RecommendationJobContainerConfig
Specifies mandatory fields for running an Inference Recommender job directly in the CreateInferenceRecommendationsJob API. The fields specified in ContainerConfig override the corresponding fields in the model package. Use ContainerConfig if you want to specify these fields for the recommendation job but don't want to edit them in your model package.
Types
Properties
Specifies the name and shape of the expected data inputs for your trained model with a JSON dictionary form. This field is used for optimizing your model using SageMaker Neo. For more information, see DataInputConfig.
The framework version of the container image.
The name of a pre-trained machine learning model benchmarked by Amazon SageMaker Inference Recommender that matches your model.
Specifies the SamplePayloadUrl and all other sample payload-related fields.
The endpoint type to receive recommendations for. By default this is null, and the results of the inference recommendation job return a combined list of both real-time and serverless benchmarks. By specifying a value for this field, you can receive a longer list of benchmarks for the desired endpoint type.
A list of the instance types that are used to generate inferences in real-time.
The supported MIME types for the output data.