Table of Contents
A low-level client representing Amazon SageMaker Runtime:
import boto3
client = boto3.client('sagemaker-runtime')
These are the available methods:
Check if an operation can be paginated.
Generate a presigned url given a client, its method, and arguments
The presigned url
Create a paginator for an operation.
Returns an object that can wait for some condition.
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'
)
[REQUIRED]
The name of the endpoint that you specified when you created the endpoint using the CreateEndpoint API.
[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.
dict
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.
The available paginators are: