def METHOD_NAME(self, model_file_path, params_file_path):
    """load_predictor
    initialize the inference engine
    Args:
        model_file_path: inference model path (*.pdmodel)
        model_file_path: inference parmaeter path (*.pdiparams)
    Return:
        predictor: Predictor created using Paddle Inference.
        config: Configuration of the predictor.
        input_tensor: Input tensor of the predictor.
        output_tensor: Output tensor of the predictor.
    """
    args = self.args
    config = inference.Config(model_file_path, params_file_path)
    if args.use_gpu:
        config.enable_use_gpu(1000, 0)
    else:
        config.disable_gpu()
        # The thread num should not be greater than the number of cores in the CPU.
        config.set_cpu_math_library_num_threads(4)
    # enable memory optim
    config.enable_memory_optim()
    config.disable_glog_info()
    config.switch_use_feed_fetch_ops(False)
    config.switch_ir_optim(True)
    # create predictor
    predictor = inference.create_predictor(config)
    # get input and output tensor property
    input_names = predictor.get_input_names()
    input_tensor = predictor.get_input_handle(input_names[0])
    output_names = predictor.get_output_names()
    output_tensor = predictor.get_output_handle(output_names[0])
    return predictor, config, input_tensor, output_tensor