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bf653d8e
编写于
12月 29, 2020
作者:
W
Wilber
提交者:
GitHub
12月 29, 2020
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差异文件
[Inference] Solve 2.0 trt performance reduce compare 1.8. (#29925) (#29964)
上级
acb29ff8
变更
9
显示空白变更内容
内联
并排
Showing
9 changed file
with
447 addition
and
9 deletion
+447
-9
paddle/fluid/framework/ir/CMakeLists.txt
paddle/fluid/framework/ir/CMakeLists.txt
+5
-1
paddle/fluid/framework/ir/adaptive_pool2d_convert_global_pass.cc
...fluid/framework/ir/adaptive_pool2d_convert_global_pass.cc
+61
-0
paddle/fluid/framework/ir/adaptive_pool2d_convert_global_pass.h
.../fluid/framework/ir/adaptive_pool2d_convert_global_pass.h
+42
-0
paddle/fluid/framework/ir/adaptive_pool2d_convert_global_pass_tester.cc
...ramework/ir/adaptive_pool2d_convert_global_pass_tester.cc
+67
-0
paddle/fluid/framework/ir/pass_tester_helper.h
paddle/fluid/framework/ir/pass_tester_helper.h
+20
-3
paddle/fluid/framework/ir/unsqueeze2_eltwise_fuse_pass.cc
paddle/fluid/framework/ir/unsqueeze2_eltwise_fuse_pass.cc
+134
-0
paddle/fluid/framework/ir/unsqueeze2_eltwise_fuse_pass.h
paddle/fluid/framework/ir/unsqueeze2_eltwise_fuse_pass.h
+45
-0
paddle/fluid/framework/ir/unsqueeze2_eltwise_fuse_pass_tester.cc
...fluid/framework/ir/unsqueeze2_eltwise_fuse_pass_tester.cc
+65
-0
paddle/fluid/inference/api/paddle_pass_builder.cc
paddle/fluid/inference/api/paddle_pass_builder.cc
+8
-5
未找到文件。
paddle/fluid/framework/ir/CMakeLists.txt
浏览文件 @
bf653d8e
...
...
@@ -88,6 +88,8 @@ pass_library(simplify_with_basic_ops_pass base)
pass_library
(
fc_elementwise_layernorm_fuse_pass base
)
pass_library
(
skip_layernorm_fuse_pass base
)
pass_library
(
multihead_matmul_fuse_pass inference
)
pass_library
(
adaptive_pool2d_convert_global_pass inference
)
pass_library
(
unsqueeze2_eltwise_fuse_pass inference
)
if
(
WITH_GPU
)
pass_library
(
cudnn_placement_pass base DEPS placement_pass_base
)
pass_library
(
embedding_eltwise_layernorm_fuse_pass inference
)
...
...
@@ -141,7 +143,9 @@ cc_test(test_simplify_with_basic_ops_pass SRCS simplify_with_basic_ops_pass_test
cc_test
(
test_fc_elementwise_layernorm_fuse_pass SRCS fc_elementwise_layernorm_fuse_pass_tester.cc DEPS fc_elementwise_layernorm_fuse_pass
)
cc_test
(
test_skip_layernorm_fuse_pass SRCS skip_layernorm_fuse_pass_tester.cc DEPS skip_layernorm_fuse_pass
)
cc_test
(
test_multihead_matmul_fuse_pass SRCS multihead_matmul_fuse_pass_tester.cc DEPS multihead_matmul_fuse_pass
)
cc_test
(
test_conv_bn_fuse_pass SRCS conv_bn_fuse_pass_tester.cc DEPS conv_bn_fuse_pass
)
cc_test
(
test_conv_bn_fuse_pass_cc SRCS conv_bn_fuse_pass_tester.cc DEPS conv_bn_fuse_pass
)
cc_test
(
test_adaptive_pool2d_convert_global_pass SRCS adaptive_pool2d_convert_global_pass_tester.cc DEPS adaptive_pool2d_convert_global_pass
)
cc_test
(
test_unsqueeze2_eltwise_fuse_pass SRCS unsqueeze2_eltwise_fuse_pass_tester.cc DEPS unsqueeze2_eltwise_fuse_pass
)
if
(
WITH_GPU
)
cc_test
(
test_embedding_eltwise_layernorm_fuse_pass SRCS embedding_eltwise_layernorm_fuse_pass_tester.cc DEPS embedding_eltwise_layernorm_fuse_pass
)
cc_test
(
test_cudnn_placement_pass SRCS cudnn_placement_pass_tester.cc DEPS cudnn_placement_pass
)
...
...
paddle/fluid/framework/ir/adaptive_pool2d_convert_global_pass.cc
0 → 100644
浏览文件 @
bf653d8e
/* Copyright (c) 2020 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/adaptive_pool2d_convert_global_pass.h"
#include <string>
#include <vector>
#include "paddle/fluid/framework/ir/graph_helper.h"
#include "paddle/fluid/framework/op_version_registry.h"
#include "paddle/fluid/platform/enforce.h"
namespace
paddle
{
namespace
framework
{
namespace
ir
{
void
AdaptivePool2dConvertGlobalPass
::
ApplyImpl
(
ir
::
Graph
*
graph
)
const
{
std
::
string
name_scope
=
"adaptive_pool2d_convert_global_pass"
;
FusePassBase
::
Init
(
name_scope
,
graph
);
int
num
=
0
;
for
(
const
Node
*
n
:
graph
->
Nodes
())
{
if
(
n
->
IsOp
())
{
auto
*
op
=
n
->
Op
();
if
(
op
->
HasAttr
(
"adaptive"
)
&&
op
->
HasAttr
(
"ksize"
))
{
bool
adaptive
=
BOOST_GET_CONST
(
bool
,
op
->
GetAttr
(
"adaptive"
));
std
::
vector
<
int
>
ksize
=
BOOST_GET_CONST
(
std
::
vector
<
int
>
,
op
->
GetAttr
(
"ksize"
));
if
(
adaptive
&&
ksize
.
size
()
==
2
&&
ksize
[
0
]
==
1
&&
ksize
[
1
]
==
1
)
{
op
->
SetAttr
(
"adaptive"
,
false
);
op
->
SetAttr
(
"global_pooling"
,
true
);
++
num
;
}
}
}
}
// LOG(INFO) << "--- processed " << num << " nodes";
AddStatis
(
num
);
}
}
// namespace ir
}
// namespace framework
}
// namespace paddle
REGISTER_PASS
(
adaptive_pool2d_convert_global_pass
,
paddle
::
framework
::
ir
::
AdaptivePool2dConvertGlobalPass
);
REGISTER_PASS_CAPABILITY
(
adaptive_pool2d_convert_global_pass
)
.
AddCombination
(
paddle
::
framework
::
compatible
::
OpVersionComparatorCombination
().
EQ
(
"pool2d"
,
0
));
paddle/fluid/framework/ir/adaptive_pool2d_convert_global_pass.h
0 → 100644
浏览文件 @
bf653d8e
/* Copyright (c) 2020 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 "paddle/fluid/framework/ir/fuse_pass_base.h"
#include "paddle/fluid/framework/ir/pass.h"
namespace
paddle
{
namespace
framework
{
namespace
ir
{
class
Graph
;
/*
* Update pool2d's attr to speed up trt engine.
*
* when adaptive=true, ksize=[1,1], we turn to adaptive=false,
* global_pooling=true.
*/
class
AdaptivePool2dConvertGlobalPass
:
public
FusePassBase
{
public:
virtual
~
AdaptivePool2dConvertGlobalPass
()
{}
protected:
void
ApplyImpl
(
ir
::
Graph
*
graph
)
const
override
;
};
}
// namespace ir
}
// namespace framework
}
// namespace paddle
paddle/fluid/framework/ir/adaptive_pool2d_convert_global_pass_tester.cc
0 → 100644
浏览文件 @
bf653d8e
/* Copyright (c) 2020 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/adaptive_pool2d_convert_global_pass.h"
#include <gtest/gtest.h>
#include "paddle/fluid/framework/ir/pass_tester_helper.h"
#include "paddle/fluid/framework/op_version_registry.h"
#include "paddle/fluid/platform/enforce.h"
namespace
paddle
{
namespace
framework
{
namespace
ir
{
TEST
(
AdaptivePool2dConvertGlobalPass
,
basic
)
{
Layers
layers
;
auto
*
x
=
layers
.
data
(
"x"
,
{
1
,
92
,
28
,
28
});
AttributeMap
attrs
;
attrs
[
"adaptive"
]
=
true
;
attrs
[
"ksize"
]
=
std
::
vector
<
int
>
{
1
,
1
};
layers
.
pool2d
(
x
,
false
,
&
attrs
);
std
::
unique_ptr
<
ir
::
Graph
>
graph
(
new
ir
::
Graph
(
layers
.
main_program
()));
auto
pass
=
PassRegistry
::
Instance
().
Get
(
"adaptive_pool2d_convert_global_pass"
);
VLOG
(
3
)
<<
DebugString
(
graph
);
graph
.
reset
(
pass
->
Apply
(
graph
.
release
()));
VLOG
(
3
)
<<
DebugString
(
graph
);
bool
global_pooling
=
false
;
for
(
auto
*
node
:
graph
->
Nodes
())
{
if
(
node
->
IsOp
()
&&
node
->
Op
()
->
Type
()
==
"pool2d"
)
{
if
(
node
->
Op
()
->
HasAttr
(
"global_pooling"
))
{
global_pooling
=
BOOST_GET_CONST
(
bool
,
node
->
Op
()
->
GetAttr
(
"global_pooling"
));
}
}
}
PADDLE_ENFORCE_EQ
(
global_pooling
,
true
,
platform
::
errors
::
PreconditionNotMet
(
"The attribute of pool2d global_pooling should be true after fuse"
));
}
TEST
(
AdaptivePool2dConvertGlobalPass
,
pass_op_version_check
)
{
ASSERT_TRUE
(
paddle
::
framework
::
compatible
::
PassVersionCheckerRegistrar
::
GetInstance
()
.
IsPassCompatible
(
"adaptive_pool2d_convert_global_pass"
));
}
}
// namespace ir
}
// namespace framework
}
// namespace paddle
USE_PASS
(
adaptive_pool2d_convert_global_pass
);
paddle/fluid/framework/ir/pass_tester_helper.h
浏览文件 @
bf653d8e
...
...
@@ -81,18 +81,34 @@ struct Layers {
return
out
;
}
VarDesc
*
pool2d
(
VarDesc
*
x
,
bool
use_cudnn
)
{
VarDesc
*
pool2d
(
VarDesc
*
x
,
bool
use_cudnn
,
const
AttributeMap
*
attrs
=
nullptr
)
{
VarDesc
*
out
=
lod_tensor
(
unique_name
());
OpDesc
*
op
=
program_
.
MutableBlock
(
0
)
->
AppendOp
();
op
->
SetType
(
"pool2d"
);
op
->
SetInput
(
"X"
,
{
x
->
Name
()});
op
->
SetOutput
(
"Out"
,
{
out
->
Name
()});
op
->
SetAttr
(
"use_cudnn"
,
use_cudnn
);
if
(
attrs
)
{
for
(
auto
&
iter
:
*
attrs
)
{
op
->
SetAttr
(
iter
.
first
,
iter
.
second
);
}
}
op
->
SetAttr
(
OpProtoAndCheckerMaker
::
OpRoleAttrName
(),
static_cast
<
int
>
(
OpRole
::
kForward
));
return
out
;
}
VarDesc
*
unsqueeze2
(
VarDesc
*
x
,
const
std
::
vector
<
int
>
axes
)
{
VarDesc
*
out
=
lod_tensor
(
unique_name
());
OpDesc
*
op
=
program_
.
MutableBlock
(
0
)
->
AppendOp
();
op
->
SetType
(
"unsqueeze2"
);
op
->
SetInput
(
"X"
,
{
x
->
Name
()});
op
->
SetOutput
(
"Out"
,
{
out
->
Name
()});
op
->
SetAttr
(
"axes"
,
axes
);
return
out
;
}
VarDesc
*
relu
(
VarDesc
*
x
,
VarDesc
*
out
=
nullptr
)
{
return
unary_op
(
"relu"
,
x
,
out
);
}
...
...
@@ -188,8 +204,9 @@ struct Layers {
return
binary_op
(
"elementwise_add"
,
x
,
y
,
out
);
}
VarDesc
*
elementwise_mul
(
VarDesc
*
x
,
VarDesc
*
y
,
VarDesc
*
out
=
nullptr
)
{
return
binary_op
(
"elementwise_mul"
,
x
,
y
,
out
);
VarDesc
*
elementwise_mul
(
VarDesc
*
x
,
VarDesc
*
y
,
VarDesc
*
out
=
nullptr
,
const
AttributeMap
*
attrs
=
nullptr
)
{
return
binary_op
(
"elementwise_mul"
,
x
,
y
,
out
,
attrs
);
}
VarDesc
*
dropout
(
VarDesc
*
x
,
float
dropout_prob
,
...
...
paddle/fluid/framework/ir/unsqueeze2_eltwise_fuse_pass.cc
0 → 100644
浏览文件 @
bf653d8e
/* 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. */
#include "paddle/fluid/framework/ir/unsqueeze2_eltwise_fuse_pass.h"
#include <string>
#include <unordered_set>
#include <vector>
#include "paddle/fluid/framework/ir/graph_pattern_detector.h"
#include "paddle/fluid/framework/op_version_registry.h"
namespace
paddle
{
namespace
framework
{
namespace
ir
{
namespace
patterns
{
struct
UnsqueezeEltwise
:
public
PatternBase
{
UnsqueezeEltwise
(
PDPattern
*
pattern
,
const
std
::
string
&
name_scope
)
:
PatternBase
(
pattern
,
name_scope
,
"unsqueeze2_eltwise_fuse_pass"
)
{}
PDNode
*
operator
()(
PDNode
*
x
,
PDNode
*
y
);
// declare operator node's name
PATTERN_DECL_NODE
(
unsqz
);
PATTERN_DECL_NODE
(
elementwise
);
// declare variable node's name
PATTERN_DECL_NODE
(
eltwise_in_x
);
PATTERN_DECL_NODE
(
unsqz_in
);
PATTERN_DECL_NODE
(
unsqz_out
);
PATTERN_DECL_NODE
(
eltwise_out
);
};
PDNode
*
UnsqueezeEltwise
::
operator
()(
PDNode
*
x
,
PDNode
*
y
)
{
x
->
assert_is_op_input
(
"elementwise_mul"
,
"X"
);
y
->
assert_is_op_input
(
"unsqueeze2"
,
"X"
);
auto
*
unsqz
=
pattern
->
NewNode
(
unsqz_repr
())
->
assert_is_op
(
"unsqueeze2"
);
auto
*
unsqz_out
=
pattern
->
NewNode
(
unsqz_out_repr
())
->
assert_is_op_output
(
"unsqueeze2"
,
"Out"
)
->
assert_is_op_input
(
"elementwise_mul"
,
"Y"
);
unsqz
->
LinksFrom
({
y
}).
LinksTo
({
unsqz_out
});
auto
*
elementwise
=
pattern
->
NewNode
(
elementwise_repr
())
->
assert_is_op
(
"elementwise_mul"
);
auto
*
eltwise_out
=
pattern
->
NewNode
(
eltwise_out_repr
())
->
AsOutput
()
->
assert_is_op_output
(
"elementwise_mul"
);
elementwise
->
LinksFrom
({
x
,
unsqz_out
}).
LinksTo
({
eltwise_out
});
return
eltwise_out
;
}
}
// namespace patterns
void
UnsqueezeEltwiseFusePass
::
ApplyImpl
(
ir
::
Graph
*
graph
)
const
{
PADDLE_ENFORCE_NOT_NULL
(
graph
,
platform
::
errors
::
PreconditionNotMet
(
"graph should not be null."
));
FusePassBase
::
Init
(
"unsqueeze2_eltwise_fuse_pass"
,
graph
);
int
found_subgraph_count
=
0
;
GraphPatternDetector
gpd
;
auto
*
x
=
gpd
.
mutable_pattern
()
->
NewNode
(
"unsqueeze2_eltwise_fuse_pass/x"
)
->
AsInput
()
->
assert_is_op_input
(
"elementwise_mul"
,
"X"
)
->
assert_var_not_persistable
();
auto
*
y
=
gpd
.
mutable_pattern
()
->
NewNode
(
"unsqueeze2_eltwise_fuse_pass/y"
)
->
AsInput
()
->
assert_is_op_input
(
"unsqueeze2"
,
"X"
)
->
assert_var_not_persistable
();
patterns
::
UnsqueezeEltwise
fused_pattern
(
gpd
.
mutable_pattern
(),
"unsqueeze2_eltwise_fuse_pass"
);
fused_pattern
(
x
,
y
);
auto
handler
=
[
&
](
const
GraphPatternDetector
::
subgraph_t
&
subgraph
,
Graph
*
graph
)
{
if
(
subgraph
.
count
(
x
)
<=
0
||
subgraph
.
count
(
y
)
<=
0
)
{
LOG
(
WARNING
)
<<
"The subgraph is empty."
;
return
;
}
VLOG
(
4
)
<<
"handle UnsqueezeEltwise fuse"
;
GET_IR_NODE_FROM_SUBGRAPH
(
eltwise_op
,
elementwise
,
fused_pattern
);
GET_IR_NODE_FROM_SUBGRAPH
(
eltwise_out
,
eltwise_out
,
fused_pattern
);
GET_IR_NODE_FROM_SUBGRAPH
(
unsqz_op
,
unsqz
,
fused_pattern
);
GET_IR_NODE_FROM_SUBGRAPH
(
unsqz_out
,
unsqz_out
,
fused_pattern
);
size_t
eltwise_in_x_rank
=
(
subgraph
.
at
(
x
)
->
Var
()
->
GetShape
()).
size
();
size_t
unsqz_in_rank
=
(
subgraph
.
at
(
y
)
->
Var
()
->
GetShape
()).
size
();
std
::
vector
<
int
>
unsqz_op_axes
=
BOOST_GET_CONST
(
std
::
vector
<
int
>
,
unsqz_op
->
Op
()
->
GetAttr
(
"axes"
));
int
eltwise_op_axis
=
BOOST_GET_CONST
(
int
,
eltwise_op
->
Op
()
->
GetAttr
(
"axis"
));
if
(
eltwise_in_x_rank
==
4
&&
unsqz_in_rank
==
2
&&
unsqz_op_axes
==
std
::
vector
<
int
>
{
2
,
3
}
&&
eltwise_op_axis
==
-
1
)
{
eltwise_op
->
Op
()
->
SetAttr
(
"axis"
,
0
);
eltwise_op
->
Op
()
->
SetInput
(
"Y"
,
{
subgraph
.
at
(
y
)
->
Name
()});
IR_NODE_LINK_TO
(
subgraph
.
at
(
x
),
eltwise_op
);
IR_NODE_LINK_TO
(
subgraph
.
at
(
y
),
eltwise_op
);
IR_NODE_LINK_TO
(
eltwise_op
,
eltwise_out
);
GraphSafeRemoveNodes
(
graph
,
{
unsqz_op
,
unsqz_out
});
found_subgraph_count
++
;
}
};
gpd
(
graph
,
handler
);
AddStatis
(
found_subgraph_count
);
}
}
// namespace ir
}
// namespace framework
}
// namespace paddle
REGISTER_PASS
(
unsqueeze2_eltwise_fuse_pass
,
paddle
::
framework
::
ir
::
UnsqueezeEltwiseFusePass
);
REGISTER_PASS_CAPABILITY
(
unsqueeze2_eltwise_fuse_pass
)
.
AddCombination
(
paddle
::
framework
::
compatible
::
OpVersionComparatorCombination
()
.
EQ
(
"unsqueeze2"
,
0
)
.
EQ
(
"elementwise_mul"
,
0
));
paddle/fluid/framework/ir/unsqueeze2_eltwise_fuse_pass.h
0 → 100644
浏览文件 @
bf653d8e
/* Copyright (c) 2020 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 "paddle/fluid/framework/ir/fuse_pass_base.h"
namespace
paddle
{
namespace
framework
{
namespace
ir
{
class
Graph
;
// |(rank 4) |(rank 2) |(rank 4) |(rank 2)
// | unsqueeze2(axes=[2,3]) | |
// | | fuse \ /
// |------elementwise_mul(axis=-1) -> elementwise_mul(axis=0)
// | |
// | |
//
// Notice:
// the rank of input is obtained from var_desc,
// it maybe change in runtime.
class
UnsqueezeEltwiseFusePass
:
public
FusePassBase
{
public:
virtual
~
UnsqueezeEltwiseFusePass
()
{}
protected:
void
ApplyImpl
(
ir
::
Graph
*
graph
)
const
override
;
};
}
// namespace ir
}
// namespace framework
}
// namespace paddle
paddle/fluid/framework/ir/unsqueeze2_eltwise_fuse_pass_tester.cc
0 → 100644
浏览文件 @
bf653d8e
/* Copyright (c) 2020 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/unsqueeze2_eltwise_fuse_pass.h"
#include <gtest/gtest.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
(
UnsqueezeEltwiseFusePass
,
basic
)
{
Layers
layers
;
auto
*
x
=
layers
.
data
(
"x"
,
{
1
,
92
,
28
,
28
});
auto
*
y
=
layers
.
data
(
"y"
,
{
1
,
92
});
std
::
vector
<
int
>
axes
{
2
,
3
};
auto
*
unsqz_out
=
layers
.
unsqueeze2
(
y
,
axes
);
AttributeMap
attrs
;
attrs
[
"axis"
]
=
-
1
;
layers
.
elementwise_mul
(
x
,
unsqz_out
,
nullptr
,
&
attrs
);
std
::
unique_ptr
<
ir
::
Graph
>
graph
(
new
ir
::
Graph
(
layers
.
main_program
()));
auto
pass
=
PassRegistry
::
Instance
().
Get
(
"unsqueeze2_eltwise_fuse_pass"
);
int
num_nodes_before
=
graph
->
Nodes
().
size
();
VLOG
(
3
)
<<
DebugString
(
graph
);
graph
.
reset
(
pass
->
Apply
(
graph
.
release
()));
int
num_nodes_after
=
graph
->
Nodes
().
size
();
int
num_fused_nodes_after
=
GetNumOpNodes
(
graph
,
"elementwise_mul"
);
VLOG
(
3
)
<<
DebugString
(
graph
);
PADDLE_ENFORCE_EQ
(
num_nodes_before
,
num_nodes_after
+
2
,
platform
::
errors
::
PreconditionNotMet
(
"The number of nodes before and after the fuse does "
"not meet expectations"
));
PADDLE_ENFORCE_EQ
(
num_fused_nodes_after
,
1
,
platform
::
errors
::
PreconditionNotMet
(
"The number of fusion nodes does not meet expectations after fuse"
));
}
TEST
(
UnsqueezeEltwiseFusePass
,
pass_op_version_check
)
{
ASSERT_TRUE
(
paddle
::
framework
::
compatible
::
PassVersionCheckerRegistrar
::
GetInstance
()
.
IsPassCompatible
(
"unsqueeze2_eltwise_fuse_pass"
));
}
}
// namespace ir
}
// namespace framework
}
// namespace paddle
USE_PASS
(
unsqueeze2_eltwise_fuse_pass
);
paddle/fluid/inference/api/paddle_pass_builder.cc
浏览文件 @
bf653d8e
...
...
@@ -72,6 +72,7 @@ void PaddlePassBuilder::ClearPasses() { passes_.clear(); }
const
std
::
vector
<
std
::
string
>
kTRTSubgraphPasses
({
"conv_affine_channel_fuse_pass"
,
//
"adaptive_pool2d_convert_global_pass"
,
"conv_eltwiseadd_affine_channel_fuse_pass"
,
//
"shuffle_channel_detect_pass"
,
//
"quant_conv2d_dequant_fuse_pass"
,
//
...
...
@@ -81,6 +82,7 @@ const std::vector<std::string> kTRTSubgraphPasses({
"embedding_eltwise_layernorm_fuse_pass"
,
//
"multihead_matmul_fuse_pass_v2"
,
//
"skip_layernorm_fuse_pass"
,
//
"unsqueeze2_eltwise_fuse_pass"
,
"conv_bn_fuse_pass"
,
//
"fc_fuse_pass"
,
//
"tensorrt_subgraph_pass"
,
//
...
...
@@ -207,6 +209,7 @@ void CpuPassStrategy::EnableMKLDNN() {
"matmul_transpose_reshape_fuse_pass"
,
//
// Disabled due to topology-dependent speed-up
// "fc_mkldnn_pass",
// "fc_act_mkldnn_fuse_pass",
"batch_norm_act_fuse_pass"
,
"mkldnn_inplace_pass"
,
// This pass should be activated after
// fuses
...
...
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