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体验新版 GitCode,发现更多精彩内容 >>
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提交
e37c9e67
编写于
10月 15, 2018
作者:
Q
Qiyang Min
提交者:
GitHub
10月 15, 2018
浏览文件
操作
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差异文件
Merge pull request #13828 from velconia/accelerate_selected_rows_functor
Accelerate SelectedRows Functors:
上级
2562eb92
3f6ec900
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
342 addition
and
9 deletion
+342
-9
paddle/fluid/operators/math/CMakeLists.txt
paddle/fluid/operators/math/CMakeLists.txt
+3
-3
paddle/fluid/operators/math/selected_rows_functor.cc
paddle/fluid/operators/math/selected_rows_functor.cc
+52
-6
paddle/fluid/operators/math/selected_rows_functor.h
paddle/fluid/operators/math/selected_rows_functor.h
+116
-0
paddle/fluid/operators/math/selected_rows_functor_test.cc
paddle/fluid/operators/math/selected_rows_functor_test.cc
+171
-0
未找到文件。
paddle/fluid/operators/math/CMakeLists.txt
浏览文件 @
e37c9e67
...
...
@@ -3,8 +3,8 @@ add_subdirectory(detail)
endif
(
NOT WIN32
)
function
(
math_library TARGET
)
# math_library is a function to create math library.
# The interface is the same as cc_library.
# math_library is a function to create math library.
# The interface is the same as cc_library.
# But it handle split GPU/CPU code and link some common library.
set
(
cc_srcs
)
set
(
cu_srcs
)
...
...
@@ -53,7 +53,7 @@ cc_library(blas SRCS blas.cc DEPS cblas framework_proto device_context)
math_library
(
math_function DEPS blas
)
math_library
(
maxouting
)
math_library
(
pooling
)
math_library
(
selected_rows_functor DEPS selected_rows math_function
)
math_library
(
selected_rows_functor DEPS selected_rows math_function
blas
)
math_library
(
sequence2batch
)
math_library
(
sequence_padding
)
math_library
(
sequence_pooling DEPS math_function
)
...
...
paddle/fluid/operators/math/selected_rows_functor.cc
浏览文件 @
e37c9e67
...
...
@@ -15,7 +15,6 @@ limitations under the License. */
#include <set>
#include <vector>
#include "paddle/fluid/operators/math/math_function.h"
#include "paddle/fluid/operators/math/selected_rows_functor.h"
namespace
paddle
{
...
...
@@ -150,6 +149,45 @@ template struct SelectedRowsAddTo<platform::CPUDeviceContext, double>;
template
struct
SelectedRowsAddTo
<
platform
::
CPUDeviceContext
,
int
>;
template
struct
SelectedRowsAddTo
<
platform
::
CPUDeviceContext
,
int64_t
>;
template
<
typename
T
>
struct
SelectedRowsSumTo
<
platform
::
CPUDeviceContext
,
T
>
{
void
operator
()(
const
platform
::
CPUDeviceContext
&
context
,
const
std
::
vector
<
framework
::
SelectedRows
*>&
input1
,
const
std
::
vector
<
int64_t
>&
input2_offsets
,
framework
::
SelectedRows
*
input2
)
{
// Ensure all selected rows have the same height
size_t
size
=
0u
;
for
(
auto
iter
=
input1
.
begin
();
iter
!=
input1
.
end
();
++
iter
)
{
auto
&
in_rows
=
(
*
iter
)
->
rows
();
size
+=
in_rows
.
end
()
-
in_rows
.
begin
();
auto
in1_height
=
(
*
iter
)
->
height
();
PADDLE_ENFORCE_EQ
(
in1_height
,
input2
->
height
());
}
// concat rows
std
::
vector
<
int64_t
>
in2_rows
;
in2_rows
.
reserve
(
in2_rows
.
size
()
+
size
);
for
(
auto
iter
=
input1
.
begin
();
iter
!=
input1
.
end
();
++
iter
)
{
const
framework
::
Vector
<
int64_t
>&
in_rows
=
(
*
iter
)
->
rows
();
in2_rows
.
insert
(
in2_rows
.
end
(),
in_rows
.
begin
(),
in_rows
.
end
());
}
input2
->
set_rows
(
in2_rows
);
auto
*
in2_value
=
input2
->
mutable_value
();
auto
*
in2_data
=
in2_value
->
data
<
T
>
();
auto
blas
=
math
::
GetBlas
<
platform
::
CPUDeviceContext
,
T
>
(
context
);
size_t
offset
=
0u
;
for
(
size_t
i
=
0u
;
i
!=
input1
.
size
();
++
i
)
{
auto
&
in_value
=
input1
[
i
]
->
value
();
const
auto
*
in_data
=
in_value
.
data
<
T
>
();
offset
+=
input2_offsets
[
i
];
blas
.
VCOPY
(
in_value
.
numel
(),
in_data
,
in2_data
+
offset
);
}
}
};
template
struct
SelectedRowsSumTo
<
platform
::
CPUDeviceContext
,
float
>;
template
struct
SelectedRowsSumTo
<
platform
::
CPUDeviceContext
,
double
>;
template
<
typename
T
>
struct
SelectedRowsAddToTensor
<
platform
::
CPUDeviceContext
,
T
>
{
void
operator
()(
const
platform
::
CPUDeviceContext
&
context
,
...
...
@@ -208,8 +246,18 @@ struct MergeAdd<platform::CPUDeviceContext, T> {
framework
::
SelectedRows
*
output
)
{
framework
::
SelectedRows
&
out
=
*
output
;
auto
input_rows
=
input
.
rows
();
std
::
set
<
int64_t
>
row_set
(
input_rows
.
begin
(),
input_rows
.
end
());
std
::
vector
<
int64_t
>
merge_rows
(
row_set
.
begin
(),
row_set
.
end
());
std
::
vector
<
int64_t
>
merge_rows
;
merge_rows
.
reserve
(
input_rows
.
size
());
std
::
unordered_map
<
int64_t
,
size_t
>
rows_pos_map
;
rows_pos_map
.
reserve
(
input_rows
.
size
());
size_t
idx
=
0u
;
for
(
std
::
vector
<
int64_t
>::
iterator
iter
=
input_rows
.
begin
();
iter
!=
input_rows
.
end
();
++
iter
)
{
if
(
rows_pos_map
.
find
(
*
iter
)
==
rows_pos_map
.
end
())
{
rows_pos_map
[
*
iter
]
=
idx
++
;
merge_rows
.
emplace_back
(
*
iter
);
}
}
auto
input_width
=
input
.
value
().
dims
()[
1
];
out
.
set_rows
(
merge_rows
);
...
...
@@ -226,7 +274,7 @@ struct MergeAdd<platform::CPUDeviceContext, T> {
auto
*
input_data
=
input
.
value
().
data
<
T
>
();
for
(
size_t
i
=
0
;
i
<
input_rows
.
size
();
i
++
)
{
size_t
out_i
=
FindPos
(
merge_rows
,
input_rows
[
i
])
;
size_t
out_i
=
rows_pos_map
[
input_rows
[
i
]]
;
for
(
int64_t
j
=
0
;
j
<
input_width
;
j
++
)
{
out_data
[
out_i
*
input_width
+
j
]
+=
input_data
[
i
*
input_width
+
j
];
}
...
...
@@ -234,8 +282,6 @@ struct MergeAdd<platform::CPUDeviceContext, T> {
}
};
template
struct
MergeAdd
<
platform
::
CPUDeviceContext
,
float
>;
template
struct
MergeAdd
<
platform
::
CPUDeviceContext
,
double
>;
template
struct
MergeAdd
<
platform
::
CPUDeviceContext
,
int
>;
template
struct
MergeAdd
<
platform
::
CPUDeviceContext
,
int64_t
>;
...
...
paddle/fluid/operators/math/selected_rows_functor.h
浏览文件 @
e37c9e67
...
...
@@ -12,8 +12,13 @@ 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. */
#pragma once
#include <vector>
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/selected_rows.h"
#include "paddle/fluid/operators/math/blas.h"
#include "paddle/fluid/operators/math/math_function.h"
#include "paddle/fluid/platform/device_context.h"
#define INLINE_FOR2(sizei, sizej) \
...
...
@@ -49,6 +54,15 @@ struct SelectedRowsAddTo {
const
int64_t
input2_offset
,
framework
::
SelectedRows
*
input2
);
};
// input2 = [all input in input1] + input2
template
<
typename
DeviceContext
,
typename
T
>
struct
SelectedRowsSumTo
{
void
operator
()(
const
DeviceContext
&
context
,
const
std
::
vector
<
framework
::
SelectedRows
*>&
input1
,
const
std
::
vector
<
int64_t
>&
input2_offsets
,
framework
::
SelectedRows
*
input2
);
};
// input2 = input1 + input2
template
<
typename
DeviceContext
,
typename
T
>
struct
SelectedRowsAddToTensor
{
...
...
@@ -70,6 +84,108 @@ struct MergeAdd {
framework
::
SelectedRows
*
output
);
};
template
<
>
struct
MergeAdd
<
platform
::
CPUDeviceContext
,
float
>
{
framework
::
SelectedRows
operator
()(
const
platform
::
CPUDeviceContext
&
context
,
const
framework
::
SelectedRows
&
input
)
{
framework
::
SelectedRows
out
;
(
*
this
)(
context
,
input
,
&
out
);
return
out
;
}
void
operator
()(
const
platform
::
CPUDeviceContext
&
context
,
const
framework
::
SelectedRows
&
input
,
framework
::
SelectedRows
*
output
)
{
framework
::
SelectedRows
&
out
=
*
output
;
auto
input_rows
=
input
.
rows
();
std
::
vector
<
int64_t
>
merge_rows
;
merge_rows
.
reserve
(
input_rows
.
size
());
std
::
unordered_map
<
int64_t
,
size_t
>
rows_pos_map
;
rows_pos_map
.
reserve
(
input_rows
.
size
());
size_t
idx
=
0u
;
for
(
std
::
vector
<
int64_t
>::
iterator
iter
=
input_rows
.
begin
();
iter
!=
input_rows
.
end
();
++
iter
)
{
if
(
rows_pos_map
.
find
(
*
iter
)
==
rows_pos_map
.
end
())
{
rows_pos_map
[
*
iter
]
=
idx
++
;
merge_rows
.
emplace_back
(
*
iter
);
}
}
auto
input_width
=
input
.
value
().
dims
()[
1
];
out
.
set_rows
(
merge_rows
);
out
.
set_height
(
input
.
height
());
out
.
mutable_value
()
->
mutable_data
<
float
>
(
framework
::
make_ddim
(
{
static_cast
<
int64_t
>
(
merge_rows
.
size
()),
input_width
}),
context
.
GetPlace
());
math
::
SetConstant
<
platform
::
CPUDeviceContext
,
float
>
constant_functor
;
constant_functor
(
context
,
out
.
mutable_value
(),
0.0
);
auto
*
out_data
=
out
.
mutable_value
()
->
data
<
float
>
();
auto
*
input_data
=
input
.
value
().
data
<
float
>
();
auto
blas
=
GetBlas
<
platform
::
CPUDeviceContext
,
float
>
(
context
);
for
(
size_t
i
=
0
;
i
<
input_rows
.
size
();
i
++
)
{
size_t
out_i
=
rows_pos_map
[
input_rows
[
i
]];
float
*
y
=
out_data
+
out_i
*
input_width
;
const
float
*
x
=
input_data
+
i
*
input_width
;
blas
.
AXPY
(
input_width
,
1.
,
x
,
y
);
}
}
};
template
<
>
struct
MergeAdd
<
platform
::
CPUDeviceContext
,
double
>
{
framework
::
SelectedRows
operator
()(
const
platform
::
CPUDeviceContext
&
context
,
const
framework
::
SelectedRows
&
input
)
{
framework
::
SelectedRows
out
;
(
*
this
)(
context
,
input
,
&
out
);
return
out
;
}
void
operator
()(
const
platform
::
CPUDeviceContext
&
context
,
const
framework
::
SelectedRows
&
input
,
framework
::
SelectedRows
*
output
)
{
framework
::
SelectedRows
&
out
=
*
output
;
auto
input_rows
=
input
.
rows
();
std
::
vector
<
int64_t
>
merge_rows
;
merge_rows
.
reserve
(
input_rows
.
size
());
std
::
unordered_map
<
int64_t
,
size_t
>
rows_pos_map
;
rows_pos_map
.
reserve
(
input_rows
.
size
());
size_t
idx
=
0u
;
for
(
std
::
vector
<
int64_t
>::
iterator
iter
=
input_rows
.
begin
();
iter
!=
input_rows
.
end
();
++
iter
)
{
if
(
rows_pos_map
.
find
(
*
iter
)
==
rows_pos_map
.
end
())
{
rows_pos_map
[
*
iter
]
=
idx
++
;
merge_rows
.
emplace_back
(
*
iter
);
}
}
auto
input_width
=
input
.
value
().
dims
()[
1
];
out
.
set_rows
(
merge_rows
);
out
.
set_height
(
input
.
height
());
out
.
mutable_value
()
->
mutable_data
<
double
>
(
framework
::
make_ddim
(
{
static_cast
<
int64_t
>
(
merge_rows
.
size
()),
input_width
}),
context
.
GetPlace
());
math
::
SetConstant
<
platform
::
CPUDeviceContext
,
double
>
constant_functor
;
constant_functor
(
context
,
out
.
mutable_value
(),
0.0
);
auto
*
out_data
=
out
.
mutable_value
()
->
data
<
double
>
();
auto
*
input_data
=
input
.
value
().
data
<
double
>
();
auto
blas
=
GetBlas
<
platform
::
CPUDeviceContext
,
double
>
(
context
);
for
(
size_t
i
=
0
;
i
<
input_rows
.
size
();
i
++
)
{
size_t
out_i
=
rows_pos_map
[
input_rows
[
i
]];
double
*
y
=
out_data
+
out_i
*
input_width
;
const
double
*
x
=
input_data
+
i
*
input_width
;
blas
.
AXPY
(
input_width
,
1.
,
x
,
y
);
}
}
};
template
<
typename
DeviceContext
,
typename
T
>
struct
Add
{
framework
::
SelectedRows
operator
()(
const
DeviceContext
&
context
,
...
...
paddle/fluid/operators/math/selected_rows_functor_test.cc
浏览文件 @
e37c9e67
...
...
@@ -219,3 +219,174 @@ TEST(selected_rows_functor, cpu_add_to) {
// row9: 2.0 + 3.0
EXPECT_EQ
(
tensor1_data
[
9
*
row_numel
+
6
],
5.0
);
}
TEST
(
selected_rows_functor
,
cpu_merge_add_float
)
{
paddle
::
platform
::
CPUPlace
cpu_place
;
paddle
::
platform
::
CPUDeviceContext
ctx
(
cpu_place
);
paddle
::
operators
::
math
::
SetConstant
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
functor
;
int64_t
height
=
10
;
int64_t
row_numel
=
10
;
std
::
vector
<
int64_t
>
rows
{
0
,
4
,
4
,
7
};
std
::
unique_ptr
<
paddle
::
framework
::
SelectedRows
>
selected_rows
{
new
paddle
::
framework
::
SelectedRows
(
rows
,
height
)};
auto
*
in_value
=
selected_rows
->
mutable_value
();
in_value
->
mutable_data
<
float
>
(
paddle
::
framework
::
make_ddim
(
{
static_cast
<
int64_t
>
(
rows
.
size
()),
row_numel
}),
cpu_place
);
functor
(
ctx
,
in_value
,
1.0
);
std
::
unique_ptr
<
paddle
::
framework
::
SelectedRows
>
output
{
new
paddle
::
framework
::
SelectedRows
()};
paddle
::
operators
::
math
::
scatter
::
MergeAdd
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
merge_add_functor
;
merge_add_functor
(
ctx
,
*
selected_rows
,
output
.
get
());
auto
out_height
=
output
->
height
();
EXPECT_EQ
(
out_height
,
height
);
auto
&
out_rows
=
output
->
rows
();
EXPECT_EQ
(
out_rows
[
0
],
0
);
EXPECT_EQ
(
out_rows
[
1
],
4
);
EXPECT_EQ
(
out_rows
[
2
],
7
);
auto
*
out_data
=
output
->
value
().
data
<
float
>
();
EXPECT_EQ
(
out_data
[
0
*
row_numel
],
1.0
);
EXPECT_EQ
(
out_data
[
1
*
row_numel
],
2.0
);
EXPECT_EQ
(
out_data
[
2
*
row_numel
],
1.0
);
}
TEST
(
selected_rows_functor
,
cpu_merge_add_int
)
{
paddle
::
platform
::
CPUPlace
cpu_place
;
paddle
::
platform
::
CPUDeviceContext
ctx
(
cpu_place
);
paddle
::
operators
::
math
::
SetConstant
<
paddle
::
platform
::
CPUDeviceContext
,
int
>
functor
;
int64_t
height
=
10
;
int64_t
row_numel
=
10
;
std
::
vector
<
int64_t
>
rows
{
0
,
4
,
4
,
7
};
std
::
unique_ptr
<
paddle
::
framework
::
SelectedRows
>
selected_rows
{
new
paddle
::
framework
::
SelectedRows
(
rows
,
height
)};
auto
*
in_value
=
selected_rows
->
mutable_value
();
in_value
->
mutable_data
<
int
>
(
paddle
::
framework
::
make_ddim
(
{
static_cast
<
int64_t
>
(
rows
.
size
()),
row_numel
}),
cpu_place
);
functor
(
ctx
,
in_value
,
1
);
std
::
unique_ptr
<
paddle
::
framework
::
SelectedRows
>
output
{
new
paddle
::
framework
::
SelectedRows
()};
paddle
::
operators
::
math
::
scatter
::
MergeAdd
<
paddle
::
platform
::
CPUDeviceContext
,
int
>
merge_add_functor
;
merge_add_functor
(
ctx
,
*
selected_rows
,
output
.
get
());
auto
out_height
=
output
->
height
();
EXPECT_EQ
(
out_height
,
height
);
auto
&
out_rows
=
output
->
rows
();
EXPECT_EQ
(
out_rows
[
0
],
0
);
EXPECT_EQ
(
out_rows
[
1
],
4
);
EXPECT_EQ
(
out_rows
[
2
],
7
);
auto
*
out_data
=
output
->
value
().
data
<
int
>
();
EXPECT_EQ
(
out_data
[
0
*
row_numel
],
1
);
EXPECT_EQ
(
out_data
[
1
*
row_numel
],
2
);
EXPECT_EQ
(
out_data
[
2
*
row_numel
],
1
);
}
TEST
(
selected_rows_functor
,
cpu_sum_to
)
{
paddle
::
platform
::
CPUPlace
cpu_place
;
paddle
::
platform
::
CPUDeviceContext
ctx
(
cpu_place
);
paddle
::
operators
::
math
::
SetConstant
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
functor
;
int64_t
height
=
10
;
int64_t
row_numel
=
10
;
std
::
vector
<
int64_t
>
rows1
{
0
,
4
,
7
};
std
::
unique_ptr
<
paddle
::
framework
::
SelectedRows
>
selected_rows1
{
new
paddle
::
framework
::
SelectedRows
(
rows1
,
height
)};
auto
*
in1_value
=
selected_rows1
->
mutable_value
();
in1_value
->
mutable_data
<
float
>
(
paddle
::
framework
::
make_ddim
(
{
static_cast
<
int64_t
>
(
rows1
.
size
()),
row_numel
}),
cpu_place
);
functor
(
ctx
,
in1_value
,
1.0
);
std
::
vector
<
int64_t
>
rows2
{
0
,
5
,
7
,
9
};
std
::
unique_ptr
<
paddle
::
framework
::
SelectedRows
>
selected_rows2
{
new
paddle
::
framework
::
SelectedRows
(
rows2
,
height
)};
auto
*
in2_value
=
selected_rows2
->
mutable_value
();
in2_value
->
mutable_data
<
float
>
(
paddle
::
framework
::
make_ddim
(
{
static_cast
<
int64_t
>
(
rows2
.
size
()),
row_numel
}),
cpu_place
);
functor
(
ctx
,
in2_value
,
2.0
);
std
::
unique_ptr
<
paddle
::
framework
::
SelectedRows
>
output
{
new
paddle
::
framework
::
SelectedRows
()};
output
->
set_height
(
height
);
auto
*
out_value
=
output
->
mutable_value
();
// simplely concat two SelectedRows
out_value
->
mutable_data
<
float
>
(
paddle
::
framework
::
make_ddim
({
7
,
10
}),
cpu_place
);
paddle
::
operators
::
math
::
SelectedRowsSumTo
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
sum_to_functor
;
sum_to_functor
(
ctx
,
std
::
vector
<
paddle
::
framework
::
SelectedRows
*>
(
{
selected_rows1
.
get
(),
selected_rows2
.
get
()}),
std
::
vector
<
int64_t
>
({
0
,
in1_value
->
numel
()}),
output
.
get
());
auto
out_height
=
output
->
height
();
EXPECT_EQ
(
out_height
,
height
);
auto
&
out_rows
=
output
->
rows
();
// input1 rows
EXPECT_EQ
(
out_rows
[
0
],
0
);
EXPECT_EQ
(
out_rows
[
1
],
4
);
EXPECT_EQ
(
out_rows
[
2
],
7
);
// input2 rows
EXPECT_EQ
(
out_rows
[
3
],
0
);
EXPECT_EQ
(
out_rows
[
4
],
5
);
EXPECT_EQ
(
out_rows
[
5
],
7
);
EXPECT_EQ
(
out_rows
[
6
],
9
);
auto
*
out_data
=
output
->
value
().
data
<
float
>
();
// input1 value
EXPECT_EQ
(
out_data
[
0
*
row_numel
+
0
],
1.0
);
EXPECT_EQ
(
out_data
[
0
*
row_numel
+
8
],
1.0
);
EXPECT_EQ
(
out_data
[
1
*
row_numel
+
1
],
1.0
);
EXPECT_EQ
(
out_data
[
2
*
row_numel
+
6
],
1.0
);
// input2 value
EXPECT_EQ
(
out_data
[
3
*
row_numel
+
3
],
2.0
);
EXPECT_EQ
(
out_data
[
3
*
row_numel
+
8
],
2.0
);
EXPECT_EQ
(
out_data
[
4
*
row_numel
+
4
],
2.0
);
EXPECT_EQ
(
out_data
[
5
*
row_numel
+
7
],
2.0
);
EXPECT_EQ
(
out_data
[
6
*
row_numel
+
9
],
2.0
);
std
::
unique_ptr
<
paddle
::
framework
::
Tensor
>
tensor1
{
new
paddle
::
framework
::
Tensor
()};
tensor1
->
mutable_data
<
float
>
(
paddle
::
framework
::
make_ddim
({
height
,
row_numel
}),
cpu_place
);
functor
(
ctx
,
tensor1
.
get
(),
3.0
);
paddle
::
operators
::
math
::
SelectedRowsAddToTensor
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
add_to_tensor_functor
;
add_to_tensor_functor
(
ctx
,
*
output
,
tensor1
.
get
());
auto
*
tensor1_data
=
tensor1
->
data
<
float
>
();
// row0: 1.0 + 2.0 + 3.0
EXPECT_EQ
(
tensor1_data
[
0
*
row_numel
+
0
],
6.0
);
// row1: 3.0
EXPECT_EQ
(
tensor1_data
[
1
*
row_numel
+
1
],
3.0
);
// row4 : 1.0 + 3.0
EXPECT_EQ
(
tensor1_data
[
4
*
row_numel
+
6
],
4.0
);
// row5: 2.0 + 3.0
EXPECT_EQ
(
tensor1_data
[
5
*
row_numel
+
7
],
5.0
);
// row6: 3.0
EXPECT_EQ
(
tensor1_data
[
6
*
row_numel
+
1
],
3.0
);
// row7: 1.0 + 2.0 + 3.0
EXPECT_EQ
(
tensor1_data
[
7
*
row_numel
+
3
],
6.0
);
// row9: 2.0 + 3.0
EXPECT_EQ
(
tensor1_data
[
9
*
row_numel
+
6
],
5.0
);
}
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