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70a887af
编写于
5月 29, 2019
作者:
P
pawelpiotrowicz
提交者:
tensor-tang
5月 29, 2019
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差异文件
[NGraph] Add reduce_sum operator for Ngraph (#17450)
test=develop
上级
29baca0d
变更
2
隐藏空白更改
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并排
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2 changed file
with
198 addition
and
0 deletion
+198
-0
paddle/fluid/operators/ngraph/ops/reduce_sum_op.h
paddle/fluid/operators/ngraph/ops/reduce_sum_op.h
+161
-0
python/paddle/fluid/tests/unittests/ngraph/test_reduce_ngraph_op.py
...dle/fluid/tests/unittests/ngraph/test_reduce_ngraph_op.py
+37
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paddle/fluid/operators/ngraph/ops/reduce_sum_op.h
0 → 100644
浏览文件 @
70a887af
/*Copyright (c) 2019 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. */
#pragma once
#include <algorithm>
#include <functional>
#include <memory>
#include <string>
#include <unordered_map>
#include <vector>
#include "ngraph/ngraph.hpp"
#include "paddle/fluid/operators/ngraph/ops/op_bridge.h"
#include "paddle/fluid/platform/ngraph_helper.h"
namespace
paddle
{
namespace
operators
{
namespace
ngraphs
{
void
BuildReduceSumNode
(
const
std
::
shared_ptr
<
paddle
::
framework
::
OperatorBase
>
&
op
,
std
::
shared_ptr
<
std
::
unordered_map
<
std
::
string
,
std
::
shared_ptr
<
ngraph
::
Node
>>>
ngb_node_map
)
{
auto
input
=
paddle
::
platform
::
GetInputNode
(
op
,
"X"
,
ngb_node_map
);
auto
op_attrs
=
paddle
::
framework
::
AttrReader
(
op
->
Attrs
());
bool
reduce_all
=
op_attrs
.
Get
<
bool
>
(
"reduce_all"
);
bool
keep_dim
=
op_attrs
.
Get
<
bool
>
(
"keep_dim"
);
std
::
vector
<
int
>
dim
=
op_attrs
.
Get
<
std
::
vector
<
int
>>
(
"dim"
);
auto
input_shape
=
input
->
get_shape
();
ngraph
::
AxisSet
axes
;
if
(
reduce_all
==
true
)
{
for
(
size_t
i
=
0
;
i
<
input_shape
.
size
();
++
i
)
{
axes
.
insert
(
i
);
}
}
else
{
for
(
auto
&
i
:
dim
)
{
if
(
i
<
0
)
{
axes
.
insert
(
input_shape
.
size
()
+
i
);
}
else
{
axes
.
insert
(
i
);
}
}
}
std
::
shared_ptr
<
ngraph
::
Node
>
reduce_sum
=
std
::
make_shared
<
ngraph
::
op
::
Sum
>
(
input
,
axes
);
if
(
keep_dim
==
true
)
{
std
::
vector
<
size_t
>
dim_shape
;
std
::
copy
(
input_shape
.
begin
(),
input_shape
.
end
(),
std
::
back_inserter
(
dim_shape
));
for
(
auto
&
i
:
dim
)
{
if
(
i
<
0
)
{
i
=
input_shape
.
size
()
+
i
;
}
dim_shape
[
i
]
=
1
;
}
std
::
vector
<
size_t
>
axis_vector
(
input_shape
.
size
()
-
dim
.
size
());
std
::
iota
(
axis_vector
.
begin
(),
axis_vector
.
end
(),
0
);
auto
reduce_sum_dim
=
std
::
make_shared
<
ngraph
::
op
::
Reshape
>
(
reduce_sum
,
ngraph
::
AxisVector
(
axis_vector
),
ngraph
::
Shape
(
dim_shape
));
paddle
::
platform
::
SetOutputNode
(
op
,
"Out"
,
reduce_sum_dim
,
ngb_node_map
);
}
else
{
if
(
reduce_sum
->
get_shape
()
==
ngraph
::
Shape
{})
{
reduce_sum
=
paddle
::
platform
::
NgReshaper
(
reduce_sum
,
ngraph
::
Shape
{
1
});
}
paddle
::
platform
::
SetOutputNode
(
op
,
"Out"
,
reduce_sum
,
ngb_node_map
);
}
}
void
BuildReduceSumGradNode
(
const
std
::
shared_ptr
<
paddle
::
framework
::
OperatorBase
>
&
op
,
std
::
shared_ptr
<
std
::
unordered_map
<
std
::
string
,
std
::
shared_ptr
<
ngraph
::
Node
>>>
ngb_node_map
)
{
auto
x
=
paddle
::
platform
::
GetInputNode
(
op
,
"X"
,
ngb_node_map
);
auto
og
=
paddle
::
platform
::
GetInputNode
(
op
,
"Out@GRAD"
,
ngb_node_map
);
auto
op_attrs
=
paddle
::
framework
::
AttrReader
(
op
->
Attrs
());
std
::
vector
<
int
>
dim
=
op_attrs
.
Get
<
std
::
vector
<
int
>>
(
"dim"
);
bool
reduce_all
=
op_attrs
.
Get
<
bool
>
(
"reduce_all"
);
bool
keep_dim
=
op_attrs
.
Get
<
bool
>
(
"keep_dim"
);
auto
og_shape
=
og
->
get_shape
();
auto
x_shape
=
x
->
get_shape
();
float
x_size
=
std
::
accumulate
(
std
::
begin
(
x_shape
),
std
::
end
(
x_shape
),
1
,
std
::
multiplies
<
float
>
());
float
og_size
=
std
::
accumulate
(
std
::
begin
(
og_shape
),
std
::
end
(
og_shape
),
1
,
std
::
multiplies
<
float
>
());
ngraph
::
AxisSet
axes
;
if
(
reduce_all
==
true
)
{
for
(
size_t
i
=
0
;
i
<
x_shape
.
size
();
i
++
)
{
axes
.
insert
(
i
);
}
}
else
{
for
(
auto
&
i
:
dim
)
{
if
(
i
<
0
)
{
axes
.
insert
(
x_shape
.
size
()
+
i
);
}
else
{
axes
.
insert
(
i
);
}
}
}
std
::
vector
<
size_t
>
axis_vector
(
og_shape
.
size
());
std
::
iota
(
axis_vector
.
begin
(),
axis_vector
.
end
(),
0
);
std
::
vector
<
size_t
>
dim_shape
;
for
(
size_t
i
=
0
;
i
<
x_shape
.
size
();
i
++
)
{
if
(
std
::
find
(
dim
.
begin
(),
dim
.
end
(),
i
)
==
dim
.
end
()
&&
std
::
find
(
dim
.
begin
(),
dim
.
end
(),
i
-
x_shape
.
size
())
==
dim
.
end
())
{
dim_shape
.
push_back
(
x_shape
[
i
]);
}
}
if
(
keep_dim
==
true
)
{
// reshape
if
(
x_size
==
og_size
)
{
paddle
::
platform
::
SetOutputNode
(
op
,
"X@GRAD"
,
og
,
ngb_node_map
);
return
;
}
auto
og_dim
=
std
::
make_shared
<
ngraph
::
op
::
Reshape
>
(
og
,
ngraph
::
AxisVector
(
axis_vector
),
ngraph
::
Shape
(
dim_shape
));
auto
result
=
std
::
make_shared
<
ngraph
::
op
::
Broadcast
>
(
og_dim
,
x_shape
,
axes
);
paddle
::
platform
::
SetOutputNode
(
op
,
"X@GRAD"
,
result
,
ngb_node_map
);
}
else
{
if
(
x_size
==
og_size
)
{
auto
og_dim
=
std
::
make_shared
<
ngraph
::
op
::
Reshape
>
(
og
,
ngraph
::
AxisVector
(
axis_vector
),
x_shape
);
paddle
::
platform
::
SetOutputNode
(
op
,
"X@GRAD"
,
og_dim
,
ngb_node_map
);
}
else
{
if
(
og
->
get_shape
().
size
()
==
1
&&
og
->
get_shape
()[
0
]
==
1
)
{
og
=
std
::
make_shared
<
ngraph
::
op
::
Reshape
>
(
og
,
ngraph
::
AxisVector
{
0
},
ngraph
::
Shape
{});
}
auto
result
=
std
::
make_shared
<
ngraph
::
op
::
Broadcast
>
(
og
,
x_shape
,
axes
);
paddle
::
platform
::
SetOutputNode
(
op
,
"X@GRAD"
,
result
,
ngb_node_map
);
}
}
}
}
// namespace ngraphs
}
// namespace operators
}
// namespace paddle
REGISTER_NG_OP
(
reduce_sum
,
BuildReduceSumNode
);
REGISTER_NG_OP
(
reduce_sum_grad
,
BuildReduceSumGradNode
);
python/paddle/fluid/tests/unittests/ngraph/test_reduce_ngraph_op.py
0 → 100644
浏览文件 @
70a887af
# Copyright (c) 2019 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.
from
__future__
import
print_function
import
unittest
,
sys
sys
.
path
.
append
(
"../"
)
import
numpy
as
np
from
test_reduce_op
import
TestSumOp
,
Test1DReduce
,
\
Test2DReduce0
,
Test2DReduce1
,
Test3DReduce0
,
Test3DReduce1
,
Test3DReduce2
,
\
Test3DReduce3
,
TestKeepDimReduce
,
TestKeepDimReduceSumMultiAxises
,
\
TestReduceSumWithDimOne
,
TestReduceSumWithNumelOne
class
Test3DReduce21
(
Test1DReduce
):
def
setUp
(
self
):
self
.
op_type
=
"reduce_sum"
self
.
attrs
=
{
'dim'
:
[
1
,
2
]}
self
.
inputs
=
{
'X'
:
np
.
random
.
random
((
20
,
1
,
5
)).
astype
(
"float64"
)}
self
.
outputs
=
{
'Out'
:
self
.
inputs
[
'X'
].
sum
(
axis
=
tuple
(
self
.
attrs
[
'dim'
]))
}
if
__name__
==
'__main__'
:
unittest
.
main
()
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