Returns a description of a model bias job definition.
Parameters:
-
job_definition_name
(Optional[MonitoringJobDefinitionName], default:
None
)
–
The name of the model bias job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
Raises:
Source code in docs_src/capo_sagemaker/_services/sage_maker.py
| def describe_model_bias_job_definition(
self,
*,
config_overrides: Optional[SageMakerClientConfig] = None,
job_definition_name: Optional[
"capo_sagemaker.types.monitoring_job_definition_name.MonitoringJobDefinitionName"
] = None,
) -> "capo_sagemaker.types.describe_model_bias_job_definition_response.DescribeModelBiasJobDefinitionResponse":
"""<p>Returns a description of a model bias job definition.</p>
Args:
job_definition_name: <p>The name of the model bias job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.</p>
Raises:
capo_sagemaker.errors.resource_not_found.ResourceNotFound: <p>Resource being access is not found.</p>
capo_sagemaker.errors.UnknownServiceError: The service returned an error code this client does not model.
"""
def _handler(
req: "OperationRequest[capo_sagemaker.types.describe_model_bias_job_definition_request.DescribeModelBiasJobDefinitionRequest]",
) -> OperationResponse[
"capo_sagemaker.types.describe_model_bias_job_definition_response.DescribeModelBiasJobDefinitionResponse"
]:
import capo_sagemaker._operations.sage_maker.describe_model_bias_job_definition
output, http_response = (
capo_sagemaker._operations.sage_maker.describe_model_bias_job_definition.describe_model_bias_job_definition(
req.options, req.input
)
)
return OperationResponse(output=output, response=http_response)
interceptors_, options_ = self.operation_options(
config_overrides, OperationLogging("DescribeModelBiasJobDefinition")
)
input_: capo_sagemaker.types.describe_model_bias_job_definition_request.DescribeModelBiasJobDefinitionRequest = {}
if job_definition_name is not None:
input_["job_definition_name"] = job_definition_name
response = execute_pipeline(
OperationRequest(input=input_, options=options_),
handler=_handler,
interceptors=list(interceptors_),
)
response.response.close()
return response.output
|