SageMaker / Client / describe_inference_component
describe_inference_component#
- SageMaker.Client.describe_inference_component(**kwargs)#
Returns information about an inference component.
See also: AWS API Documentation
Request Syntax
response = client.describe_inference_component( InferenceComponentName='string' )
- Parameters:
InferenceComponentName (string) –
[REQUIRED]
The name of the inference component.
- Return type:
dict
- Returns:
Response Syntax
{ 'InferenceComponentName': 'string', 'InferenceComponentArn': 'string', 'EndpointName': 'string', 'EndpointArn': 'string', 'VariantName': 'string', 'FailureReason': 'string', 'Specification': { 'ModelName': 'string', 'Container': { 'DeployedImage': { 'SpecifiedImage': 'string', 'ResolvedImage': 'string', 'ResolutionTime': datetime(2015, 1, 1) }, 'ArtifactUrl': 'string', 'Environment': { 'string': 'string' } }, 'StartupParameters': { 'ModelDataDownloadTimeoutInSeconds': 123, 'ContainerStartupHealthCheckTimeoutInSeconds': 123 }, 'ComputeResourceRequirements': { 'NumberOfCpuCoresRequired': ..., 'NumberOfAcceleratorDevicesRequired': ..., 'MinMemoryRequiredInMb': 123, 'MaxMemoryRequiredInMb': 123 }, 'BaseInferenceComponentName': 'string' }, 'RuntimeConfig': { 'DesiredCopyCount': 123, 'CurrentCopyCount': 123 }, 'CreationTime': datetime(2015, 1, 1), 'LastModifiedTime': datetime(2015, 1, 1), 'InferenceComponentStatus': 'InService'|'Creating'|'Updating'|'Failed'|'Deleting' }
Response Structure
(dict) –
InferenceComponentName (string) –
The name of the inference component.
InferenceComponentArn (string) –
The Amazon Resource Name (ARN) of the inference component.
EndpointName (string) –
The name of the endpoint that hosts the inference component.
EndpointArn (string) –
The Amazon Resource Name (ARN) of the endpoint that hosts the inference component.
VariantName (string) –
The name of the production variant that hosts the inference component.
FailureReason (string) –
If the inference component status is
Failed
, the reason for the failure.Specification (dict) –
Details about the resources that are deployed with this inference component.
ModelName (string) –
The name of the SageMaker AI model object that is deployed with the inference component.
Container (dict) –
Details about the container that provides the runtime environment for the model that is deployed with the inference component.
DeployedImage (dict) –
Gets the Amazon EC2 Container Registry path of the docker image of the model that is hosted in this ProductionVariant.
If you used the
registry/repository[:tag]
form to specify the image path of the primary container when you created the model hosted in thisProductionVariant
, the path resolves to a path of the formregistry/repository[@digest]
. A digest is a hash value that identifies a specific version of an image. For information about Amazon ECR paths, see Pulling an Image in the Amazon ECR User Guide.SpecifiedImage (string) –
The image path you specified when you created the model.
ResolvedImage (string) –
The specific digest path of the image hosted in this
ProductionVariant
.ResolutionTime (datetime) –
The date and time when the image path for the model resolved to the
ResolvedImage
ArtifactUrl (string) –
The Amazon S3 path where the model artifacts are stored.
Environment (dict) –
The environment variables to set in the Docker container.
(string) –
(string) –
StartupParameters (dict) –
Settings that take effect while the model container starts up.
ModelDataDownloadTimeoutInSeconds (integer) –
The timeout value, in seconds, to download and extract the model that you want to host from Amazon S3 to the individual inference instance associated with this inference component.
ContainerStartupHealthCheckTimeoutInSeconds (integer) –
The timeout value, in seconds, for your inference container to pass health check by Amazon S3 Hosting. For more information about health check, see How Your Container Should Respond to Health Check (Ping) Requests.
ComputeResourceRequirements (dict) –
The compute resources allocated to run the model, plus any adapter models, that you assign to the inference component.
NumberOfCpuCoresRequired (float) –
The number of CPU cores to allocate to run a model that you assign to an inference component.
NumberOfAcceleratorDevicesRequired (float) –
The number of accelerators to allocate to run a model that you assign to an inference component. Accelerators include GPUs and Amazon Web Services Inferentia.
MinMemoryRequiredInMb (integer) –
The minimum MB of memory to allocate to run a model that you assign to an inference component.
MaxMemoryRequiredInMb (integer) –
The maximum MB of memory to allocate to run a model that you assign to an inference component.
BaseInferenceComponentName (string) –
The name of the base inference component that contains this inference component.
RuntimeConfig (dict) –
Details about the runtime settings for the model that is deployed with the inference component.
DesiredCopyCount (integer) –
The number of runtime copies of the model container that you requested to deploy with the inference component.
CurrentCopyCount (integer) –
The number of runtime copies of the model container that are currently deployed.
CreationTime (datetime) –
The time when the inference component was created.
LastModifiedTime (datetime) –
The time when the inference component was last updated.
InferenceComponentStatus (string) –
The status of the inference component.