Merge remote-tracking branch 'upstream/master'

README.md

@@ -8,6 +8,8 @@ X2Paddle支持将Caffe和TensorFlow模型转至PaddlePaddle模型，同时我们
 
 任何使用问题均可通过[ISSUE](https://github.com/PaddlePaddle/X2Paddle/issues)的方式及时反馈，或者也可直接通过pull request的方式一起更新代码和文档。
 
+> **目前X2Paddle主要支持CV部分模型，对于NLP模型暂未支持。**
+
 ## [caffe2fluid](caffe2fluid)
 1. 支持将Caffe模型转至PaddlePaddle fluid可加载预测模型
 2. 提供Caffe-PaddlePaddle常用API的对比文档[[doc](caffe2fluid/doc)]

caffe2fluid/README.md

@@ -69,7 +69,23 @@ bash tools/diff.sh alexnet ../../alexnet.prototxt \
 2. 添加`import mylayer`至`kaffe/custom_layers/__init__.py`
 
 3. 准备你的pycaffe作为你的定制版本（与以前的env准备相同）
-> 选择一：编译你自己的caffe.proto来代替proto/caffe.proto  
+> 选择一：
+1. 编译你自己的caffe.proto来代替proto/caffe.proto       
+2. 修改./kaffe/caffe/resolver.py
+```python
+try:
+    # Try to import PyCaffe first
+    import caffe
+    self.caffe = caffe
+except ImportError:
+    # Fall back to the protobuf implementation
+    self.caffepb = import_caffepb()
+    show_fallback_warning()
+# 将上述代码替换为下列代码：
+self.caffepb = import_caffepb()
+show_fallback_warning()
+```
+	 
 > 选择二：更换你的pycaffe到特定的版本
 
 4. 按照之前步骤，将Caffe模型转换为PaddlePaddle模型

caffe2fluid/README_en.md

@@ -72,7 +72,22 @@ In the model conversion, when encounter an unsupported custom layer, users can a
 2. Add ```import mylayer``` to  `kaffe/custom_layers/__init__.py`
 
 3. Prepare your pycaffe as your customized version(same as previous env prepare)
-    - (option1) replace `proto/caffe.proto` with your own caffe.proto and compile it
+    - (option1) 
+    1. replace `proto/caffe.proto` with your own caffe.proto and compile it
+    2. modify the ./kaffe/caffe/resolver.py
+```python
+try:
+    # Try to import PyCaffe first
+    import caffe
+    self.caffe = caffe
+except ImportError:
+    # Fall back to the protobuf implementation
+    self.caffepb = import_caffepb()
+    show_fallback_warning()
+# replace the above code with:
+self.caffepb = import_caffepb()
+show_fallback_warning()
+```
     - (option2) change your `pycaffe` to the customized version
 
 4. Convert the Caffe model to Fluid model

caffe2fluid/doc/Slice.md

@@ -51,8 +51,8 @@ layer {
     top: "out3"
     slice_param {
 	axis: 1    # 使用-1效果相同
-	alice_point: 1
-	alice_point: 2
+	slice_point: 1
+	slice_point: 2
     }
 }
 # 输出3个数组，第一个shape：(2,1)，第二个shape：(2,1)，第三个shape：(2,4)

caffe2fluid/examples/imagenet/infer.py

@@ -172,7 +172,7 @@ def load_model(exe, place, net_file, net_name, net_weight, debug):
 
 def get_shape(fluid, program, name):
     for var in program.list_vars():
-        if var.name == 'data':
+        if var.type == 'Input':
             return list(var.shape[1:])
 
     raise ValueError('not found shape for input layer[%s], '

caffe2fluid/examples/imagenet/tools/diff.sh

@@ -49,7 +49,7 @@ if [[ -z $PYTHON ]];then
     PYTHON=`which python`
 fi
 $PYTHON ../../convert.py \
-        $proto_file \
+        --npy_path $proto_file \
         --caffemodel $caffemodel_file \
         --data-output-path $weight_file\
         --code-output-path $net_file

caffe2fluid/kaffe/caffe/resolver.py

 import os
 import sys
+import subprocess
 
 SHARED_CAFFE_RESOLVER = None
 
@@ -9,6 +10,10 @@ def import_caffepb():
     p = os.path.dirname(p)
     p = os.path.join(p, '../../proto')
     sys.path.insert(0, p)
+    pb_version = subprocess.getstatusoutput('protoc --version')[1]
+    ver_str = pb_version.split(' ')[-1].replace('.', '')
+    ver_int = int(ver_str)
+    assert vaer_int >= 360, 'The version of protobuf must be larger than 3.6.0!'
     import caffe_pb2
     return caffe_pb2
 

caffe2fluid/kaffe/custom_layers/detection_out.py

@@ -49,13 +49,13 @@ def detectionoutput_layer(inputs,
     pbv = fluid.layers.reshape(x=pbv, shape=[-1, 4])
     mbox_loc = inputs[0]
     mbox_loc = fluid.layers.reshape(
-        x=mbox_loc, shape=[-1, mbox_conf_flatten.shape[1], 4])
+        x=mbox_loc, shape=[0, mbox_conf_flatten.shape[1], 4])
 
     default = {"nms_threshold": 0.3, "top_k": 10, "eta": 1.0}
     fields = ['eta', 'top_k', 'nms_threshold']
 
     for f in default.keys():
-        if not nms_param.has_key(f):
+        if f not in nms_param:
             nms_param[f] = default[f]
 
     nmsed_outs = fluid.layers.detection_output(

caffe2fluid/kaffe/custom_layers/flatten.py

@@ -2,7 +2,7 @@
     more info can be found here: http://caffe.berkeleyvision.org/tutorial/layers/flatten.html
 """
 from .register import register
-
+from functools import reduce
 
 def flatten_shape(input_shape, axis=1, end_axis=-1):
     """ calculate the output shape of this layer using input shape
@@ -29,6 +29,8 @@ def flatten_shape(input_shape, axis=1, end_axis=-1):
             % (start_axis, end_axis)
     output_shape = input_shape[0:start_axis]
     flat_sz = reduce(lambda a, b: a * b, input_shape[start_axis:end_axis])
+    if flat_sz < 0:
+        flat_sz = -1
     output_shape += [flat_sz]
     output_shape += input_shape[end_axis:-1]
 
@@ -52,9 +54,8 @@ def flatten_layer(input, name, axis=1, end_axis=-1):
     input_shape = list(input.shape)
 
     if input_shape[0] == -1:
-        input_shape[0] = 1
+        input_shape[0] = 0
         output_shape = flatten_shape(input_shape, axis=axis, end_axis=end_axis)
-        output_shape[0] = -1
     else:
         output_shape = flatten_shape(input_shape, axis=axis, end_axis=end_axis)
 

caffe2fluid/kaffe/custom_layers/reshape.py

@@ -2,6 +2,7 @@
     more info can be found here: http://caffe.berkeleyvision.org/tutorial/layers/reshape.html
 """
 from .register import register
+from functools import reduce
 
 
 def import_fluid():
@@ -61,43 +62,6 @@ def reshape_shape(input_sp, shape, axis=0, num_axes=-1):
     assert len(output_shape) == num_axes_retained + num_new_axes,\
             "[Reshape]invalid dims of output shape[%s]" % (str(output_shape))
 
-    inferred_axis = -1
-    copy_axes = []
-    constant_count = 1
-    for i in range(num_new_axes):
-        top_dim = shape['dim'][i]
-        if top_dim == 0:
-            copy_axes.append(i)
-            copy_axis_index = start_axis + i
-            output_shape[copy_axis_index] = input_shape[copy_axis_index]
-        elif top_dim == -1:
-            assert inferred_axis == -1, "[Reshape]new shape contains multiple -1 dims"
-            inferred_axis = i
-        else:
-            constant_count *= top_dim
-
-    if inferred_axis >= 0:
-        explicit_count = constant_count
-        l = input_shape[0:start_axis]
-        if len(l) > 0:
-            explicit_count *= count(l)
-
-        l = input_shape[end_axis:]
-        if len(l) > 0:
-            explicit_count *= count(l)
-
-        for i in range(len(copy_axes)):
-            explicit_count *= output_shape[start_axis + copy_axes[i]]
-
-        assert input_count % explicit_count == 0, "[Reshape]botom count[%d] "\
-                "must be divisible by product of the specified dimensions[%d] "\
-                % (input_count, explicit_count)
-        output_shape[start_axis + inferred_axis] = input_count / explicit_count
-
-    output_count = count(output_shape)
-    assert output_count == input_count, "[Reshape]output count[%d] must match input count[%d]" % (
-        output_count, input_count)
-
     return output_shape
 
 
@@ -115,19 +79,16 @@ def reshape_layer(input, name, shape, axis=0, num_axes=-1):
         output (variable): output variable for this layer
     """
     fluid = import_fluid()
-
     input_shape = list(input.shape)
-
     if input_shape[0] == -1:
-        input_shape[0] = 1
+        input_shape[0] = 0
         output_shape = reshape_shape(input_shape, shape, axis, num_axes)
-        output_shape[0] = -1
     else:
         output_shape = reshape_shape(input_shape, shape, axis, num_axes)
-
     output = fluid.layers.reshape(input, shape=output_shape, name=name)
 
     return output
 
 
 register(kind='Reshape', shape=reshape_shape, layer=reshape_layer)
+

caffe2fluid/kaffe/paddle/network.py

@@ -103,7 +103,7 @@ class Network(object):
                 place = self.paddle_env['place']
                 exe = self.paddle_env['exe']
 
-        data_dict = np.load(data_path).item()
+        data_dict = np.load(data_path, allow_pickle=True).item()
         for op_name in data_dict:
             if op_name == 'caffe2fluid_name_trace':
                 self.name_trace = data_dict[op_name]
@@ -441,7 +441,7 @@ class Network(object):
             need_transpose = True
 
         if need_transpose:
-            in_order = range(dims)
+            in_order = list(range(dims))
             in_order.remove(axis)
             in_order.append(axis)
             input = fluid.layers.transpose(

caffe2fluid/kaffe/shapes.py

@@ -3,6 +3,9 @@ from collections import namedtuple
 
 from .errors import KaffeError
 
+Tensor5DShape = namedtuple('Tensor5DShape',
+                           ['batch_size', 'data1', 'daat2', 'data3', 'data4'])
+
 Tensor4DShape = namedtuple('Tensor4DShape',
                            ['batch_size', 'channels', 'height', 'width'])
 

tensorflow2fluid/README.md

@@ -103,6 +103,8 @@ tensorflow2fluid在如下tensorflow模型上测试了模型转换前后的diff
 |          | ResNet V1 50  | [code](https://github.com/tensorflow/models/blob/master/research/slim/nets/resnet_v1.py) | 1.31E-06 |
 |          | ResNet V1 101 | [code](https://github.com/tensorflow/models/blob/master/research/slim/nets/resnet_v1.py) | 4.74E-07 |
 |          | Inception V3  | [code](https://github.com/tensorflow/models/blob/master/research/slim/nets/inception_v3.py) | 1.55E-04 |
+|         | NASNet_Large | [code](https://github.com/tensorflow/models/blob/master/research/slim/nets/nasnet/nasnet.py) | - |
+|         | PNASNet_Large | [code](https://github.com/tensorflow/models/blob/master/research/slim/nets/nasnet/pnasnet.py) | - |
 | 目标检测 | YOLO-Small    | [code](https://github.com/gliese581gg/YOLO_tensorflow) | 1.40E-06 |
 |          | YOLO-V3       | [code](https://github.com/mystic123/tensorflow-yolo-v3) | 6.20E-04 |
 | 语义分割 | Unet          | [code](https://github.com/jakeret/tf_unet) | 4.17E-07 |

tensorflow2fluid/doc/compare_op.md

@@ -4,8 +4,8 @@
 
 | TensorFlow接口 | PaddlePaddle接口 |
 |--------------------------|-------------------------------------------------|
-|[tf.math.less_equal](https://www.tensorflow.org/api_docs/python/tf/math/less_equal)|运算符`<=`|
-|[tf.math.greater](https://www.tensorflow.org/api_docs/python/tf/math/greater)|运算符`>`|
-|[tf.math.greater_equal](https://www.tensorflow.org/api_docs/python/tf/math/greater_equal)|运算符`>=`|
-|[tf.math.equal](https://www.tensorflow.org/api_docs/python/tf/math/equal)|运算符`==` 或 [paddle.fluid.layers.equal](http://paddlepaddle.org/documentation/docs/zh/1.3/api_cn/layers_cn.html#permalink-7-equal) |
-|[tf.math.less](https://www.tensorflow.org/api_docs/python/tf/math/less)|运算符`<` 或 [paddle.fluid.layers.less_than](http://paddlepaddle.org/documentation/docs/zh/1.3/api_cn/layers_cn.html#permalink-11-less_than) |
+|[tf.math.less_equal](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/math/less_equal)|运算符`<=`|
+|[tf.math.greater](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/math/greater)|运算符`>`|
+|[tf.math.greater_equal](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/math/greater_equal)|运算符`>=`|
+|[tf.math.equal](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/math/equal)|运算符`==` 或 [paddle.fluid.layers.equal](http://paddlepaddle.org/documentation/docs/zh/1.3/api_cn/layers_cn.html#permalink-7-equal) |
+|[tf.math.less](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/math/less)|运算符`<` 或 [paddle.fluid.layers.less_than](http://paddlepaddle.org/documentation/docs/zh/1.3/api_cn/layers_cn.html#permalink-11-less_than) |
\ No newline at end of file

tensorflow2fluid/doc/tf.case.md

 ## tf.case
 
-### [tf.case](https://www.tensorflow.org/api_docs/python/tf/case)
+### [tf.case](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/case)
 
 ```python
 tf.case(
@@ -52,4 +52,4 @@ with fluid.layers.control_flow.Switch() as switch:
     with switch.default():
         fluid.layers.tensor.assign(input=lr_0, output=lr)
 
-```
+```
\ No newline at end of file

tensorflow2fluid/doc/tf.clip_by_global_norm.md

 ## tf.clip_by_global_norm
 
-### [tf.clip_by_global_norm](https://www.tensorflow.org/api_docs/python/tf/clip_by_global_norm)
+### [tf.clip_by_global_norm](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/clip_by_global_norm)
 
 ```python
 tf.clip_by_global_norm(
@@ -46,4 +46,4 @@ with fluid.program_guard(main_program=prog_clip):
     # 执行裁剪并获取结果
     p_g_clip = fluid.clip.append_gradient_clip_ops(p_g_clip)
 
-```
+```
\ No newline at end of file

tensorflow2fluid/doc/tf.clip_by_norm.md

 ## tf.clip_by_norm
 
-### [tf.clip_by_norm](https://www.tensorflow.org/api_docs/python/tf/clip_by_norm)
+### [tf.clip_by_norm](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/clip_by_norm)
 
 ``` python
 tf.clip_by_norm(
@@ -24,4 +24,4 @@ paddle.fluid.layers.clip_by_norm(
 
 #### 计算方式
 TensorFlow: 使用参数`axis`指定的轴计算L2范数`l2-norm`，如若`axis`为None，则表示使用整个输入数据的L2范数；  
-PaddlePaddle：使用整个输入数据的L2范数。
+PaddlePaddle：使用整个输入数据的L2范数。
\ No newline at end of file

tensorflow2fluid/doc/tf.contrib.layers.flatten.md

 ## tf.contrib.layers.flatten
 
-### [tf.contrib.layers.flatten](https://www.tensorflow.org/api_docs/python/tf/contrib/layers/flatten)
+### [tf.contrib.layers.flatten](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/contrib/layers/flatten)
 
 ```python
 tf.contrib.layers.flatten(
@@ -34,4 +34,4 @@ PaddlePaddle：使用`axis`指定两次合并的维度边界，参考下面示
 out = fluid.layers.flatten(x, axis=2)
 out.shape # [2*3, 4*5]
 
-```
+```
\ No newline at end of file

tensorflow2fluid/doc/tf.expand_dims.md

-
 ## tf.expand_dims
 
-### [tf.expand_dims](https://www.tensorflow.org/api_docs/python/tf/expand_dims)
+### [tf.expand_dims](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/math/expand_dims)
 ``` python
 tf.expand_dims(
     input,
@@ -39,5 +38,4 @@ out = fluid.layers.unsqueeze(t, [-1])
 
 # 输出 tensor out 的 shape 为[1, 1，3, 4]
 out = fluid.layers.unsqueeze(t, [0, 1])  
-```
-
+```
\ No newline at end of file

tensorflow2fluid/doc/tf.image.non_max_suppression.md

-
 ## tf.image.non_max_suppression
 
-### [tf.image.non_max_suppression](https://www.tensorflow.org/api_docs/python/tf/image/non_max_suppression)
+### [tf.image.non_max_suppression](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/image/non_max_suppression)
 ``` python
 tf.image.non_max_suppression(
     boxes,
@@ -54,4 +53,4 @@ selected_boxes = fluid.layers.multiclass_nms(
             nms_top_k=-1, 
             keep_top_k=300,
             nms_threshold=0.7)
-```
+```
\ No newline at end of file

tensorflow2fluid/doc/tf.image.resize_images.md

-
 ## tf.image.resize_images
 
-### [tf.image.resize_images](https://www.tensorflow.org/api_docs/python/tf/image/resize_images)
+### [tf.image.resize_images](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/image/resize_images)
 ``` python
 tf.image.resize_images(
     images,
@@ -38,5 +37,4 @@ inputs = fluid.layers.data(dtype='float32', shape=[3, 300, 300], name='inputs')
 
 # 输出shape为[3, 400, 500]
 outputs = fluid.layers.image_reisze(inputs, [400, 500])
-```
-
+```
\ No newline at end of file

tensorflow2fluid/doc/tf.layers.conv2d.md

-
 ## tf.layers.conv2d
 
-### [tf.layers.conv2d](https://www.tensorflow.org/api_docs/python/tf/layers/conv2d)
+### [tf.layers.conv2d](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/layers/conv2d)
 ``` python
 tf.layers.conv2d(
     inputs,
@@ -73,7 +72,7 @@ pad_right = pad_size - pad_left
 PaddlePaddle：`padding`参数表示在输入图像四周padding的size大小。
 
 #### 参数差异
-TensorFlow：深度可分离卷积使用[tf.layers.separable_conv2d](https://www.tensorflow.org/api_docs/python/tf/layers/separable_conv2d)接口;  
+TensorFlow：深度可分离卷积使用[tf.layers.separable_conv2d](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/layers/separable_conv2d)接口;  
 PaddlePaddle: 使用`paddle.fluid.layers.conv2d`，可参考
 [PaddlePaddle对卷积的说明文档](http://paddlepaddle.org/documentation/docs/zh/1.4/api_guides/low_level/layers/conv.html), 同时也可参考[tf.nn.separable_conv2d](https://github.com/PaddlePaddle/X2Paddle/blob/master/tensorflow2fluid/doc/tf.nn.separable_conv2d.md)中的代码示例。
 
@@ -85,4 +84,4 @@ PaddlePaddle: 使用`paddle.fluid.layers.conv2d`，可参考
 # 卷积核Shape: (5, 3, 4, 4)
 inputs = paddle.fluid.layers.data(dtype='float32', shape=[3, 200, 200], name='inputs)
 pad_inputs = paddle.fluid.layers.pad2d(inputs, paddings=[1, 2, 1, 2])
-outputs = paddle.fluid.layers.conv2d(pad_inputs, 5, [4, 4], (1, 1))
+outputs = paddle.fluid.layers.conv2d(pad_inputs, 5, [4, 4], (1, 1))
\ No newline at end of file

tensorflow2fluid/doc/tf.layers.dense.md

-
 ## tf.layers.dense
 
-### [tf.layers.dense](https://www.tensorflow.org/api_docs/python/tf/layers/dense)
+### [tf.layers.dense](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/layers/dense)
 ``` python
 tf.layers.dense(
     inputs,
@@ -63,4 +62,4 @@ out = fluid.layers.fc(t, size=6, \
 # size=6, num_flatten_dims=2，输出tensor的shape为[2, 3, 6]
 out = fluid.layers.fc(t, size=6, num_flatten_dims=2)
 
-```
+```
\ No newline at end of file

tensorflow2fluid/doc/tf.losses.mean_and_squared_error.md

 ## tf.losses.mean_and_squared_error
 
-### [tf.losses.mean_and_squared_error](https://www.tensorflow.org/api_docs/python/tf/losses/mean_squared_error)
+### [tf.losses.mean_and_squared_error](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/losses/mean_squared_error)
 
 ``` python
 tf.losses.mean_squared_error(
@@ -25,4 +25,4 @@ paddle.fluid.layers.square_error_cost(
 
 #### 计算方式
 TensorFlow: 提供`weights`参数，通过传入`weights`参数的shape，可实现不同的加权方式；  
-PaddlePaddle：不支持加权。
+PaddlePaddle：不支持加权。
\ No newline at end of file

tensorflow2fluid/doc/tf.losses.sigmoid_cross_entropy.md

 ## tf.losses.sigmoid_cross_entropy
 
-### [tf.losses.sigmoid_cross_entropy](https://www.tensorflow.org/api_docs/python/tf/losses/sigmoid_cross_entropy)
+### [tf.losses.sigmoid_cross_entropy](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/losses/sigmoid_cross_entropy)
 
 ```python
 tf.losses.sigmoid_cross_entropy(
@@ -53,4 +53,4 @@ PaddlePaddle：通过设置`normalize`，各样本损失函数会除以除去`ig
 out = fluid.layers.sigmoid_cross_entropy_with_logits(x, label)
 
 
-```
+```
\ No newline at end of file

tensorflow2fluid/doc/tf.math.is_finite.md

-
 ## tf.math.is_finite
 
-### [tf.math.is_finite](https://www.tensorflow.org/api_docs/python/tf/math/is_finite)
+### [tf.math.is_finite](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/math/is_finite)
 ``` python
 tf.math.is_finite(
     x,
@@ -31,4 +30,4 @@ result = tf.is_finite(inputs)
 # 输入[2.1, 3.2, 4.5]
 # 输出True
 result = fluid.layers.isfinite(inputs)
-```
+```
\ No newline at end of file

tensorflow2fluid/doc/tf.math.rsqrt.md

 ## tf.math.rsqrt
 
-### [tf.math.rsqrt](https://www.tensorflow.org/api_docs/python/tf/math/rsqrt)
+### [tf.math.rsqrt](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/math/rsqrt)
 ``` python
 tf.math.rsqrt(
     x,
@@ -23,4 +23,4 @@ inputs = fluid.layers.data(dtype='float32', shape=[1000], name='inputs')
 
 # 调用上述自定义函数
 result = rsqrt(inputs)
-```
+```
\ No newline at end of file

tensorflow2fluid/doc/tf.matmul.md

-
 ## tf.matmul
 
-### [tf.matmul](https://www.tensorflow.org/api_docs/python/tf/linalg/matmul)
+### [tf.matmul](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/linalg/matmul)
 ``` python
 tf.matmul(
     a,
@@ -60,4 +59,4 @@ fluid.layers.matmul(x, y)  # out: [1]
 
 # x: [M], y: [N]
 fluid.layers.matmul(x, y, True, True)  # out: [M, N]
-```
+```
\ No newline at end of file

tensorflow2fluid/doc/tf.nn.avg_pool.md

 ## tf.nn.avg_pool
 
-### [tf.nn.avg_pool](https://www.tensorflow.org/versions/r1.10/api_docs/python/tf/nn/avg_pool)
+### [tf.nn.avg_pool](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/nn/avg_pool)
 
 ``` python
 tf.nn.avg_pool(

tensorflow2fluid/doc/tf.nn.bidirectional_dynamic_rnn.md

 ## tf.nn.bidirectional_dynamic_rnn
 
 
-### [tf.nn.bidirectional_dynamic_rnn](https://www.tensorflow.org/api_docs/python/tf/nn/bidirectional_dynamic_rnn)
+### [tf.nn.bidirectional_dynamic_rnn](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/nn/bidirectional_dynamic_rnn)
 
 ```python
 tf.nn.bidirectional_dynamic_rnn(
@@ -71,4 +71,4 @@ rev_rev_out = fluid.layers.sequence_reverse(rev_out)
 # 合并得到最后的输出，其shape为(-1, 32)
 concat_out = layers.concat([out, rev_rev_out], axis=1)                                               
 
-```
+```
\ No newline at end of file

tensorflow2fluid/doc/tf.nn.conv2d.md

 ## tf.nn.conv2d
 
-### [tf.nn.conv2d](https://www.tensorflow.org/api_docs/python/tf/nn/conv2d)
+### [tf.nn.conv2d](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/nn/conv2d)
 
 ```python
 tf.nn.conv2d(
@@ -48,4 +48,4 @@ create_kernel = fluid.layers.create_parameters(shape=[5, 3, 2, 2], dtype='float3
 # PaddlePaddle中可通过相同的参数命名引用同一个参数变量
 # 通过指定卷积核参数名(param_attr)为'kernel'，引用了create_kernel
 result = fluid.layers.conv2d(inputs, 5, [2, 2], param_attr='kernel')
-```
+```
\ No newline at end of file

tensorflow2fluid/doc/tf.nn.conv2d_transpose.md

-
 ## tf.nn.conv2d_transpose
 
-### [tf.nn.conv2d_transpose](https://www.tensorflow.org/api_docs/python/tf/nn/conv2d_transpose)
+### [tf.nn.conv2d_transpose](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/nn/conv2d_transpose)
 ``` python
 tf.nn.conv2d_transpose(
     value,
@@ -93,4 +92,4 @@ inputs = fluid.layers.data(dtype='float32', shape=[3, 20, 20], name='inputs)
 outputs = fluid.layers.conv2d_transpose(pad_inputs, 3, filter_size=[5, 5], 
                         padding=[1, 1],  stride=[2, 2], bias_attr=False)
 # 裁剪后结果即为与TensorFlow一致
-outputs = fluid.layers.crop(outputs, shape=[-1, 3, 40, 40])
+outputs = fluid.layers.crop(outputs, shape=[-1, 3, 40, 40])
\ No newline at end of file

tensorflow2fluid/doc/tf.nn.conv3d_transpose.md

-
 ## tf.nn.conv3d_transpose
 
-### [tf.nn.conv3d_transpose](https://www.tensorflow.org/api_docs/python/tf/nn/conv3d_transpose)
+### [tf.nn.conv3d_transpose](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/nn/conv3d_transpose)
 ``` python
 tf.nn.conv3d_transpose(
     value,
@@ -93,4 +92,4 @@ inputs = fluid.layers.data(dtype='float32', shape=[3, 5, 20, 40], name='inputs)
 outputs = fluid.layers.conv3d(inputs, 7, filter_size=(2, 4, 5), stride=(1, 2, 2), 
                         padding=(0, 1, 1), bias_attr=False)
 # 裁剪后结果即为与TensorFlow一致
-outputs = fluid.layers.crop(outputs, shape=[-1, 7, 5, 40, 80])
+outputs = fluid.layers.crop(outputs, shape=[-1, 7, 5, 40, 80])
\ No newline at end of file

tensorflow2fluid/doc/tf.nn.depthwise_conv2d.md

 ## tf.nn.depthwise_conv2d
 
-### [tf.nn.depthwise_conv2d](https://www.tensorflow.org/api_docs/python/tf/nn/depthwise_conv2d)
+### [tf.nn.depthwise_conv2d](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/nn/depthwise_conv2d)
 
 ```python
 tf.nn.depthwise_conv2d(
@@ -84,4 +84,4 @@ inputs = fluid.layers.data(dtype='float32', shape=[3, 20, 20], name='inputs')
 inputs = fluid.layers.pad2d(inputs, paddings=[1, 2, 1, 2])
 #输出shape:[-1, 3, 20, 20]
 result = fluid.layers.conv2d(inputs, 3, filter_size=[4, 4], groups=3, bias_attr=False)
-```
+```
\ No newline at end of file

tensorflow2fluid/doc/tf.nn.dropout.md

-
 ## tf.dropout
 
-### [tf.nn.dropout](https://www.tensorflow.org/api_docs/python/tf/nn/dropout)
+### [tf.nn.dropout](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/nn/dropout)
 ``` python
 tf.nn.dropout(
     x,
@@ -47,4 +46,4 @@ out = fluid.layers.dropout(t, dropout_prob=0.2, dropout_implementation="upscale_
 
 # inference 时关闭dropout
 inference_program = fluid.default_main_program().clone(for_test=True)
-```
+```
\ No newline at end of file

tensorflow2fluid/doc/tf.nn.dynamic_rnn.md

 ## tf.nn.dynamic_rnn
 
-### [tf.nn.dynamic_rnn](https://www.tensorflow.org/api_docs/python/tf/nn/dynamic_rnn)
+### [tf.nn.dynamic_rnn](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/nn/dynamic_rnn)
 ``` python
 tf.nn.dynamic_rnn(
     cell,
@@ -75,4 +75,4 @@ state = fluid.layers.sequence_last_step(outputs)
 
 为了简化用户定义动态RNN的过程，paddle有如下op可供选择：
 - [paddle.fluid.layers.dynamic_lstm](http://www.paddlepaddle.org/documentation/docs/zh/1.4/api_cn/layers_cn.html#dynamic-lstm)：相当于  `tf.nn.dynamic_rnn`结合`tf.nn.rnn_cell.LSTMCell`
-- [paddle.fluid.layers.dynamic_gru](http://www.paddlepaddle.org/documentation/docs/zh/1.4/api_cn/layers_cn.html#dynamic-gru)：相当于`tf.nn.dynamic_rnn`结合`tf.nn.rnn_cell.GRUCell`
+- [paddle.fluid.layers.dynamic_gru](http://www.paddlepaddle.org/documentation/docs/zh/1.4/api_cn/layers_cn.html#dynamic-gru)：相当于`tf.nn.dynamic_rnn`结合`tf.nn.rnn_cell.GRUCell`
\ No newline at end of file

tensorflow2fluid/doc/tf.nn.l2_normalize.md

-
 ## tf.nn.l2_normalize
 
-### [tf.nn.l2_normalize](https://www.tensorflow.org/api_docs/python/tf/math/l2_normalize)
+### [tf.nn.l2_normalize](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/math/l2_normalize)
 
 ```python
 tf.math.l2_normalize(
@@ -38,4 +37,4 @@ PaddlePaddle：计算方式为`output = x / sqrt(sum(x^2) + epsilon))`。
 
 # out同样是shape[3,2]的张量，axis设置为1，表示将x中每个行向量做归一化
 out = fluid.layers.l2_normalize(x, axis=1)
-```
+```
\ No newline at end of file

tensorflow2fluid/doc/tf.nn.lrn.md

-
 ## tf.nn.lrn
 
-### [tf.nn.lrn](https://www.tensorflow.org/api_docs/python/tf/nn/local_response_normalization)
+### [tf.nn.lrn](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/nn/local_response_normalization)
 
 ```python
 tf.nn.local_response_normalization(
@@ -38,4 +37,4 @@ $$output(i,x,y)=input(i,x,y)/(k+\alpha\sum_{j=max(0,i-\frac{n}{2})}^{min(C,i+\fr
 
 #### 输入格式
 TensorFlow: 默认输入`NHWC`格式数据；  
-PaddlePaddle: 默认输入`NCHW`格式数据，
+PaddlePaddle: 默认输入`NCHW`格式数据，
\ No newline at end of file

tensorflow2fluid/doc/tf.nn.max_pool.md

 ## tf.nn.max_pool
 
-### [tf.nn.max_pool](https://www.tensorflow.org/api_docs/python/tf/nn/max_pool)
+### [tf.nn.max_pool](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/nn/max_pool)
 
 ``` python
 tf.nn.max_pool(
@@ -51,4 +51,4 @@ inputs = fluid.layers.data(dtype='float32', shape=[3, 300, 300], name='inputs')
 # 在最右、最下进行padding
 pad_res = fluid.layers.pad2d(inputs, padding=[0, 1, 0, 1])
 conv_res = fluid.layers.pool2d(pad_res, pool_size=3, pool_type='max', pool_stride=2)
-```
+```
\ No newline at end of file

tensorflow2fluid/doc/tf.nn.reduce_logsumexp.md

 ## tf.math.reduce_logsumexp
 
-### [tf.math.reduce_logsumexp](https://www.tensorflow.org/api_docs/python/tf/math/reduce_logsumexp)
+### [tf.math.reduce_logsumexp](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/math/reduce_logsumexp)
 ``` python
 tf.math.log_softmax(
     logits,
@@ -26,4 +26,4 @@ inputs = fluid.layers.data(dtype='float32', shape=[1000], name='inputs')
 
 # 调用上述自定义函数
 result = reduce_logsumexp(inputs)
-```
+```
\ No newline at end of file

tensorflow2fluid/doc/tf.contrib.rnn.GRUCell.md → tensorflow2fluid/doc/tf.nn.rnn.GRUCell.md

 ## tf.contrib.rnn.GRUCell
 
-### [tf.contrib.rnn.GRUCell](https://www.tensorflow.org/api_docs/python/tf/nn/rnn_cell/GRUCell)
+### [tf.nn.rnn.GRUCell](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/nn/rnn_cell/GRUCell)
 
 ```python
-tf.contrib.rnn.GRUCell(
+__init__(
     num_units,
     activation=None,
     reuse=None,
@@ -13,7 +13,6 @@ tf.contrib.rnn.GRUCell(
     dtype=None,
     **kwargs
 )
-
 ```
 
 ### [paddle.fluid.layers.gru_unit](http://paddlepaddle.org/documentation/docs/zh/1.4/api_cn/layers_cn.html#gru-unit)

tensorflow2fluid/doc/tf.nn.rnn_cell.LSTMCell.md

 ## tf.nn.rnn_cell.LSTMCell
 
-### [tf.nn.rnn_cell.LSTMCell](https://www.tensorflow.org/api_docs/python/tf/nn/rnn_cell/LSTMCell)
+### [tf.nn.rnn_cell.LSTMCell](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/nn/rnn_cell/LSTMCell)
 
 ```python
 tf.nn.rnn_cell.LSTMCell(
@@ -85,4 +85,4 @@ out = drnn()
 # 获取最后时刻的输出
 last = fluid.layers.sequence_last(out)                                                  
 
-```
+```
\ No newline at end of file

tensorflow2fluid/doc/tf.nn.rnn_cell.MultiRNNCell.md

 ## tf.nn.rnn_cell.MultiRNNCell
 
-### [tf.nn.rnn_cell.MultiRNNCell](https://www.tensorflow.org/api_docs/python/tf/nn/rnn_cell/MultiRNNCell)
+### [tf.nn.rnn_cell.MultiRNNCell](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/nn/rnn_cell/MultiRNNCell)
 
 ```python
-tf.nn.rnn_cell.MultiRNNCell(
+__init__(
     cells,
     state_is_tuple=True
 )

tensorflow2fluid/doc/tf.nn.separable_conv2d.md

 ## tf.nn.separable_conv2d
 
-### [tf.nn.separable_conv2d](https://www.tensorflow.org/api_docs/python/tf/nn/separable_conv2d)
+### [tf.nn.separable_conv2d](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/nn/separable_conv2d)
 ``` python
 tf.nn.separable_conv2d(
     input,
@@ -30,4 +30,4 @@ depthwise_result = fluid.layers.conv2d(input, 3, filter_size=[4, 4],
 pointwise_result = fluid.layers.conv2d(depthwise_result, filter_size=[1, 1], 
                                 stride=[1, 1], bias_attr=False)
 
-```
+```
\ No newline at end of file

tensorflow2fluid/doc/tf.nn.softmax_cross_entropy_with_logits.md

 ## tf.nn.softmax_cross_entropy_with_logits
 
-### [tf.nn.rnn_cell.MultiRNNCell](https://www.tensorflow.org/api_docs/python/tf/nn/softmax_cross_entropy_with_logits)
+### [tf.nn.rnn_cell.MultiRNNCell](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/nn/softmax_cross_entropy_with_logits)
 
 ```python
 tf.nn.softmax_cross_entropy_with_logits(
@@ -20,7 +20,8 @@ paddle.fluid.layers.softmax_with_cross_entropy(
     soft_label=False, 
     ignore_index=-100, 
     numeric_stable_mode=False, 
-    return_softmax=False
+    return_softmax=False,
+    axis=-1
 )
 ```
 

tensorflow2fluid/doc/tf.nn.top_k.md

-
 ## tf.nn.top_k
 
-### [tf.nn.top_k](https://www.tensorflow.org/api_docs/python/tf/nn/top_k)
+### [tf.nn.top_k](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/nn/top_k)
 ``` python
 tf.math.top_k(
     input,
@@ -32,4 +31,4 @@ PaddlePaddle: 对返回的top-k tensor进行降序排序；`k`没有默认值，
 # 当k=2时，输出 tensor out 为[[6,3], [8,3]]，index为[[1,2],[2,0]]
 out, index = fluid.layers.topk(t, k=1)
 
-```
+```
\ No newline at end of file

tensorflow2fluid/doc/tf.one_hot.md

-
 ## tf.one_hot
 
-### [tf.one_hot](https://www.tensorflow.org/api_docs/python/tf/one_hot)
+### [tf.one_hot](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/one_hot)
 ``` python
 tf.one_hot(
     indices,
@@ -38,4 +37,4 @@ PaddlePaddle：无对应配置选项，即为默认的`1`和`0`。
 
 # depth 为3时，输出 tensor out 为[[0, 1, 0], [0, 0, 1]]
 out = fluid.layers.one_hot(t, 3)
-```
+```
\ No newline at end of file

tensorflow2fluid/doc/tf.pad.md

-
 ## tf.pad
 
-### [tf.pad](https://www.tensorflow.org/api_docs/python/tf/pad)
+### [tf.pad](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/pad)
 ``` python
 tf.pad(
     tensor,
@@ -34,4 +33,4 @@ PaddlePaddle：目前仅支持采用常量进行padding；指定padding长度时
 
 # 第0维前面padding长度为0，后面padding长度为1；第1维前面padding长度为1，后面padding长度为2
 out = fluid.layers.pad(t, paddings=[0,1,1,2])  
-```
+```
\ No newline at end of file

tensorflow2fluid/doc/tf.placeholder.md

-
 ## tf.placeholder
 
-### [tf.placeholder](https://www.tensorflow.org/api_docs/python/tf/placeholder)
+### [tf.placeholder](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/placeholder)
 ``` python
 tf.placeholder(
     dtype,
@@ -36,4 +35,4 @@ out = fluid.layers.data('out', shape=[3, 4], dtype='float32')
 
 # 创建输入型tensor out，其shape为[3, -1, 4], 数据类型为float32
 out = fluid.layers.data('out', shape=[3, -1, 4], append_batch_size=False, dtype='float32')
-```
+```
\ No newline at end of file

tensorflow2fluid/doc/tf.pow.md

 ## tf.pow
 
-### [tf.pow](https://www.tensorflow.org/api_docs/python/tf/math/pow)
+### [tf.pow](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/math/pow)
 
 ```python
 tf.math.pow(
@@ -33,4 +33,4 @@ PaddlePaddle：`x`为tensor，`factor`为浮点数，返回值为`x`每个元素
 # x为张量 [2, 3]
 out = fluid.layers.pow(x, 2.0) # [4，9]
 
-```
+```
\ No newline at end of file

tensorflow2fluid/doc/tf.print.md

 ## tf.print
 
-### [tf.print](https://www.tensorflow.org/api_docs/python/tf/print)
+### [tf.print](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/print)
 
 ```python
 tf.print(
@@ -47,4 +47,4 @@ PaddlePaddle：通过设置`print_phase`，可以控制是否打印`input`的梯
 
 # 打印input的内容，如果有梯度的话也将打印梯度
 print(input, message="content of input")
-```
+```
\ No newline at end of file

tensorflow2fluid/doc/tf.reshape.md

-
 ## tf.reshape
 
-### [tf.reshape](https://www.tensorflow.org/api_docs/python/tf/reshape)
+### [tf.reshape](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/reshape)
 ``` python
 tf.reshape(
     tensor,
@@ -37,5 +36,4 @@ out = fluid.layers.reshape(t, [-1, 6])
 
 # 输出 tensor out 的 shape 为[3, 2, 2]
 out = fluid.layers.reshape(t, [0, 2, 2])
-```
-
+```
\ No newline at end of file

tensorflow2fluid/doc/tf.reverse_sequence.md

 ## tf.reverse_sequence
 
-### [tf.reverse_sequence](https://www.tensorflow.org/api_docs/python/tf/reverse_sequence)
+### [tf.reverse_sequence](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/reverse_sequence)
 
 ```python
 tf.reverse_sequence(
@@ -44,4 +44,4 @@ PaddlePaddle：由于`LoDTensor`本身已经携带序列信息，因而不需要
 # out[0:2, 6] = x[2:0:-1, 6]
 # out[2:5, 6] = x[5:2:-1, 6]
 out = fluid.layers.sequence_reverse(x)
-```
+```
\ No newline at end of file

tensorflow2fluid/doc/tf.scatter_update.md

 ## tf.scatter_update
 
-### [tf.scatter_update](https://www.tensorflow.org/api_docs/python/tf/scatter_update)
+### [tf.scatter_update](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/scatter_update)
 
 ```python
 tf.scatter_update(
@@ -19,7 +19,8 @@ paddle.fluid.layers.scatter(
     input, 
     index, 
     updates, 
-    name=None
+    name=None,
+    overwrite=True
 )
 ```
 
@@ -32,7 +33,7 @@ PaddlePaddle：`index`只支持1-d Variable。
 
 #### 其他
 Tensorflow：`updates`支持numpy-style broadcasting;  
-PaddlePaddle：`updates`要求其rank与`input`相同，同时`updates.shape[0]`等于`index.shape[0]`。
+PaddlePaddle：`updates`要求其rank与`input`相同，同时`updates.shape[0]`等于`index.shape[0]`。此外`overwrite`参数提供了当存在重复index时，两种不同的梯度更新策略。
 
 ### 代码示例
 ```

tensorflow2fluid/doc/tf.slice.md

-
 ## tf.slice
 
-### [tf.slice](https://www.tensorflow.org/api_docs/python/tf/slice)
+### [tf.slice](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/slice)
 ``` python
 tf.slice(
     input_,
@@ -40,4 +39,4 @@ out = fluid.layers.slice(t, axes=[0,1], starts=[0,1], ends=[2,3])
 
 # 输出 tensor out 为[[1,2],[5,6],[9,10]]
 out = fluid.layers.slice(t, axes=[1], starts=[1], ends=[3])
-```
+```
\ No newline at end of file

tensorflow2fluid/doc/tf.split.md

 ## tf.split
 
-### [tf.split](https://www.tensorflow.org/api_docs/python/tf/split)
+### [tf.split](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/split)
 
 ```python
 tf.split(
@@ -39,4 +39,4 @@ x0.shape  # [3, 3, 5]
 x1.shape  # [3, 3, 5]
 x2.shape  # [3, 3, 5]
 
-```
+```
\ No newline at end of file

tensorflow2fluid/doc/tf.squared_difference.md

 ## tf.squared_difference
 
-### [tf.squared_diffenrece](https://www.tensorflow.org/api_docs/python/tf/math/squared_difference)
+### [tf.squared_diffenrece](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/math/squared_difference)
 ``` python
 tf.math.squared_difference(
     x,
@@ -24,4 +24,4 @@ input_x = fluid.layers.data(dtype='float32', shape=[1000], name='input_x')
 input_y = fluid.layers.data(dtype='float32', shape=[1000], name='input_y')
 # 调用上述自定义函数
 result = squared_difference(input_x, input_y)
-```
+```
\ No newline at end of file

tensorflow2fluid/doc/tf.stop_gradient.md

-
 ## tf.stop_gradient
 
-### [tf.stop_gradient](https://www.tensorflow.org/api_docs/python/tf/stop_gradient)
+### [tf.stop_gradient](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/stop_gradient)
 ``` python
 tf.stop_gradient(
     input,
@@ -15,4 +14,4 @@ TensorFlow中，使用`stop_gradient`表示该tensor不需要进行bp。而在Pa
 ## 代码示例
 ```python
 # 将tensor t设置成不需要bp
-t.stop_gradient = True
+t.stop_gradient = True
\ No newline at end of file

tensorflow2fluid/doc/tf.while_loop.md

 ## tf.while_loop
 
-### [tf.while_loop](https://www.tensorflow.org/api_docs/python/tf/while_loop)
+### [tf.while_loop](https://www.tensorflow.org/versions/r1.13/api_docs/python/tf/while_loop)
 
 ```python
 tf.while_loop(
@@ -53,4 +53,4 @@ with while_op.block():
     i = layers.increment(x=i, in_place=True)
     # 更新条件状态
     layers.less_than(x=i, y=limit, cond=cond)
-```
+```
\ No newline at end of file