Merge pull request #357 from mamingjie-China/develop

fix bug in 1.8.2

README.md

@@ -58,7 +58,7 @@ x2paddle --framework=paddle2onnx --model=paddle_infer_model_dir --save_dir=onnx_
 |--save_dir | 指定转换后的模型保存目录路径 |
 |--model | 当framework为tensorflow/onnx时，该参数指定tensorflow的pb模型文件或onnx模型路径 |
 |--caffe_proto | **[可选]** 由caffe.proto编译成caffe_pb2.py文件的存放路径，当存在自定义Layer时使用，默认为None |
-|--without_data_format_optimization | **[可选]** For TensorFlow, 当指定该参数时，关闭NHWC->NCHW的优化，见[文档Q2](FAQ.md) |
+|--without_data_format_optimization | **[可选]** For TensorFlow, 当指定该参数为False时，打开NHWC->NCHW的优化，见[文档Q2](FAQ.md)，默认为True|
 |--define_input_shape | **[可选]** For TensorFlow, 当指定该参数时，强制用户输入每个Placeholder的shape，见[文档Q2](FAQ.md) |
 |--params_merge | **[可选]** 当指定该参数时，转换完成后，inference_model中的所有模型参数将合并保存为一个文件__params__ |
 |--onnx_opset | **[可选]** 当framework为paddle2onnx时，该参数可设置转换为ONNX的OpSet版本，目前支持9、10、11，默认为10 |

x2paddle/convert.py

@@ -66,8 +66,8 @@ def arg_parser():
     parser.add_argument(
         "--without_data_format_optimization",
         "-wo",
-        action="store_true",
-        default=False,
+        type=_text_type,
+        default="True",
         help="tf model conversion without data format optimization")
     parser.add_argument(
         "--define_input_shape",
@@ -93,7 +93,7 @@ def arg_parser():
 
 def tf2paddle(model_path,
               save_dir,
-              without_data_format_optimization=False,
+              without_data_format_optimization,
               define_input_shape=False,
               params_merge=False):
     # check tensorflow installation and version
@@ -240,11 +240,12 @@ def main():
 
     if args.framework == "tensorflow":
         assert args.model is not None, "--model should be defined while translating tensorflow model"
-        without_data_format_optimization = False
+        assert args.without_data_format_optimization in [
+            "True", "False"
+        ], "--the param without_data_format_optimization should be defined True or False"
         define_input_shape = False
         params_merge = False
-        if args.without_data_format_optimization:
-            without_data_format_optimization = True
+        without_data_format_optimization = True if args.without_data_format_optimization == "True" else False
         if args.define_input_shape:
             define_input_shape = True
         if args.params_merge:

x2paddle/op_mapper/tf_op_mapper_nhwc.py

@@ -1068,13 +1068,25 @@ class TFOpMapperNHWC(OpMapper):
         axis = axis.value.tolist()
         assert axis == 0, "Only support axis=0 in GatherV2 OP"
         attr = {'overwrite': False}
+        embeddings_shape = embeddings.out_shapes[0][-1]
+        reshape_list = list()
+        reshape_name = index.layer_name
         if len(index.out_shapes[0]) != 1:
+            reshape_list = index.out_shapes[0]
             reshape_attr = {"shape": [-1]}
+            reshape_name = "{}_reshape".format(index.layer_name)
             node.fluid_code.add_layer(
-                "reshape", inputs=index, output=index, param_attr=reshape_attr)
-        inputs = {'input': embeddings, 'index': index}
+                "reshape",
+                inputs=index,
+                output=reshape_name,
+                param_attr=reshape_attr)
+        inputs = {'input': embeddings, 'index': reshape_name}
         node.fluid_code.add_layer(
             "gather", inputs=inputs, output=node, param_attr=attr)
+        if len(index.out_shapes[0]) != 1:
+            reshape_attr = {"shape": reshape_list + [embeddings_shape]}
+            node.fluid_code.add_layer(
+                "reshape", inputs=node, output=node, param_attr=reshape_attr)
 
     def OneShotIterator(self, node):
         return self.Placeholder(node)

x2paddle/optimizer/tf_optimizer.py

@@ -864,8 +864,8 @@ class TFOptimizer(object):
                     weight = numpy.expand_dims(weight, 3)
                     self.op_mapper.weights[in_nodes3[0].layer_name] = weight
                     # fix bug in Paddle1.8.3 and may change in next version.
-                    self.op_mapper.weights[in_nodes3[0].layer_name +
-                                           '_1'] = weight.reshape(1, -1)
+                    # self.op_mapper.weights[in_nodes3[0].layer_name +
+                    #                        '_1'] = weight.reshape(1, -1)
                     in_nodes3[0].fluid_code.layers[0].param_attr["shape"] = [
                         1, in_shape[-1], 1, 1
                     ]
@@ -888,7 +888,7 @@ class TFOptimizer(object):
                     node.fluid_code.clear()
                     attr = {
                         "mode": string(mode),
-                        "param_attr": string(in_nodes3[0].layer_name + "_1")
+                        "param_attr": string(in_nodes3[0].layer_name)
                     }
 
                     node.fluid_code.add_layer(