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体验新版 GitCode,发现更多精彩内容 >>
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提交
d0fdcb2f
编写于
10月 25, 2018
作者:
Q
Qiyang Min
提交者:
GitHub
10月 25, 2018
浏览文件
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差异文件
Merge pull request #14048 from velconia/change_sequence_pool_to_cpu
Accelerate Sequence Pool Grad Op
上级
97a87bb3
e2a348cd
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
159 addition
and
7 deletion
+159
-7
paddle/fluid/operators/math/CMakeLists.txt
paddle/fluid/operators/math/CMakeLists.txt
+1
-0
paddle/fluid/operators/math/sequence_pooling.cc
paddle/fluid/operators/math/sequence_pooling.cc
+32
-7
paddle/fluid/operators/math/sequence_pooling_test.cc
paddle/fluid/operators/math/sequence_pooling_test.cc
+126
-0
未找到文件。
paddle/fluid/operators/math/CMakeLists.txt
浏览文件 @
d0fdcb2f
...
@@ -68,6 +68,7 @@ cc_test(selected_rows_functor_test SRCS selected_rows_functor_test.cc DEPS selec
...
@@ -68,6 +68,7 @@ cc_test(selected_rows_functor_test SRCS selected_rows_functor_test.cc DEPS selec
cc_test
(
im2col_test SRCS im2col_test.cc DEPS im2col
)
cc_test
(
im2col_test SRCS im2col_test.cc DEPS im2col
)
cc_test
(
vol2col_test SRCS vol2col_test.cc DEPS vol2col
)
cc_test
(
vol2col_test SRCS vol2col_test.cc DEPS vol2col
)
cc_test
(
sequence_padding_test SRCS sequence_padding_test.cc DEPS sequence_padding
)
cc_test
(
sequence_padding_test SRCS sequence_padding_test.cc DEPS sequence_padding
)
cc_test
(
sequence_pooling_test SRCS sequence_pooling_test.cc DEPS sequence_pooling
)
if
(
WITH_GPU
)
if
(
WITH_GPU
)
nv_test
(
math_function_gpu_test SRCS math_function_test.cu DEPS math_function
)
nv_test
(
math_function_gpu_test SRCS math_function_test.cu DEPS math_function
)
nv_test
(
selected_rows_functor_gpu_test SRCS selected_rows_functor_test.cu DEPS selected_rows_functor math_function
)
nv_test
(
selected_rows_functor_gpu_test SRCS selected_rows_functor_test.cu DEPS selected_rows_functor math_function
)
...
...
paddle/fluid/operators/math/sequence_pooling.cc
浏览文件 @
d0fdcb2f
...
@@ -157,6 +157,31 @@ class FirstSeqPoolFunctor {
...
@@ -157,6 +157,31 @@ class FirstSeqPoolFunctor {
}
}
};
};
template
<
typename
T
>
class
SumSeqPoolGradFunctor
{
public:
void
operator
()(
const
platform
::
CPUDeviceContext
&
context
,
const
framework
::
Tensor
&
out_grad
,
framework
::
LoDTensor
*
in_grad
)
{
auto
lod
=
in_grad
->
lod
()[
0
];
int64_t
out_w
=
out_grad
.
numel
()
/
out_grad
.
dims
()[
0
];
int64_t
in_w
=
in_grad
->
numel
()
/
in_grad
->
dims
()[
0
];
PADDLE_ENFORCE
(
in_w
==
out_w
);
const
T
*
out_g_data
=
out_grad
.
data
<
T
>
();
T
*
in_g_data
=
in_grad
->
mutable_data
<
T
>
(
context
.
GetPlace
());
auto
blas
=
math
::
GetBlas
<
platform
::
CPUDeviceContext
,
T
>
(
context
);
for
(
int
i
=
0
;
i
<
static_cast
<
int
>
(
lod
.
size
())
-
1
;
++
i
)
{
int64_t
h
=
static_cast
<
int64_t
>
(
lod
[
i
+
1
]
-
lod
[
i
]);
int64_t
in_offset
=
lod
[
i
]
*
in_w
;
const
T
*
out_pos
=
out_g_data
+
i
*
out_w
;
T
*
in_pos
=
in_g_data
+
in_offset
;
for
(
int
r
=
0
;
r
!=
h
;
++
r
)
{
blas
.
VCOPY
(
in_w
,
out_pos
,
in_pos
+
r
*
in_w
);
}
}
}
};
template
<
typename
T
>
template
<
typename
T
>
class
SequencePoolFunctor
<
platform
::
CPUDeviceContext
,
T
>
{
class
SequencePoolFunctor
<
platform
::
CPUDeviceContext
,
T
>
{
public:
public:
...
@@ -231,9 +256,15 @@ class SequencePoolGradFunctor<platform::CPUDeviceContext, T> {
...
@@ -231,9 +256,15 @@ class SequencePoolGradFunctor<platform::CPUDeviceContext, T> {
math
::
SetConstant
<
platform
::
CPUDeviceContext
,
T
>
functor
;
math
::
SetConstant
<
platform
::
CPUDeviceContext
,
T
>
functor
;
functor
(
context
,
in_grad
,
0
);
functor
(
context
,
in_grad
,
0
);
}
}
if
(
pooltype
==
"SUM"
)
{
math
::
SumSeqPoolGradFunctor
<
T
>
sum_pool_grad
;
sum_pool_grad
(
context
,
out_grad
,
in_grad
);
return
;
}
auto
lod
=
in_grad
->
lod
()[
0
];
auto
lod
=
in_grad
->
lod
()[
0
];
auto
&
place
=
*
context
.
eigen_device
();
auto
&
place
=
*
context
.
eigen_device
();
auto
blas
=
math
::
GetBlas
<
platform
::
CPUDeviceContext
,
T
>
(
context
);
for
(
int
i
=
0
;
i
<
static_cast
<
int
>
(
lod
.
size
())
-
1
;
++
i
)
{
for
(
int
i
=
0
;
i
<
static_cast
<
int
>
(
lod
.
size
())
-
1
;
++
i
)
{
auto
in_g_t
=
in_grad
->
Slice
(
static_cast
<
int
>
(
lod
[
i
]),
auto
in_g_t
=
in_grad
->
Slice
(
static_cast
<
int
>
(
lod
[
i
]),
static_cast
<
int
>
(
lod
[
i
+
1
]));
static_cast
<
int
>
(
lod
[
i
+
1
]));
...
@@ -247,12 +278,6 @@ class SequencePoolGradFunctor<platform::CPUDeviceContext, T> {
...
@@ -247,12 +278,6 @@ class SequencePoolGradFunctor<platform::CPUDeviceContext, T> {
if
(
pooltype
==
"AVERAGE"
)
{
if
(
pooltype
==
"AVERAGE"
)
{
in_g_e
.
device
(
place
)
=
(
out_g_e
/
static_cast
<
T
>
(
h
)).
broadcast
(
bcast
);
in_g_e
.
device
(
place
)
=
(
out_g_e
/
static_cast
<
T
>
(
h
)).
broadcast
(
bcast
);
}
else
if
(
pooltype
==
"SUM"
)
{
const
T
*
out_g_data
=
out_g_t
.
data
<
T
>
();
T
*
in_g_data
=
in_g_t
.
mutable_data
<
T
>
(
context
.
GetPlace
());
for
(
int
r
=
0
;
r
!=
h
;
++
r
)
{
blas
.
VCOPY
(
w
,
out_g_data
,
in_g_data
+
r
*
w
);
}
}
else
if
(
pooltype
==
"SQRT"
)
{
}
else
if
(
pooltype
==
"SQRT"
)
{
in_g_e
.
device
(
place
)
=
in_g_e
.
device
(
place
)
=
(
out_g_e
/
std
::
sqrt
(
static_cast
<
T
>
(
h
))).
broadcast
(
bcast
);
(
out_g_e
/
std
::
sqrt
(
static_cast
<
T
>
(
h
))).
broadcast
(
bcast
);
...
...
paddle/fluid/operators/math/sequence_pooling_test.cc
0 → 100644
浏览文件 @
d0fdcb2f
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/operators/math/sequence_pooling.h"
#include <gtest/gtest.h>
#include <vector>
template
<
typename
DeviceContext
,
typename
Place
,
typename
T
>
void
TestSequencePoolingSum
(
const
paddle
::
framework
::
LoD
&
lod
)
{
paddle
::
framework
::
LoDTensor
cpu_out_grad
;
paddle
::
framework
::
LoDTensor
cpu_in_grad
;
paddle
::
framework
::
LoDTensor
out_grad
;
paddle
::
framework
::
LoDTensor
in_grad
;
const
size_t
second_dim
=
128u
;
// construct out_grad's tensor in cpu
const
size_t
out_first_dim
=
lod
[
0
].
size
()
-
1
;
auto
out_dims
=
paddle
::
framework
::
make_ddim
(
{
static_cast
<
int64_t
>
(
out_first_dim
),
static_cast
<
int64_t
>
(
second_dim
)});
cpu_out_grad
.
mutable_data
<
T
>
(
out_dims
,
paddle
::
platform
::
CPUPlace
());
for
(
int64_t
i
=
0
;
i
<
cpu_out_grad
.
numel
();
++
i
)
{
cpu_out_grad
.
data
<
T
>
()[
i
]
=
static_cast
<
T
>
(
i
);
}
// copy to dst out_grad
auto
*
place
=
new
Place
();
DeviceContext
*
context
=
new
DeviceContext
(
*
place
);
if
(
paddle
::
platform
::
is_cpu_place
(
*
place
))
{
out_grad
=
cpu_out_grad
;
}
else
{
TensorCopySync
(
cpu_out_grad
,
*
place
,
&
out_grad
);
}
// construct in_grad
in_grad
.
set_lod
(
lod
);
auto
in_dims
=
paddle
::
framework
::
make_ddim
(
{
static_cast
<
int64_t
>
(
lod
[
0
].
back
()),
static_cast
<
int64_t
>
(
second_dim
)});
in_grad
.
mutable_data
<
T
>
(
in_dims
,
context
->
GetPlace
());
// check tensor contruction result
PADDLE_ENFORCE_EQ
(
in_grad
.
dims
().
size
(),
out_grad
.
dims
().
size
());
for
(
int64_t
i
=
1
;
i
<
out_grad
.
dims
().
size
();
++
i
)
{
PADDLE_ENFORCE_EQ
(
in_grad
.
dims
()[
i
],
out_grad
.
dims
()[
i
]);
}
// call functor
paddle
::
operators
::
math
::
SequencePoolGradFunctor
<
DeviceContext
,
T
>
()(
*
context
,
"SUM"
,
out_grad
,
&
in_grad
);
if
(
paddle
::
platform
::
is_cpu_place
(
*
place
))
{
cpu_in_grad
=
in_grad
;
}
else
{
TensorCopySync
(
in_grad
,
paddle
::
platform
::
CPUPlace
(),
&
cpu_in_grad
);
cpu_in_grad
.
set_lod
(
in_grad
.
lod
());
}
EXPECT_EQ
(
in_grad
.
numel
(),
lod
[
0
].
back
()
*
second_dim
);
EXPECT_EQ
(
in_grad
.
lod
(),
lod
);
if
(
paddle
::
platform
::
is_cpu_place
(
*
place
))
{
for
(
int64_t
i
=
0
;
i
<
in_grad
.
lod
()[
0
].
size
()
-
1
;
++
i
)
{
int64_t
begin
=
in_grad
.
lod
()[
0
][
i
];
int64_t
end
=
in_grad
.
lod
()[
0
][
i
+
1
];
paddle
::
framework
::
Tensor
tmp
=
in_grad
.
Slice
(
begin
,
end
);
for
(
int64_t
j
=
0
;
j
!=
tmp
.
numel
()
/
second_dim
;
++
j
)
{
for
(
int64_t
m
=
0
;
m
!=
second_dim
;
++
m
)
{
EXPECT_EQ
(
tmp
.
data
<
T
>
()[
m
+
j
*
second_dim
],
out_grad
.
data
<
T
>
()[
m
+
i
*
second_dim
]);
}
}
}
}
else
{
for
(
int64_t
i
=
0
;
i
<
cpu_in_grad
.
lod
()[
0
].
size
()
-
1
;
++
i
)
{
int64_t
begin
=
cpu_in_grad
.
lod
()[
0
][
i
];
int64_t
end
=
cpu_in_grad
.
lod
()[
0
][
i
+
1
];
paddle
::
framework
::
Tensor
tmp
=
cpu_in_grad
.
Slice
(
begin
,
end
);
for
(
int64_t
j
=
0
;
j
!=
tmp
.
numel
()
/
second_dim
;
++
j
)
{
for
(
int64_t
m
=
0
;
m
!=
second_dim
;
++
m
)
{
EXPECT_EQ
(
tmp
.
data
<
T
>
()[
m
+
j
*
second_dim
],
cpu_out_grad
.
data
<
T
>
()[
m
+
i
*
second_dim
]);
}
}
}
}
delete
place
;
delete
context
;
}
TEST
(
SequencePoolingGrad
,
CPU_SUM
)
{
paddle
::
framework
::
LoD
lod1
;
lod1
.
push_back
(
std
::
vector
<
size_t
>
{
0
,
10
});
TestSequencePoolingSum
<
paddle
::
platform
::
CPUDeviceContext
,
paddle
::
platform
::
CPUPlace
,
float
>
(
lod1
);
paddle
::
framework
::
LoD
lod2
;
lod2
.
push_back
(
std
::
vector
<
size_t
>
{
0
,
2
,
7
,
10
});
TestSequencePoolingSum
<
paddle
::
platform
::
CPUDeviceContext
,
paddle
::
platform
::
CPUPlace
,
float
>
(
lod2
);
}
#ifdef PADDLE_WITH_CUDA
TEST
(
SequencePoolingGrad
,
CUDA_SUM
)
{
paddle
::
framework
::
LoD
lod1
;
lod1
.
push_back
(
std
::
vector
<
size_t
>
{
0
,
10
});
TestSequencePoolingSum
<
paddle
::
platform
::
CUDADeviceContext
,
paddle
::
platform
::
CUDAPlace
,
float
>
(
lod1
);
paddle
::
framework
::
LoD
lod2
;
lod2
.
push_back
(
std
::
vector
<
size_t
>
{
0
,
2
,
7
,
10
});
TestSequencePoolingSum
<
paddle
::
platform
::
CUDADeviceContext
,
paddle
::
platform
::
CUDAPlace
,
float
>
(
lod2
);
}
#endif
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