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71dd8f8f
编写于
12月 20, 2017
作者:
G
Guo Sheng
提交者:
GitHub
12月 20, 2017
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差异文件
Merge pull request #6716 from guoshengCS/add-python-reduceSum
Add python wrapper for reduce_sum
上级
2d5ec16b
0ab5d8e1
变更
2
隐藏空白更改
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Showing
2 changed file
with
53 addition
and
3 deletion
+53
-3
doc/api/v2/fluid/layers.rst
doc/api/v2/fluid/layers.rst
+6
-0
python/paddle/v2/fluid/layers/nn.py
python/paddle/v2/fluid/layers/nn.py
+47
-3
未找到文件。
doc/api/v2/fluid/layers.rst
浏览文件 @
71dd8f8f
...
...
@@ -312,3 +312,9 @@ sequence_softmax
.. autofunction:: paddle.v2.fluid.layers.sequence_softmax
:noindex:
reduce_sum
---------
.. autofunction:: paddle.v2.fluid.layers.reduce_sum
:noindex:
python/paddle/v2/fluid/layers/nn.py
浏览文件 @
71dd8f8f
...
...
@@ -13,7 +13,7 @@ __all__ = [
'crf_decoding'
,
'cos_sim'
,
'cross_entropy'
,
'square_error_cost'
,
'accuracy'
,
'chunk_eval'
,
'sequence_conv'
,
'conv2d'
,
'sequence_pool'
,
'pool2d'
,
'batch_norm'
,
'beam_search_decode'
,
'conv2d_transpose'
,
'sequence_expand'
,
'lstm_unit'
'lstm_unit'
,
'reduce_sum'
]
...
...
@@ -402,8 +402,8 @@ def chunk_eval(input,
},
attrs
=
{
"num_chunk_types"
:
num_chunk_types
,
'chunk_scheme'
:
chunk_scheme
,
'excluded_chunk_types'
:
excluded_chunk_types
or
[]
"chunk_scheme"
:
chunk_scheme
,
"excluded_chunk_types"
:
excluded_chunk_types
or
[]
})
return
precision
,
recall
,
f1_score
,
num_infer_chunks
,
num_label_chunks
,
num_correct_chunks
...
...
@@ -935,3 +935,47 @@ def lstm_unit(x_t,
attrs
=
{
"forget_bias"
:
forget_bias
})
return
h
,
c
def
reduce_sum
(
input
,
dim
=
None
,
keep_dim
=
False
):
"""
Computes the sum of tensor elements over the given dimension.
Args:
input (Variable): The input variable which is a Tensor or LoDTensor.
dim (int|None): The dimension along which the sum is performed. If
:attr:`None`, sum all elements of :attr:`input` and return a
Tensor variable with a single element, otherwise must be in the
range :math:`[-rank(input), rank(input))`. If :math:`dim < 0`,
the dimension to reduce is :math:`rank + dim`.
keep_dim (bool): Whether to reserve the reduced dimension in the
output Tensor. The result tensor will have one fewer dimension
than the :attr:`input` unless :attr:`keep_dim` is true.
Returns:
Variable: The reduced Tensor variable.
Examples:
.. code-block:: python
# x is a Tensor variable with following elements:
# [[0.2, 0.3, 0.5, 0.9]
# [0.1, 0.2, 0.6, 0.7]]
# Each example is followed by the correspending output tensor.
fluid.layers.reduce_sum(x) # [3.5]
fluid.layers.reduce_sum(x, dim=0) # [0.3, 0.5, 1.1, 1.6]
fluid.layers.reduce_sum(x, dim=-1) # [1.9, 1.6]
fluid.layers.reduce_sum(x, dim=1, keep_dim=True) # [[1.9], [1.6]]
"""
helper
=
LayerHelper
(
'reduce_sum'
,
**
locals
())
out
=
helper
.
create_tmp_variable
(
dtype
=
helper
.
input_dtype
())
helper
.
append_op
(
type
=
'reduce_sum'
,
inputs
=
{
'X'
:
input
},
outputs
=
{
'Out'
:
out
},
attrs
=
{
'dim'
:
dim
if
dim
!=
None
else
0
,
'keep_dim'
:
keep_dim
,
'reduce_all'
:
True
if
dim
==
None
else
False
})
return
out
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