list_inference_experiments ¶

def list_inference_experiments(
    self,
    *,
    config_overrides: Optional[SageMakerClientConfig] = None,
    name_contains: Optional[
        "capo_sagemaker.types.name_contains.NameContains"
    ] = None,
    type: Optional[
        "capo_sagemaker.types.inference_experiment_type.InferenceExperimentType"
    ] = None,
    status_equals: Optional[
        "capo_sagemaker.types.inference_experiment_status.InferenceExperimentStatus"
    ] = None,
    creation_time_after: Optional[
        "capo_sagemaker.types.timestamp.Timestamp"
    ] = None,
    creation_time_before: Optional[
        "capo_sagemaker.types.timestamp.Timestamp"
    ] = None,
    last_modified_time_after: Optional[
        "capo_sagemaker.types.timestamp.Timestamp"
    ] = None,
    last_modified_time_before: Optional[
        "capo_sagemaker.types.timestamp.Timestamp"
    ] = None,
    sort_by: Optional[
        "capo_sagemaker.types.sort_inference_experiments_by.SortInferenceExperimentsBy"
    ] = 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,
) -> "capo_sagemaker.types.list_inference_experiments_response.ListInferenceExperimentsResponse":
    """<p>Returns the list of all inference experiments.</p>

    Args:
        name_contains: <p>Selects inference experiments whose names contain this name.</p>
        type: <p> Selects inference experiments of this type. For the possible types of inference experiments, see <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateInferenceExperiment.html">CreateInferenceExperiment</a>. </p>
        status_equals: <p> Selects inference experiments which are in this status. For the possible statuses, see <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DescribeInferenceExperiment.html">DescribeInferenceExperiment</a>. </p>
        creation_time_after: <p>Selects inference experiments which were created after this timestamp.</p>
        creation_time_before: <p>Selects inference experiments which were created before this timestamp.</p>
        last_modified_time_after: <p>Selects inference experiments which were last modified after this timestamp.</p>
        last_modified_time_before: <p>Selects inference experiments which were last modified before this timestamp.</p>
        sort_by: <p>The column by which to sort the listed inference experiments.</p>
        sort_order: <p>The direction of sorting (ascending or descending).</p>
        next_token: <p> The response from the last list when returning a list large enough to need tokening. </p>
        max_results: <p>The maximum number of results to select.</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_inference_experiments_request.ListInferenceExperimentsRequest]",
    ) -> OperationResponse[
        "capo_sagemaker.types.list_inference_experiments_response.ListInferenceExperimentsResponse"
    ]:
        import capo_sagemaker._operations.sage_maker.list_inference_experiments

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

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("ListInferenceExperiments")
    )
    input_: capo_sagemaker.types.list_inference_experiments_request.ListInferenceExperimentsRequest = {}
    if name_contains is not None:
        input_["name_contains"] = name_contains
    if type is not None:
        input_["type"] = type
    if status_equals is not None:
        input_["status_equals"] = status_equals
    if creation_time_after is not None:
        input_["creation_time_after"] = creation_time_after
    if creation_time_before is not None:
        input_["creation_time_before"] = creation_time_before
    if last_modified_time_after is not None:
        input_["last_modified_time_after"] = last_modified_time_after
    if last_modified_time_before is not None:
        input_["last_modified_time_before"] = last_modified_time_before
    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

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