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体验新版 GitCode,发现更多精彩内容 >>
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b41f8b9d
编写于
7月 23, 2018
作者:
Q
Qiao Longfei
提交者:
GitHub
7月 23, 2018
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差异文件
Merge pull request #12295 from jacquesqiao/speedup-reduce-sum-grad-op
Speedup reduce sum grad op
上级
eec412b2
273f7375
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
137 addition
and
32 deletion
+137
-32
paddle/fluid/operators/reduce_sum_op.cc
paddle/fluid/operators/reduce_sum_op.cc
+10
-9
paddle/fluid/operators/reduce_sum_op.h
paddle/fluid/operators/reduce_sum_op.h
+59
-1
python/paddle/fluid/layers/nn.py
python/paddle/fluid/layers/nn.py
+2
-2
python/paddle/fluid/tests/unittests/test_reduce_op.py
python/paddle/fluid/tests/unittests/test_reduce_op.py
+66
-20
未找到文件。
paddle/fluid/operators/reduce_sum_op.cc
浏览文件 @
b41f8b9d
...
...
@@ -23,12 +23,13 @@ REGISTER_OP_CPU_KERNEL(
ops
::
ReduceKernel
<
paddle
::
platform
::
CPUDeviceContext
,
int
,
ops
::
SumFunctor
>
,
ops
::
ReduceKernel
<
paddle
::
platform
::
CPUDeviceContext
,
int64_t
,
ops
::
SumFunctor
>
);
REGISTER_OP_CPU_KERNEL
(
reduce_sum_grad
,
ops
::
ReduceGradKernel
<
paddle
::
platform
::
CPUDeviceContext
,
float
,
ops
::
SumGradFunctor
>
,
ops
::
ReduceGradKernel
<
paddle
::
platform
::
CPUDeviceContext
,
double
,
ops
::
SumGradFunctor
>
,
ops
::
ReduceGradKernel
<
paddle
::
platform
::
CPUDeviceContext
,
int
,
ops
::
SumGradFunctor
>
,
ops
::
ReduceGradKernel
<
paddle
::
platform
::
CPUDeviceContext
,
int64_t
,
ops
::
SumGradFunctor
>
);
REGISTER_OP_CPU_KERNEL
(
reduce_sum_grad
,
ops
::
ReduceSumGradKernel
<
paddle
::
platform
::
CPUDeviceContext
,
float
,
ops
::
SumGradFunctor
>
,
ops
::
ReduceSumGradKernel
<
paddle
::
platform
::
CPUDeviceContext
,
double
,
ops
::
SumGradFunctor
>
,
ops
::
ReduceSumGradKernel
<
paddle
::
platform
::
CPUDeviceContext
,
int
,
ops
::
SumGradFunctor
>
,
ops
::
ReduceSumGradKernel
<
paddle
::
platform
::
CPUDeviceContext
,
int64_t
,
ops
::
SumGradFunctor
>
);
paddle/fluid/operators/reduce_sum_op.h
浏览文件 @
b41f8b9d
...
...
@@ -14,11 +14,69 @@
#pragma once
#include <vector>
#include "paddle/fluid/operators/reduce_op.h"
namespace
paddle
{
namespace
operators
{
// use for loop to speed up Eigen broadcast. 4 timer faster then broadcast
template
<
typename
DeviceContext
,
typename
T
,
typename
Functor
>
class
ReduceSumGradKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
auto
dims
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"dim"
);
if
(
context
.
GetPlace
().
type
()
==
typeid
(
platform
::
CPUPlace
)
&&
dims
.
size
()
==
1
)
{
auto
*
input0
=
context
.
Input
<
Tensor
>
(
"X"
);
auto
*
input2
=
context
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
auto
*
output
=
context
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
output
->
mutable_data
<
T
>
(
context
.
GetPlace
());
const
auto
*
input2_d
=
input2
->
data
<
T
>
();
auto
*
output_d
=
output
->
data
<
T
>
();
// handle reduce_all
if
(
input2
->
dims
().
size
()
==
1
&&
input2
->
dims
()[
0
]
==
1
)
{
for
(
int64_t
i
=
0
;
i
<
framework
::
product
(
input0
->
dims
());
++
i
)
{
output_d
[
i
]
=
input2_d
[
0
];
}
return
;
}
// handle reduce by one dimension
int
reduce_dim_index
=
dims
[
0
];
if
(
reduce_dim_index
<
0
)
{
reduce_dim_index
+=
input0
->
dims
().
size
();
}
auto
&
input_dim
=
input0
->
dims
();
int64_t
before_dim
=
1
;
for
(
int
i
=
0
;
i
<
reduce_dim_index
;
++
i
)
{
before_dim
*=
input_dim
[
i
];
}
int64_t
reduce_dim
=
input_dim
[
reduce_dim_index
];
int64_t
after_dim
=
1
;
for
(
int
i
=
reduce_dim_index
+
1
;
i
<
input_dim
.
size
();
++
i
)
{
after_dim
*=
input_dim
[
i
];
}
for
(
int64_t
i
=
0
;
i
<
before_dim
;
++
i
)
{
for
(
int64_t
j
=
0
;
j
<
reduce_dim
;
++
j
)
{
for
(
int64_t
k
=
0
;
k
<
after_dim
;
++
k
)
{
output_d
[
i
*
reduce_dim
*
after_dim
+
j
*
after_dim
+
k
]
=
input2_d
[
i
*
after_dim
+
k
];
}
}
}
return
;
}
// default use Eigen broadcast
ReduceGradKernel
<
DeviceContext
,
T
,
Functor
>
kernel
;
kernel
.
Compute
(
context
);
}
};
struct
SumFunctor
{
template
<
typename
DeviceContext
,
typename
X
,
typename
Y
,
typename
Dim
>
void
operator
()(
const
DeviceContext
&
place
,
X
*
x
,
Y
*
y
,
const
Dim
&
dim
)
{
...
...
@@ -31,7 +89,7 @@ struct SumGradFunctor {
typename
DY
,
typename
Dim
>
void
operator
()(
const
DeviceContext
&
place
,
X
*
x
,
Y
*
y
,
DX
*
dx
,
DY
*
dy
,
const
Dim
&
dim
,
int
size
)
{
dx
->
device
(
place
)
=
dy
->
broadcast
(
dim
);
dx
->
device
(
place
)
=
dy
->
eval
().
broadcast
(
dim
);
}
};
...
...
python/paddle/fluid/layers/nn.py
浏览文件 @
b41f8b9d
...
...
@@ -2961,7 +2961,7 @@ def reduce_sum(input, dim=None, keep_dim=False, name=None):
# x is a Tensor variable with following elements:
# [[0.2, 0.3, 0.5, 0.9]
# [0.1, 0.2, 0.6, 0.7]]
# Each example is followed by the corresp
e
nding output tensor.
# Each example is followed by the corresp
o
nding output tensor.
fluid.layers.reduce_sum(x) # [3.5]
fluid.layers.reduce_sum(x, dim=0) # [0.3, 0.5, 1.1, 1.6]
fluid.layers.reduce_sum(x, dim=-1) # [1.9, 1.6]
...
...
@@ -2970,7 +2970,7 @@ def reduce_sum(input, dim=None, keep_dim=False, name=None):
# x is a Tensor variable with shape [2, 2, 2] and elements as below:
# [[[1, 2], [3, 4]],
# [[5, 6], [7, 8]]]
# Each example is followed by the corresp
e
nding output tensor.
# Each example is followed by the corresp
o
nding output tensor.
fluid.layers.reduce_sum(x, dim=[1, 2]) # [10, 26]
fluid.layers.reduce_sum(x, dim=[0, 1]) # [16, 20]
...
...
python/paddle/fluid/tests/unittests/test_reduce_op.py
浏览文件 @
b41f8b9d
...
...
@@ -89,15 +89,11 @@ class TestProdOp(OpTest):
self
.
check_grad
([
'X'
],
'Out'
)
class
Test
KeepDim
Reduce
(
OpTest
):
class
Test
1D
Reduce
(
OpTest
):
def
setUp
(
self
):
self
.
op_type
=
"reduce_sum"
self
.
inputs
=
{
'X'
:
np
.
random
.
random
((
5
,
6
,
10
)).
astype
(
"float64"
)}
self
.
attrs
=
{
'dim'
:
[
-
2
],
'keep_dim'
:
True
}
self
.
outputs
=
{
'Out'
:
self
.
inputs
[
'X'
].
sum
(
axis
=
tuple
(
self
.
attrs
[
'dim'
]),
keepdims
=
True
)
}
self
.
inputs
=
{
'X'
:
np
.
random
.
random
(
20
).
astype
(
"float64"
)}
self
.
outputs
=
{
'Out'
:
self
.
inputs
[
'X'
].
sum
(
axis
=
0
)}
def
test_check_output
(
self
):
self
.
check_output
()
...
...
@@ -106,32 +102,82 @@ class TestKeepDimReduce(OpTest):
self
.
check_grad
([
'X'
],
'Out'
)
class
Test
1DReduce
(
OpTest
):
class
Test
2DReduce0
(
Test1DReduce
):
def
setUp
(
self
):
self
.
op_type
=
"reduce_sum"
self
.
inputs
=
{
'X'
:
np
.
random
.
random
(
20
).
astype
(
"float64"
)}
self
.
attrs
=
{
'dim'
:
[
0
]}
self
.
inputs
=
{
'X'
:
np
.
random
.
random
((
20
,
10
)).
astype
(
"float64"
)}
self
.
outputs
=
{
'Out'
:
self
.
inputs
[
'X'
].
sum
(
axis
=
0
)}
def
test_check_output
(
self
):
self
.
check_output
()
def
test_check_grad
(
self
):
self
.
check_grad
([
'X'
],
'Out'
)
class
Test2DReduce1
(
Test1DReduce
):
def
setUp
(
self
):
self
.
op_type
=
"reduce_sum"
self
.
attrs
=
{
'dim'
:
[
1
]}
self
.
inputs
=
{
'X'
:
np
.
random
.
random
((
20
,
10
)).
astype
(
"float64"
)}
self
.
outputs
=
{
'Out'
:
self
.
inputs
[
'X'
].
sum
(
axis
=
tuple
(
self
.
attrs
[
'dim'
]))
}
class
TestReduceAll
(
OpTest
):
class
Test3DReduce0
(
Test1DReduce
):
def
setUp
(
self
):
self
.
op_type
=
"reduce_sum"
self
.
attrs
=
{
'dim'
:
[
1
]}
self
.
inputs
=
{
'X'
:
np
.
random
.
random
((
5
,
6
,
7
)).
astype
(
"float64"
)}
self
.
outputs
=
{
'Out'
:
self
.
inputs
[
'X'
].
sum
(
axis
=
tuple
(
self
.
attrs
[
'dim'
]))
}
class
Test3DReduce1
(
Test1DReduce
):
def
setUp
(
self
):
self
.
op_type
=
"reduce_sum"
self
.
attrs
=
{
'dim'
:
[
2
]}
self
.
inputs
=
{
'X'
:
np
.
random
.
random
((
5
,
6
,
7
)).
astype
(
"float64"
)}
self
.
outputs
=
{
'Out'
:
self
.
inputs
[
'X'
].
sum
(
axis
=
tuple
(
self
.
attrs
[
'dim'
]))
}
class
Test3DReduce2
(
Test1DReduce
):
def
setUp
(
self
):
self
.
op_type
=
"reduce_sum"
self
.
attrs
=
{
'dim'
:
[
-
2
]}
self
.
inputs
=
{
'X'
:
np
.
random
.
random
((
5
,
6
,
7
)).
astype
(
"float64"
)}
self
.
outputs
=
{
'Out'
:
self
.
inputs
[
'X'
].
sum
(
axis
=
tuple
(
self
.
attrs
[
'dim'
]))
}
class
Test3DReduce3
(
Test1DReduce
):
def
setUp
(
self
):
self
.
op_type
=
"reduce_sum"
self
.
attrs
=
{
'dim'
:
[
1
,
2
]}
self
.
inputs
=
{
'X'
:
np
.
random
.
random
((
5
,
6
,
7
)).
astype
(
"float64"
)}
self
.
outputs
=
{
'Out'
:
self
.
inputs
[
'X'
].
sum
(
axis
=
tuple
(
self
.
attrs
[
'dim'
]))
}
class
TestKeepDimReduce
(
Test1DReduce
):
def
setUp
(
self
):
self
.
op_type
=
"reduce_sum"
self
.
inputs
=
{
'X'
:
np
.
random
.
random
((
5
,
6
,
10
)).
astype
(
"float64"
)}
self
.
attrs
=
{
'dim'
:
[
1
],
'keep_dim'
:
True
}
self
.
outputs
=
{
'Out'
:
self
.
inputs
[
'X'
].
sum
(
axis
=
tuple
(
self
.
attrs
[
'dim'
]),
keepdims
=
self
.
attrs
[
'keep_dim'
])
}
class
TestReduceAll
(
Test1DReduce
):
def
setUp
(
self
):
self
.
op_type
=
"reduce_sum"
self
.
inputs
=
{
'X'
:
np
.
random
.
random
((
5
,
6
,
2
,
10
)).
astype
(
"float64"
)}
self
.
attrs
=
{
'reduce_all'
:
True
}
self
.
outputs
=
{
'Out'
:
self
.
inputs
[
'X'
].
sum
()}
def
test_check_output
(
self
):
self
.
check_output
()
def
test_check_grad
(
self
):
self
.
check_grad
([
'X'
],
'Out'
)
## reduction in multi dims
class
TestReduceMeanOpMultiAxises
(
OpTest
):
...
...
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