Merge pull request #510 from SunAhong1993/develop

添加LRN+修复文档

README.md

@@ -9,7 +9,7 @@ X2Paddle在多个主流的CV模型上，测试过TensorFlow/Caffe/ONNX/PyTorch
 
 ## 环境依赖
 
-python == 2.7 | python >= 3.5  
+python >= 3.5  
 paddlepaddle 2.0.0-rc1 或者 develop  
 
 **按需安装以下依赖**  

docs/introduction/op_list.md

@@ -42,7 +42,7 @@
 | 21 | Axpy      | 22 | ROIPolling   | 23 | Permute        | 24 | DetectionOutput      |
 | 25 | Normalize | 26 | Select       | 27 | ShuffleChannel | 28 | ConvolutionDepthwise |
 | 29 | ReLU      | 30 | AbsVal       | 31 | Sigmoid        | 32 | TanH                 |
-| 33 | ReLU6     | 34 | Upsample | |          |   |                   |
+| 33 | ReLU6     | 34 | Upsample     | 35 | MemoryData     |    |                      |
 
 ## ONNX
 
@@ -63,7 +63,7 @@
 | 49 | MaxPool  | 50 | Conv      | 51 | Gemm      | 52 | NonZero            |
 | 53 | Abs      | 54 | Floor     | 56 | ArgMax    | 57 | Sign               |
 | 58 | Reciprocal  | 59 | Size     | 60 | OneHot    | 61 | ReduceProd       |
-| 62 | LogSoftmax  | 63 | LSTM     |  |     |  |        |
+| 62 | LogSoftmax  | 63 | LSTM     | 64 |   LRN  |  |        |
 
 
 
@@ -99,7 +99,7 @@ Aten:
 | 101 | aten::upsample\_bilinear2d | 102 | aten::values |103|aten::view|104|aten::warn|
 | 105 | aten::where | 106 | aten::zeros |107|aten::zeros\_like|108|aten::bmm|
 | 109 | aten::sub\_ | 110 | aten:erf |111|aten::lstm|112|aten::gather|
-| 113 | aten::upsample\_nearest2d ||  |||||
+| 113 | aten::upsample\_nearest2d | 114 |aten::split\_with\_sizes  |||||
 
 Prim:
 | 序号 | OP | 序号 | OP | 序号 | OP | 序号 | OP |

docs/introduction/x2paddle_model_zoo.md

 # X2Paddle模型测试库
-> 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。
+> 目前X2Paddle支持80+的TensorFlow OP，30+的Caffe Layer，60+的ONNX OP，110+的PyTorch Aten，10+的PyTorch Prim，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：）
 

x2paddle/convert.py

@@ -229,6 +229,11 @@ def main():
     assert args.paddle_type in ["dygraph", "static"], "--paddle_type must be 'dygraph' or 'static'"
 
     try:
+        import platform
+        v0, v1, v2 = platform.python_version().split('.')
+        if not(int(v0) >= 3 and int(v1) >= 5):
+            print("[ERROR] python>=3.5 is required")
+            return
         import paddle
         v0, v1, v2 = paddle.__version__.split('.')
         print("paddle.__version__ = {}".format(paddle.__version__))

x2paddle/op_mapper/dygraph/onnx2paddle/onnx_custom_layer/__init__.py

@@ -18,3 +18,4 @@ from .pad_two_input import PadWithTwoInput
 from .pad_all_dim2 import PadAllDim2
 from .pad_all_dim4 import PadAllDim4
 from .pad_all_dim4_one_input import PadAllDim4WithOneInput
+from .lrn import LocalResponseNorm

x2paddle/op_mapper/dygraph/onnx2paddle/onnx_custom_layer/lrn.py

+# Copyright (c) 2020  PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License"
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import paddle
+
+class LocalResponseNorm(object):
+    def __init__(self, 
+                 size,
+                 alpha=1e-4,
+                 beta=0.75,
+                 k=1.):
+        self.size = size
+        self.alpha = alpha
+        self.beta = beta
+        self.k = k
+        
+    def __call__(self, x):
+        sizes = x.shape
+        dim = len(sizes)
+        if dim < 3:
+            raise ValueError(
+                'Expected 3D or higher dimensionality input, but got {} dimensions'.
+                format(dim))
+        div = paddle.unsqueeze(paddle.multiply(x, x), axis=1)
+        pad4d_shape = [self.size // 2, (self.size - 1) // 2, 0, 0]
+        pool2d_shape = (1, self.size)
+        pad5d_shape = [self.size // 2, (self.size - 1) // 2, 0, 0, 0, 0]
+        pool3d_shape = (1, 1, self.size)
+
+        if dim == 3:
+            div = paddle.nn.functional.pad(div, pad=pad4d_shape)
+            div = paddle.nn.functional.avg_pool2d(
+                div, kernel_size=pool2d_shape, stride=1)
+            div = paddle.squeeze(div, axis=1)
+        else:
+            tmp = paddle.unsqueeze(x, axis=1)
+            reshape_shape = paddle.shape(tmp)
+            new_reshape_shape = paddle.cast(reshape_shape, "float32")
+            index = paddle.full(shape=[1], fill_value=-2, dtype="int32")
+            value = paddle.full(shape=[1], fill_value=-1, dtype="float32")
+            new_reshape_shape = paddle.scatter(new_reshape_shape, index, value)
+            new_reshape_shape = paddle.cast(new_reshape_shape, "int32")
+            div = paddle.reshape(div, shape=reshape_shape)
+            div = paddle.nn.functional.pad(div,
+                                           pad=pad5d_shape,
+                                           data_format='NCDHW')
+            div = paddle.nn.functional.avg_pool3d(
+                div, kernel_size=pool3d_shape, stride=1)
+            div = paddle.reshape(paddle.squeeze(div, axis=1), sizes)
+
+        div = paddle.scale(div, scale=self.alpha, bias=self.k)
+        div = paddle.pow(div, self.beta)
+        res = paddle.divide(x, div)
+        return res
\ No newline at end of file

x2paddle/op_mapper/dygraph/onnx2paddle/opset9/opset.py

@@ -542,7 +542,6 @@ class OpSet9():
                         value=value,
                         mode=string(mode))
             else:
-                print(pads_len)
                 raise Exception("The padding value is wrong!")   
             if not op_independent:
                 return node.name + '_paded'
@@ -2013,3 +2012,25 @@ class OpSet9():
                     "k": val_k.name}, 
             outputs=["{}_p{}".format(node.layer_name, 0), "{}_p{}".format(node.layer_name, 1)],
             **layer_attrs)
+        
+    @print_mapping_info
+    def LRN(self, node):
+        op_name = name_generator("lrn", self.nn_name2id)
+        output_name = node.name
+        layer_outputs = [op_name, output_name]
+        val_x = self.graph.get_input_node(node, idx=0, copy=True)
+        alpha = node.get_attr('alpha', 0.0001)
+        beta = node.get_attr('beta', 0.75)
+        bias = node.get_attr('bias', 1.0)
+        size = node.get_attr('size')
+        layer_attrs = {
+            'size': size,
+            'alpha': alpha,
+            'beta': beta,
+            'k': bias
+        }
+        self.paddle_graph.add_layer(
+            "custom_layer:LocalResponseNorm", 
+            inputs={"x": val_x.name}, 
+            outputs=layer_outputs, 
+            **layer_attrs)

x2paddle/op_mapper/static/onnx2paddle/onnx_custom_layer/__init__.py

@@ -17,4 +17,5 @@ from .one_hot import one_hot
 from .pad_two_input import pad_with_two_input
 from .pad_all_dim2 import pad_all_dim2
 from .pad_all_dim4 import pad_all_dim4
-from .pad_all_dim4_one_input import pad_all_dim4_one_input
\ No newline at end of file
+from .pad_all_dim4_one_input import pad_all_dim4_one_input
+from .lrn import local_response_norm
\ No newline at end of file

x2paddle/op_mapper/static/onnx2paddle/onnx_custom_layer/lrn.py

+# Copyright (c) 2020  PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License"
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import paddle
+
+def local_response_norm(x, size, alpha=1e-4, beta=0.75, k=1.):
+    sizes = x.shape
+    dim = len(sizes)
+    if dim < 3:
+        raise ValueError(
+            'Expected 3D or higher dimensionality input, but got {} dimensions'.
+            format(dim))
+    div = paddle.unsqueeze(paddle.multiply(x, x), axis=1)
+    pad4d_shape = [size // 2, (size - 1) // 2, 0, 0]
+    pool2d_shape = (1, size)
+    pad5d_shape = [size // 2, (size - 1) // 2, 0, 0, 0, 0]
+    pool3d_shape = (1, 1, size)
+
+    if dim == 3:
+        div = paddle.nn.functional.pad(div, pad=pad4d_shape)
+        div = paddle.nn.functional.avg_pool2d(
+            div, kernel_size=pool2d_shape, stride=1)
+        div = paddle.squeeze(div, axis=1)
+    else:
+        tmp = paddle.unsqueeze(x, axis=1)
+        reshape_shape = paddle.shape(tmp)
+        new_reshape_shape = paddle.cast(reshape_shape, "float32")
+        index = paddle.full(shape=[1], fill_value=-2, dtype="int32")
+        value = paddle.full(shape=[1], fill_value=-1, dtype="float32")
+        new_reshape_shape = paddle.scatter(new_reshape_shape, index, value)
+        new_reshape_shape = paddle.cast(new_reshape_shape, "int32")
+        div = paddle.reshape(div, shape=reshape_shape)
+        div = paddle.nn.functional.pad(div,
+                                       pad=pad5d_shape,
+                                       data_format='NCDHW')
+        div = paddle.nn.functional.avg_pool3d(
+            div, kernel_size=pool3d_shape, stride=1)
+        div = paddle.reshape(paddle.squeeze(div, axis=1), sizes)
+
+    div = paddle.scale(div, scale=alpha, bias=k)
+    div = paddle.pow(div, beta)
+    res = paddle.divide(x, div)
+    return res
\ No newline at end of file

x2paddle/op_mapper/static/onnx2paddle/opset9/opset.py

@@ -1780,4 +1780,24 @@ class OpSet9():
             inputs={"x": val_x.name,
                     "k": val_k.name}, 
             outputs=["{}_p{}".format(node.layer_name, 0), "{}_p{}".format(node.layer_name, 1)],
-            **layer_attrs)
\ No newline at end of file
+            **layer_attrs)
+        
+    @print_mapping_info
+    def LRN(self, node):
+        val_x = self.graph.get_input_node(node, idx=0, copy=True)
+        val_x = self.graph.get_input_node(node, idx=0, copy=True)
+        alpha = node.get_attr('alpha', 0.0001)
+        beta = node.get_attr('beta', 0.75)
+        bias = node.get_attr('bias', 1.0)
+        size = node.get_attr('size')
+        layer_attrs = {
+            'size': size,
+            'alpha': alpha,
+            'beta': beta,
+            'k': bias
+        }
+        self.paddle_graph.add_layer(
+            "custom_layer:local_response_norm", 
+            inputs={"x": val_x.name}, 
+            outputs=[node.name], 
+            **layer_attrs)