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体验新版 GitCode,发现更多精彩内容 >>
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c97369b4
编写于
12月 20, 2017
作者:
G
guosheng
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差异文件
Add python wrapper for reduce_mean
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a948fac4
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2
隐藏空白更改
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2 changed file
with
51 addition
and
1 deletion
+51
-1
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
+45
-1
未找到文件。
doc/api/v2/fluid/layers.rst
浏览文件 @
c97369b4
...
...
@@ -318,3 +318,9 @@ reduce_sum
.. autofunction:: paddle.v2.fluid.layers.reduce_sum
:noindex:
reduce_mean
---------
.. autofunction:: paddle.v2.fluid.layers.reduce_mean
:noindex:
python/paddle/v2/fluid/layers/nn.py
浏览文件 @
c97369b4
...
...
@@ -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'
,
'reduce_sum'
'lstm_unit'
,
'reduce_sum'
,
'reduce_mean'
]
...
...
@@ -979,3 +979,47 @@ def reduce_sum(input, dim=None, keep_dim=False):
'reduce_all'
:
True
if
dim
==
None
else
False
})
return
out
def
reduce_mean
(
input
,
dim
=
None
,
keep_dim
=
False
):
"""
Computes the mean 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 mean is computed. If
:attr:`None`, compute the mean over 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_mean(x) # [0.4375]
fluid.layers.reduce_mean(x, dim=0) # [0.15, 0.25, 0.55, 0.8]
fluid.layers.reduce_mean(x, dim=-1) # [0.475, 0.4]
fluid.layers.reduce_mean(x, dim=1, keep_dim=True) # [[0.475], [0.4]]
"""
helper
=
LayerHelper
(
'reduce_mean'
,
**
locals
())
out
=
helper
.
create_tmp_variable
(
dtype
=
helper
.
input_dtype
())
helper
.
append_op
(
type
=
'reduce_mean'
,
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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