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体验新版 GitCode,发现更多精彩内容 >>
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0329ee74
编写于
6月 15, 2018
作者:
T
tensor-tang
提交者:
GitHub
6月 15, 2018
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差异文件
Merge pull request #11497 from tensor-tang/doc
Doc update
上级
5fd142c3
98ab2b40
变更
6
隐藏空白更改
内联
并排
Showing
6 changed file
with
33 addition
and
28 deletion
+33
-28
paddle/fluid/operators/activation_op.cc
paddle/fluid/operators/activation_op.cc
+8
-9
paddle/fluid/operators/mean_op.cc
paddle/fluid/operators/mean_op.cc
+3
-5
python/paddle/fluid/layers/control_flow.py
python/paddle/fluid/layers/control_flow.py
+1
-1
python/paddle/fluid/layers/io.py
python/paddle/fluid/layers/io.py
+3
-0
python/paddle/fluid/layers/nn.py
python/paddle/fluid/layers/nn.py
+17
-13
python/paddle/fluid/layers/tensor.py
python/paddle/fluid/layers/tensor.py
+1
-0
未找到文件。
paddle/fluid/operators/activation_op.cc
浏览文件 @
0329ee74
...
...
@@ -252,15 +252,14 @@ class SoftShrinkOpMaker : public framework::OpProtoAndCheckerMaker {
AddOutput
(
"Out"
,
"Output of Softshrink operator"
);
AddAttr
<
float
>
(
"lambda"
,
"non-negative offset"
).
SetDefault
(
0.5
f
);
AddComment
(
R"DOC(
Softshrink Activation Operator.
$$
out = \begin{cases}
x - \lambda, \text{if } x > \lambda \\
x + \lambda, \text{if } x < -\lambda \\
0, \text{otherwise}
\end{cases}
$$
:strong:`Softshrink Activation Operator`
.. math::
out = \begin{cases}
x - \lambda, \text{if } x > \lambda \\
x + \lambda, \text{if } x < -\lambda \\
0, \text{otherwise}
\end{cases}
)DOC"
);
}
...
...
paddle/fluid/operators/mean_op.cc
浏览文件 @
0329ee74
...
...
@@ -33,12 +33,10 @@ class MeanOp : public framework::OperatorWithKernel {
class
MeanOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
void
Make
()
override
{
AddInput
(
"X"
,
"The input of mean op"
);
AddOutput
(
"Out"
,
"The output of mean op"
).
Reuse
(
"X"
);
AddInput
(
"X"
,
"
(Tensor)
The input of mean op"
);
AddOutput
(
"Out"
,
"
(Tensor)
The output of mean op"
).
Reuse
(
"X"
);
AddComment
(
R"DOC(
Mean Operator.
Out is a scalar which is the mean of all elements in X.
Mean Operator calculates the mean of all elements in X.
)DOC"
);
}
...
...
python/paddle/fluid/layers/control_flow.py
浏览文件 @
0329ee74
...
...
@@ -707,7 +707,7 @@ def lod_rank_table(x, level=0):
.. code-block:: python
x = fluid.layers.data(name='x', shape=[10],
dtype='float32', lod_level=1)
dtype='float32', lod_level=1)
out = layers.lod_rank_table(x=x, level=0)
"""
helper
=
LayerHelper
(
"lod_rank_table"
,
**
locals
())
...
...
python/paddle/fluid/layers/io.py
浏览文件 @
0329ee74
...
...
@@ -541,6 +541,9 @@ def __create_unshared_decorated_reader__(op_type, reader, attrs, name=None):
def
shuffle
(
reader
,
buffer_size
):
"""
Shuffle the reader.
"""
return
__create_unshared_decorated_reader__
(
'create_shuffle_reader'
,
reader
,
{
'buffer_size'
:
int
(
buffer_size
)})
...
...
python/paddle/fluid/layers/nn.py
浏览文件 @
0329ee74
...
...
@@ -225,11 +225,11 @@ def embedding(input,
have two elements which indicate the size of the dictionary of
embeddings and the size of each embedding vector respectively.
is_sparse(bool): The flag indicating whether to use sparse update.
is_distributed
(bool): Whether to run lookup table from remote parameter server.
is_distributed(bool): Whether to run lookup table from remote parameter server.
padding_idx(int|long|None): If :attr:`None`, it makes no effect to lookup.
Otherwise the given :attr:`padding_idx` indicates padding the output
with zeros whenever lookup encounters it in :attr:`input`. If
:math:`padding_idx < 0`, the
padding_idx
to use in lookup is
:math:`padding_idx < 0`, the
:attr:`padding_idx`
to use in lookup is
:math:`size[0] + dim`.
param_attr(ParamAttr): Parameters for this layer
dtype(np.dtype|core.VarDesc.VarType|str): The type of data : float32, float_16, int etc
...
...
@@ -1235,14 +1235,17 @@ def conv2d(input,
act
=
None
,
name
=
None
):
"""
**Convlution2D Layer**
The convolution2D layer calculates the output based on the input, filter
and strides, paddings, dilations, groups parameters. Input
(Input)
and
Output
(Output) are in NCHW format. W
here N is batch size, C is the number of
and strides, paddings, dilations, groups parameters. Input and
Output
are in NCHW format, w
here N is batch size, C is the number of
channels, H is the height of the feature, and W is the width of the feature.
The details of convolution layer, please refer UFLDL's `convolution,
<http://ufldl.stanford.edu/tutorial/supervised/FeatureExtractionUsingConvolution/>`_ .
Filter is in MCHW format, where M is the number of output image channels,
C is the number of input image channels, H is the height of the filter,
and W is the width of the filter. If the groups is greater than 1,
C will equal the number of input image channels divided by the groups.
Please refer to UFLDL's `convolution
<http://ufldl.stanford.edu/tutorial/supervised/FeatureExtractionUsingConvolution/>`_
for more detials.
If bias attribution and activation type are provided, bias is added to the
output of the convolution, and the corresponding activation function is
applied to the final result.
...
...
@@ -1253,15 +1256,14 @@ def conv2d(input,
Out = \sigma (W
\\
ast X + b)
In the above equation
:
Where
:
* :math:`X`: Input value, a tensor with NCHW format.
* :math:`W`: Filter value, a tensor with MCHW format.
* :math:`
\\
ast`: Convolution operation.
* :math:`b`: Bias value, a 2-D tensor with shape [M, 1].
* :math:`
\\
sigma`: Activation function.
* :math:`Out`: Output value, the shape of :math:`Out` and :math:`X` may be
different.
* :math:`Out`: Output value, the shape of :math:`Out` and :math:`X` may be different.
Example:
...
...
@@ -1272,6 +1274,7 @@ def conv2d(input,
Filter shape: :math:`(C_{out}, C_{in}, H_f, W_f)`
- Output:
Output shape: :math:`(N, C_{out}, H_{out}, W_{out})`
Where
...
...
@@ -1283,7 +1286,7 @@ def conv2d(input,
Args:
input (Variable): The input image with [N, C, H, W] format.
num_filters(int): The number of filter. It is as same as the output
num_filters(int): The number of filter. It is as same as the output
image channel.
filter_size (int|tuple|None): The filter size. If filter_size is a tuple,
it must contain two integers, (filter_size_H, filter_size_W).
...
...
@@ -1306,7 +1309,8 @@ def conv2d(input,
bias_attr (ParamAttr): Bias parameter for the Conv2d layer. Default: None
use_cudnn (bool): Use cudnn kernel or not, it is valid only when the cudnn
library is installed. Default: True
use_mkldnn (bool): Use mkldnn kernels or not.
use_mkldnn (bool): Use mkldnn kernels or not, it is valid only when compiled
with mkldnn library. Default: False
act (str): Activation type. Default: None
name (str|None): A name for this layer(optional). If set None, the layer
will be named automatically.
...
...
python/paddle/fluid/layers/tensor.py
浏览文件 @
0329ee74
...
...
@@ -201,6 +201,7 @@ def assign(input, output):
Examples:
.. code-block:: python
out = fluid.layers.create_tensor(dtype='float32')
hidden = fluid.layers.fc(input=data, size=10)
fluid.layers.assign(hidden, out)
...
...
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