diff --git a/x2paddle/decoder/onnx_decoder.py b/x2paddle/decoder/onnx_decoder.py
index bb271a961c8dc2b46e5923491bad8b885bd8d8cf..2671dd10769afa3d758e22e40bfd324610f3c494 100644
--- a/x2paddle/decoder/onnx_decoder.py
+++ b/x2paddle/decoder/onnx_decoder.py
@@ -241,7 +241,6 @@ class ONNXDecoder(object):
                 model.opset_import[0].version)
         check_model(model)
 
-        #         model = convert_version(model, 10)
         model = polish_model(model)
 
         model = self.optimize_model_skip_op_for_inference(model)
diff --git a/x2paddle/op_mapper/onnx_op_mapper.py b/x2paddle/op_mapper/onnx_op_mapper.py
index 0fb57ef313ab122a086ce77d8963129e155ab859..2fc4ff15c3dee0e87c48de53a4f1f2529494d360 100644
--- a/x2paddle/op_mapper/onnx_op_mapper.py
+++ b/x2paddle/op_mapper/onnx_op_mapper.py
@@ -49,6 +49,12 @@ class ONNXOpMapper(OpMapper):
             raise Exception("Model are not supported yet.")
 
         #mapping op
+
+        print("Total nodes: {}".format(
+            sum([
+                isinstance(node, ONNXGraphNode)
+                for name, node in self.graph.node_map.items()
+            ])))
         for node_name in self.graph.topo_sort:
             node = self.graph.get_node(node_name)
             op = node.layer_type
diff --git a/x2paddle_model_zoo.md b/x2paddle_model_zoo.md
index c0f30b25bf3d96b219d84e368cdc99c05043ab15..80d12d9fdc91ead399bc6c9da26d8be5929becfd 100644
--- a/x2paddle_model_zoo.md
+++ b/x2paddle_model_zoo.md
@@ -27,7 +27,6 @@
 | mNASNet | [code](https://github.com/LiJianfei06/MnasNet-caffe) |
 | MTCNN | [code](https://github.com/kpzhang93/MTCNN_face_detection_alignment/tree/master/code/codes/MTCNNv1/model) |
 
-
 # ONNX
 
 | 模型 | 来源 | operator version|
@@ -44,7 +43,6 @@
 | Shufflenet | [onnx official](https://github.com/onnx/models/tree/master/vision/classification/shufflenet) |9|
 | Inception_v2 | [onnx official](https://github.com/onnx/models/tree/master/vision/classification/inception_and_googlenet/inception_v2) |9|
 
-
 目前onnx2paddle主要支持onnx operator version 9，关于如何使用torchvison的model:
 ```
 import torch