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X2Paddle
未验证 提交 be3d799b 编写于 作者: J Jason 提交者： GitHub
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Merge pull request #355 from mamingjie-China/develop 

update op_list
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op_list.md
浏览文件 @ be3d799b
# 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
浏览文件 @ be3d799b
......@@ -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
浏览文件 @ be3d799b
......@@ -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
浏览文件 @ be3d799b
# 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：）
......
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