[Tools] Add x2paddle tool (#631)

* add onnx_ort_runtime demo

* rm in requirements

* support batch eval

* fixed MattingResults bug

* move assignment for DetectionResult

* integrated x2paddle

* add model convert readme

* update readme

* re-lint

Co-authored-by: Jason <jiangjiajun@baidu.com>

tools/common_tools/common_tools.py

@@ -1,8 +1,8 @@
 import argparse
+import ast
 
 
 def argsparser():
-
     parser = argparse.ArgumentParser(description=__doc__)
     ## argumentments for auto compression
     parser.add_argument('--auto_compress', default=False, action='store_true')
@@ -10,31 +10,71 @@ def argsparser():
         '--config_path',
         type=str,
         default=None,
-        help="path of compression strategy config.",
-        required=True)
+        help="path of compression strategy config.")
     parser.add_argument(
         '--method',
         type=str,
         default=None,
-        help="choose PTQ or QAT as quantization method",
-        required=True)
+        help="choose PTQ or QAT as quantization method")
     parser.add_argument(
         '--save_dir',
         type=str,
         default='./output',
-        help="directory to save compressed model.")
+        help="directory to save model.")
     parser.add_argument(
         '--devices',
         type=str,
         default='gpu',
         help="which device used to compress.")
-
+    ## arguments for other x2paddle
+    parser.add_argument('--convert', default=False, action='store_true')
+    parser.add_argument(
+        '--framework',
+        type=str,
+        default=None,
+        help="define which deeplearning framework(tensorflow/caffe/onnx)")
+    parser.add_argument(
+        '--model',
+        type=str,
+        default=None,
+        help="define model file path for tensorflow or onnx")
+    parser.add_argument(
+        "--prototxt",
+        "-p",
+        type=str,
+        default=None,
+        help="prototxt file of caffe model")
+    parser.add_argument(
+        "--weight",
+        "-w",
+        type=str,
+        default=None,
+        help="weight file of caffe model")
+    parser.add_argument(
+        "--caffe_proto",
+        "-c",
+        type=str,
+        default=None,
+        help="optional: the .py file compiled by caffe proto file of caffe model"
+    )
+    parser.add_argument(
+       "--input_shape_dict",
+       "-isd",
+       type=str,
+       default=None,
+       help="define input shapes, e.g --input_shape_dict=\"{'image':[1, 3, 608, 608]}\" or" \
+       "--input_shape_dict=\"{'image':[1, 3, 608, 608], 'im_shape': [1, 2], 'scale_factor': [1, 2]}\"")
+    parser.add_argument(
+        "--enable_code_optim",
+        "-co",
+        type=ast.literal_eval,
+        default=False,
+        help="Turn on code optimization")
     ## arguments for other tools
     return parser
 
 
 def main():
-
     args = argsparser().parse_args()
     if args.auto_compress == True:
         try:
@@ -45,6 +85,43 @@ def main():
             print(
                 "Can not start auto compresssion successfully! Please check if you have installed it!"
             )
+    if args.convert == True:
+        try:
+            import platform
+            import logging
+            v0, v1, v2 = platform.python_version().split('.')
+            if not (int(v0) >= 3 and int(v1) >= 5):
+                logging.info("[ERROR] python>=3.5 is required")
+                return
+            import paddle
+            v0, v1, v2 = paddle.__version__.split('.')
+            logging.info("paddle.__version__ = {}".format(paddle.__version__))
+            if v0 == '0' and v1 == '0' and v2 == '0':
+                logging.info(
+                    "[WARNING] You are use develop version of paddlepaddle")
+            elif int(v0) != 2 or int(v1) < 0:
+                logging.info("[ERROR] paddlepaddle>=2.0.0 is required")
+                return
+            from x2paddle.convert import tf2paddle, caffe2paddle, onnx2paddle
+            if args.framework == "tensorflow":
+                assert args.model is not None, "--model should be defined while convert tensorflow model"
+                tf2paddle(args.model, args.save_dir)
+            elif args.framework == "caffe":
+                assert args.prototxt is not None and args.weight is not None, "--prototxt and --weight should be defined while convert caffe model"
+                caffe2paddle(args.prototxt, args.weight, args.save_dir,
+                             args.caffe_proto)
+            elif args.framework == "onnx":
+                assert args.model is not None, "--model should be defined while convert onnx model"
+                onnx2paddle(
+                    args.model,
+                    args.save_dir,
+                    input_shape_dict=args.input_shape_dict)
+            else:
+                raise Exception(
+                    "--framework only support tensorflow/caffe/onnx now")
+        except ImportError:
+            print(
+                "Model convert failed! Please check if you have installed it!")
 
 
 if __name__ == '__main__':