untag_resource(
resource_arn: ResourceArn,
tag_keys: TagKeyList,
*,
config_overrides: Optional[AsyncElementalInferenceClientConfig] = None,
) -> None
Deletes specified tags from the specified resource in the current region.
Parameters:
-
resource_arn
(ResourceArn)
–
The ARN of the resource where you want to delete one or more tags.
-
tag_keys
(TagKeyList)
–
The keys of the tags to delete.
Raises:
-
AccessDeniedException
–
You do not have sufficient access to perform this action.
-
ConflictException
–
The request could not be completed due to a conflict.
-
InternalServerErrorException
–
An internal server error occurred. This is a temporary condition and the request can be retried. If the problem persists, contact AWS Support.
-
ResourceNotFoundException
–
The resource specified in the action doesn't exist.
-
TooManyRequestException
–
The request was denied due to request throttling. Too many requests have been made within a given time period. Reduce the frequency of requests and use exponential backoff when retrying.
-
ValidationException
–
The input fails to satisfy the constraints specified by the service. Check the error message for details about which parameter or field is invalid and correct the request before retrying.
-
UnknownServiceError
–
The service returned an error code this client does not model.
Source code in docs_src/capo_elementalinference/_services/async_elemental_inference.py
| async def untag_resource(
self,
resource_arn: "capo_elementalinference.types.resource_arn.ResourceArn",
tag_keys: "capo_elementalinference.types.tag_key_list.TagKeyList",
*,
config_overrides: Optional[AsyncElementalInferenceClientConfig] = None,
) -> None:
"""<p>Deletes specified tags from the specified resource in the current region.</p>
Args:
resource_arn: <p>The ARN of the resource where you want to delete one or more tags.</p>
tag_keys: <p>The keys of the tags to delete.</p>
Raises:
capo_elementalinference.errors.access_denied_exception.AccessDeniedException: <p>You do not have sufficient access to perform this action.</p>
capo_elementalinference.errors.conflict_exception.ConflictException: <p>The request could not be completed due to a conflict.</p>
capo_elementalinference.errors.internal_server_error_exception.InternalServerErrorException: <p>An internal server error occurred. This is a temporary condition and the request can be retried. If the problem persists, contact AWS Support. </p>
capo_elementalinference.errors.resource_not_found_exception.ResourceNotFoundException: <p>The resource specified in the action doesn't exist.</p>
capo_elementalinference.errors.too_many_request_exception.TooManyRequestException: <p>The request was denied due to request throttling. Too many requests have been made within a given time period. Reduce the frequency of requests and use exponential backoff when retrying. </p>
capo_elementalinference.errors.validation_exception.ValidationException: <p>The input fails to satisfy the constraints specified by the service. Check the error message for details about which parameter or field is invalid and correct the request before retrying. </p>
capo_elementalinference.errors.UnknownServiceError: The service returned an error code this client does not model.
"""
async def _handler(
req: "AsyncOperationRequest[capo_elementalinference.types.untag_resource_request.UntagResourceRequest]",
) -> AsyncOperationResponse[None]:
import capo_elementalinference._operations.elemental_inference.untag_resource
(
output,
http_response,
) = await capo_elementalinference._operations.elemental_inference.untag_resource.async_untag_resource(
req.options, req.input
)
return AsyncOperationResponse(output=output, response=http_response)
interceptors_, options_ = self.operation_options(
config_overrides, OperationLogging("UntagResource")
)
input_: capo_elementalinference.types.untag_resource_request.UntagResourceRequest = {
"resource_arn": resource_arn,
"tag_keys": tag_keys,
}
response = await aexecute_pipeline(
AsyncOperationRequest(input=input_, options=options_),
handler=_handler,
interceptors=list(interceptors_),
)
await response.response.aclose()
return response.output
|