import argparse
import numpy as np
from paddle.fluid.core import AnalysisConfig
from paddle.fluid.core import create_paddle_predictor

def main():
    args = parse_args()

    config = set_config(args)

    predictor = create_paddle_predictor(config)

    input_names = predictor.get_input_names()
    input_tensor = predictor.get_input_tensor(input_names[0])

    fake_input = np.random.randn(1, 3, 769, 769).astype("float32")
    input_tensor.reshape([1, 3, 769, 769])
    input_tensor.copy_from_cpu(fake_input)

    predictor.zero_copy_run()

    output_names = predictor.get_output_names()
    output_tensor = predictor.get_output_tensor(output_names[0])
    output_data = output_tensor.copy_to_cpu()

def parse_args():
    parser = argparse.ArgumentParser()
    parser.add_argument("--model_file", type=str, help="model filename")
    parser.add_argument("--params_file", type=str, help="parameter filename")
    parser.add_argument("--batch_size", type=int, default=1, help="batch size")

    return parser.parse_args()

def set_config(args):
    config = AnalysisConfig(args.model_file, args.params_file)
    config.disable_gpu()
    config.enable_mkldnn()
    config.switch_use_feed_fetch_ops(False)
    config.switch_specify_input_names(True)
    # config.delete_pass("depthwise_conv_mkldnn_pass")
    return config

if __name__ == "__main__":
    main()