Adds or overwrites one or more tags for the specified SageMaker resource. You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints.
Each tag consists of a key and an optional value. Tag keys must be unique per resource. For more information about tags, see For more information, see Amazon Web Services Tagging Strategies.
Tags that you add to a hyperparameter tuning job by calling this API are also added to any training jobs that the hyperparameter tuning job launches after you call this API, but not to training jobs that the hyperparameter tuning job launched before you called this API. To make sure that the tags associated with a hyperparameter tuning job are also added to all training jobs that the hyperparameter tuning job launches, add the tags when you first create the tuning job by specifying them in the Tags parameter of CreateHyperParameterTuningJob
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.
Parameters:
-
resource_arn
(Optional[ResourceArn], default:
None
)
–
The Amazon Resource Name (ARN) of the resource that you want to tag.
-
tags
(Optional[TagList], default:
None
)
–
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.
Raises:
Source code in docs_src/capo_sagemaker/_services/sage_maker.py
| def add_tags(
self,
*,
config_overrides: Optional[SageMakerClientConfig] = None,
resource_arn: Optional["capo_sagemaker.types.resource_arn.ResourceArn"] = None,
tags: Optional["capo_sagemaker.types.tag_list.TagList"] = None,
) -> "capo_sagemaker.types.add_tags_output.AddTagsOutput":
"""<p>Adds or overwrites one or more tags for the specified SageMaker resource. You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints.</p> <p>Each tag consists of a key and an optional value. Tag keys must be unique per resource. For more information about tags, see For more information, see <a href="https://aws.amazon.com/answers/account-management/aws-tagging-strategies/">Amazon Web Services Tagging Strategies</a>.</p> <note> <p>Tags that you add to a hyperparameter tuning job by calling this API are also added to any training jobs that the hyperparameter tuning job launches after you call this API, but not to training jobs that the hyperparameter tuning job launched before you called this API. To make sure that the tags associated with a hyperparameter tuning job are also added to all training jobs that the hyperparameter tuning job launches, add the tags when you first create the tuning job by specifying them in the <code>Tags</code> parameter of <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateHyperParameterTuningJob.html">CreateHyperParameterTuningJob</a> </p> </note> <note> <p>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 <code>Tags</code> parameter of <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateDomain.html">CreateDomain</a> or <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateUserProfile.html">CreateUserProfile</a>.</p> </note>
Args:
resource_arn: <p>The Amazon Resource Name (ARN) of the resource that you want to tag.</p>
tags: <p>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 <a href="https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html">Tagging Amazon Web Services Resources</a>.</p>
Raises:
capo_sagemaker.errors.UnknownServiceError: The service returned an error code this client does not model.
"""
def _handler(
req: "OperationRequest[capo_sagemaker.types.add_tags_input.AddTagsInput]",
) -> OperationResponse["capo_sagemaker.types.add_tags_output.AddTagsOutput"]:
import capo_sagemaker._operations.sage_maker.add_tags
output, http_response = (
capo_sagemaker._operations.sage_maker.add_tags.add_tags(
req.options, req.input
)
)
return OperationResponse(output=output, response=http_response)
interceptors_, options_ = self.operation_options(
config_overrides, OperationLogging("AddTags")
)
input_: capo_sagemaker.types.add_tags_input.AddTagsInput = {}
if resource_arn is not None:
input_["resource_arn"] = resource_arn
if tags is not None:
input_["tags"] = tags
response = execute_pipeline(
OperationRequest(input=input_, options=options_),
handler=_handler,
interceptors=list(interceptors_),
)
response.response.close()
return response.output
|