Describes a SageMaker AI image.
Parameters:
-
image_name
(Optional[ImageName], default:
None
)
–
The name of the image to describe.
Raises:
Source code in docs_src/capo_sagemaker/_services/sage_maker.py
| def describe_image(
self,
*,
config_overrides: Optional[SageMakerClientConfig] = None,
image_name: Optional["capo_sagemaker.types.image_name.ImageName"] = None,
) -> "capo_sagemaker.types.describe_image_response.DescribeImageResponse":
"""<p>Describes a SageMaker AI image.</p>
Args:
image_name: <p>The name of the image to describe.</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_request.DescribeImageRequest]",
) -> OperationResponse[
"capo_sagemaker.types.describe_image_response.DescribeImageResponse"
]:
import capo_sagemaker._operations.sage_maker.describe_image
output, http_response = (
capo_sagemaker._operations.sage_maker.describe_image.describe_image(
req.options, req.input
)
)
return OperationResponse(output=output, response=http_response)
interceptors_, options_ = self.operation_options(
config_overrides, OperationLogging("DescribeImage")
)
input_: capo_sagemaker.types.describe_image_request.DescribeImageRequest = {}
if image_name is not None:
input_["image_name"] = image_name
response = execute_pipeline(
OperationRequest(input=input_, options=options_),
handler=_handler,
interceptors=list(interceptors_),
)
response.response.close()
return response.output
|