tfx_bsl.public.beam.run_inference.CreateModelHandler

Creates a Beam ModelHandler based on the inference spec type.

tfx_bsl.public.beam.run_inference.CreateModelHandler(
    inference_spec_type: tfx_bsl.public.proto.model_spec_pb2.InferenceSpecType
) -> tfx_bsl.public.beam.run_inference.ModelHandler

There are two model handlers:

1. In-process inference from a SavedModel instance. Used when saved_model_spec field is set in inference_spec_type.
2. Remote inference by using a service endpoint. Used when ai_platform_prediction_model_spec field is set in inference_spec_type.

Example Usage
from apache_beam.ml.inference import base tf_handler = CreateModelHandler(inference_spec_type) # unkeyed base.RunInference(tf_handler) # keyed base.RunInference(base.KeyedModelHandler(tf_handler))

Args
inference_spec_type	Model inference endpoint.

Returns
A Beam RunInference ModelHandler for TensorFlow