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list_model_bias_job_definitions

list_model_bias_job_definitions(
    *,
    config_overrides: Optional[SageMakerClientConfig] = None,
    endpoint_name: Optional[EndpointName] = None,
    sort_by: Optional[MonitoringJobDefinitionSortKey] = None,
    sort_order: Optional[SortOrder] = None,
    next_token: Optional[NextToken] = None,
    max_results: Optional[MaxResults] = None,
    name_contains: Optional[NameContains] = None,
    creation_time_before: Optional[Timestamp] = None,
    creation_time_after: Optional[Timestamp] = None,
) -> ListModelBiasJobDefinitionsResponse

Lists model bias jobs definitions that satisfy various filters.

Parameters:

  • endpoint_name (Optional[EndpointName], default: None ) –

    Name of the endpoint to monitor for model bias.

  • sort_by (Optional[MonitoringJobDefinitionSortKey], default: None ) –

    Whether to sort results by the Name or CreationTime field. The default is CreationTime.

  • sort_order (Optional[SortOrder], default: None ) –

    Whether to sort the results in Ascending or Descending order. The default is Descending.

  • next_token (Optional[NextToken], default: None ) –

    The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.

  • max_results (Optional[MaxResults], default: None ) –

    The maximum number of model bias jobs to return in the response. The default value is 10.

  • name_contains (Optional[NameContains], default: None ) –

    Filter for model bias jobs whose name contains a specified string.

  • creation_time_before (Optional[Timestamp], default: None ) –

    A filter that returns only model bias jobs created before a specified time.

  • creation_time_after (Optional[Timestamp], default: None ) –

    A filter that returns only model bias jobs created after a specified time.

Raises:

Source code in docs_src/capo_sagemaker/_services/sage_maker.py
def list_model_bias_job_definitions(
    self,
    *,
    config_overrides: Optional[SageMakerClientConfig] = None,
    endpoint_name: Optional[
        "capo_sagemaker.types.endpoint_name.EndpointName"
    ] = None,
    sort_by: Optional[
        "capo_sagemaker.types.monitoring_job_definition_sort_key.MonitoringJobDefinitionSortKey"
    ] = None,
    sort_order: Optional["capo_sagemaker.types.sort_order.SortOrder"] = None,
    next_token: Optional["capo_sagemaker.types.next_token.NextToken"] = None,
    max_results: Optional["capo_sagemaker.types.max_results.MaxResults"] = None,
    name_contains: Optional[
        "capo_sagemaker.types.name_contains.NameContains"
    ] = None,
    creation_time_before: Optional[
        "capo_sagemaker.types.timestamp.Timestamp"
    ] = None,
    creation_time_after: Optional[
        "capo_sagemaker.types.timestamp.Timestamp"
    ] = None,
) -> "capo_sagemaker.types.list_model_bias_job_definitions_response.ListModelBiasJobDefinitionsResponse":
    """<p>Lists model bias jobs definitions that satisfy various filters.</p>

    Args:
        endpoint_name: <p>Name of the endpoint to monitor for model bias.</p>
        sort_by: <p>Whether to sort results by the <code>Name</code> or <code>CreationTime</code> field. The default is <code>CreationTime</code>.</p>
        sort_order: <p>Whether to sort the results in <code>Ascending</code> or <code>Descending</code> order. The default is <code>Descending</code>.</p>
        next_token: <p>The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.</p>
        max_results: <p>The maximum number of model bias jobs to return in the response. The default value is 10.</p>
        name_contains: <p>Filter for model bias jobs whose name contains a specified string.</p>
        creation_time_before: <p>A filter that returns only model bias jobs created before a specified time.</p>
        creation_time_after: <p>A filter that returns only model bias jobs created after a specified time.</p>

    Raises:
        capo_sagemaker.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_sagemaker.types.list_model_bias_job_definitions_request.ListModelBiasJobDefinitionsRequest]",
    ) -> OperationResponse[
        "capo_sagemaker.types.list_model_bias_job_definitions_response.ListModelBiasJobDefinitionsResponse"
    ]:
        import capo_sagemaker._operations.sage_maker.list_model_bias_job_definitions

        output, http_response = (
            capo_sagemaker._operations.sage_maker.list_model_bias_job_definitions.list_model_bias_job_definitions(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("ListModelBiasJobDefinitions")
    )
    input_: capo_sagemaker.types.list_model_bias_job_definitions_request.ListModelBiasJobDefinitionsRequest = {}
    if endpoint_name is not None:
        input_["endpoint_name"] = endpoint_name
    if sort_by is not None:
        input_["sort_by"] = sort_by
    if sort_order is not None:
        input_["sort_order"] = sort_order
    if next_token is not None:
        input_["next_token"] = next_token
    if max_results is not None:
        input_["max_results"] = max_results
    if name_contains is not None:
        input_["name_contains"] = name_contains
    if creation_time_before is not None:
        input_["creation_time_before"] = creation_time_before
    if creation_time_after is not None:
        input_["creation_time_after"] = creation_time_after

    response = execute_pipeline(
        OperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    response.response.close()
    return response.output