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
wmsofts
Paddle
提交
7c6835ca
P
Paddle
项目概览
wmsofts
/
Paddle
与 Fork 源项目一致
Fork自
PaddlePaddle / Paddle
通知
1
Star
0
Fork
0
代码
文件
提交
分支
Tags
贡献者
分支图
Diff
Issue
0
列表
看板
标记
里程碑
合并请求
0
Wiki
0
Wiki
分析
仓库
DevOps
项目成员
Pages
P
Paddle
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
0
Issue
0
列表
看板
标记
里程碑
合并请求
0
合并请求
0
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 >>
未验证
提交
7c6835ca
编写于
10月 17, 2022
作者:
H
hong
提交者:
GitHub
10月 17, 2022
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
Revert "add common subexpression elimination (#44386)" (#47062)
This reverts commit
166ff39a
.
上级
776e80a6
变更
5
隐藏空白更改
内联
并排
Showing
5 changed file
with
0 addition
and
523 deletion
+0
-523
paddle/fluid/framework/ir/CMakeLists.txt
paddle/fluid/framework/ir/CMakeLists.txt
+0
-5
paddle/fluid/framework/ir/common_subexpression_elimination_pass.cc
...uid/framework/ir/common_subexpression_elimination_pass.cc
+0
-335
paddle/fluid/framework/ir/common_subexpression_elimination_pass.h
...luid/framework/ir/common_subexpression_elimination_pass.h
+0
-51
paddle/fluid/framework/ir/common_subexpression_elimination_pass_tester.cc
...mework/ir/common_subexpression_elimination_pass_tester.cc
+0
-131
paddle/fluid/inference/api/paddle_pass_builder.cc
paddle/fluid/inference/api/paddle_pass_builder.cc
+0
-1
未找到文件。
paddle/fluid/framework/ir/CMakeLists.txt
100644 → 100755
浏览文件 @
7c6835ca
...
...
@@ -115,7 +115,6 @@ pass_library(gpu_cpu_map_matmul_to_mul_pass inference)
pass_library
(
dense_fc_to_sparse_pass inference
)
pass_library
(
dense_multihead_matmul_to_sparse_pass inference
)
pass_library
(
generate_pass DEPS pass_desc_proto
)
pass_library
(
common_subexpression_elimination_pass inference
)
target_link_libraries
(
generate_pass pass_desc_proto
)
if
(
WITH_TENSORRT
)
...
...
@@ -327,10 +326,6 @@ cc_test(
test_generate_pass_cc
SRCS generate_pass_tester.cc
DEPS generate_pass pass_desc_proto
)
cc_test
(
test_common_subexpression_elimination_pass_cc
SRCS common_subexpression_elimination_pass_tester.cc
DEPS common_subexpression_elimination_pass
)
cc_test
(
test_delete_dropout_pass_cc
SRCS delete_dropout_op_pass_test.cc
...
...
paddle/fluid/framework/ir/common_subexpression_elimination_pass.cc
已删除
100644 → 0
浏览文件 @
776e80a6
// Copyright (c) 2022 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/common_subexpression_elimination_pass.h"
#include <string>
#include <type_traits>
#include "paddle/fluid/framework/framework.pb.h"
#include "paddle/fluid/framework/ir/graph_helper.h"
#include "paddle/fluid/framework/ir/graph_pattern_detector.h"
#include "paddle/fluid/framework/ir/node.h"
#include "paddle/fluid/framework/op_version_registry.h"
#include "paddle/fluid/framework/type_defs.h"
#include "paddle/phi/core/enforce.h"
#include "paddle/utils/variant.h"
namespace
{
std
::
string
NodeTypeToString
(
paddle
::
framework
::
ir
::
Node
::
Type
type
)
{
if
(
type
==
paddle
::
framework
::
ir
::
Node
::
Type
::
kOperation
)
{
return
"kOperation"
;
}
else
{
return
"kVariable"
;
}
}
const
std
::
unordered_set
<
std
::
string
>
commutative_operators
{
"mul"
,
"bitwise_and"
,
"bitwise_or"
,
"equal_all"
,
"equal"
,
"not_equal"
,
"logical_and"
,
"logical_or"
,
"elementwise_max"
,
"elementwise_fmax"
,
"elementwise_min"
,
"elementwise_fmin"
,
"elementwise_mul"
,
"elementwise_add"
,
"add_p"
,
"max_p"
,
"mul_p"
,
"eq_p"
,
"ne_p"
};
const
std
::
unordered_set
<
std
::
string
>
nondeterministic_operators
{
"dropout"
,
"dropout_nd"
,
"gaussian_random_batch_size_like"
,
"gaussian_random"
,
"randint"
,
"random_crop"
,
"random_routing"
,
"randperm"
,
"uniform_random_batch_size_like"
,
"uniform_random_inplace"
,
"uniform_random"
,
"fused_bias_dropout_residual_layer_norm"
};
const
std
::
unordered_set
<
std
::
string
>
side_effect_operators
{
"feed"
,
"cast"
,
"fetch"
,
"fill_constant"
,
"fill_constant_batch_size_like"
};
template
<
class
T
>
inline
void
HashCombine
(
std
::
size_t
*
seed
,
const
T
&
v
)
{
std
::
hash
<
T
>
hasher
;
(
*
seed
)
^=
hasher
(
v
)
+
0x9e3779b9
+
((
*
seed
)
<<
6
)
+
((
*
seed
)
>>
2
);
}
}
// namespace
namespace
std
{
#define HASH_ATTRIBUTE(attr, id, type) \
do { \
if (attr.index() == id) { \
return std::hash<type>{}(get<id>(attr)); \
} \
} while (0)
#define HASH_VECTOR_ATTRIBUTE(attr, id, type) \
do { \
if (attr.index() == id) { \
std::vector<type> vec = get<id>(attr); \
size_t seed = 0; \
for (const auto &v : vec) { \
HashCombine(&seed, v); \
} \
return seed; \
} \
} while (0)
template
<
>
struct
hash
<
paddle
::
framework
::
proto
::
VarType_Type
>
{
size_t
operator
()(
const
paddle
::
framework
::
proto
::
VarType_Type
&
attr
)
const
{
using
type
=
typename
std
::
underlying_type
<
paddle
::
framework
::
proto
::
VarType_Type
>::
type
;
return
std
::
hash
<
type
>
()(
static_cast
<
type
>
(
attr
));
}
};
template
<
>
struct
hash
<
paddle
::
framework
::
Attribute
>
{
size_t
operator
()(
const
paddle
::
framework
::
Attribute
&
attr
)
const
{
if
(
attr
.
index
()
==
0
)
{
return
0
;
}
if
(
attr
.
index
()
==
7
)
{
return
static_cast
<
size_t
>
(
get
<
7
>
(
attr
));
}
HASH_ATTRIBUTE
(
attr
,
1
,
int
);
HASH_ATTRIBUTE
(
attr
,
2
,
float
);
HASH_ATTRIBUTE
(
attr
,
3
,
std
::
string
);
HASH_VECTOR_ATTRIBUTE
(
attr
,
4
,
int
);
HASH_VECTOR_ATTRIBUTE
(
attr
,
5
,
float
);
HASH_VECTOR_ATTRIBUTE
(
attr
,
6
,
std
::
string
);
HASH_ATTRIBUTE
(
attr
,
8
,
std
::
vector
<
bool
>
);
HASH_ATTRIBUTE
(
attr
,
9
,
paddle
::
framework
::
BlockDesc
*
);
HASH_ATTRIBUTE
(
attr
,
10
,
int64_t
);
HASH_VECTOR_ATTRIBUTE
(
attr
,
11
,
paddle
::
framework
::
BlockDesc
*
);
HASH_VECTOR_ATTRIBUTE
(
attr
,
12
,
int64_t
);
HASH_VECTOR_ATTRIBUTE
(
attr
,
13
,
double
);
return
0
;
}
};
}
// namespace std
namespace
paddle
{
namespace
framework
{
namespace
ir
{
void
CommonSubexpressionEliminationPass
::
ApplyImpl
(
ir
::
Graph
*
graph
)
const
{
PADDLE_ENFORCE_EQ
(
graph
->
IsMainGraph
(),
true
,
platform
::
errors
::
InvalidArgument
(
"CommonSubexpressionEliminationPass only accepts main graph"
));
CommonSubexpressionEliminate
(
graph
,
graph
,
[](
Node
*
)
->
Node
*
{
return
nullptr
;
});
}
void
CommonSubexpressionEliminationPass
::
CommonSubexpressionEliminate
(
ir
::
Graph
*
main_graph
,
ir
::
Graph
*
graph
,
std
::
function
<
Node
*
(
Node
*
)
>
parent_exist_nodes
)
const
{
const
char
*
kSubBlock
=
"sub_block"
;
std
::
unordered_set
<
ir
::
Node
*
,
HashOpNode
,
EqualOpNode
>
exist_nodes
;
std
::
vector
<
Node
*>
nodes
=
TopologySortOperations
(
*
graph
);
for
(
Node
*
node
:
nodes
)
{
if
(
node
->
inputs
.
empty
())
{
continue
;
}
if
(
side_effect_operators
.
count
(
node
->
Name
())
!=
0
)
{
continue
;
}
if
(
nondeterministic_operators
.
count
(
node
->
Name
())
!=
0
)
{
continue
;
}
if
(
node
->
Op
()
->
HasAttr
(
kSubBlock
))
{
auto
sub_block_id
=
node
->
Op
()
->
GetAttrIfExists
<
BlockDesc
*>
(
kSubBlock
)
->
ID
();
CommonSubexpressionEliminate
(
main_graph
,
main_graph
->
GetSubGraph
(
sub_block_id
),
[
&
exist_nodes
,
&
parent_exist_nodes
](
Node
*
node
)
->
Node
*
{
auto
exist_node
=
exist_nodes
.
find
(
node
);
if
(
exist_node
!=
exist_nodes
.
end
())
{
return
*
exist_node
;
}
return
parent_exist_nodes
(
node
);
});
continue
;
}
Node
*
exist_node
=
parent_exist_nodes
(
node
);
if
(
exist_node
==
nullptr
)
{
auto
res
=
exist_nodes
.
insert
(
node
);
if
(
!
res
.
second
)
{
exist_node
=
*
res
.
first
;
}
}
if
(
exist_node
!=
nullptr
)
{
for
(
size_t
i
=
0
;
i
<
exist_node
->
outputs
.
size
();
++
i
)
{
Node
*
exist_node_output
=
exist_node
->
outputs
[
i
];
Node
*
current_node_output
=
node
->
outputs
[
i
];
std
::
vector
<
Node
*>
current_node_output_outputs
=
current_node_output
->
outputs
;
for
(
size_t
i
=
0
;
i
<
current_node_output_outputs
.
size
();
++
i
)
{
IR_NODE_LINK_TO
(
exist_node_output
,
current_node_output_outputs
[
i
]);
}
}
GraphSafeRemoveNodes
(
graph
,
std
::
unordered_set
<
const
Node
*>
(
node
->
outputs
.
begin
(),
node
->
outputs
.
end
()));
GraphSafeRemoveNodes
(
graph
,
{
node
});
}
}
}
size_t
HashOpNode
::
operator
()(
const
Node
*
node
)
const
{
PADDLE_ENFORCE_EQ
(
node
->
IsOp
(),
true
,
platform
::
errors
::
InvalidArgument
(
"HashOpNode only supports operation node type"
));
size_t
seed
=
0
;
std
::
vector
<
Node
*>
inputs
(
node
->
inputs
);
if
(
commutative_operators
.
count
(
node
->
Name
())
!=
0
)
{
auto
comparator
=
[](
Node
*
a
,
Node
*
b
)
{
return
a
->
Name
()
>
b
->
Name
();
};
std
::
stable_sort
(
inputs
.
begin
(),
inputs
.
end
(),
comparator
);
}
for
(
size_t
i
=
0
;
i
<
inputs
.
size
();
++
i
)
{
HashCombine
(
&
seed
,
inputs
[
i
]
->
id
());
HashCombine
(
&
seed
,
node
->
GraphId
());
}
const
std
::
string
kDepVarName
=
std
::
string
(
Node
::
kControlDepVarName
);
for
(
size_t
i
=
0
;
i
<
node
->
outputs
.
size
();
++
i
)
{
if
(
node
->
outputs
[
i
]
==
nullptr
)
{
continue
;
}
if
(
node
->
outputs
[
i
]
->
IsCtrlVar
())
{
HashCombine
(
&
seed
,
kDepVarName
);
}
else
if
(
node
->
outputs
[
i
]
->
IsVar
())
{
HashCombine
(
&
seed
,
node
->
outputs
[
i
]
->
Var
()
->
GetType
());
}
}
OpDesc
*
desc
=
node
->
Op
();
std
::
vector
<
std
::
string
>
attributes
=
desc
->
AttrNames
();
sort
(
attributes
.
begin
(),
attributes
.
end
());
for
(
const
std
::
string
&
attribute
:
attributes
)
{
HashCombine
(
&
seed
,
desc
->
GetAttr
(
attribute
));
}
return
seed
;
}
bool
EqualOpNode
::
operator
()(
const
Node
*
lhs
,
const
Node
*
rhs
)
const
{
PADDLE_ENFORCE_EQ
(
lhs
->
IsOp
()
&&
rhs
->
IsOp
(),
true
,
platform
::
errors
::
InvalidArgument
(
"EqualOpNode only supports operation node type"
));
if
(
lhs
==
nullptr
&&
rhs
==
nullptr
)
{
return
true
;
}
if
(
lhs
==
nullptr
||
rhs
==
nullptr
)
{
return
false
;
}
if
(
lhs
->
NodeType
()
!=
rhs
->
NodeType
())
{
return
false
;
}
if
(
lhs
->
Name
()
!=
rhs
->
Name
())
{
return
false
;
}
std
::
vector
<
Node
*>
lhs_inputs
(
lhs
->
inputs
);
std
::
vector
<
Node
*>
rhs_inputs
(
rhs
->
inputs
);
if
(
commutative_operators
.
count
(
lhs
->
Name
())
!=
0
)
{
auto
comparator
=
[](
Node
*
a
,
Node
*
b
)
{
return
a
->
Name
()
>
b
->
Name
();
};
std
::
stable_sort
(
lhs_inputs
.
begin
(),
lhs_inputs
.
end
(),
comparator
);
std
::
stable_sort
(
rhs_inputs
.
begin
(),
rhs_inputs
.
end
(),
comparator
);
}
// compare inputs value
if
(
lhs_inputs
.
size
()
!=
rhs_inputs
.
size
())
{
return
false
;
}
if
(
!
std
::
equal
(
lhs_inputs
.
begin
(),
lhs_inputs
.
end
(),
rhs_inputs
.
begin
()))
{
return
false
;
}
// compare attribute
const
OpDesc
*
lhs_desc
=
lhs
->
Op
();
const
OpDesc
*
rhs_desc
=
rhs
->
Op
();
std
::
vector
<
std
::
string
>
lhs_attr_names
=
lhs_desc
->
AttrNames
();
std
::
vector
<
std
::
string
>
rhs_attr_names
=
rhs_desc
->
AttrNames
();
if
(
lhs_attr_names
.
size
()
!=
rhs_attr_names
.
size
())
{
return
false
;
}
std
::
sort
(
lhs_attr_names
.
begin
(),
lhs_attr_names
.
end
());
std
::
sort
(
rhs_attr_names
.
begin
(),
rhs_attr_names
.
end
());
for
(
size_t
i
=
0
;
i
<
lhs_attr_names
.
size
();
++
i
)
{
if
(
lhs_attr_names
[
i
]
!=
rhs_attr_names
[
i
])
{
return
false
;
}
if
(
lhs_desc
->
GetAttr
(
lhs_attr_names
[
i
])
!=
rhs_desc
->
GetAttr
(
rhs_attr_names
[
i
]))
{
return
false
;
}
}
// compare outputs value type
std
::
vector
<
Node
*>
lhs_outputs
(
lhs
->
outputs
);
std
::
vector
<
Node
*>
rhs_outputs
(
rhs
->
outputs
);
if
(
lhs_outputs
.
size
()
!=
rhs_outputs
.
size
())
{
return
false
;
}
for
(
size_t
i
=
0
;
i
<
lhs_outputs
.
size
();
++
i
)
{
if
(
!
lhs_outputs
[
i
]
->
IsVar
()
||
!
rhs_outputs
[
i
]
->
IsVar
())
{
return
false
;
}
if
(
lhs_outputs
[
i
]
->
IsCtrlVar
()
!=
rhs_outputs
[
i
]
->
IsCtrlVar
())
{
return
false
;
}
if
(
lhs_outputs
[
i
]
->
IsCtrlVar
()
&&
rhs_outputs
[
i
]
->
IsCtrlVar
())
{
continue
;
}
if
(
lhs_outputs
[
i
]
->
Var
()
->
GetType
()
!=
rhs_outputs
[
i
]
->
Var
()
->
GetType
())
{
return
false
;
}
}
return
true
;
}
}
// namespace ir
}
// namespace framework
}
// namespace paddle
REGISTER_PASS
(
common_subexpression_elimination_pass
,
paddle
::
framework
::
ir
::
CommonSubexpressionEliminationPass
);
REGISTER_PASS_CAPABILITY
(
common_subexpression_elimination_pass
);
paddle/fluid/framework/ir/common_subexpression_elimination_pass.h
已删除
100644 → 0
浏览文件 @
776e80a6
// Copyright (c) 2022 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 <iostream>
#include "paddle/fluid/framework/ir/fuse_pass_base.h"
namespace
paddle
{
namespace
framework
{
namespace
ir
{
class
Graph
;
class
CommonSubexpressionEliminationPass
:
public
FusePassBase
{
public:
CommonSubexpressionEliminationPass
()
{}
protected:
void
ApplyImpl
(
ir
::
Graph
*
graph
)
const
override
;
private:
void
CommonSubexpressionEliminate
(
ir
::
Graph
*
main_graph
,
ir
::
Graph
*
graph
,
std
::
function
<
Node
*
(
Node
*
)
>
parent_exist_nodes
)
const
;
};
struct
HashOpNode
{
size_t
operator
()(
const
Node
*
node
)
const
;
};
struct
EqualOpNode
{
bool
operator
()(
const
Node
*
lhs
,
const
Node
*
rhs
)
const
;
};
}
// namespace ir
}
// namespace framework
}
// namespace paddle
paddle/fluid/framework/ir/common_subexpression_elimination_pass_tester.cc
已删除
100644 → 0
浏览文件 @
776e80a6
/* Copyright (c) 2022 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 <gtest/gtest.h>
#include <functional>
#include <sstream>
#include <string>
#include <unordered_set>
#include "paddle/fluid/framework/ir/common_subexpression_elimination_pass.h"
#include "paddle/fluid/framework/ir/graph_helper.h"
#include "paddle/fluid/framework/ir/pass_tester_helper.h"
#include "paddle/fluid/framework/op_version_registry.h"
namespace
paddle
{
namespace
framework
{
namespace
ir
{
TEST
(
CommonSubexpressionEliminationPass
,
basic_test
)
{
// inputs operator output
// --------------------------------------------------------------------
// (relu(a), b) elementwise_add -> d
// (relu(a), c) elementwise_add -> e
// (d, e) elementwise_add -> f
Layers
layers
;
auto
*
a
=
layers
.
data
(
"a"
,
{
1024
,
768
});
auto
*
b
=
layers
.
data
(
"b"
,
{
1024
,
768
});
auto
*
c
=
layers
.
data
(
"c"
,
{
1024
,
768
});
auto
*
d
=
layers
.
elementwise_add
(
layers
.
relu
(
a
),
b
);
auto
*
e
=
layers
.
elementwise_add
(
layers
.
relu
(
a
),
c
);
auto
*
f
=
layers
.
data
(
"f"
,
{
1024
,
768
});
layers
.
elementwise_add
(
d
,
e
,
f
,
0
);
std
::
unique_ptr
<
ir
::
Graph
>
graph
(
new
ir
::
Graph
(
layers
.
main_program
()));
auto
pass
=
PassRegistry
::
Instance
().
Get
(
"common_subexpression_elimination_pass"
);
graph
.
reset
(
pass
->
Apply
(
graph
.
release
()));
int
num_nodes_after
=
GetNumOpNodes
(
graph
,
"relu"
);
PADDLE_ENFORCE_EQ
(
num_nodes_after
,
1
,
platform
::
errors
::
InvalidArgument
(
"Before the common subexpression elimination pass, "
"there should be 1 "
"relu op, but the result is %d"
,
num_nodes_after
));
}
TEST
(
CommonSubexpressionEliminationPass
,
commutative_operator_test
)
{
// inputs operator output
// --------------------------------------------------------------------
// (a, b) elementwise_add -> e
// (b, a) elementwise_add -> f
// (e, c) elementwise_add -> g
// (f, d) elementwise_add -> h
Layers
layers
;
auto
*
a
=
layers
.
data
(
"a"
,
{
1024
,
768
});
auto
*
b
=
layers
.
data
(
"b"
,
{
1024
,
768
});
auto
*
c
=
layers
.
data
(
"c"
,
{
1024
,
768
});
auto
*
d
=
layers
.
data
(
"d"
,
{
1024
,
768
});
auto
*
e
=
layers
.
data
(
"e"
,
{
1024
,
768
});
auto
*
f
=
layers
.
data
(
"f"
,
{
1024
,
768
});
auto
*
g
=
layers
.
data
(
"g"
,
{
1024
,
768
});
auto
*
h
=
layers
.
data
(
"h"
,
{
1024
,
768
});
layers
.
elementwise_add
(
a
,
b
,
e
,
0
);
layers
.
elementwise_add
(
b
,
a
,
f
,
0
);
layers
.
elementwise_add
(
e
,
c
,
g
,
0
);
layers
.
elementwise_add
(
f
,
d
,
h
,
0
);
std
::
unique_ptr
<
ir
::
Graph
>
graph
(
new
ir
::
Graph
(
layers
.
main_program
()));
auto
pass
=
PassRegistry
::
Instance
().
Get
(
"common_subexpression_elimination_pass"
);
graph
.
reset
(
pass
->
Apply
(
graph
.
release
()));
int
num_nodes_after
=
GetNumOpNodes
(
graph
,
"elementwise_add"
);
PADDLE_ENFORCE_EQ
(
num_nodes_after
,
3
,
platform
::
errors
::
InvalidArgument
(
"Before the common subexpression elimination pass, "
"there should be 3 "
"elementwise_add op, but the result is %d"
,
num_nodes_after
));
}
TEST
(
CommonSubexpressionEliminationPass
,
nondeterministic_operator_test
)
{
// inputs operator output
// --------------------------------------------------------------------
// (dropout(a), b) elementwise_add -> d
// (dropout(a), c) elementwise_add -> e
// (d, e) elementwise_add -> f
Layers
layers
;
auto
*
a
=
layers
.
data
(
"a"
,
{
1024
,
768
});
auto
*
b
=
layers
.
data
(
"b"
,
{
1024
,
768
});
auto
*
c
=
layers
.
data
(
"c"
,
{
1024
,
768
});
auto
*
d
=
layers
.
elementwise_add
(
layers
.
dropout
(
a
,
0.5
,
"downgrade_in_infer"
),
b
);
auto
*
e
=
layers
.
elementwise_add
(
layers
.
dropout
(
a
,
0.5
,
"downgrade_in_infer"
),
c
);
auto
*
f
=
layers
.
data
(
"f"
,
{
1024
,
768
});
layers
.
elementwise_add
(
d
,
e
,
f
,
0
);
std
::
unique_ptr
<
ir
::
Graph
>
graph
(
new
ir
::
Graph
(
layers
.
main_program
()));
auto
pass
=
PassRegistry
::
Instance
().
Get
(
"common_subexpression_elimination_pass"
);
graph
.
reset
(
pass
->
Apply
(
graph
.
release
()));
int
num_nodes_after
=
GetNumOpNodes
(
graph
,
"dropout"
);
PADDLE_ENFORCE_EQ
(
num_nodes_after
,
2
,
platform
::
errors
::
InvalidArgument
(
"After the common subexpression elimination pass, "
"there should still be 2 "
"dropout op, but the result is %d"
,
num_nodes_after
));
}
}
// namespace ir
}
// namespace framework
}
// namespace paddle
USE_PASS
(
common_subexpression_elimination_pass
);
paddle/fluid/inference/api/paddle_pass_builder.cc
浏览文件 @
7c6835ca
...
...
@@ -282,7 +282,6 @@ CpuPassStrategy::CpuPassStrategy() : PassStrategy({}) {
"conv_eltwiseadd_bn_fuse_pass"
,
//
"conv_transpose_bn_fuse_pass"
,
//
"conv_transpose_eltwiseadd_bn_fuse_pass"
,
//
"common_subexpression_elimination_pass"
,
//
"is_test_pass"
,
//
"constant_folding_pass"
,
// following pass should be located in the last, since
...
...
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