code: def main():
      
  
      parser = argparse.ArgumentParser(
          description='Tool for testing caffe to mxnet conversion layer by layer')
      parser.add_argument('--image_url', type=str,
                          default='https://github.com/dmlc/web-data/raw/master/mxnet/doc/'\
                                  'tutorials/python/predict_image/cat.jpg',
                          help='input image to test inference, can be either file path or url')
      parser.add_argument('--caffe_prototxt_path', type=str,
                          default='./model.prototxt',
                          help='path to caffe prototxt')
      parser.add_argument('--caffe_model_path', type=str,
                          default='./model.caffemodel',
                          help='path to caffe weights')
      parser.add_argument('--caffe_mean', type=str,
                          default='./model_mean.binaryproto',
                          help='path to caffe mean file')
      parser.add_argument('--mean_diff_allowed', type=int, default=1e-03,
                          help='mean difference allowed between caffe blob and mxnet blob')
      parser.add_argument('--max_diff_allowed', type=int, default=1e-01,
                          help='max difference allowed between caffe blob and mxnet blob')
      parser.add_argument('--gpu', type=int, default=-1, help='the gpu id used for predict')
      args = parser.parse_args()
      convert_and_compare_caffe_to_mxnet(args.image_url, args.gpu, args.caffe_prototxt_path,
                                         args.caffe_model_path, args.caffe_mean,
                                         args.mean_diff_allowed, args.max_diff_allowed)
docs: Entrypoint for compare_layers