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体验新版 GitCode,发现更多精彩内容 >>
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d91060d3
编写于
6月 15, 2018
作者:
F
fengjiayi
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电子邮件补丁
差异文件
fix errors
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a6e69d3c
变更
4
隐藏空白更改
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并排
Showing
4 changed file
with
10 addition
and
9 deletion
+10
-9
paddle/fluid/operators/activation_op.cc
paddle/fluid/operators/activation_op.cc
+1
-1
paddle/fluid/operators/pool_op.cc
paddle/fluid/operators/pool_op.cc
+4
-4
python/paddle/fluid/layers/nn.py
python/paddle/fluid/layers/nn.py
+3
-3
python/paddle/fluid/layers/tensor.py
python/paddle/fluid/layers/tensor.py
+2
-1
未找到文件。
paddle/fluid/operators/activation_op.cc
浏览文件 @
d91060d3
...
@@ -444,7 +444,7 @@ class SwishOpMaker : public framework::OpProtoAndCheckerMaker {
...
@@ -444,7 +444,7 @@ class SwishOpMaker : public framework::OpProtoAndCheckerMaker {
AddComment
(
R"DOC(
AddComment
(
R"DOC(
Swish Activation Operator.
Swish Activation Operator.
$$out = \frac{x}{1 + e^{- \beta x}}$$
$$out = \
\
frac{x}{1 + e^{- \beta x}}$$
)DOC"
);
)DOC"
);
}
}
...
...
paddle/fluid/operators/pool_op.cc
浏览文件 @
d91060d3
...
@@ -224,17 +224,17 @@ Example:
...
@@ -224,17 +224,17 @@ Example:
For ceil_mode = false:
For ceil_mode = false:
$$
$$
H_{out} = \frac{(H_{in} - ksize[0] + 2 * paddings[0])}{strides[0]} + 1
H_{out} = \
\
frac{(H_{in} - ksize[0] + 2 * paddings[0])}{strides[0]} + 1
$$
$$
$$
$$
W_{out} = \frac{(W_{in} - ksize[1] + 2 * paddings[1])}{strides[1]} + 1
W_{out} = \
\
frac{(W_{in} - ksize[1] + 2 * paddings[1])}{strides[1]} + 1
$$
$$
For ceil_mode = true:
For ceil_mode = true:
$$
$$
H_{out} = \frac{(H_{in} - ksize[0] + 2 * paddings[0] + strides[0] - 1)}{strides[0]} + 1
H_{out} = \
\
frac{(H_{in} - ksize[0] + 2 * paddings[0] + strides[0] - 1)}{strides[0]} + 1
$$
$$
$$
$$
W_{out} = \frac{(W_{in} - ksize[1] + 2 * paddings[1] + strides[1] - 1)}{strides[1]} + 1
W_{out} = \
\
frac{(W_{in} - ksize[1] + 2 * paddings[1] + strides[1] - 1)}{strides[1]} + 1
$$
$$
)DOC"
);
)DOC"
);
...
...
python/paddle/fluid/layers/nn.py
浏览文件 @
d91060d3
...
@@ -1495,9 +1495,9 @@ def pool2d(input,
...
@@ -1495,9 +1495,9 @@ def pool2d(input,
Args:
Args:
input (Variable): The input tensor of pooling operator. The format of
input (Variable): The input tensor of pooling operator. The format of
input tensor is NCHW, where N is batch size, C is the number of
input tensor is NCHW, where N is batch size, C is
channels, H is the height of the feature, and W is the width of
the number of channels, H is the height of the
the feature.
feature, and W is the width of
the feature.
pool_size (int): The side length of pooling windows. All pooling
pool_size (int): The side length of pooling windows. All pooling
windows are squares with pool_size on a side.
windows are squares with pool_size on a side.
pool_type: ${pooling_type_comment}
pool_type: ${pooling_type_comment}
...
...
python/paddle/fluid/layers/tensor.py
浏览文件 @
d91060d3
...
@@ -146,7 +146,8 @@ def concat(input, axis=0, name=None):
...
@@ -146,7 +146,8 @@ def concat(input, axis=0, name=None):
Examples:
Examples:
.. code-block:: python
.. code-block:: python
out = fluid.layers.concat(input=[Efirst, Esecond, Ethird, Efourth])
out = fluid.layers.concat(input=[Efirst, Esecond, Ethird, Efourth])
"""
"""
helper
=
LayerHelper
(
'concat'
,
**
locals
())
helper
=
LayerHelper
(
'concat'
,
**
locals
())
out
=
helper
.
create_tmp_variable
(
dtype
=
helper
.
input_dtype
())
out
=
helper
.
create_tmp_variable
(
dtype
=
helper
.
input_dtype
())
...
...
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