class Aws::SageMakerRuntime::Types::InvokeEndpointInput

@note When making an API call, you may pass InvokeEndpointInput

data as a hash:

    {
      endpoint_name: "EndpointName", # required
      body: "data", # required
      content_type: "Header",
      accept: "Header",
      custom_attributes: "CustomAttributesHeader",
      target_model: "TargetModelHeader",
      target_variant: "TargetVariantHeader",
      target_container_hostname: "TargetContainerHostnameHeader",
      inference_id: "InferenceId",
    }

@!attribute [rw] endpoint_name

The name of the endpoint that you specified when you created the
endpoint using the [CreateEndpoint][1] API.

[1]: https://docs.aws.amazon.com/sagemaker/latest/dg/API_CreateEndpoint.html
@return [String]

@!attribute [rw] body

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.

For information about the format of the request body, see [Common
Data Formats-Inference][1].

[1]: https://docs.aws.amazon.com/sagemaker/latest/dg/cdf-inference.html
@return [String]

@!attribute [rw] content_type

The MIME type of the input data in the request body.
@return [String]

@!attribute [rw] accept

The desired MIME type of the inference in the response.
@return [String]

@!attribute [rw] custom_attributes

Provides additional information about a request for an inference
submitted to a model hosted at an Amazon SageMaker endpoint. The
information is an opaque value that is forwarded verbatim. You could
use this value, for example, to provide an ID that you can use to
track a request or to provide other metadata that a service endpoint
was programmed to process. The value must consist of no more than
1024 visible US-ASCII characters as specified in [Section 3.3.6.
Field Value Components][1] of the Hypertext Transfer Protocol
(HTTP/1.1).

The code in your model is responsible for setting or updating any
custom attributes in the response. If your code does not set this
value in the response, an empty value is returned. For example, if a
custom attribute represents the trace ID, your model can prepend the
custom attribute with `Trace ID:` in your post-processing function.

This feature is currently supported in the AWS SDKs but not in the
Amazon SageMaker Python SDK.

[1]: https://tools.ietf.org/html/rfc7230#section-3.2.6
@return [String]

@!attribute [rw] target_model

The model to request for inference when invoking a multi-model
endpoint.
@return [String]

@!attribute [rw] target_variant

Specify the production variant to send the inference request to when
invoking an endpoint that is running two or more variants. Note that
this parameter overrides the default behavior for the endpoint,
which is to distribute the invocation traffic based on the variant
weights.

For information about how to use variant targeting to perform a/b
testing, see [Test models in production][1]

[1]: https://docs.aws.amazon.com/sagemaker/latest/dg/model-ab-testing.html
@return [String]

@!attribute [rw] target_container_hostname

If the endpoint hosts multiple containers and is configured to use
direct invocation, this parameter specifies the host name of the
container to invoke.
@return [String]

@!attribute [rw] inference_id

If you provide a value, it is added to the captured data when you
enable data capture on the endpoint. For information about data
capture, see [Capture Data][1].

[1]: https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor-data-capture.html
@return [String]

@see docs.aws.amazon.com/goto/WebAPI/runtime.sagemaker-2017-05-13/InvokeEndpointInput AWS API Documentation

Constants

SENSITIVE