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7ad39c40
编写于
8月 28, 2018
作者:
C
chengduo
提交者:
GitHub
8月 28, 2018
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差异文件
Enhance pad_constant_like_op (#12999)
* enhance pad_constant_like_op * add API * add API
上级
0353eddb
变更
3
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3 changed file
with
99 addition
and
1 deletion
+99
-1
paddle/fluid/API.spec
paddle/fluid/API.spec
+1
-0
paddle/fluid/operators/pad_constant_like_op.cc
paddle/fluid/operators/pad_constant_like_op.cc
+16
-0
python/paddle/fluid/layers/nn.py
python/paddle/fluid/layers/nn.py
+82
-1
未找到文件。
paddle/fluid/API.spec
浏览文件 @
7ad39c40
...
...
@@ -147,6 +147,7 @@ paddle.fluid.layers.reshape ArgSpec(args=['x', 'shape', 'actual_shape', 'act', '
paddle.fluid.layers.lod_reset ArgSpec(args=['x', 'y', 'target_lod'], varargs=None, keywords=None, defaults=(None, None))
paddle.fluid.layers.lrn ArgSpec(args=['input', 'n', 'k', 'alpha', 'beta', 'name'], varargs=None, keywords=None, defaults=(5, 1.0, 0.0001, 0.75, None))
paddle.fluid.layers.pad ArgSpec(args=['x', 'paddings', 'pad_value', 'name'], varargs=None, keywords=None, defaults=(0.0, None))
paddle.fluid.layers.pad_constant_like ArgSpec(args=['x', 'y', 'pad_value', 'name'], varargs=None, keywords=None, defaults=(0.0, None))
paddle.fluid.layers.label_smooth ArgSpec(args=['label', 'prior_dist', 'epsilon', 'dtype', 'name'], varargs=None, keywords=None, defaults=(None, 0.1, 'float32', None))
paddle.fluid.layers.roi_pool ArgSpec(args=['input', 'rois', 'pooled_height', 'pooled_width', 'spatial_scale'], varargs=None, keywords=None, defaults=(1, 1, 1.0))
paddle.fluid.layers.dice_loss ArgSpec(args=['input', 'label', 'epsilon'], varargs=None, keywords=None, defaults=(1e-05,))
...
...
paddle/fluid/operators/pad_constant_like_op.cc
浏览文件 @
7ad39c40
...
...
@@ -43,6 +43,14 @@ class PadConstantLikeOp : public framework::OperatorWithKernel {
ctx
->
SetOutputDim
(
"Out"
,
x_dim
);
ctx
->
ShareLoD
(
"X"
,
/*->*/
"Out"
);
}
protected:
framework
::
OpKernelType
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
return
framework
::
OpKernelType
(
framework
::
ToDataType
(
ctx
.
Input
<
Tensor
>
(
"Y"
)
->
type
()),
ctx
.
device_context
());
}
};
class
PadConstantLikeOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
...
...
@@ -159,6 +167,14 @@ class PadConstantLikeOpGrad : public framework::OperatorWithKernel {
}
}
}
protected:
framework
::
OpKernelType
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
return
framework
::
OpKernelType
(
framework
::
ToDataType
(
ctx
.
Input
<
Tensor
>
(
"Y"
)
->
type
()),
ctx
.
device_context
());
}
};
class
PadConstantLikeOpGradMaker
:
public
framework
::
SingleGradOpDescMaker
{
...
...
python/paddle/fluid/layers/nn.py
浏览文件 @
7ad39c40
...
...
@@ -88,6 +88,7 @@ __all__ = [
'lod_reset'
,
'lrn'
,
'pad'
,
'pad_constant_like'
,
'label_smooth'
,
'roi_pool'
,
'dice_loss'
,
...
...
@@ -4755,6 +4756,86 @@ def pad(x, paddings, pad_value=0., name=None):
return
out
def
pad_constant_like
(
x
,
y
,
pad_value
=
0.
,
name
=
None
):
"""
Pad input(Y) with :attr:`pad_value`, the number of values padded to
the edges of each axis is specified by the difference of the shape
of X and Y. ((0, shape_x_0 - shape_y_0), ... (0, shape_x_n - shape_y_n))
unique pad widths for each axis. The input should be a k-D
tensor(k > 0 and k < 7).
See below for an example.
.. code-block:: text
Given:
X = [[[[ 0, 1, 2],
[ 3, 4, 5]],
[[ 6, 7, 8],
[ 9, 10, 11]],
[[12, 13, 14],
[15, 16, 17]]],
[[[18, 19, 20],
[21, 22, 23]],
[[24, 25, 26],
[27, 28, 29]],
[[30, 31, 32],
[33, 34, 35]]]]
X.shape = (2, 3, 2, 3)
Y = [[[[35, 36, 37]],
[[38, 39, 40]],
[[41, 42, 43]]]]
Y.shape = (1, 3, 1, 3)
And
pad_value = -1,
Return:
Out = [[[[35, 36, 37],
[-1, -1, -1]],
[[38, 39, 40],
[-1, -1, -1]],
[[41, 42, 43],
[-1, -1, -1]]],
[[[-1, -1, -1],
[-1, -1, -1]],
[[-1, -1, -1],
[-1, -1, -1]],
[[-1, -1, -1],
[-1, -1, -1]]]]
Out.shape = (2, 3, 2, 3)
Args:
x (Variable): The input tensor variable.
y (Variable): The input tensor variable.
pad_value (float): The constant value used to pad.
name(str|None): A name for this layer(optional). If set None, the layer
will be named automatically.
Returns:
Variable: The padded tensor variable.
Examples:
.. code-block:: python
# x is a rank 4 tensor variable, x.shape = (2, 3, 2, 3)
# y is a rank 4 tensor variable, y.shape = (1, 3, 1, 3)
out = fluid.layers.pad_constant_like(x=x, y=y, pad_value=0.)
# out is a rank 4 tensor variable, and out.shape = [2, 3 ,2 , 3]
"""
helper
=
LayerHelper
(
'pad_constant_like'
,
input
=
x
,
**
locals
())
dtype
=
helper
.
input_dtype
()
out
=
helper
.
create_tmp_variable
(
dtype
)
helper
.
append_op
(
type
=
'pad_constant_like'
,
inputs
=
{
'X'
:
x
,
'Y'
:
y
},
outputs
=
{
'Out'
:
out
},
attrs
=
{
'pad_value'
:
float
(
pad_value
)})
return
out
def
label_smooth
(
label
,
prior_dist
=
None
,
epsilon
=
0.1
,
...
...
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