describe_image_version ¶

def describe_image_version(
    self,
    *,
    config_overrides: Optional[SageMakerClientConfig] = None,
    image_name: Optional["capo_sagemaker.types.image_name.ImageName"] = None,
    version: Optional[
        "capo_sagemaker.types.image_version_number.ImageVersionNumber"
    ] = None,
    alias: Optional[
        "capo_sagemaker.types.sage_maker_image_version_alias.SageMakerImageVersionAlias"
    ] = None,
) -> "capo_sagemaker.types.describe_image_version_response.DescribeImageVersionResponse":
    """<p>Describes a version of a SageMaker AI image.</p>

    Args:
        image_name: <p>The name of the image.</p>
        version: <p>The version of the image. If not specified, the latest version is described.</p>
        alias: <p>The alias of the image version.</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_image_version_request.DescribeImageVersionRequest]",
    ) -> OperationResponse[
        "capo_sagemaker.types.describe_image_version_response.DescribeImageVersionResponse"
    ]:
        import capo_sagemaker._operations.sage_maker.describe_image_version

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

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("DescribeImageVersion")
    )
    input_: capo_sagemaker.types.describe_image_version_request.DescribeImageVersionRequest = {}
    if image_name is not None:
        input_["image_name"] = image_name
    if version is not None:
        input_["version"] = version
    if alias is not None:
        input_["alias"] = alias

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