update readme.md

README.md

@@ -10,7 +10,7 @@ paddlepaddle >= 1.5.0
 **以下依赖只需对应安装自己需要的即可**  
 转换tensorflow模型 ： tensorflow == 1.14.0  
 转换caffe模型 ： caffe == 1.0.0  
-
+转换onnx模型 ： onnx == 1.5.0  pytorch == 1.5.0(optional for dynamic graph)
 ## 安装
 ```
 pip install x2paddle
@@ -30,8 +30,9 @@ x2paddle --framework=tensorflow --model=tf_model.pb --save_dir=pd_model
 x2paddle --framework=caffe --prototxt=deploy.proto --weight=deploy.caffemodel --save_dir=pd_model
 ```
 ### ONNX
-即将release，目前仍可使用[onnx2fluid](https://github.com/PaddlePaddle/X2Paddle/tree/release-0.3/onnx2fluid)
-
+```
+x2paddle --framework=onnx --model=onnx_model.onnx --save_dir=pd_model
+```
 ### 参数选项
 | 参数 | |
 |----------|--------------|
@@ -50,7 +51,7 @@ x2paddle --framework=caffe --prototxt=deploy.proto --weight=deploy.caffemodel --
 ## 相关文档
 1. [X2Paddle使用过程中常见问题](Q&A.md)  
 2. [如何导出TensorFlow的pb模型](export_tf_model.md)
-3. [X2Paddle测试模型库](test_model_zoo.md)
+3. [X2Paddle测试模型库](x2paddle_model_zoo.md)
 
 ## 更新历史
 2019.08.05  

x2paddle/op_mapper/onnx_directly_map.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 from collections import OrderedDict as _dict
+import numpy as _np
 
 default_op_mapping_field_values = _dict()
 default_op_mapping_field_values['FLUID_OP'] = ''
@@ -30,6 +31,21 @@ default_op_mapping = {
     'Mul': ['elementwise_mul', ['X', 'Y'], ['Out'],
             dict(),
             dict(axis=-1)],
+    'Clip': [
+        'clip', ['X'], ['Out'],
+        dict(),
+        dict(
+            min=(_np.asarray([255, 255, 127, 255],
+                             dtype=_np.uint8).view(_np.float32)),
+            max=(_np.asarray([255, 255, 127, 127],
+                             dtype=_np.uint8).view(_np.float32)),
+        )
+    ],
+    'ReduceMean': [
+        'reduce_mean', ['X'], ['Out'],
+        dict(axes='dim', keepdims='keep_dim'),
+        dict(keep_dim=1)
+    ]
 }
 
 default_ioa_constraint = {

x2paddle/op_mapper/onnx_op_mapper.py

@@ -62,7 +62,7 @@ class ONNXOpMapper(OpMapper):
                 func = getattr(self, op)
                 func(node)
             elif op in default_op_mapping:
-                self._default(node)
+                self.directly_map(node)
 
     def op_checker(self):
         unsupported_ops = set()
@@ -80,7 +80,7 @@ class ONNXOpMapper(OpMapper):
                 print(op)
             return False
 
-    def _default(self, node, *args, name='', **kwargs):
+    def directly_map(self, node, *args, name='', **kwargs):
         inputs = node.layer.input
         outputs = node.layer.output
         op_type = node.layer_type
@@ -544,7 +544,7 @@ class ONNXOpMapper(OpMapper):
             "momentum": momentum,
             "epsilon": epsilon,
             "data_layout": string('NCHW'),
-            "is_test": 'True',
+            "is_test": True,
             "param_attr": string(val_scale.layer_name),
             "bias_attr": string(val_b.layer_name),
             "moving_mean_name": string(val_mean.layer_name),

x2paddle_model_zoo.md

@@ -47,8 +47,12 @@
 ```
 import torch
 import torchvision
-dummy_input = torch.randn(1, 3, 224, 224) #根据不同模型调整shape
+
+#根据不同模型调整输入的shape
+dummy_input = torch.randn(1, 3, 224, 224)
 resnet18 = torchvision.models.resnet18(pretrained=True)
-torch.onnx.export(resnet18, dummy_input, "resnet18.onnx",verbose=True)#"resnet18.onnx"为onnx model的存储路径
+
+#"resnet18.onnx"为onnx model的存储路径
+torch.onnx.export(resnet18, dummy_input, "resnet18.onnx",verbose=True)
 
 ```