SageMakerRuntime

Table of Contents

Client

class SageMakerRuntime.Client

A low-level client representing Amazon SageMaker Runtime:

import boto3

client = boto3.client('runtime.sagemaker')

These are the available methods:

can_paginate(operation_name)

Check if an operation can be paginated.

Parameters
operation_name (string) -- The operation name. This is the same name as the method name on the client. For example, if the method name is create_foo, and you'd normally invoke the operation as client.create_foo(**kwargs), if the create_foo operation can be paginated, you can use the call client.get_paginator("create_foo").
Returns
True if the operation can be paginated, False otherwise.
generate_presigned_url(ClientMethod, Params=None, ExpiresIn=3600, HttpMethod=None)

Generate a presigned url given a client, its method, and arguments

Parameters
  • ClientMethod (string) -- The client method to presign for
  • Params (dict) -- The parameters normally passed to ClientMethod.
  • ExpiresIn (int) -- The number of seconds the presigned url is valid for. By default it expires in an hour (3600 seconds)
  • HttpMethod (string) -- The http method to use on the generated url. By default, the http method is whatever is used in the method's model.
Returns

The presigned url

get_paginator(operation_name)

Create a paginator for an operation.

Parameters
operation_name (string) -- The operation name. This is the same name as the method name on the client. For example, if the method name is create_foo, and you'd normally invoke the operation as client.create_foo(**kwargs), if the create_foo operation can be paginated, you can use the call client.get_paginator("create_foo").
Raises OperationNotPageableError
Raised if the operation is not pageable. You can use the client.can_paginate method to check if an operation is pageable.
Return type
L{botocore.paginate.Paginator}
Returns
A paginator object.
get_waiter(waiter_name)
invoke_endpoint(**kwargs)

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

response = client.invoke_endpoint(
    EndpointName='string',
    Body=b'bytes'|file,
    ContentType='string',
    Accept='string'
)
Parameters
  • EndpointName (string) --

    [REQUIRED]

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

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

    [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.

  • ContentType (string) -- The MIME type of the input data in the request body.
  • Accept (string) -- The desired MIME type of the inference in the response.
Return type

dict

Returns

Response Syntax

{
    'Body': StreamingBody(),
    'ContentType': 'string',
    'InvokedProductionVariant': 'string'
}

Response Structure

  • (dict) --

    • Body (StreamingBody) --

      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.

Paginators

The available paginators are: