profile launched before you called this
+ * API. To make sure that the tags associated with a Domain or User Profile are also
+ * added to all Apps that the Domain or User Profile launches, add the tags when you
+ * first create the Domain or User Profile by specifying them in the Tags
+ * parameter of CreateDomain
* or CreateUserProfile.
Deletes a hyperparameter tuning job. The DeleteHyperParameterTuningJob
* API deletes only the tuning job entry that was created in SageMaker when you called the
- * CreateHyperParameterTuningJob
API. It does not delete training jobs,
+ * CreateHyperParameterTuningJob
API. It does not delete training jobs,
* artifacts, or the IAM role that you specified when creating the model.
When you call this API to delete tags from a SageMaker Domain or User - * Profile, the deleted tags are not removed from Apps that the SageMaker Domain - * or User Profile launched before you called this API.
+ *When you call this API to delete tags from a SageMaker Domain or User Profile, the + * deleted tags are not removed from Apps that the SageMaker Domain or User Profile + * launched before you called this API.
*Update a SageMaker HyperPod cluster.
+ *Updates a SageMaker HyperPod cluster.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/UpdateClusterSoftwareCommand.ts b/clients/client-sagemaker/src/commands/UpdateClusterSoftwareCommand.ts new file mode 100644 index 000000000000..6867a6a1c757 --- /dev/null +++ b/clients/client-sagemaker/src/commands/UpdateClusterSoftwareCommand.ts @@ -0,0 +1,89 @@ +// smithy-typescript generated code +import { getEndpointPlugin } from "@smithy/middleware-endpoint"; +import { getSerdePlugin } from "@smithy/middleware-serde"; +import { Command as $Command } from "@smithy/smithy-client"; +import { MetadataBearer as __MetadataBearer } from "@smithy/types"; + +import { commonParams } from "../endpoint/EndpointParameters"; +import { UpdateClusterSoftwareRequest, UpdateClusterSoftwareResponse } from "../models/models_4"; +import { de_UpdateClusterSoftwareCommand, se_UpdateClusterSoftwareCommand } from "../protocols/Aws_json1_1"; +import { SageMakerClientResolvedConfig, ServiceInputTypes, ServiceOutputTypes } from "../SageMakerClient"; + +/** + * @public + */ +export { __MetadataBearer, $Command }; +/** + * @public + * + * The input for {@link UpdateClusterSoftwareCommand}. + */ +export interface UpdateClusterSoftwareCommandInput extends UpdateClusterSoftwareRequest {} +/** + * @public + * + * The output of {@link UpdateClusterSoftwareCommand}. + */ +export interface UpdateClusterSoftwareCommandOutput extends UpdateClusterSoftwareResponse, __MetadataBearer {} + +/** + * @public + *Updates the platform software of a SageMaker HyperPod cluster for security patching. To learn how to + * use this API, see Update the SageMaker HyperPod platform software of a cluster.
+ * @example + * Use a bare-bones client and the command you need to make an API call. + * ```javascript + * import { SageMakerClient, UpdateClusterSoftwareCommand } from "@aws-sdk/client-sagemaker"; // ES Modules import + * // const { SageMakerClient, UpdateClusterSoftwareCommand } = require("@aws-sdk/client-sagemaker"); // CommonJS import + * const client = new SageMakerClient(config); + * const input = { // UpdateClusterSoftwareRequest + * ClusterName: "STRING_VALUE", // required + * }; + * const command = new UpdateClusterSoftwareCommand(input); + * const response = await client.send(command); + * // { // UpdateClusterSoftwareResponse + * // ClusterArn: "STRING_VALUE", // required + * // }; + * + * ``` + * + * @param UpdateClusterSoftwareCommandInput - {@link UpdateClusterSoftwareCommandInput} + * @returns {@link UpdateClusterSoftwareCommandOutput} + * @see {@link UpdateClusterSoftwareCommandInput} for command's `input` shape. + * @see {@link UpdateClusterSoftwareCommandOutput} for command's `response` shape. + * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. + * + * @throws {@link ConflictException} (client fault) + *There was a conflict when you attempted to modify a SageMaker entity such as an
+ * Experiment
or Artifact
.
Resource being access is not found.
+ * + * @throws {@link SageMakerServiceException} + *Base exception class for all service exceptions from SageMaker service.
+ * + */ +export class UpdateClusterSoftwareCommand extends $Command + .classBuilder< + UpdateClusterSoftwareCommandInput, + UpdateClusterSoftwareCommandOutput, + SageMakerClientResolvedConfig, + ServiceInputTypes, + ServiceOutputTypes + >() + .ep({ + ...commonParams, + }) + .m(function (this: any, Command: any, cs: any, config: SageMakerClientResolvedConfig, o: any) { + return [ + getSerdePlugin(config, this.serialize, this.deserialize), + getEndpointPlugin(config, Command.getEndpointParameterInstructions()), + ]; + }) + .s("SageMaker", "UpdateClusterSoftware", {}) + .n("SageMakerClient", "UpdateClusterSoftwareCommand") + .f(void 0, void 0) + .ser(se_UpdateClusterSoftwareCommand) + .de(de_UpdateClusterSoftwareCommand) + .build() {} diff --git a/clients/client-sagemaker/src/commands/UpdateEndpointCommand.ts b/clients/client-sagemaker/src/commands/UpdateEndpointCommand.ts index 8b108dc5e2ec..f0974e730a98 100644 --- a/clients/client-sagemaker/src/commands/UpdateEndpointCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdateEndpointCommand.ts @@ -28,16 +28,15 @@ export interface UpdateEndpointCommandOutput extends UpdateEndpointOutput, __Met /** * @public - *Deploys the EndpointConfig
specified in the request
- * to a new fleet of instances. SageMaker shifts endpoint traffic to the new instances
- * with the updated endpoint configuration and then deletes the old instances
- * using the previous EndpointConfig
(there is no availability loss).
- * For more information about how to control the update and traffic shifting process, see
- *
- * Update models in production.
When SageMaker receives the request, it sets the endpoint status to
- * Updating
. After updating the endpoint, it sets the status to
- * InService
. To check the status of an endpoint, use the DescribeEndpoint API.
+ *
Deploys the EndpointConfig
specified in the request to a new fleet of
+ * instances. SageMaker shifts endpoint traffic to the new instances with the updated endpoint
+ * configuration and then deletes the old instances using the previous
+ * EndpointConfig
(there is no availability loss). For more information
+ * about how to control the update and traffic shifting process, see Update
+ * models in production.
When SageMaker receives the request, it sets the endpoint status to Updating
.
+ * After updating the endpoint, it sets the status to InService
. To check the
+ * status of an endpoint, use the DescribeEndpoint API.
*
*
A key name prefix might look like this:
- * s3://bucketname/exampleprefix/
+ * s3://bucketname/exampleprefix/
*
The KMS key policy must grant permission to the IAM role that you specify in your
* CreateTrainingJob
, CreateTransformJob
, or
* CreateHyperParameterTuningJob
requests. For more information, see
diff --git a/clients/client-sagemaker/src/models/models_2.ts b/clients/client-sagemaker/src/models/models_2.ts
index 1c7053cfe1f0..21947bb69416 100644
--- a/clients/client-sagemaker/src/models/models_2.ts
+++ b/clients/client-sagemaker/src/models/models_2.ts
@@ -362,9 +362,10 @@ export interface ProfilerRuleConfiguration {
/**
* @public
- *
Configuration for remote debugging for the CreateTrainingJob API. To learn more about the remote - * debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) - * for remote debugging.
+ *Configuration for remote debugging for the CreateTrainingJob API. To learn more about the remote debugging + * functionality of SageMaker, see Access a training container + * through Amazon Web Services Systems Manager (SSM) for remote + * debugging.
*/ export interface RemoteDebugConfig { /** @@ -628,9 +629,10 @@ export interface CreateTrainingJobRequest { /** * @public - *Configuration for remote debugging. To learn more about the remote - * debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) - * for remote debugging.
+ *Configuration for remote debugging. To learn more about the remote debugging + * functionality of SageMaker, see Access a training container + * through Amazon Web Services Systems Manager (SSM) for remote + * debugging.
*/ RemoteDebugConfig?: RemoteDebugConfig; @@ -3656,9 +3658,11 @@ export interface DescribeCompilationJobRequest { * @public *Provides information about the location that is configured for storing model * artifacts.
- *Model artifacts are the output that results from training a model, and typically - * consist of trained parameters, a model definition that describes how to compute - * inferences, and other metadata.
+ *Model artifacts are outputs that result from training a model. They typically consist
+ * of trained parameters, a model definition that describes how to compute inferences, and
+ * other metadata. A SageMaker container stores your trained model artifacts in the
+ * /opt/ml/model
directory. After training has completed, by default, these artifacts
+ * are uploaded to your Amazon S3 bucket as compressed files.
Configuration for remote debugging. To learn more about the remote - * debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) - * for remote debugging.
+ *Configuration for remote debugging. To learn more about the remote debugging + * functionality of SageMaker, see Access a training container + * through Amazon Web Services Systems Manager (SSM) for remote + * debugging.
*/ RemoteDebugConfig?: RemoteDebugConfig; diff --git a/clients/client-sagemaker/src/models/models_4.ts b/clients/client-sagemaker/src/models/models_4.ts index 4cd30d98e1a9..e3a7ab0ab7ac 100644 --- a/clients/client-sagemaker/src/models/models_4.ts +++ b/clients/client-sagemaker/src/models/models_4.ts @@ -4277,9 +4277,10 @@ export interface RegisterDevicesRequest { /** * @public - *Configuration for remote debugging for the UpdateTrainingJob API. To learn more about the remote - * debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) - * for remote debugging.
+ *Configuration for remote debugging for the UpdateTrainingJob API. To learn more about the remote debugging + * functionality of SageMaker, see Access a training container + * through Amazon Web Services Systems Manager (SSM) for remote + * debugging.
*/ export interface RemoteDebugConfigForUpdate { /** @@ -5858,6 +5859,29 @@ export interface UpdateClusterResponse { ClusterArn: string | undefined; } +/** + * @public + */ +export interface UpdateClusterSoftwareRequest { + /** + * @public + *Specify the name or the Amazon Resource Name (ARN) of the SageMaker HyperPod cluster you want to update for security + * patching.
+ */ + ClusterName: string | undefined; +} + +/** + * @public + */ +export interface UpdateClusterSoftwareResponse { + /** + * @public + *The Amazon Resource Name (ARN) of the SageMaker HyperPod cluster being updated for security patching.
+ */ + ClusterArn: string | undefined; +} + /** * @public */ @@ -7302,11 +7326,12 @@ export interface UpdateTrainingJobRequest { /** * @public - *Configuration for remote debugging while the training job is running. You can
- * update the remote debugging configuration when the SecondaryStatus
of the job
- * is Downloading
or Training
.To learn more about the remote
- * debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM)
- * for remote debugging.
Configuration for remote debugging while the training job is running. You can update
+ * the remote debugging configuration when the SecondaryStatus
of the job is
+ * Downloading
or Training
.To learn more about the remote
+ * debugging functionality of SageMaker, see Access a training container
+ * through Amazon Web Services Systems Manager (SSM) for remote
+ * debugging.
Adds or overwrites one or more tags for the specified SageMaker resource. You can add\n tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform\n jobs, models, labeling jobs, work teams, endpoint configurations, and\n endpoints.
\nEach tag consists of a key and an optional value. Tag keys must be unique per\n resource. For more information about tags, see For more information, see Amazon Web Services Tagging Strategies.
\nTags that you add to a hyperparameter tuning job by calling this API are also\n added to any training jobs that the hyperparameter tuning job launches after you\n call this API, but not to training jobs that the hyperparameter tuning job launched\n before you called this API. To make sure that the tags associated with a\n hyperparameter tuning job are also added to all training jobs that the\n hyperparameter tuning job launches, add the tags when you first create the tuning\n job by specifying them in the Tags
parameter of CreateHyperParameterTuningJob\n
Tags that you add to a SageMaker Domain or User Profile by calling this API\n are also added to any Apps that the Domain or User Profile launches after you call\n this API, but not to Apps that the Domain or User Profile launched before you called\n this API. To make sure that the tags associated with a Domain or User Profile are\n also added to all Apps that the Domain or User Profile launches, add the tags when\n you first create the Domain or User Profile by specifying them in the\n Tags
parameter of CreateDomain\n or CreateUserProfile.
Adds or overwrites one or more tags for the specified SageMaker resource. You can add\n tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform\n jobs, models, labeling jobs, work teams, endpoint configurations, and\n endpoints.
\nEach tag consists of a key and an optional value. Tag keys must be unique per\n resource. For more information about tags, see For more information, see Amazon Web Services Tagging Strategies.
\nTags that you add to a hyperparameter tuning job by calling this API are also\n added to any training jobs that the hyperparameter tuning job launches after you\n call this API, but not to training jobs that the hyperparameter tuning job launched\n before you called this API. To make sure that the tags associated with a\n hyperparameter tuning job are also added to all training jobs that the\n hyperparameter tuning job launches, add the tags when you first create the tuning\n job by specifying them in the Tags
parameter of CreateHyperParameterTuningJob\n
Tags that you add to a SageMaker Domain or User Profile by calling this API are\n also added to any Apps that the Domain or User Profile launches after you call this\n API, but not to Apps that the Domain or User Profile launched before you called this\n API. To make sure that the tags associated with a Domain or User Profile are also\n added to all Apps that the Domain or User Profile launches, add the tags when you\n first create the Domain or User Profile by specifying them in the Tags
\n parameter of CreateDomain\n or CreateUserProfile.
Configuration for remote debugging. To learn more about the remote \n debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) \n for remote debugging.
" + "smithy.api#documentation": "Configuration for remote debugging. To learn more about the remote debugging\n functionality of SageMaker, see Access a training container\n through Amazon Web Services Systems Manager (SSM) for remote\n debugging.
" } }, "InfraCheckConfig": { @@ -14599,7 +14599,7 @@ "target": "smithy.api#Unit" }, "traits": { - "smithy.api#documentation": "Deletes a hyperparameter tuning job. The DeleteHyperParameterTuningJob
\n API deletes only the tuning job entry that was created in SageMaker when you called the\n CreateHyperParameterTuningJob
API. It does not delete training jobs,\n artifacts, or the IAM role that you specified when creating the model.
Deletes a hyperparameter tuning job. The DeleteHyperParameterTuningJob
\n API deletes only the tuning job entry that was created in SageMaker when you called the\n CreateHyperParameterTuningJob
API. It does not delete training jobs,\n artifacts, or the IAM role that you specified when creating the model.
Deletes the specified tags from an SageMaker resource.
\nTo list a resource's tags, use the ListTags
API.
When you call this API to delete tags from a hyperparameter tuning job, the\n deleted tags are not removed from training jobs that the hyperparameter tuning job\n launched before you called this API.
\nWhen you call this API to delete tags from a SageMaker Domain or User\n Profile, the deleted tags are not removed from Apps that the SageMaker Domain\n or User Profile launched before you called this API.
\nDeletes the specified tags from an SageMaker resource.
\nTo list a resource's tags, use the ListTags
API.
When you call this API to delete tags from a hyperparameter tuning job, the\n deleted tags are not removed from training jobs that the hyperparameter tuning job\n launched before you called this API.
\nWhen you call this API to delete tags from a SageMaker Domain or User Profile, the\n deleted tags are not removed from Apps that the SageMaker Domain or User Profile\n launched before you called this API.
\nConfiguration for remote debugging. To learn more about the remote \n debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) \n for remote debugging.
" + "smithy.api#documentation": "Configuration for remote debugging. To learn more about the remote debugging\n functionality of SageMaker, see Access a training container\n through Amazon Web Services Systems Manager (SSM) for remote\n debugging.
" } }, "InfraCheckConfig": { @@ -41688,7 +41688,7 @@ } }, "traits": { - "smithy.api#documentation": "Provides information about the location that is configured for storing model\n artifacts.
\nModel artifacts are the output that results from training a model, and typically\n consist of trained parameters, a model definition that describes how to compute\n inferences, and other metadata.
" + "smithy.api#documentation": "Provides information about the location that is configured for storing model\n artifacts.
\nModel artifacts are outputs that result from training a model. They typically consist\n of trained parameters, a model definition that describes how to compute inferences, and\n other metadata. A SageMaker container stores your trained model artifacts in the\n /opt/ml/model
directory. After training has completed, by default, these artifacts\n are uploaded to your Amazon S3 bucket as compressed files.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker\n uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption. The\n KmsKeyId
can be any of the following formats:
// KMS Key ID
\n\n \"1234abcd-12ab-34cd-56ef-1234567890ab\"
\n
// Amazon Resource Name (ARN) of a KMS Key
\n\n \"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\"
\n
// KMS Key Alias
\n\n \"alias/ExampleAlias\"
\n
// Amazon Resource Name (ARN) of a KMS Key Alias
\n\n \"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias\"
\n
If you use a KMS key ID or an alias of your KMS key, the SageMaker execution role must\n include permissions to call kms:Encrypt
. If you don't provide a KMS key ID,\n SageMaker uses the default KMS key for Amazon S3 for your role's account.\n \n For more information, see KMS-Managed Encryption\n Keys in the Amazon Simple Storage Service Developer Guide. If the output\n data is stored in Amazon S3 Express One Zone, it is encrypted with server-side\n encryption with Amazon S3 managed keys (SSE-S3). KMS key is not supported for Amazon S3 Express One Zone
The KMS key policy must grant permission to the IAM role that you specify in your\n CreateTrainingJob
, CreateTransformJob
, or\n CreateHyperParameterTuningJob
requests. For more information, see\n Using\n Key Policies in Amazon Web Services KMS in the Amazon Web Services\n Key Management Service Developer Guide.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker\n uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption. The\n KmsKeyId
can be any of the following formats:
// KMS Key ID
\n\n \"1234abcd-12ab-34cd-56ef-1234567890ab\"
\n
// Amazon Resource Name (ARN) of a KMS Key
\n\n \"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\"
\n
// KMS Key Alias
\n\n \"alias/ExampleAlias\"
\n
// Amazon Resource Name (ARN) of a KMS Key Alias
\n\n \"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias\"
\n
If you use a KMS key ID or an alias of your KMS key, the SageMaker execution role must\n include permissions to call kms:Encrypt
. If you don't provide a KMS key ID,\n SageMaker uses the default KMS key for Amazon S3 for your role's account.\n \n For more information, see KMS-Managed Encryption\n Keys in the Amazon Simple Storage Service Developer Guide. If the output\n data is stored in Amazon S3 Express One Zone, it is encrypted with server-side encryption with Amazon S3\n managed keys (SSE-S3). KMS key is not supported for Amazon S3 Express One Zone
The KMS key policy must grant permission to the IAM role that you specify in your\n CreateTrainingJob
, CreateTransformJob
, or\n CreateHyperParameterTuningJob
requests. For more information, see\n Using\n Key Policies in Amazon Web Services KMS in the Amazon Web Services\n Key Management Service Developer Guide.
Configuration for remote debugging for the CreateTrainingJob API. To learn more about the remote \n debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) \n for remote debugging.
" + "smithy.api#documentation": "Configuration for remote debugging for the CreateTrainingJob API. To learn more about the remote debugging\n functionality of SageMaker, see Access a training container\n through Amazon Web Services Systems Manager (SSM) for remote\n debugging.
" } }, "com.amazonaws.sagemaker#RemoteDebugConfigForUpdate": { @@ -52293,7 +52293,7 @@ } }, "traits": { - "smithy.api#documentation": "Configuration for remote debugging for the UpdateTrainingJob API. To learn more about the remote \n debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) \n for remote debugging.
" + "smithy.api#documentation": "Configuration for remote debugging for the UpdateTrainingJob API. To learn more about the remote debugging\n functionality of SageMaker, see Access a training container\n through Amazon Web Services Systems Manager (SSM) for remote\n debugging.
" } }, "com.amazonaws.sagemaker#RenderUiTemplate": { @@ -53222,7 +53222,7 @@ "target": "com.amazonaws.sagemaker#S3Uri", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Depending on the value specified for the S3DataType
, identifies either\n a key name prefix or a manifest. For example:
A key name prefix might look like this:\n\t\ts3://bucketname/exampleprefix/
\n
A manifest might look like this:\n s3://bucketname/example.manifest
\n
A manifest is an S3 object which is a JSON file consisting of an array of\n elements. The first element is a prefix which is followed by one or more\n suffixes. SageMaker appends the suffix elements to the prefix to get a full set of\n S3Uri
. Note that the prefix must be a valid non-empty\n S3Uri
that precludes users from specifying a manifest whose\n individual S3Uri
is sourced from different S3 buckets.
The following code example shows a valid manifest format:
\n\n [ {\"prefix\": \"s3://customer_bucket/some/prefix/\"},
\n
\n \"relative/path/to/custdata-1\",
\n
\n \"relative/path/custdata-2\",
\n
\n ...
\n
\n \"relative/path/custdata-N\"
\n
\n ]
\n
This JSON is equivalent to the following S3Uri
\n list:
\n s3://customer_bucket/some/prefix/relative/path/to/custdata-1
\n
\n s3://customer_bucket/some/prefix/relative/path/custdata-2
\n
\n ...
\n
\n s3://customer_bucket/some/prefix/relative/path/custdata-N
\n
The complete set of S3Uri
in this manifest is the input data\n for the channel for this data source. The object that each S3Uri
\n points to must be readable by the IAM role that SageMaker uses to perform tasks on\n your behalf.
Your input bucket must be located in same Amazon Web Services region as your\n training job.
", + "smithy.api#documentation": "Depending on the value specified for the S3DataType
, identifies either\n a key name prefix or a manifest. For example:
A key name prefix might look like this:\n s3://bucketname/exampleprefix/
\n
A manifest might look like this:\n s3://bucketname/example.manifest
\n
A manifest is an S3 object which is a JSON file consisting of an array of\n elements. The first element is a prefix which is followed by one or more\n suffixes. SageMaker appends the suffix elements to the prefix to get a full set of\n S3Uri
. Note that the prefix must be a valid non-empty\n S3Uri
that precludes users from specifying a manifest whose\n individual S3Uri
is sourced from different S3 buckets.
The following code example shows a valid manifest format:
\n\n [ {\"prefix\": \"s3://customer_bucket/some/prefix/\"},
\n
\n \"relative/path/to/custdata-1\",
\n
\n \"relative/path/custdata-2\",
\n
\n ...
\n
\n \"relative/path/custdata-N\"
\n
\n ]
\n
This JSON is equivalent to the following S3Uri
\n list:
\n s3://customer_bucket/some/prefix/relative/path/to/custdata-1
\n
\n s3://customer_bucket/some/prefix/relative/path/custdata-2
\n
\n ...
\n
\n s3://customer_bucket/some/prefix/relative/path/custdata-N
\n
The complete set of S3Uri
in this manifest is the input data\n for the channel for this data source. The object that each S3Uri
\n points to must be readable by the IAM role that SageMaker uses to perform tasks on\n your behalf.
Your input bucket must be located in same Amazon Web Services region as your\n training job.
", "smithy.api#required": {} } }, @@ -54250,6 +54250,9 @@ { "target": "com.amazonaws.sagemaker#UpdateCluster" }, + { + "target": "com.amazonaws.sagemaker#UpdateClusterSoftware" + }, { "target": "com.amazonaws.sagemaker#UpdateCodeRepository" }, @@ -62665,7 +62668,7 @@ } ], "traits": { - "smithy.api#documentation": "Update a SageMaker HyperPod cluster.
" + "smithy.api#documentation": "Updates a SageMaker HyperPod cluster.
" } }, "com.amazonaws.sagemaker#UpdateClusterRequest": { @@ -62708,6 +62711,58 @@ "smithy.api#output": {} } }, + "com.amazonaws.sagemaker#UpdateClusterSoftware": { + "type": "operation", + "input": { + "target": "com.amazonaws.sagemaker#UpdateClusterSoftwareRequest" + }, + "output": { + "target": "com.amazonaws.sagemaker#UpdateClusterSoftwareResponse" + }, + "errors": [ + { + "target": "com.amazonaws.sagemaker#ConflictException" + }, + { + "target": "com.amazonaws.sagemaker#ResourceNotFound" + } + ], + "traits": { + "smithy.api#documentation": "Updates the platform software of a SageMaker HyperPod cluster for security patching. To learn how to\n use this API, see Update the SageMaker HyperPod platform software of a cluster.
" + } + }, + "com.amazonaws.sagemaker#UpdateClusterSoftwareRequest": { + "type": "structure", + "members": { + "ClusterName": { + "target": "com.amazonaws.sagemaker#ClusterNameOrArn", + "traits": { + "smithy.api#clientOptional": {}, + "smithy.api#documentation": "Specify the name or the Amazon Resource Name (ARN) of the SageMaker HyperPod cluster you want to update for security\n patching.
", + "smithy.api#required": {} + } + } + }, + "traits": { + "smithy.api#input": {} + } + }, + "com.amazonaws.sagemaker#UpdateClusterSoftwareResponse": { + "type": "structure", + "members": { + "ClusterArn": { + "target": "com.amazonaws.sagemaker#ClusterArn", + "traits": { + "smithy.api#clientOptional": {}, + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the SageMaker HyperPod cluster being updated for security patching.
", + "smithy.api#required": {} + } + } + }, + "traits": { + "smithy.api#output": {} + } + }, "com.amazonaws.sagemaker#UpdateCodeRepository": { "type": "operation", "input": { @@ -63029,7 +63084,7 @@ } ], "traits": { - "smithy.api#documentation": "Deploys the EndpointConfig
specified in the request\n to a new fleet of instances. SageMaker shifts endpoint traffic to the new instances\n with the updated endpoint configuration and then deletes the old instances\n using the previous EndpointConfig
(there is no availability loss).\n For more information about how to control the update and traffic shifting process, see\n \n Update models in production.
When SageMaker receives the request, it sets the endpoint status to\n Updating
. After updating the endpoint, it sets the status to\n InService
. To check the status of an endpoint, use the DescribeEndpoint API.\n \n
You must not delete an EndpointConfig
in use by an endpoint that is\n live or while the UpdateEndpoint
or CreateEndpoint
\n operations are being performed on the endpoint. To update an endpoint, you must\n create a new EndpointConfig
.
If you delete the EndpointConfig
of an endpoint that is active or\n being created or updated you may lose visibility into the instance type the endpoint\n is using. The endpoint must be deleted in order to stop incurring charges.
Deploys the EndpointConfig
specified in the request to a new fleet of\n instances. SageMaker shifts endpoint traffic to the new instances with the updated endpoint\n configuration and then deletes the old instances using the previous\n EndpointConfig
(there is no availability loss). For more information\n about how to control the update and traffic shifting process, see Update\n models in production.
When SageMaker receives the request, it sets the endpoint status to Updating
.\n After updating the endpoint, it sets the status to InService
. To check the\n status of an endpoint, use the DescribeEndpoint API.\n \n
You must not delete an EndpointConfig
in use by an endpoint that is\n live or while the UpdateEndpoint
or CreateEndpoint
\n operations are being performed on the endpoint. To update an endpoint, you must\n create a new EndpointConfig
.
If you delete the EndpointConfig
of an endpoint that is active or\n being created or updated you may lose visibility into the instance type the endpoint\n is using. The endpoint must be deleted in order to stop incurring charges.
Configuration for remote debugging while the training job is running. You can\n update the remote debugging configuration when the SecondaryStatus
of the job\n is Downloading
or Training
.To learn more about the remote \n debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) \n for remote debugging.
Configuration for remote debugging while the training job is running. You can update\n the remote debugging configuration when the SecondaryStatus
of the job is\n Downloading
or Training
.To learn more about the remote\n debugging functionality of SageMaker, see Access a training container\n through Amazon Web Services Systems Manager (SSM) for remote\n debugging.