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11b4471a
编写于
1月 17, 2018
作者:
W
wanghaoshuang
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差异文件
Add python API for block expand op
上级
38c61053
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
128 addition
and
6 deletion
+128
-6
doc/api/v2/fluid/layers.rst
doc/api/v2/fluid/layers.rst
+5
-0
python/paddle/v2/fluid/layers/nn.py
python/paddle/v2/fluid/layers/nn.py
+123
-6
未找到文件。
doc/api/v2/fluid/layers.rst
浏览文件 @
11b4471a
...
...
@@ -493,3 +493,8 @@ swish
------
.. autofunction:: paddle.v2.fluid.layers.swish
:noindex:
block_expand
------
.. autofunction:: paddle.v2.fluid.layers.block_expand
:noindex:
python/paddle/v2/fluid/layers/nn.py
浏览文件 @
11b4471a
...
...
@@ -50,6 +50,7 @@ __all__ = [
'sequence_last_step'
,
'dropout'
,
'split'
,
'block_expand'
,
]
...
...
@@ -1547,13 +1548,13 @@ def split(input, num_or_sections, dim=-1):
Args:
input (Variable): The input variable which is a Tensor or LoDTensor.
num_or_sections (int|list): If :attr:`num_or_sections` is an integer,
then the integer indicates the number of equal sized sub-tensors
that the tensor will be divided into. If :attr:`num_or_sections`
is a list of integers, the length of list indicates the number of
sub-tensors and the integers indicate the sizes of sub-tensors'
num_or_sections (int|list): If :attr:`num_or_sections` is an integer,
then the integer indicates the number of equal sized sub-tensors
that the tensor will be divided into. If :attr:`num_or_sections`
is a list of integers, the length of list indicates the number of
sub-tensors and the integers indicate the sizes of sub-tensors'
:attr:`dim` dimension orderly.
dim (int): The dimension along which to split. If :math:`dim < 0`, the
dim (int): The dimension along which to split. If :math:`dim < 0`, the
dimension to split along is :math:`rank(input) + dim`.
Returns:
...
...
@@ -1597,3 +1598,119 @@ def split(input, num_or_sections, dim=-1):
'axis'
:
dim
})
return
outs
def
block_expand
(
input
,
block_x
=
1
,
block_y
=
1
,
stride_x
=
1
,
stride_y
=
1
,
padding_x
=
0
,
padding_y
=
0
,
name
=
None
,
layer_attr
=
None
):
"""
This op use block to scan images and convert these images to sequences.
After expanding, the number of time step are output_height * output_width
for an image, in which output_height and output_width are calculated
by below equation:
.. math::
output\_size = 1 +
\
(2 * padding + img\_size - block\_size + stride - 1) / stride
And the dimension of each time step is block_y * block_x * input.channels.
Args:
input (Variable): The input should be a tensor in NCHW format.
block_x (int): The width of sub block.
block_y (int): The width of sub block.
stride_x (int): The stride size in horizontal direction.
stride_y (int): The stride size in vertical direction.
padding_x (int): The padding size in horizontal direction.
padding_y (int): The padding size in vertical direction.
name (int): The name of this layer. It is optional.
Returns:
output: The output is a LoDTensor woth shape
{input.batch_size * output_y * x,
block_y * block_x * input.channels}.
If we regard output as matrix, each row of this matrix is a step of sequence.
Examples:
As an example:
.. code-block:: text
Given:
x = [[[[ 6. 2. 1.]
[ 8. 3. 5.]
[ 0. 2. 6.]]
[[ 2. 4. 4.]
[ 6. 3. 0.]
[ 6. 4. 7.]]]
[[[ 6. 7. 1.]
[ 5. 7. 9.]
[ 2. 4. 8.]]
[[ 1. 2. 1.]
[ 1. 3. 5.]
[ 9. 0. 8.]]]]
x.dims = {2, 2, 3, 3}
And:
block_height = 2
block_width = 2
stride_height = 1
stride_width = 1
padding_height = 0
padding_width = 0
Then:
output.data = [[ 6. 2. 8. 3. 2. 4. 6. 3.]
[ 2. 1. 3. 5. 4. 4. 3. 0.]
[ 8. 3. 0. 2. 6. 3. 6. 4.]
[ 3. 5. 2. 6. 3. 0. 4. 7.]
[ 6. 7. 5. 7. 1. 2. 1. 3.]
[ 7. 1. 7. 9. 2. 1. 3. 5.]
[ 5. 7. 2. 4. 1. 3. 9. 0.]
[ 7. 9. 4. 8. 3. 5. 0. 8.]]
output.dims = {8, 9}
output.lod = [[0, 4, 8]]
The simple usage is:
.. code-block:: python
output = fluid.layers.block_expand(input=layer, stride_x=1, stride_y=1, block_x=2, block_y=2)
"""
helper
=
LayerHelper
(
'block_expand'
,
**
locals
())
out
=
helper
.
create_tmp_variable
(
dtype
=
helper
.
input_dtype
())
helper
.
append_op
(
type
=
'block_expand'
,
inputs
=
{
'X'
:
input
},
outputs
=
{
'Out'
:
out
},
attrs
=
{
'block_height'
:
block_y
,
'block_width'
:
block_x
,
'stride_height'
:
stride_y
,
'stride_width'
:
stride_x
,
'padding_height'
:
padding_y
,
'padding_width'
:
padding_x
})
return
out
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