[ aws . sagemaker ]

describe-inference-component

Description

Returns information about an inference component.

See also: AWS API Documentation

Synopsis

  describe-inference-component
--inference-component-name <value>
[--cli-input-json | --cli-input-yaml]
[--generate-cli-skeleton <value>]
[--debug]
[--endpoint-url <value>]
[--no-verify-ssl]
[--no-paginate]
[--output <value>]
[--query <value>]
[--profile <value>]
[--region <value>]
[--version <value>]
[--color <value>]
[--no-sign-request]
[--ca-bundle <value>]
[--cli-read-timeout <value>]
[--cli-connect-timeout <value>]
[--cli-binary-format <value>]
[--no-cli-pager]
[--cli-auto-prompt]
[--no-cli-auto-prompt]

Options

--inference-component-name (string)

The name of the inference component.

--cli-input-json | --cli-input-yaml (string) Reads arguments from the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, those values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally. This may not be specified along with --cli-input-yaml.

--generate-cli-skeleton (string) Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for --cli-input-json. Similarly, if provided yaml-input it will print a sample input YAML that can be used with --cli-input-yaml. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command. The generated JSON skeleton is not stable between versions of the AWS CLI and there are no backwards compatibility guarantees in the JSON skeleton generated.

Global Options

--debug (boolean)

Turn on debug logging.

--endpoint-url (string)

Override command’s default URL with the given URL.

--no-verify-ssl (boolean)

By default, the AWS CLI uses SSL when communicating with AWS services. For each SSL connection, the AWS CLI will verify SSL certificates. This option overrides the default behavior of verifying SSL certificates.

--no-paginate (boolean)

Disable automatic pagination. If automatic pagination is disabled, the AWS CLI will only make one call, for the first page of results.

--output (string)

The formatting style for command output.

• json
• text
• table
• yaml
• yaml-stream

--query (string)

A JMESPath query to use in filtering the response data.

--profile (string)

Use a specific profile from your credential file.

--region (string)

The region to use. Overrides config/env settings.

--version (string)

Display the version of this tool.

--color (string)

Turn on/off color output.

• on
• off
• auto

--no-sign-request (boolean)

Do not sign requests. Credentials will not be loaded if this argument is provided.

--ca-bundle (string)

The CA certificate bundle to use when verifying SSL certificates. Overrides config/env settings.

--cli-read-timeout (int)

The maximum socket read time in seconds. If the value is set to 0, the socket read will be blocking and not timeout. The default value is 60 seconds.

--cli-connect-timeout (int)

The maximum socket connect time in seconds. If the value is set to 0, the socket connect will be blocking and not timeout. The default value is 60 seconds.

--cli-binary-format (string)

The formatting style to be used for binary blobs. The default format is base64. The base64 format expects binary blobs to be provided as a base64 encoded string. The raw-in-base64-out format preserves compatibility with AWS CLI V1 behavior and binary values must be passed literally. When providing contents from a file that map to a binary blob fileb:// will always be treated as binary and use the file contents directly regardless of the cli-binary-format setting. When using file:// the file contents will need to properly formatted for the configured cli-binary-format.

• base64
• raw-in-base64-out

--no-cli-pager (boolean)

Disable cli pager for output.

--cli-auto-prompt (boolean)

Automatically prompt for CLI input parameters.

--no-cli-auto-prompt (boolean)

Disable automatically prompt for CLI input parameters.

Output

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 -> (structure)

Details about the resources that are deployed with this inference component.

ModelName -> (string)

The name of the SageMaker model object that is deployed with the inference component.

Container -> (structure)

Details about the container that provides the runtime environment for the model that is deployed with the inference component.

DeployedImage -> (structure)

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 this ProductionVariant , the path resolves to a path of the form registry/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 -> (timestamp)

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 -> (map)

The environment variables to set in the Docker container.

key -> (string)

value -> (string)

StartupParameters -> (structure)

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 -> (structure)

The compute resources allocated to run the model assigned 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.

RuntimeConfig -> (structure)

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 -> (timestamp)

The time when the inference component was created.

LastModifiedTime -> (timestamp)

The time when the inference component was last updated.

InferenceComponentStatus -> (string)

The status of the inference component.