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体验新版 GitCode,发现更多精彩内容 >>
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caf6914f
编写于
6月 14, 2018
作者:
L
Luo Tao
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电子邮件补丁
差异文件
add doc of sequence_softmax and parallelDo
上级
9169b3b8
变更
2
隐藏空白更改
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并排
Showing
2 changed file
with
37 addition
and
3 deletion
+37
-3
python/paddle/fluid/layers/control_flow.py
python/paddle/fluid/layers/control_flow.py
+2
-3
python/paddle/fluid/layers/nn.py
python/paddle/fluid/layers/nn.py
+35
-0
未找到文件。
python/paddle/fluid/layers/control_flow.py
浏览文件 @
caf6914f
...
@@ -233,9 +233,8 @@ class BlockGuard(object):
...
@@ -233,9 +233,8 @@ class BlockGuard(object):
class
ParallelDo
(
object
):
class
ParallelDo
(
object
):
"""
"""
ParallelDo class.
ParallelDo class is used to create a ParallelDo.
It will be soon deprecated, please use ParallelExecutor instead.
ParallelDo class is used to create a ParallelDo.
"""
"""
def
__init__
(
self
,
places
,
use_nccl
=
False
,
name
=
None
):
def
__init__
(
self
,
places
,
use_nccl
=
False
,
name
=
None
):
...
...
python/paddle/fluid/layers/nn.py
浏览文件 @
caf6914f
...
@@ -1146,6 +1146,41 @@ def sequence_conv(input,
...
@@ -1146,6 +1146,41 @@ def sequence_conv(input,
def
sequence_softmax
(
input
,
param_attr
=
None
,
bias_attr
=
None
,
use_cudnn
=
True
):
def
sequence_softmax
(
input
,
param_attr
=
None
,
bias_attr
=
None
,
use_cudnn
=
True
):
"""
This function computes the softmax activation among all time-steps for each
sequence. The dimension of each time-step should be 1. Thus, the shape of
input Tensor can be either :math:`[N, 1]` or :math:`[N]`, where :math:`N`
is the sum of the length of all sequences.
For i-th sequence in a mini-batch:
.. math::
Out(X[lod[i]:lod[i+1]], :) =
\\
frac{\exp(X[lod[i]:lod[i+1], :])}{\sum(\exp(X[lod[i]:lod[i+1], :]))}
For example, for a mini-batch of 3 sequences with variable-length,
each containing 2, 3, 2 time-steps, the lod of which is [0, 2, 5, 7],
then softmax will be computed among :math:`X[0:2, :]`, :math:`X[2:5, :]`,
:math:`X[5:7, :]`, and :math:`N` turns out to be 7.
Args:
input (Variable): The input variable which is a LoDTensor.
bias_attr (ParamAttr|None): attributes for bias
param_attr (ParamAttr|None): attributes for parameter
use_cudnn (bool): Use cudnn kernel or not, it is valid only when the cudnn
\
library is installed. Default: True
Returns:
Variable: output of sequence_softmax
Examples:
.. code-block:: python
x = fluid.layers.data(name='x', shape=[7, 1],
dtype='float32', lod_level=1)
x_sequence_softmax = fluid.layers.sequence_softmax(input=x)
"""
helper
=
LayerHelper
(
'sequence_softmax'
,
**
locals
())
helper
=
LayerHelper
(
'sequence_softmax'
,
**
locals
())
dtype
=
helper
.
input_dtype
()
dtype
=
helper
.
input_dtype
()
softmax_out
=
helper
.
create_tmp_variable
(
dtype
)
softmax_out
=
helper
.
create_tmp_variable
(
dtype
)
...
...
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