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体验新版 GitCode,发现更多精彩内容 >>
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6fc9a9fd
编写于
11月 28, 2017
作者:
S
sweetsky0901
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
modify for del T2 and doc update
上级
ee0a794c
变更
7
显示空白变更内容
内联
并排
Showing
7 changed file
with
52 addition
and
50 deletion
+52
-50
paddle/operators/math/unpooling.cc
paddle/operators/math/unpooling.cc
+10
-10
paddle/operators/math/unpooling.cu
paddle/operators/math/unpooling.cu
+18
-21
paddle/operators/math/unpooling.h
paddle/operators/math/unpooling.h
+2
-2
paddle/operators/unpool_op.cc
paddle/operators/unpool_op.cc
+12
-7
paddle/operators/unpool_op.cu.cc
paddle/operators/unpool_op.cu.cc
+4
-4
paddle/operators/unpool_op.h
paddle/operators/unpool_op.h
+4
-4
python/paddle/v2/fluid/tests/test_unpool_op.py
python/paddle/v2/fluid/tests/test_unpool_op.py
+2
-2
未找到文件。
paddle/operators/math/unpooling.cc
浏览文件 @
6fc9a9fd
...
...
@@ -19,8 +19,8 @@ namespace operators {
namespace
math
{
// All tensors are in NCHW format
template
<
typename
T
,
typename
T2
>
class
Unpool2dMaxFunctor
<
platform
::
CPUPlace
,
T
,
T2
>
{
template
<
typename
T
>
class
Unpool2dMaxFunctor
<
platform
::
CPUPlace
,
T
>
{
public:
void
operator
()(
const
platform
::
DeviceContext
&
context
,
const
framework
::
Tensor
&
input
,
...
...
@@ -35,7 +35,7 @@ class Unpool2dMaxFunctor<platform::CPUPlace, T, T2> {
int
input_feasize
=
input_height
*
input_width
;
int
output_feasize
=
output_height
*
output_width
;
const
T
*
input_data
=
input
.
data
<
T
>
();
const
T2
*
indices_data
=
indices
.
data
<
T2
>
();
const
int
*
indices_data
=
indices
.
data
<
int
>
();
T
*
output_data
=
output
->
mutable_data
<
T
>
(
context
.
GetPlace
());
for
(
int
b
=
0
;
b
<
batch_size
;
++
b
)
{
for
(
int
c
=
0
;
c
<
output_channels
;
++
c
)
{
...
...
@@ -54,8 +54,8 @@ class Unpool2dMaxFunctor<platform::CPUPlace, T, T2> {
template
<
class
T
,
typename
T2
>
class
Unpool2dMaxGradFunctor
<
platform
::
CPUPlace
,
T
,
T2
>
{
template
<
class
T
>
class
Unpool2dMaxGradFunctor
<
platform
::
CPUPlace
,
T
>
{
public:
void
operator
()(
const
platform
::
DeviceContext
&
context
,
const
framework
::
Tensor
&
input
,
...
...
@@ -71,7 +71,7 @@ public:
const
int
output_width
=
output
.
dims
()[
3
];
int
input_feasize
=
input_height
*
input_width
;
int
output_feasize
=
output_height
*
output_width
;
const
T2
*
indices_data
=
indices
.
data
<
T2
>
();
const
int
*
indices_data
=
indices
.
data
<
int
>
();
const
T
*
output_grad_data
=
output_grad
.
data
<
T
>
();
T
*
input_grad_data
=
input_grad
->
mutable_data
<
T
>
(
context
.
GetPlace
());
...
...
@@ -90,10 +90,10 @@ public:
}
};
template
class
Unpool2dMaxGradFunctor
<
platform
::
CPUPlace
,
float
,
int
>;
template
class
Unpool2dMaxGradFunctor
<
platform
::
CPUPlace
,
double
,
int
>;
template
class
Unpool2dMaxFunctor
<
platform
::
CPUPlace
,
float
,
int
>;
template
class
Unpool2dMaxFunctor
<
platform
::
CPUPlace
,
double
,
int
>;
template
class
Unpool2dMaxGradFunctor
<
platform
::
CPUPlace
,
float
>;
template
class
Unpool2dMaxGradFunctor
<
platform
::
CPUPlace
,
double
>;
template
class
Unpool2dMaxFunctor
<
platform
::
CPUPlace
,
float
>;
template
class
Unpool2dMaxFunctor
<
platform
::
CPUPlace
,
double
>;
}
// namespace math
}
// namespace operators
...
...
paddle/operators/math/unpooling.cu
浏览文件 @
6fc9a9fd
...
...
@@ -19,10 +19,10 @@ namespace paddle {
namespace
operators
{
namespace
math
{
template
<
typename
T
,
typename
T2
>
template
<
typename
T
>
__global__
void
KernelUnpool2dMax
(
const
int
nthreads
,
const
T
*
input_data
,
const
T2
*
indices_data
,
const
int
*
indices_data
,
const
int
input_height
,
const
int
input_width
,
const
int
channels
,
...
...
@@ -45,10 +45,10 @@ __global__ void KernelUnpool2dMax(const int nthreads,
output_data
[
out_offset
+
out_index
]
=
input_data
[
i
];
}
}
template
<
typename
T
,
typename
T2
>
template
<
typename
T
>
__global__
void
KernelUnpool2dMaxGrad
(
const
int
nthreads
,
const
T
*
input_data
,
const
T2
*
indices_data
,
const
int
*
indices_data
,
const
int
input_height
,
const
int
input_width
,
const
int
channels
,
...
...
@@ -76,8 +76,8 @@ __global__ void KernelUnpool2dMaxGrad(const int nthreads,
/*
* All tensors are in NCHW format.
*/
template
<
typename
T
,
typename
T2
>
class
Unpool2dMaxFunctor
<
platform
::
GPUPlace
,
T
,
T2
>
{
template
<
typename
T
>
class
Unpool2dMaxFunctor
<
platform
::
GPUPlace
,
T
>
{
public:
void
operator
()(
const
platform
::
DeviceContext
&
context
,
const
framework
::
Tensor
&
input
,
...
...
@@ -90,15 +90,14 @@ class Unpool2dMaxFunctor<platform::GPUPlace, T, T2> {
const
int
output_height
=
output
->
dims
()[
2
];
const
int
output_width
=
output
->
dims
()[
3
];
const
T
*
input_data
=
input
.
data
<
T
>
();
const
T2
*
indices_data
=
indices
.
data
<
T2
>
();
const
int
*
indices_data
=
indices
.
data
<
int
>
();
T
*
output_data
=
output
->
mutable_data
<
T
>
(
context
.
GetPlace
());
int
nthreads
=
batch_size
*
output_channels
*
input_height
*
input_width
;
int
threads
=
1024
;
int
grid
=
(
input
.
numel
()
+
threads
-
1
)
/
threads
;
KernelUnpool2dMax
<
T
,
T2
><<<
grid
,
threads
,
0
,
T
><<<
grid
,
threads
,
0
,
reinterpret_cast
<
const
platform
::
CUDADeviceContext
&>
(
context
)
.
stream
()
>>>
(
nthreads
,
input_data
,
indices_data
,
.
stream
()
>>>
(
input
.
numel
()
,
input_data
,
indices_data
,
input_height
,
input_width
,
output_channels
,
output_data
,
output_height
,
output_width
);
}
...
...
@@ -106,8 +105,8 @@ class Unpool2dMaxFunctor<platform::GPUPlace, T, T2> {
/*
* All tensors are in NCHW format.
*/
template
<
typename
T
,
typename
T2
>
class
Unpool2dMaxGradFunctor
<
platform
::
GPUPlace
,
T
,
T2
>
{
template
<
typename
T
>
class
Unpool2dMaxGradFunctor
<
platform
::
GPUPlace
,
T
>
{
public:
void
operator
()(
const
platform
::
DeviceContext
&
context
,
const
framework
::
Tensor
&
input
,
...
...
@@ -122,18 +121,16 @@ class Unpool2dMaxGradFunctor<platform::GPUPlace, T, T2> {
const
int
output_height
=
output
.
dims
()[
2
];
const
int
output_width
=
output
.
dims
()[
3
];
const
T
*
input_data
=
input
.
data
<
T
>
();
const
T2
*
indices_data
=
indices
.
data
<
T2
>
();
const
int
*
indices_data
=
indices
.
data
<
int
>
();
const
T
*
output_data
=
output
.
data
<
T
>
();
const
T
*
output_grad_data
=
output_grad
.
data
<
T
>
();
T
*
input_grad_data
=
input_grad
->
mutable_data
<
T
>
(
context
.
GetPlace
());
int
nthreads
=
batch_size
*
output_channels
*
input_height
*
input_width
;
int
threads
=
1024
;
int
grid
=
(
input
.
numel
()
+
threads
-
1
)
/
threads
;
KernelUnpool2dMaxGrad
<
T
,
T2
><<<
grid
,
threads
,
0
,
T
><<<
grid
,
threads
,
0
,
reinterpret_cast
<
const
platform
::
CUDADeviceContext
&>
(
context
)
.
stream
()
>>>
(
nthreads
,
input_data
,
indices_data
,
.
stream
()
>>>
(
input
.
numel
(),
input_data
,
indices_data
,
input_height
,
input_width
,
output_channels
,
output_data
,
output_grad_data
,
output_height
,
output_width
,
...
...
@@ -141,11 +138,11 @@ class Unpool2dMaxGradFunctor<platform::GPUPlace, T, T2> {
}
};
template
class
Unpool2dMaxGradFunctor
<
platform
::
GPUPlace
,
float
,
int
>;
template
class
Unpool2dMaxGradFunctor
<
platform
::
GPUPlace
,
double
,
int
>;
template
class
Unpool2dMaxGradFunctor
<
platform
::
GPUPlace
,
float
>;
template
class
Unpool2dMaxGradFunctor
<
platform
::
GPUPlace
,
double
>;
template
class
Unpool2dMaxFunctor
<
platform
::
GPUPlace
,
float
,
int
>;
template
class
Unpool2dMaxFunctor
<
platform
::
GPUPlace
,
double
,
int
>;
template
class
Unpool2dMaxFunctor
<
platform
::
GPUPlace
,
float
>;
template
class
Unpool2dMaxFunctor
<
platform
::
GPUPlace
,
double
>;
}
// namespace math
}
// namespace operators
...
...
paddle/operators/math/unpooling.h
浏览文件 @
6fc9a9fd
...
...
@@ -19,7 +19,7 @@ namespace paddle {
namespace
operators
{
namespace
math
{
template
<
typename
Place
,
typename
T
,
typename
T2
>
template
<
typename
Place
,
typename
T
>
class
Unpool2dMaxFunctor
{
public:
...
...
@@ -29,7 +29,7 @@ class Unpool2dMaxFunctor {
framework
::
Tensor
*
output
);
};
template
<
typename
Place
,
class
T
,
typename
T2
>
template
<
typename
Place
,
class
T
>
class
Unpool2dMaxGradFunctor
{
public:
void
operator
()(
const
platform
::
DeviceContext
&
context
,
...
...
paddle/operators/unpool_op.cc
浏览文件 @
6fc9a9fd
...
...
@@ -50,10 +50,15 @@ class Unpool2dOpMaker : public framework::OpProtoAndCheckerMaker {
"(string), unpooling type, can be
\"
max
\"
for max-unpooling "
)
.
InEnum
({
"max"
});
AddComment
(
R"DOC(
"Paper: http://www.matthewzeiler.com/wp-content/uploads/2017
"Input shape: $(N, C_{in}, H_{in}, W_{in})$
Output shape: $(N, C_{out}, H_{out}, W_{out})$
Where
$$
H_{out} = (H_{in}−1) * strides[0] − 2 * paddings[0] + ksize[0] \\
W_{out} = (W_{in}−1) * strides[1] − 2 * paddings[1] + ksize[1]
$$
Paper: http://www.matthewzeiler.com/wp-content/uploads/2017
/07/iccv2011.pdf
PyTorch: http://pytorch.org/docs/master/nn.html?highlight=unpool#
torch.nn.MaxUnpool2d"
)DOC"
);
}
};
...
...
@@ -125,9 +130,9 @@ namespace ops = paddle::operators;
REGISTER_OP
(
unpool
,
ops
::
UnpoolOp
,
ops
::
Unpool2dOpMaker
,
unpool_grad
,
ops
::
UnpoolOpGrad
);
REGISTER_OP_CPU_KERNEL
(
unpool
,
ops
::
UnpoolKernel
<
paddle
::
platform
::
CPUPlace
,
float
,
int
>
,
ops
::
UnpoolKernel
<
paddle
::
platform
::
CPUPlace
,
double
,
int
>
);
ops
::
UnpoolKernel
<
paddle
::
platform
::
CPUPlace
,
float
>
,
ops
::
UnpoolKernel
<
paddle
::
platform
::
CPUPlace
,
double
>
);
REGISTER_OP_CPU_KERNEL
(
unpool_grad
,
ops
::
UnpoolGradKernel
<
paddle
::
platform
::
CPUPlace
,
float
,
int
>
,
ops
::
UnpoolGradKernel
<
paddle
::
platform
::
CPUPlace
,
double
,
int
>
);
ops
::
UnpoolGradKernel
<
paddle
::
platform
::
CPUPlace
,
float
>
,
ops
::
UnpoolGradKernel
<
paddle
::
platform
::
CPUPlace
,
double
>
);
paddle/operators/unpool_op.cu.cc
浏览文件 @
6fc9a9fd
...
...
@@ -16,10 +16,10 @@ limitations under the License. */
namespace
ops
=
paddle
::
operators
;
REGISTER_OP_GPU_KERNEL
(
unpool
,
ops
::
UnpoolKernel
<
paddle
::
platform
::
GPUPlace
,
float
,
int
>
,
ops
::
UnpoolKernel
<
paddle
::
platform
::
GPUPlace
,
double
,
int
>
);
ops
::
UnpoolKernel
<
paddle
::
platform
::
GPUPlace
,
float
>
,
ops
::
UnpoolKernel
<
paddle
::
platform
::
GPUPlace
,
double
>
);
REGISTER_OP_GPU_KERNEL
(
unpool_grad
,
ops
::
UnpoolGradKernel
<
paddle
::
platform
::
GPUPlace
,
float
,
int
>
,
float
>
,
ops
::
UnpoolGradKernel
<
paddle
::
platform
::
GPUPlace
,
double
,
int
>
);
double
>
);
paddle/operators/unpool_op.h
浏览文件 @
6fc9a9fd
...
...
@@ -21,7 +21,7 @@ limitations under the License. */
namespace
paddle
{
namespace
operators
{
template
<
typename
Place
,
typename
T
,
typename
T2
>
template
<
typename
Place
,
typename
T
>
class
UnpoolKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
...
...
@@ -37,12 +37,12 @@ class UnpoolKernel : public framework::OpKernel<T> {
math
::
SetConstant
<
Place
,
T
>
set_zero
;
set_zero
(
context
.
device_context
(),
out
,
static_cast
<
T
>
(
0
));
}
math
::
Unpool2dMaxFunctor
<
Place
,
T
,
T2
>
unpool2d_max_forward
;
math
::
Unpool2dMaxFunctor
<
Place
,
T
>
unpool2d_max_forward
;
unpool2d_max_forward
(
context
.
device_context
(),
*
in_x
,
*
in_y
,
out
);
}
};
template
<
typename
Place
,
typename
T
,
typename
T2
>
template
<
typename
Place
,
typename
T
>
class
UnpoolGradKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
...
...
@@ -64,7 +64,7 @@ class UnpoolGradKernel : public framework::OpKernel<T> {
in_x_grad
->
mutable_data
<
T
>
(
context
.
GetPlace
());
zero
(
device_ctx
,
in_x_grad
,
static_cast
<
T
>
(
0
));
}
math
::
Unpool2dMaxGradFunctor
<
Place
,
T
,
T2
>
unpool2d_max_backward
;
math
::
Unpool2dMaxGradFunctor
<
Place
,
T
>
unpool2d_max_backward
;
unpool2d_max_backward
(
context
.
device_context
(),
*
in_x
,
*
in_y
,
*
out
,
*
out_grad
,
in_x_grad
);
}
...
...
python/paddle/v2/fluid/tests/test_unpool_op.py
浏览文件 @
6fc9a9fd
...
...
@@ -50,7 +50,7 @@ class TestUnpoolOp(OpTest):
indices
[
nidx
,
cidx
,
i
,
j
]
=
\
(
r_start
+
arg
/
self
.
ksize
[
1
])
*
wsize
+
\
c_start
+
arg
%
self
.
ksize
[
1
]
output
=
self
.
U
npool2d_forward_naive
(
input
,
indices
,
self
.
ksize
,
\
output
=
self
.
u
npool2d_forward_naive
(
input
,
indices
,
self
.
ksize
,
\
self
.
strides
,
self
.
paddings
).
astype
(
"float32"
)
self
.
inputs
=
{
'X'
:
input
.
astype
(
'float32'
),
'Indices'
:
indices
.
astype
(
'int32'
)}
...
...
@@ -69,7 +69,7 @@ class TestUnpoolOp(OpTest):
self
.
check_grad
([
'X'
],
'Out'
)
def
init_test_case
(
self
):
self
.
U
npool2d_forward_naive
=
unpool2dmax_forward_naive
self
.
u
npool2d_forward_naive
=
unpool2dmax_forward_naive
self
.
unpooling_type
=
"max"
self
.
shape
=
[
6
,
4
,
5
,
5
]
self
.
ksize
=
[
3
,
3
]
...
...
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