Amazon SageMaker Runtime

2017/11/29 - Amazon SageMaker Runtime - 1 new api methods

Changes  Amazon SageMaker is a fully-managed service that enables data scientists and developers to quickly and easily build, train, and deploy machine learning models, at scale.

InvokeEndpoint (new) Link ΒΆ

After you deploy a model into production using Amazon SageMaker hosting services, your client applications use this API to get inferences from the model hosted at the specified endpoint.

For an overview of Amazon SageMaker, see How It Works

Amazon SageMaker strips all POST headers except those supported by the API. Amazon SageMaker might add additional headers. You should not rely on the behavior of headers outside those enumerated in the request syntax.

See also: AWS API Documentation

Request Syntax

client.invoke_endpoint(
    EndpointName='string',
    Body=b'bytes'|file,
    ContentType='string',
    Accept='string'
)
type EndpointName

string

param EndpointName

[REQUIRED]

The name of the endpoint that you specified when you created the endpoint using the CreateEndpoint API.

type Body

bytes or seekable file-like object

param Body

[REQUIRED]

Provides input data, in the format specified in the ContentType request header. Amazon SageMaker passes all of the data in the body to the model.

type ContentType

string

param ContentType

The MIME type of the input data in the request body.

type Accept

string

param Accept

The desired MIME type of the inference in the response.

rtype

dict

returns

Response Syntax

{
    'Body': b'bytes'|file,
    'ContentType': 'string',
    'InvokedProductionVariant': 'string'
}

Response Structure

  • (dict) --

    • Body (bytes or seekable file-like object) --

      Includes the inference provided by the model.

    • ContentType (string) --

      The MIME type of the inference returned in the response body.

    • InvokedProductionVariant (string) --

      Identifies the production variant that was invoked.