set asymmetric as defalut mode of Resize

x2paddle/convert.py

@@ -75,6 +75,12 @@ def arg_parser():
         action="store_true",
         default=False,
         help="define input shape for tf model")
+    parser.add_argument(
+        "--onnx_opset",
+        "-oo",
+        type=int,
+        default=10,
+        help="when paddle2onnx set onnx opset version to export")
     parser.add_argument(
         "--params_merge",
         "-pm",
@@ -186,12 +192,12 @@ def onnx2paddle(model_path, save_dir, params_merge=False):
     print("Paddle model and code generated.")
 
 
-def paddle2onnx(model_path, save_dir):
+def paddle2onnx(model_path, save_dir, opset):
     from x2paddle.decoder.paddle_decoder import PaddleDecoder
     from x2paddle.op_mapper.paddle_op_mapper import PaddleOpMapper
     model = PaddleDecoder(model_path, '__model__', '__params__')
     mapper = PaddleOpMapper()
-    mapper.convert(model.program, save_dir)
+    mapper.convert(model.program, save_dir, opset)
 
 
 def main():
@@ -258,7 +264,7 @@ def main():
 
     elif args.framework == "paddle2onnx":
         assert args.model is not None, "--model should be defined while translating paddle model to onnx"
-        paddle2onnx(args.model, args.save_dir)
+        paddle2onnx(args.model, args.save_dir, args.onnx_opset)
 
     else:
         raise Exception(

x2paddle/op_mapper/paddle_op_mapper.py

@@ -37,12 +37,11 @@ class PaddleOpMapper(object):
 
         self.name_counter = dict()
 
-    def convert(self, program, save_dir):
+    def convert(self, program, save_dir, opset=10):
         weight_nodes = self.convert_weights(program)
         op_nodes = list()
         input_nodes = list()
         output_nodes = list()
-
         unsupported_ops = set()
 
         print("Translating PaddlePaddle to ONNX...\n")
@@ -81,7 +80,9 @@ class PaddleOpMapper(object):
             initializer=[],
             inputs=input_nodes,
             outputs=output_nodes)
-        model = helper.make_model(graph, producer_name='X2Paddle')
+        opset_imports = [helper.make_opsetid("", opset)]
+        model = helper.make_model(
+            graph, producer_name='X2Paddle', opset_imports=opset_imports)
         onnx.checker.check_model(model)
 
         if not os.path.isdir(save_dir):