def METHOD_NAME():
    with open(
        os.path.join(os.path.dirname(__file__), inference_stream_data_json), "rb"
    ) as f:
        test_data = json.loads(f.read())
    for item in test_data:
        if item["url"].startswith("{{mar_path_"):
            path = test_utils.mar_file_table[item["url"][2:-2]]
        else:
            path = item["url"]
        managment_stub = test_gRPC_utils.get_management_stub()
        response = managment_stub.RegisterModel(
            management_pb2.RegisterModelRequest(
                url=path,
                initial_workers=item["worker"],
                synchronous=bool(item["synchronous"]),
                model_name=item["model_name"],
            )
        )
        print(response.msg)
        model_input = os.path.join(os.path.dirname(__file__), "..", item["file"])
        prediction = __infer_stream(
            test_gRPC_utils.get_inference_stub(), item["model_name"], model_input
        )
        print("Stream prediction is : ", str(prediction))
        if "expected" in item:
            assert str(prediction) == str(item["expected"])
        response = managment_stub.UnregisterModel(
            management_pb2.UnregisterModelRequest(
                model_name=item["model_name"],
            )
        )
        print(response.msg)