Merge pull request #355 from mamingjie-China/develop

update op_list

op_list.md

 # X2Paddle支持OP列表
-> 目前X2Paddle支持50+的TensorFlow OP，30+的Caffe Layer，覆盖了大部分CV分类模型常用的操作。我们在如下列表中给出了目前X2Paddle支持的全部OP。
+> 目前X2Paddle支持70+的TensorFlow OP，30+的Caffe Layer，覆盖了大部分CV分类模型常用的操作。我们在如下列表中给出了目前X2Paddle支持的全部OP。
 
 **注：** 目前，部分OP暂未支持，如您在转换过程中出现OP不支持的情况，可自行添加或反馈给我们。欢迎通过[ISSUE反馈](https://github.com/PaddlePaddle/X2Paddle/issues/new)的方式告知我们(模型名，代码实现或模型获取方式)，我们会及时跟进：）
 
@@ -7,20 +7,24 @@
 
 | 序号 | OP | 序号 | OP | 序号 | OP | 序号 | OP |
 |------|------|------|------|------|------|------|------|
-| 1  | Relu        | 2  | Relu6     | 3  | Shape     | 4  | Abs                   |
-| 5  | Sigmoid     | 6  | Exp       | 7  | Rsqrt     | 8  | swish_f32             |
-| 9  | Tanh        | 10 | LeakyRelu | 11 | Add       | 12 | RealDiv               |
-| 13 | Sub         | 14 | Maximum   | 15 | Mul       | 16 | FloorDiv              |
-| 17 | Placeholder | 18 | Const     | 19 | Transpose | 20 | FusedBatchNorm        |
-| 21 | Conv2D      | 22 | BiasAdd   | 23 | MaxPool   | 24 | DepthwiseConv2dNative |
-| 25 | Reshape     | 26 | AvgPool   | 27 | SplitV    | 28 | SquaredDifference     |
-| 29 | Tile        | 30 | Pack      | 31 | Pad       | 32 | ResizeBilinear        |
-| 33 | Mean        | 34 | MatMul    | 35 | ArgMax    | 36 | StridedSlice          |
-| 37 | Slice       | 38 | Sum       | 39 | Max       | 40 | Conv2DBackpropInput   |
-| 41 | Cast        | 42 | Split     | 43 | Squeeze   | 44 | ResizeNearestNeighbor |
-| 45 | Softmax     | 46 | Range     | 47 | ConcatV2  | 48 | MirrorPad             |
-| 49 | Identity    | 50 | GreaterEqual  | 51 | StopGradient | 52 | Minimum |
-| 53 | RadnomUniform | 54 | Fill | 55 | Floor | 56 | DepthToSpace |
+| 1  | Relu             | 2  | Relu6          | 3  | Shape          | 4  | Abs                   |
+| 5  | Sigmoid          | 6  | Exp            | 7  | Rsqrt          | 8  | swish_f32             |
+| 9  | Tanh             | 10 | LeakyRelu      | 11 | Add            | 12 | RealDiv               |
+| 13 | Sub              | 14 | Maximum        | 15 | Mul            | 16 | FloorDiv              |
+| 17 | Placeholder      | 18 | Const          | 19 | Transpose      | 20 | FusedBatchNorm        |
+| 21 | Conv2D           | 22 | BiasAdd        | 23 | MaxPool        | 24 | DepthwiseConv2dNative |
+| 25 | Reshape          | 26 | AvgPool        | 27 | SplitV         | 28 | SquaredDifference     |
+| 29 | Tile             | 30 | Pack           | 31 | Pad            | 32 | ResizeBilinear        |
+| 33 | Mean             | 34 | MatMul         | 35 | ArgMax         | 36 | StridedSlice          |
+| 37 | Slice            | 38 | Sum            | 39 | Max            | 40 | Conv2DBackpropInput   |
+| 41 | Cast             | 42 | Split          | 43 | Squeeze        | 44 | ResizeNearestNeighbor |
+| 45 | Softmax          | 46 | Range          | 47 | ConcatV2       | 48 | MirrorPad             |
+| 49 | Identity         | 50 | GreaterEqual   | 51 | StopGradient   | 52 | Minimum               |
+| 53 | RadnomUniform    | 54 | Fill           | 55 | Floor          | 56 | DepthToSpace          |
+| 57 | Sqrt             | 58 | Softplus       | 59 | Erf            | 60 | AddV2                 |
+| 61 | LessEqual        | 62 | BatchMatMul    | 63 | BatchMatMulV2  | 64 | ExpandDims            |
+| 65 | BatchToSpaceND   | 66 | SpaceToBatchND | 67 | OneHot         | 68 | Pow                   |
+| 69 | All              | 70 | GatherV2       | 71 | IteratorV2     |    |                       |
 
 ## Caffe
 

x2paddle/op_mapper/tf_op_mapper_nhwc.py

@@ -299,6 +299,10 @@ class TFOpMapperNHWC(OpMapper):
         data_format = node.get_attr("data_format").decode()
         pad_mode = node.get_attr("padding").decode()
         channel_first = data_format == "NCHW"
+        if data_format == "NHWC":
+            n, h, w, c = input.out_shapes[0]
+        else:
+            n, c, h, w = input.out_shapes[0]
 
         if kernel.layer_type == 'Const':
             kernel_value = kernel.value
@@ -329,10 +333,15 @@ class TFOpMapperNHWC(OpMapper):
             "dilation": dilations[2:4],
             "padding": string(pad_mode)
         }
-
         if hasattr(node, 'dilation') and attr['dilation'] == [1, 1]:
             if len(node.dilation) == 1:
                 attr['dilation'] = [1, node.dilation[0]]
+
+        if c == -1:
+            reshape_attr = {"shape": [0, k_size[2], 0, 0]}
+            node.fluid_code.add_layer(
+                "reshape", inputs=input, output=input, param_attr=reshape_attr)
+
         node.fluid_code.add_layer(
             "conv2d", inputs=input, output=node, param_attr=attr)
         if not channel_first:
@@ -748,11 +757,12 @@ class TFOpMapperNHWC(OpMapper):
             self.add_omit_nodes(begin.layer_name, node.layer_name)
             begin = begin.value.tolist()
         else:
-            begin = begin
-            shape = begin.out_shapes[0]
-            attr = {"shape": shape}
-            node.fluid_code.add_layer(
-                "reshape", inputs=begin, output=begin, param_attr=attr)
+            begin = self.decoder.infer_tensor(begin).tolist()
+
+#             shape = begin.out_shapes[0]
+#             attr = {"shape": shape}
+#             node.fluid_code.add_layer(
+#                 "reshape", inputs=begin, output=begin, param_attr=attr)
         if size.layer_type == "Const":
             self.add_omit_nodes(size.layer_name, node.layer_name)
             size = size.value.tolist()

x2paddle/optimizer/tf_optimizer.py

@@ -863,6 +863,9 @@ class TFOptimizer(object):
                     weight = numpy.expand_dims(weight, 2)
                     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)
                     in_nodes3[0].fluid_code.layers[0].param_attr["shape"] = [
                         1, in_shape[-1], 1, 1
                     ]
@@ -885,7 +888,7 @@ class TFOptimizer(object):
                     node.fluid_code.clear()
                     attr = {
                         "mode": string(mode),
-                        "param_attr": string(in_nodes3[0].layer_name)
+                        "param_attr": string(in_nodes3[0].layer_name + "_1")
                     }
 
                     node.fluid_code.add_layer(

x2paddle_model_zoo.md

 # X2Paddle模型测试库
-> 目前X2Paddle支持50+的TensorFlow OP，40+的Caffe Layer，覆盖了大部分CV分类模型常用的操作。我们在如下模型列表中测试了X2Paddle的转换。
+> 目前X2Paddle支持70+的TensorFlow OP，40+的Caffe Layer，覆盖了大部分CV分类模型常用的操作。我们在如下模型列表中测试了X2Paddle的转换。
 
 **注：** 受限于不同框架的差异，部分模型可能会存在目前无法转换的情况，如TensorFlow中包含控制流的模型，NLP模型等。对于CV常见的模型，如若您发现无法转换或转换失败，存在较大diff等问题，欢迎通过[ISSUE反馈](https://github.com/PaddlePaddle/X2Paddle/issues/new)的方式告知我们(模型名，代码实现或模型获取方式)，我们会及时跟进：）