Skip to content
体验新版
项目
组织
正在加载...
登录
切换导航
打开侧边栏
PaddlePaddle
PaddleDetection
提交
27573ece
P
PaddleDetection
项目概览
PaddlePaddle
/
PaddleDetection
12 个月 前同步成功
通知
692
Star
11112
Fork
2696
代码
文件
提交
分支
Tags
贡献者
分支图
Diff
Issue
184
列表
看板
标记
里程碑
合并请求
40
Wiki
0
Wiki
分析
仓库
DevOps
项目成员
Pages
P
PaddleDetection
项目概览
项目概览
详情
发布
仓库
仓库
文件
提交
分支
标签
贡献者
分支图
比较
Issue
184
Issue
184
列表
看板
标记
里程碑
合并请求
40
合并请求
40
Pages
分析
分析
仓库分析
DevOps
Wiki
0
Wiki
成员
成员
收起侧边栏
关闭侧边栏
动态
分支图
创建新Issue
提交
Issue看板
体验新版 GitCode,发现更多精彩内容 >>
提交
27573ece
编写于
9月 18, 2018
作者:
T
Tomasz Patejko
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
MKLDNN conv + elementwise_add fusion: trailing spaces removed
上级
7f5c8a95
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
117 addition
and
89 deletion
+117
-89
paddle/fluid/framework/ir/conv_elementwise_add_mkldnn_fuse_pass.cc
...uid/framework/ir/conv_elementwise_add_mkldnn_fuse_pass.cc
+74
-63
paddle/fluid/framework/ir/conv_elementwise_add_mkldnn_fuse_pass_tester.cc
...mework/ir/conv_elementwise_add_mkldnn_fuse_pass_tester.cc
+43
-26
未找到文件。
paddle/fluid/framework/ir/conv_elementwise_add_mkldnn_fuse_pass.cc
浏览文件 @
27573ece
// 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/framework/ir/conv_elementwise_add_mkldnn_fuse_pass.h"
#include <functional>
#include "paddle/fluid/framework/ir/graph_traits.h"
namespace
paddle
{
...
...
@@ -8,15 +24,14 @@ namespace patterns {
struct
Pattern
:
public
PatternBase
{
Pattern
(
PDPattern
*
pattern
,
const
std
::
string
&
name_scope
)
:
PatternBase
{
pattern
,
name_scope
,
""
}
{
}
private:
:
PatternBase
{
pattern
,
name_scope
,
""
}
{}
private:
std
::
string
name_scope
()
{
return
name_scope_
;
}
std
::
string
repr
()
{
return
repr_
;
}
std
::
string
repr
()
{
return
repr_
;
}
size_t
id
()
{
return
id_
;
}
PDPattern
*
node_pattern
()
{
return
pattern
;
}
public:
std
::
string
node_name
(
std
::
string
op_name
)
{
return
PDNodeName
(
name_scope
(),
repr
(),
id
(),
op_name
);
...
...
@@ -37,22 +52,18 @@ struct Conv {
std
::
string
filter_name
()
{
return
"Filter"
;
}
std
::
string
output_name
()
{
return
"Output"
;
}
std
::
function
<
PDNode
*
()
>
operator
()(
std
::
shared_ptr
<
Pattern
>
pattern
)
{
std
::
function
<
PDNode
*
()
>
operator
()(
std
::
shared_ptr
<
Pattern
>
pattern
)
{
return
[
&
]()
->
PDNode
*
{
auto
conv_op
=
pattern
->
new_node
(
op_name
())
->
assert_is_op
(
"conv2d"
);
auto
conv_op
=
pattern
->
new_node
(
op_name
())
->
assert_is_op
(
"conv2d"
);
auto
input_var
=
pattern
->
new_node
(
input_name
())
->
assert_is_op_input
(
op_name
(),
input_name
());
->
assert_is_op_input
(
op_name
(),
input_name
());
auto
filter_var
=
pattern
->
new_node
(
filter_name
())
->
assert_is_op_input
(
op_name
(),
filter_name
());
->
assert_is_op_input
(
op_name
(),
filter_name
());
auto
output_var
=
pattern
->
new_node
(
output_name
())
->
assert_is_op_output
(
op_name
(),
output_name
());
->
assert_is_op_output
(
op_name
(),
output_name
());
conv_op
->
LinksFrom
({
input_var
,
filter_var
});
conv_op
->
LinksTo
({
output_var
});
...
...
@@ -68,22 +79,19 @@ struct ElementwiseAdd {
std
::
string
y_name
()
{
return
"Y"
;
}
std
::
string
out_name
()
{
return
"Out"
;
}
std
::
function
<
PDNode
*
(
PDNode
*
)
>
operator
()(
std
::
shared_ptr
<
Pattern
>
pattern
)
{
std
::
function
<
PDNode
*
(
PDNode
*
)
>
operator
()(
std
::
shared_ptr
<
Pattern
>
pattern
)
{
return
[
&
](
PDNode
*
conv_output
)
->
PDNode
*
{
auto
elementwise_add_op
=
pattern
->
new_node
(
op_name
())
->
assert_is_op
(
"elementwise_add"
);
auto
elementwise_add_op
=
pattern
->
new_node
(
op_name
())
->
assert_is_op
(
"elementwise_add"
);
auto
x_var
=
pattern
->
new_node
(
x_name
())
->
assert_is_op_input
(
op_name
(),
x_name
());
auto
x_var
=
pattern
->
new_node
(
x_name
())
->
assert_is_op_input
(
op_name
(),
x_name
());
conv_output
->
assert_is_op_input
(
op_name
(),
y_name
());
conv_output
->
assert_is_op_input
(
op_name
(),
y_name
());
auto
out_var
=
pattern
->
new_node
(
out_name
())
->
AsOutput
()
->
assert_is_op_output
(
op_name
(),
out_name
());
->
AsOutput
()
->
assert_is_op_output
(
op_name
(),
out_name
());
elementwise_add_op
->
LinksFrom
({
x_var
,
conv_output
});
elementwise_add_op
->
LinksTo
({
out_var
});
...
...
@@ -94,13 +102,13 @@ struct ElementwiseAdd {
};
Node
*
GetNodeFromSubgraph
(
const
GraphPatternDetector
::
subgraph_t
&
subgraph
,
std
::
shared_ptr
<
patterns
::
Pattern
>
pattern
,
const
std
::
string
&
op_name
)
{
std
::
shared_ptr
<
patterns
::
Pattern
>
pattern
,
const
std
::
string
&
op_name
)
{
PADDLE_ENFORCE
(
subgraph
.
count
(
pattern
->
retrieve_node
(
op_name
)),
"Node not found for PDNode %s"
,
pattern
->
node_name
(
op_name
));
Node
*
var
=
subgraph
.
at
(
pattern
->
retrieve_node
(
op_name
));
PADDLE_ENFORCE
(
var
,
"node %s not exists in the sub-graph"
);
return
var
;
}
...
...
@@ -109,10 +117,9 @@ void LinkNodes(Node* from, Node* to) {
to
->
inputs
.
push_back
(
from
);
}
template
<
typename
IT
,
typename
FindFunc
,
typename
ReplaceFunc
>
template
<
typename
IT
,
typename
FindFunc
,
typename
ReplaceFunc
>
void
ReplaceAllOccurances
(
IT
s
,
IT
e
,
FindFunc
f
,
ReplaceFunc
r
)
{
if
(
s
==
e
)
return
;
if
(
s
==
e
)
return
;
auto
it
=
std
::
find_if
(
s
,
e
,
f
);
...
...
@@ -126,8 +133,7 @@ void ReplaceAllOccurances(IT s, IT e, FindFunc f, ReplaceFunc r) {
void
CorrectGraphEdges
(
Graph
*
graph
,
Node
*
from
,
Node
*
to
)
{
for
(
auto
&
node
:
GraphTraits
::
DFS
(
*
graph
))
{
auto
same
=
std
::
find_if
(
std
::
begin
(
node
.
inputs
),
std
::
end
(
node
.
inputs
),
auto
same
=
std
::
find_if
(
std
::
begin
(
node
.
inputs
),
std
::
end
(
node
.
inputs
),
[
from
](
Node
*
n
)
{
return
n
==
from
;
});
if
(
same
!=
std
::
end
(
node
.
inputs
))
{
...
...
@@ -137,17 +143,19 @@ void CorrectGraphEdges(Graph* graph, Node* from, Node* to) {
using
input_type
=
VariableNameMap
::
value_type
;
ReplaceAllOccurances
(
std
::
begin
(
inputs
),
std
::
end
(
inputs
),
[
from
](
const
input_type
&
i
)
->
bool
{
auto
params
=
i
.
second
;
auto
pi
=
std
::
find_if
(
std
::
begin
(
params
),
std
::
end
(
params
),
std
::
bind
(
std
::
equal_to
<
std
::
string
>
(),
from
->
Name
(),
std
::
placeholders
::
_1
));
return
pi
!=
std
::
end
(
params
);
},
[
to
,
&
node
](
const
input_type
&
i
)
{
node
.
Op
()
->
SetInput
(
i
.
first
,
{
to
->
Name
()});
});
ReplaceAllOccurances
(
std
::
begin
(
inputs
),
std
::
end
(
inputs
),
[
from
](
const
input_type
&
i
)
->
bool
{
auto
params
=
i
.
second
;
auto
pi
=
std
::
find_if
(
std
::
begin
(
params
),
std
::
end
(
params
),
std
::
bind
(
std
::
equal_to
<
std
::
string
>
(),
from
->
Name
(),
std
::
placeholders
::
_1
));
return
pi
!=
std
::
end
(
params
);
},
[
to
,
&
node
](
const
input_type
&
i
)
{
node
.
Op
()
->
SetInput
(
i
.
first
,
{
to
->
Name
()});
});
}
}
}
...
...
@@ -169,7 +177,8 @@ graph_ptr ConvElementwiseAddMKLDNNFusePass::ApplyImpl(graph_ptr graph) const {
conv_output
->
AsIntermediate
();
auto
fuse_conv
=
[](
Graph
*
g
,
Node
*
conv_input
,
Node
*
conv_filter
,
Node
*
conv_output
,
Node
*
elementwise_add_x
)
{
auto
fuse_conv
=
[](
Graph
*
g
,
Node
*
conv_input
,
Node
*
conv_filter
,
Node
*
conv_output
,
Node
*
elementwise_add_x
)
{
OpDesc
op_desc
;
op_desc
.
SetType
(
"conv2d"
);
...
...
@@ -189,22 +198,23 @@ graph_ptr ConvElementwiseAddMKLDNNFusePass::ApplyImpl(graph_ptr graph) const {
patterns
::
LinkNodes
(
fused_conv_op
,
conv_output
);
};
auto
handler
=
[
&
](
const
GraphPatternDetector
::
subgraph_t
&
subgraph
,
Graph
*
g
)
{
auto
handler
=
[
&
](
const
GraphPatternDetector
::
subgraph_t
&
subgraph
,
Graph
*
g
)
{
auto
conv_op
=
patterns
::
GetNodeFromSubgraph
(
subgraph
,
pattern_ptr
,
conv_pattern
.
op_name
());
conv_pattern
.
op_name
());
auto
conv_input
=
patterns
::
GetNodeFromSubgraph
(
subgraph
,
pattern_ptr
,
conv_pattern
.
input_name
());
auto
conv_filter
=
patterns
::
GetNodeFromSubgraph
(
subgraph
,
pattern_ptr
,
conv_pattern
.
filter_name
());
auto
conv_output
=
patterns
::
GetNodeFromSubgraph
(
subgraph
,
pattern_ptr
,
conv_pattern
.
output_name
());
auto
elementwise_add_op
=
patterns
::
GetNodeFromSubgraph
(
subgraph
,
pattern_ptr
,
elementwise_add_pattern
.
op_name
());
auto
elementwise_add_x
=
patterns
::
GetNodeFromSubgraph
(
subgraph
,
pattern_ptr
,
elementwise_add_pattern
.
x_name
());
auto
elementwise_add_out
=
patterns
::
GetNodeFromSubgraph
(
subgraph
,
pattern_ptr
,
elementwise_add_pattern
.
out_name
());
conv_pattern
.
input_name
());
auto
conv_filter
=
patterns
::
GetNodeFromSubgraph
(
subgraph
,
pattern_ptr
,
conv_pattern
.
filter_name
());
auto
conv_output
=
patterns
::
GetNodeFromSubgraph
(
subgraph
,
pattern_ptr
,
conv_pattern
.
output_name
());
auto
elementwise_add_op
=
patterns
::
GetNodeFromSubgraph
(
subgraph
,
pattern_ptr
,
elementwise_add_pattern
.
op_name
());
auto
elementwise_add_x
=
patterns
::
GetNodeFromSubgraph
(
subgraph
,
pattern_ptr
,
elementwise_add_pattern
.
x_name
());
auto
elementwise_add_out
=
patterns
::
GetNodeFromSubgraph
(
subgraph
,
pattern_ptr
,
elementwise_add_pattern
.
out_name
());
fuse_conv
(
g
,
conv_input
,
conv_filter
,
conv_output
,
elementwise_add_x
);
patterns
::
CorrectGraphEdges
(
g
,
elementwise_add_out
,
conv_output
);
...
...
@@ -219,4 +229,5 @@ graph_ptr ConvElementwiseAddMKLDNNFusePass::ApplyImpl(graph_ptr graph) const {
}
// namespace framework
}
// namespace paddle
REGISTER_PASS
(
conv_elementwise_add_mkldnn_fuse_pass
,
paddle
::
framework
::
ir
::
ConvElementwiseAddMKLDNNFusePass
);
REGISTER_PASS
(
conv_elementwise_add_mkldnn_fuse_pass
,
paddle
::
framework
::
ir
::
ConvElementwiseAddMKLDNNFusePass
);
paddle/fluid/framework/ir/conv_elementwise_add_mkldnn_fuse_pass_tester.cc
浏览文件 @
27573ece
#include "paddle/fluid/framework/ir/conv_elementwise_add_mkldnn_fuse_pass.h"
#include "paddle/fluid/framework/ir/graph_traits.h"
// 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 <string>
#include <gtest/gtest.h>
#include <string>
#include "paddle/fluid/framework/ir/conv_elementwise_add_mkldnn_fuse_pass.h"
#include "paddle/fluid/framework/ir/graph_traits.h"
namespace
paddle
{
namespace
framework
{
...
...
@@ -33,10 +47,11 @@ void SetOp(ProgramDesc* prog, const std::string& type,
}
struct
IsReachable
{
using
func
=
std
::
function
<
bool
(
const
std
::
string
&
,
const
std
::
string
&
)
>
;
using
func
=
std
::
function
<
bool
(
const
std
::
string
&
,
const
std
::
string
&
)
>
;
auto
operator
()(
const
std
::
unique_ptr
<
ir
::
Graph
>&
graph
)
->
func
{
auto
find_node
=
[](
const
std
::
unique_ptr
<
ir
::
Graph
>&
graph
,
const
std
::
string
&
name
)
->
Node
*
{
auto
find_node
=
[](
const
std
::
unique_ptr
<
ir
::
Graph
>&
graph
,
const
std
::
string
&
name
)
->
Node
*
{
for
(
auto
&
node
:
GraphTraits
::
DFS
(
*
graph
))
{
if
(
name
==
node
.
Name
())
{
return
&
node
;
...
...
@@ -47,8 +62,7 @@ struct IsReachable {
};
return
[
&
](
std
::
string
from
,
const
std
::
string
to
)
->
bool
{
if
(
from
==
to
)
return
true
;
if
(
from
==
to
)
return
true
;
std
::
map
<
std
::
string
,
bool
>
visited
;
...
...
@@ -61,16 +75,14 @@ struct IsReachable {
std
::
list
<
std
::
string
>
queue
;
queue
.
push_back
(
from
);
while
(
!
queue
.
empty
())
{
while
(
!
queue
.
empty
())
{
auto
cur
=
find_node
(
graph
,
queue
.
front
());
queue
.
pop_front
();
if
(
cur
==
nullptr
)
return
false
;
if
(
cur
==
nullptr
)
return
false
;
for
(
auto
n
:
cur
->
outputs
)
{
if
(
n
->
Name
()
==
to
)
return
true
;
if
(
n
->
Name
()
==
to
)
return
true
;
if
(
!
visited
[
n
->
Name
()])
{
visited
[
n
->
Name
()]
=
true
;
...
...
@@ -87,14 +99,14 @@ TEST(ConvElementwiseAddMKLDNNFusePass, ConvolutionWithElementwiseAddRelu) {
auto
build_program_desc
=
[
&
]()
->
ProgramDesc
{
ProgramDesc
prog
;
for
(
auto
&
v
:
std
::
vector
<
std
::
string
>
({
"a"
,
"b"
,
"weights"
,
"c"
,
"d"
,
"e"
}))
{
std
::
vector
<
std
::
string
>
({
"a"
,
"b"
,
"weights"
,
"c"
,
"d"
,
"e"
}))
{
auto
*
var
=
prog
.
MutableBlock
(
0
)
->
Var
(
v
);
var
->
SetType
(
proto
::
VarType
::
LOD_TENSOR
);
if
(
v
==
"weights"
)
{
var
->
SetPersistable
(
true
);
}
}
SetOp
(
&
prog
,
"conv2d"
,
{
"a"
,
"weights"
},
{
"b"
});
SetOp
(
&
prog
,
"elementwise_add"
,
{
"c"
,
"b"
},
{
"d"
});
SetOp
(
&
prog
,
"relu"
,
{
"d"
},
{
"e"
});
...
...
@@ -109,14 +121,16 @@ TEST(ConvElementwiseAddMKLDNNFusePass, ConvolutionWithElementwiseAddRelu) {
EXPECT_TRUE
(
is_reachable
(
graph
)(
"a"
,
"relu"
));
auto
pass
=
PassRegistry
::
Instance
().
Get
(
"conv_elementwise_add_mkldnn_fuse_pass"
);
auto
pass
=
PassRegistry
::
Instance
().
Get
(
"conv_elementwise_add_mkldnn_fuse_pass"
);
int
original_nodes_num
=
graph
->
Nodes
().
size
();
graph
=
pass
->
Apply
(
std
::
move
(
graph
));
int
current_nodes_num
=
graph
->
Nodes
().
size
();
EXPECT_TRUE
(
is_reachable
(
graph
)(
"a"
,
"relu"
));
EXPECT_EQ
(
original_nodes_num
-
nodes_removed
+
nodes_added
,
current_nodes_num
);
EXPECT_EQ
(
original_nodes_num
-
nodes_removed
+
nodes_added
,
current_nodes_num
);
// Assert conv_relu op in newly generated graph
int
conv_count
=
0
;
int
elementwise_add_count
=
0
;
...
...
@@ -136,15 +150,14 @@ TEST(ConvElementwiseAddMKLDNNFusePass, ConvolutionWithElementwiseAddRelu) {
TEST
(
ConvElementwiseAddMKLDNNFusePass
,
ConvolutionElementwiseAdd
)
{
auto
build_program_desc
=
[
&
]()
->
ProgramDesc
{
ProgramDesc
prog
;
for
(
auto
&
v
:
std
::
vector
<
std
::
string
>
({
"a"
,
"b"
,
"weights"
}))
{
for
(
auto
&
v
:
std
::
vector
<
std
::
string
>
({
"a"
,
"b"
,
"weights"
}))
{
auto
*
var
=
prog
.
MutableBlock
(
0
)
->
Var
(
v
);
var
->
SetType
(
proto
::
VarType
::
LOD_TENSOR
);
if
(
v
==
"weights"
||
v
==
"bias"
)
{
var
->
SetPersistable
(
true
);
}
}
SetOp
(
&
prog
,
"conv2d"
,
{
"a"
,
"weights"
},
{
"b"
});
SetOp
(
&
prog
,
"elementwise_add"
,
{
"c"
,
"b"
},
{
"d"
});
...
...
@@ -157,14 +170,16 @@ TEST(ConvElementwiseAddMKLDNNFusePass, ConvolutionElementwiseAdd) {
IsReachable
is_reachable
;
EXPECT_TRUE
(
is_reachable
(
graph
)(
"a"
,
"d"
));
auto
pass
=
PassRegistry
::
Instance
().
Get
(
"conv_elementwise_add_mkldnn_fuse_pass"
);
auto
pass
=
PassRegistry
::
Instance
().
Get
(
"conv_elementwise_add_mkldnn_fuse_pass"
);
int
original_nodes_num
=
graph
->
Nodes
().
size
();
graph
=
pass
->
Apply
(
std
::
move
(
graph
));
int
current_nodes_num
=
graph
->
Nodes
().
size
();
EXPECT_FALSE
(
is_reachable
(
graph
)(
"a"
,
"d"
));
EXPECT_EQ
(
original_nodes_num
-
nodes_removed
+
nodes_added
,
current_nodes_num
);
EXPECT_EQ
(
original_nodes_num
-
nodes_removed
+
nodes_added
,
current_nodes_num
);
// Assert conv_relu op in newly generated graph
int
conv_count
=
0
;
int
elementwise_add_count
=
0
;
...
...
@@ -185,14 +200,14 @@ TEST(ConvElementwiseAddMKLDNNFusePass, SigmoidConvolutionAddElementwiseRelu) {
auto
build_program_desc
=
[
&
]()
->
ProgramDesc
{
ProgramDesc
prog
;
for
(
auto
&
v
:
std
::
vector
<
std
::
string
>
({
"a"
,
"b"
,
"weights"
,
"c"
,
"d"
,
"e"
,
"f"
}))
{
std
::
vector
<
std
::
string
>
({
"a"
,
"b"
,
"weights"
,
"c"
,
"d"
,
"e"
,
"f"
}))
{
auto
*
var
=
prog
.
MutableBlock
(
0
)
->
Var
(
v
);
var
->
SetType
(
proto
::
VarType
::
LOD_TENSOR
);
if
(
v
.
find
(
"weights"
))
{
var
->
SetPersistable
(
true
);
}
}
SetOp
(
&
prog
,
"sigmoid"
,
{
"a"
},
{
"b"
});
SetOp
(
&
prog
,
"conv2d"
,
{
"b"
,
"weights"
},
{
"c"
});
SetOp
(
&
prog
,
"elementwise_add"
,
{
"d"
,
"c"
},
{
"e"
});
...
...
@@ -208,14 +223,16 @@ TEST(ConvElementwiseAddMKLDNNFusePass, SigmoidConvolutionAddElementwiseRelu) {
EXPECT_TRUE
(
is_reachable
(
graph
)(
"a"
,
"f"
));
auto
pass
=
PassRegistry
::
Instance
().
Get
(
"conv_elementwise_add_mkldnn_fuse_pass"
);
auto
pass
=
PassRegistry
::
Instance
().
Get
(
"conv_elementwise_add_mkldnn_fuse_pass"
);
int
original_nodes_num
=
graph
->
Nodes
().
size
();
graph
=
pass
->
Apply
(
std
::
move
(
graph
));
int
current_nodes_num
=
graph
->
Nodes
().
size
();
EXPECT_TRUE
(
is_reachable
(
graph
)(
"a"
,
"f"
));
EXPECT_EQ
(
original_nodes_num
-
nodes_removed
+
nodes_added
,
current_nodes_num
);
EXPECT_EQ
(
original_nodes_num
-
nodes_removed
+
nodes_added
,
current_nodes_num
);
// Assert conv_relu op in newly generated graph
int
conv_count
=
0
;
int
elementwise_add_count
=
0
;
...
...
编辑
预览
Markdown
is supported
0%
请重试
或
添加新附件
.
添加附件
取消
You are about to add
0
people
to the discussion. Proceed with caution.
先完成此消息的编辑!
取消
想要评论请
注册
或
登录