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体验新版 GitCode,发现更多精彩内容 >>
提交
2fbaa5c0
编写于
5月 30, 2019
作者:
B
baojun
提交者:
tensor-tang
5月 31, 2019
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
[NGraph] added matmul op to ngraph engine test=develop (#17645)
上级
68dcb1bd
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
274 addition
and
0 deletion
+274
-0
paddle/fluid/operators/ngraph/ngraph_engine.cc
paddle/fluid/operators/ngraph/ngraph_engine.cc
+5
-0
paddle/fluid/operators/ngraph/ops/matmul_op.h
paddle/fluid/operators/ngraph/ops/matmul_op.h
+248
-0
python/paddle/fluid/tests/unittests/ngraph/test_matmul_ngraph_op.py
...dle/fluid/tests/unittests/ngraph/test_matmul_ngraph_op.py
+21
-0
未找到文件。
paddle/fluid/operators/ngraph/ngraph_engine.cc
浏览文件 @
2fbaa5c0
...
...
@@ -571,6 +571,11 @@ void NgraphEngine::Run(const framework::Scope& scope,
auto
m_parameters
=
ng_func
->
get_parameters
();
auto
m_results
=
ng_func
->
get_results
();
// Due to optimization backend may produce results in other layouts,
// make sure we get default layout for results.
for
(
auto
&
r
:
m_results
)
{
r
->
set_needs_default_layout
(
true
);
}
if
(
is_test
&&
use_cache
&&
t_in_cache_
.
find
(
func_cache_key_
)
!=
t_in_cache_
.
end
())
{
p_t_in
=
&
(
t_in_cache_
[
func_cache_key_
]);
...
...
paddle/fluid/operators/ngraph/ops/matmul_op.h
0 → 100644
浏览文件 @
2fbaa5c0
/*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 <memory>
#include <string>
#include <unordered_map>
#include <vector>
#include "ngraph/ngraph.hpp"
#include "paddle/fluid/operators/ngraph/ops/elementwise_scalar_op.h"
#include "paddle/fluid/operators/ngraph/ops/op_bridge.h"
#include "paddle/fluid/platform/ngraph_helper.h"
namespace
paddle
{
namespace
operators
{
namespace
ngraphs
{
std
::
shared_ptr
<
ngraph
::
Node
>
transposeAndFlat3D
(
const
std
::
shared_ptr
<
ngraph
::
Node
>&
input
,
const
bool
transpose
,
bool
x
=
true
)
{
auto
shape
=
input
->
get_shape
();
size_t
n
=
shape
.
size
();
std
::
shared_ptr
<
ngraph
::
Node
>
output
;
if
(
n
>=
3
)
{
std
::
vector
<
size_t
>
order
(
n
);
std
::
iota
(
std
::
begin
(
order
),
std
::
end
(
order
),
0
);
size_t
outer
=
1
;
for
(
size_t
i
=
0
;
i
<
n
-
2
;
i
++
)
{
outer
=
outer
*
shape
[
i
];
}
std
::
vector
<
size_t
>
reshape
{
outer
,
shape
[
n
-
2
],
shape
[
n
-
1
]};
if
(
transpose
==
true
)
{
order
[
n
-
2
]
=
n
-
1
;
order
[
n
-
1
]
=
n
-
2
;
reshape
[
2
]
=
shape
[
n
-
2
];
reshape
[
1
]
=
shape
[
n
-
1
];
}
output
=
std
::
make_shared
<
ngraph
::
op
::
Reshape
>
(
input
,
ngraph
::
AxisVector
(
order
),
ngraph
::
Shape
(
reshape
));
}
else
{
std
::
shared_ptr
<
ngraph
::
Node
>
temp
;
if
(
n
==
1
&&
x
==
true
)
{
temp
=
std
::
make_shared
<
ngraph
::
op
::
Reshape
>
(
input
,
ngraph
::
AxisVector
{
0
},
ngraph
::
Shape
{
1
,
shape
[
0
]});
}
else
if
(
n
==
1
&&
x
==
false
)
{
temp
=
std
::
make_shared
<
ngraph
::
op
::
Reshape
>
(
input
,
ngraph
::
AxisVector
{
0
},
ngraph
::
Shape
{
shape
[
0
],
1
});
}
else
{
temp
=
input
;
}
auto
temp_shape
=
temp
->
get_shape
();
if
(
transpose
==
true
)
{
output
=
std
::
make_shared
<
ngraph
::
op
::
Reshape
>
(
temp
,
ngraph
::
AxisVector
{
1
,
0
},
ngraph
::
Shape
{
temp_shape
[
1
],
temp_shape
[
0
]});
}
else
{
output
=
temp
;
}
}
return
output
;
}
std
::
shared_ptr
<
ngraph
::
Node
>
broadcast3D
(
const
std
::
shared_ptr
<
ngraph
::
Node
>&
input
,
size_t
axis0
)
{
auto
shape
=
input
->
get_shape
();
size_t
n
=
shape
.
size
();
if
(
n
==
2
)
{
auto
output
=
std
::
make_shared
<
ngraph
::
op
::
Broadcast
>
(
input
,
ngraph
::
Shape
{
axis0
,
shape
[
0
],
shape
[
1
]},
ngraph
::
AxisSet
{
0
});
return
output
;
}
return
input
;
}
std
::
shared_ptr
<
ngraph
::
Node
>
dotOp
(
const
std
::
shared_ptr
<
ngraph
::
Node
>&
a
,
const
std
::
shared_ptr
<
ngraph
::
Node
>&
b
)
{
std
::
shared_ptr
<
ngraph
::
Node
>
out
;
auto
a_shape
=
a
->
get_shape
();
auto
na
=
a_shape
.
size
();
auto
b_shape
=
b
->
get_shape
();
auto
nb
=
b_shape
.
size
();
if
(
na
>
2
&&
nb
>
2
)
{
out
=
std
::
make_shared
<
ngraph
::
op
::
BatchMatMul
>
(
a
,
b
);
}
else
{
out
=
std
::
make_shared
<
ngraph
::
op
::
Dot
>
(
a
,
b
);
}
return
out
;
}
std
::
shared_ptr
<
ngraph
::
Node
>
reshapeToOriginal
(
std
::
shared_ptr
<
ngraph
::
Node
>
input
,
const
ngraph
::
Shape
&
shape
)
{
auto
input_shape
=
input
->
get_shape
();
std
::
vector
<
size_t
>
axis
(
input_shape
.
size
());
std
::
iota
(
axis
.
begin
(),
axis
.
end
(),
0
);
auto
out
=
std
::
make_shared
<
ngraph
::
op
::
Reshape
>
(
input
,
axis
,
shape
);
return
out
;
}
void
BuildMatMulNode
(
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
y
=
paddle
::
platform
::
GetInputNode
(
op
,
"Y"
,
ngb_node_map
);
auto
op_attrs
=
paddle
::
framework
::
AttrReader
(
op
->
Attrs
());
bool
transpose_x
=
op_attrs
.
Get
<
bool
>
(
"transpose_X"
);
bool
transpose_y
=
op_attrs
.
Get
<
bool
>
(
"transpose_Y"
);
float
alpha
=
op_attrs
.
Get
<
float
>
(
"alpha"
);
std
::
shared_ptr
<
ngraph
::
Node
>
out
;
auto
x_shape
=
x
->
get_shape
();
auto
y_shape
=
y
->
get_shape
();
size_t
nx
=
x_shape
.
size
();
size_t
ny
=
y_shape
.
size
();
x
=
transposeAndFlat3D
(
x
,
transpose_x
,
true
);
y
=
transposeAndFlat3D
(
y
,
transpose_y
,
false
);
auto
y_shape3
=
y
->
get_shape
();
auto
x_shape3
=
x
->
get_shape
();
if
(
nx
>
2
||
ny
>
2
)
{
ngraph
::
Shape
out_shape
=
x_shape
;
if
(
nx
!=
3
)
{
x
=
broadcast3D
(
x
,
y_shape3
[
0
]);
out_shape
=
y_shape
;
}
if
(
ny
!=
3
)
{
y
=
broadcast3D
(
y
,
x_shape3
[
0
]);
out_shape
=
x_shape
;
}
auto
nout
=
out_shape
.
size
();
auto
out3
=
std
::
make_shared
<
ngraph
::
op
::
BatchMatMul
>
(
x
,
y
);
auto
out3_shape
=
out3
->
get_shape
();
out_shape
[
nout
-
1
]
=
out3_shape
[
2
];
out_shape
[
nout
-
2
]
=
out3_shape
[
1
];
out
=
std
::
make_shared
<
ngraph
::
op
::
Reshape
>
(
out3
,
ngraph
::
AxisVector
{
0
,
1
,
2
},
out_shape
);
}
else
{
out
=
std
::
make_shared
<
ngraph
::
op
::
Dot
>
(
x
,
y
);
}
auto
out_shape
=
out
->
get_shape
();
std
::
vector
<
size_t
>
axis
(
out_shape
.
size
());
std
::
iota
(
axis
.
begin
(),
axis
.
end
(),
0
);
for
(
size_t
i
=
out_shape
.
size
()
-
1
;
i
>
0
;
i
--
)
{
if
(
out_shape
[
i
]
==
1
)
{
out_shape
.
erase
(
out_shape
.
begin
()
+
i
);
}
}
auto
out_
=
std
::
make_shared
<
ngraph
::
op
::
Reshape
>
(
out
,
ngraph
::
AxisVector
(
axis
),
out_shape
);
auto
out_alpha
=
ElementwiseScalar
<
ngraph
::
op
::
Multiply
>
(
alpha
,
out_
);
paddle
::
platform
::
SetOutputNode
(
op
,
"Out"
,
out_alpha
,
ngb_node_map
);
}
void
BuildMatMulGradNode
(
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
op_attrs
=
paddle
::
framework
::
AttrReader
(
op
->
Attrs
());
auto
dout
=
paddle
::
platform
::
GetInputNode
(
op
,
"Out@GRAD"
,
ngb_node_map
);
auto
y
=
paddle
::
platform
::
GetInputNode
(
op
,
"Y"
,
ngb_node_map
);
auto
x
=
paddle
::
platform
::
GetInputNode
(
op
,
"X"
,
ngb_node_map
);
bool
is_dx
=
paddle
::
platform
::
HasOutput
(
op
,
"X@GRAD"
)
?
true
:
false
;
bool
is_dy
=
paddle
::
platform
::
HasOutput
(
op
,
"Y@GRAD"
)
?
true
:
false
;
bool
transpose_x
=
op_attrs
.
Get
<
bool
>
(
"transpose_X"
);
bool
transpose_y
=
op_attrs
.
Get
<
bool
>
(
"transpose_Y"
);
float
alpha
=
op_attrs
.
Get
<
float
>
(
"alpha"
);
auto
dout_shape
=
dout
->
get_shape
();
auto
x_shape
=
x
->
get_shape
();
auto
y_shape
=
y
->
get_shape
();
size_t
nx
=
x_shape
.
size
();
size_t
ny
=
y_shape
.
size
();
size_t
ndout
=
dout_shape
.
size
();
std
::
shared_ptr
<
ngraph
::
Node
>
x2
,
y2
;
std
::
shared_ptr
<
ngraph
::
Node
>
dout2
;
x2
=
transposeAndFlat3D
(
x
,
false
);
y2
=
transposeAndFlat3D
(
y
,
false
,
false
);
dout2
=
transposeAndFlat3D
(
dout
,
false
);
auto
x2_shape
=
x2
->
get_shape
();
auto
y2_shape
=
y2
->
get_shape
();
if
(
nx
>=
3
||
ny
>=
3
)
{
std
::
shared_ptr
<
ngraph
::
Node
>
dout_temp
;
if
(
ndout
==
2
)
{
dout_temp
=
std
::
make_shared
<
ngraph
::
op
::
Reshape
>
(
dout
,
ngraph
::
AxisVector
{
0
,
1
},
ngraph
::
Shape
{
dout_shape
[
0
],
dout_shape
[
1
],
1
});
if
(
ny
<
3
)
{
dout2
=
dout_temp
;
}
else
{
dout2
=
transposeAndFlat3D
(
dout_temp
,
true
);
}
}
x2
=
broadcast3D
(
x2
,
y_shape
[
0
]);
y2
=
broadcast3D
(
y2
,
x_shape
[
0
]);
}
else
{
dout2
=
transposeAndFlat3D
(
dout
,
false
,
nx
==
1
&&
transpose_x
==
false
);
}
if
(
transpose_y
==
false
)
{
y2
=
transposeAndFlat3D
(
y2
,
true
);
}
if
(
transpose_x
==
false
)
{
x2
=
transposeAndFlat3D
(
x2
,
true
);
}
auto
dx
=
dotOp
(
dout2
,
y2
);
auto
dy
=
dotOp
(
x2
,
dout2
);
if
(
transpose_x
==
true
)
{
dx
=
transposeAndFlat3D
(
dx
,
true
);
}
if
(
transpose_y
==
true
)
{
dy
=
transposeAndFlat3D
(
dy
,
true
);
}
if
(
nx
<
3
&&
ny
>=
3
)
{
dx
=
std
::
make_shared
<
ngraph
::
op
::
Sum
>
(
dx
,
ngraph
::
AxisSet
{
0
});
}
if
(
ny
<
3
&&
nx
>=
3
)
{
dy
=
std
::
make_shared
<
ngraph
::
op
::
Sum
>
(
dy
,
ngraph
::
AxisSet
{
0
});
}
auto
dx_t
=
reshapeToOriginal
(
dx
,
x_shape
);
auto
dy_t
=
reshapeToOriginal
(
dy
,
y_shape
);
auto
dx_scale
=
ElementwiseScalar
<
ngraph
::
op
::
Multiply
>
(
1
/
alpha
,
dx_t
);
auto
dy_scale
=
ElementwiseScalar
<
ngraph
::
op
::
Multiply
>
(
1
/
alpha
,
dy_t
);
if
(
is_dx
)
paddle
::
platform
::
SetOutputNode
(
op
,
"X@GRAD"
,
dx_scale
,
ngb_node_map
);
if
(
is_dy
)
paddle
::
platform
::
SetOutputNode
(
op
,
"Y@GRAD"
,
dy_scale
,
ngb_node_map
);
}
}
// namespace ngraphs
}
// namespace operators
}
// namespace paddle
REGISTER_NG_OP
(
matmul
,
BuildMatMulNode
);
REGISTER_NG_OP
(
matmul_grad
,
BuildMatMulGradNode
);
python/paddle/fluid/tests/unittests/ngraph/test_matmul_ngraph_op.py
0 → 100644
浏览文件 @
2fbaa5c0
# 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
from
paddle.fluid.tests.unittests.test_matmul_op
import
*
if
__name__
==
'__main__'
:
unittest
.
main
()
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