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体验新版 GitCode,发现更多精彩内容 >>
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97d47ca3
编写于
12月 25, 2017
作者:
G
guosheng
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电子邮件补丁
差异文件
Add python wrapper for reduce_max and reduce_min
上级
efd37269
变更
2
隐藏空白更改
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Showing
2 changed file
with
103 addition
and
3 deletion
+103
-3
doc/api/v2/fluid/layers.rst
doc/api/v2/fluid/layers.rst
+13
-1
python/paddle/v2/fluid/layers/nn.py
python/paddle/v2/fluid/layers/nn.py
+90
-2
未找到文件。
doc/api/v2/fluid/layers.rst
浏览文件 @
97d47ca3
...
...
@@ -332,7 +332,19 @@ reduce_sum
reduce_mean
---------
---------
--
.. autofunction:: paddle.v2.fluid.layers.reduce_mean
:noindex:
reduce_max
----------
.. autofunction:: paddle.v2.fluid.layers.reduce_max
:noindex:
reduce_min
----------
.. autofunction:: paddle.v2.fluid.layers.reduce_min
:noindex:
python/paddle/v2/fluid/layers/nn.py
浏览文件 @
97d47ca3
...
...
@@ -13,8 +13,8 @@ __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'
,
'reduce_mean'
,
'
sequence_first_step
'
,
'sequence_last_step'
'lstm_unit'
,
'reduce_sum'
,
'reduce_mean'
,
'
reduce_max'
,
'reduce_min
'
,
'sequence_
first_step'
,
'sequence_
last_step'
]
...
...
@@ -1201,3 +1201,91 @@ def reduce_mean(input, dim=None, keep_dim=False):
'reduce_all'
:
True
if
dim
==
None
else
False
})
return
out
def
reduce_max
(
input
,
dim
=
None
,
keep_dim
=
False
):
"""
Computes the maximum 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 maximum is computed.
If :attr:`None`, compute the maximum 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_max(x) # [0.9]
fluid.layers.reduce_max(x, dim=0) # [0.2, 0.3, 0.6, 0.9]
fluid.layers.reduce_max(x, dim=-1) # [0.9, 0.7]
fluid.layers.reduce_max(x, dim=1, keep_dim=True) # [[0.9], [0.7]]
"""
helper
=
LayerHelper
(
'reduce_max'
,
**
locals
())
out
=
helper
.
create_tmp_variable
(
dtype
=
helper
.
input_dtype
())
helper
.
append_op
(
type
=
'reduce_max'
,
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
def
reduce_min
(
input
,
dim
=
None
,
keep_dim
=
False
):
"""
Computes the minimum 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 minimum is computed.
If :attr:`None`, compute the minimum 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_min(x) # [0.1]
fluid.layers.reduce_min(x, dim=0) # [0.1, 0.2, 0.5, 0.7]
fluid.layers.reduce_min(x, dim=-1) # [0.2, 0.1]
fluid.layers.reduce_min(x, dim=1, keep_dim=True) # [[0.2], [0.1]]
"""
helper
=
LayerHelper
(
'reduce_min'
,
**
locals
())
out
=
helper
.
create_tmp_variable
(
dtype
=
helper
.
input_dtype
())
helper
.
append_op
(
type
=
'reduce_min'
,
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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