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体验新版 GitCode,发现更多精彩内容 >>
提交
b837689e
编写于
8月 15, 2019
作者:
A
Adam
提交者:
Tao Luo
8月 15, 2019
浏览文件
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电子邮件补丁
差异文件
Add generalized Conv+Activation MKLDNN fuse pass creation (#19072)
test=develop
上级
50b1cab1
变更
19
隐藏空白更改
内联
并排
Showing
19 changed file
with
495 addition
and
108 deletion
+495
-108
paddle/fluid/framework/ir/CMakeLists.txt
paddle/fluid/framework/ir/CMakeLists.txt
+2
-4
paddle/fluid/framework/ir/graph_pattern_detector.cc
paddle/fluid/framework/ir/graph_pattern_detector.cc
+29
-0
paddle/fluid/framework/ir/graph_pattern_detector.h
paddle/fluid/framework/ir/graph_pattern_detector.h
+22
-0
paddle/fluid/framework/ir/mkldnn/conv_activation_mkldnn_fuse_pass.cc
...d/framework/ir/mkldnn/conv_activation_mkldnn_fuse_pass.cc
+101
-0
paddle/fluid/framework/ir/mkldnn/conv_activation_mkldnn_fuse_pass.h
...id/framework/ir/mkldnn/conv_activation_mkldnn_fuse_pass.h
+55
-0
paddle/fluid/framework/ir/mkldnn/conv_activation_mkldnn_fuse_pass_tester.cc
...work/ir/mkldnn/conv_activation_mkldnn_fuse_pass_tester.cc
+145
-0
paddle/fluid/framework/ir/mkldnn/conv_concat_relu_mkldnn_fuse_pass.cc
.../framework/ir/mkldnn/conv_concat_relu_mkldnn_fuse_pass.cc
+1
-1
paddle/fluid/framework/ir/mkldnn/conv_concat_relu_mkldnn_fuse_pass_tester.cc
...ork/ir/mkldnn/conv_concat_relu_mkldnn_fuse_pass_tester.cc
+4
-3
paddle/fluid/framework/ir/mkldnn/conv_elementwise_add_mkldnn_fuse_pass.cc
...mework/ir/mkldnn/conv_elementwise_add_mkldnn_fuse_pass.cc
+11
-4
paddle/fluid/inference/api/mkldnn_quantizer.cc
paddle/fluid/inference/api/mkldnn_quantizer.cc
+7
-4
paddle/fluid/inference/api/paddle_pass_builder.cc
paddle/fluid/inference/api/paddle_pass_builder.cc
+3
-2
paddle/fluid/operators/conv_op.cc
paddle/fluid/operators/conv_op.cc
+16
-0
paddle/fluid/operators/conv_transpose_op.cc
paddle/fluid/operators/conv_transpose_op.cc
+8
-0
paddle/fluid/operators/mkldnn/conv_mkldnn_op.cc
paddle/fluid/operators/mkldnn/conv_mkldnn_op.cc
+34
-33
paddle/fluid/operators/mkldnn/conv_transpose_mkldnn_op.cc
paddle/fluid/operators/mkldnn/conv_transpose_mkldnn_op.cc
+6
-3
paddle/fluid/platform/mkldnn_reuse.h
paddle/fluid/platform/mkldnn_reuse.h
+15
-23
python/paddle/fluid/tests/unittests/mkldnn/test_conv2d_int8_mkldnn_op.py
...luid/tests/unittests/mkldnn/test_conv2d_int8_mkldnn_op.py
+16
-16
python/paddle/fluid/tests/unittests/mkldnn/test_conv2d_mkldnn_op.py
...dle/fluid/tests/unittests/mkldnn/test_conv2d_mkldnn_op.py
+12
-11
python/paddle/fluid/tests/unittests/mkldnn/test_conv2d_transpose_mkldnn_op.py
...tests/unittests/mkldnn/test_conv2d_transpose_mkldnn_op.py
+8
-4
未找到文件。
paddle/fluid/framework/ir/CMakeLists.txt
浏览文件 @
b837689e
...
...
@@ -86,8 +86,7 @@ if(WITH_MKLDNN)
pass_library
(
mkldnn_placement_pass base mkldnn
)
pass_library
(
depthwise_conv_mkldnn_pass base mkldnn
)
pass_library
(
conv_bias_mkldnn_fuse_pass inference mkldnn
)
pass_library
(
conv_relu_mkldnn_fuse_pass inference mkldnn
)
pass_library
(
conv_brelu_mkldnn_fuse_pass inference mkldnn
)
pass_library
(
conv_activation_mkldnn_fuse_pass inference mkldnn
)
pass_library
(
conv_concat_relu_mkldnn_fuse_pass inference mkldnn
)
pass_library
(
conv_elementwise_add_mkldnn_fuse_pass inference mkldnn
)
pass_library
(
fc_mkldnn_pass inference mkldnn
)
...
...
@@ -127,8 +126,7 @@ endif()
if
(
WITH_MKLDNN
)
cc_test
(
test_depthwise_conv_mkldnn_pass SRCS mkldnn/depthwise_conv_mkldnn_pass_tester.cc DEPS depthwise_conv_mkldnn_pass
)
cc_test
(
test_conv_bias_mkldnn_fuse_pass SRCS mkldnn/conv_bias_mkldnn_fuse_pass_tester.cc DEPS conv_bias_mkldnn_fuse_pass naive_executor
)
cc_test
(
test_conv_relu_mkldnn_fuse_pass SRCS mkldnn/conv_relu_mkldnn_fuse_pass_tester.cc DEPS conv_relu_mkldnn_fuse_pass
)
cc_test
(
test_conv_brelu_mkldnn_fuse_pass SRCS mkldnn/conv_brelu_mkldnn_fuse_pass_tester.cc DEPS conv_brelu_mkldnn_fuse_pass
)
cc_test
(
test_conv_activation_mkldnn_fuse_pass SRCS mkldnn/conv_activation_mkldnn_fuse_pass_tester.cc DEPS conv_activation_mkldnn_fuse_pass
)
cc_test
(
test_conv_concat_relu_mkldnn_fuse_pass SRCS mkldnn/conv_concat_relu_mkldnn_fuse_pass_tester.cc DEPS conv_concat_relu_mkldnn_fuse_pass
)
cc_test
(
test_conv_elementwise_add_mkldnn_fuse_pass SRCS mkldnn/conv_elementwise_add_mkldnn_fuse_pass_tester.cc DEPS conv_elementwise_add_mkldnn_fuse_pass
)
cc_test
(
test_mkldnn_placement_pass SRCS mkldnn/mkldnn_placement_pass_tester.cc DEPS mkldnn_placement_pass
)
...
...
paddle/fluid/framework/ir/graph_pattern_detector.cc
浏览文件 @
b837689e
...
...
@@ -771,6 +771,35 @@ PDNode *patterns::ConvBN::operator()(paddle::framework::ir::PDNode *conv_input,
return
bn_out_var
;
}
PDNode
*
patterns
::
ConvActivation
::
operator
()(
paddle
::
framework
::
ir
::
PDNode
*
conv_input
,
std
::
string
conv_type
,
std
::
string
activation_type
)
{
// Create Operators
conv_input
->
assert_is_op_input
(
conv_type
,
"Input"
);
auto
*
conv_op
=
pattern
->
NewNode
(
conv_repr
())
->
assert_is_op
(
conv_type
);
auto
*
activation_op
=
pattern
->
NewNode
(
activation_repr
())
->
assert_is_op
(
activation_type
);
// Create variables
// Filter
auto
*
conv_weight_var
=
pattern
->
NewNode
(
conv_weight_repr
())
->
AsInput
()
->
assert_is_persistable_var
()
->
assert_is_op_input
(
conv_type
,
"Filter"
);
// intermediate variable, will be removed in the IR after fuse.
auto
*
conv_out_var
=
pattern
->
NewNode
(
conv_out_repr
())
->
AsIntermediate
()
->
assert_is_only_output_of_op
(
conv_type
)
->
assert_is_op_input
(
activation_type
);
// output
auto
*
activation_out_var
=
pattern
->
NewNode
(
activation_out_repr
())
->
AsOutput
()
->
assert_is_op_output
(
activation_type
);
conv_op
->
LinksFrom
({
conv_input
,
conv_weight_var
}).
LinksTo
({
conv_out_var
});
activation_op
->
LinksFrom
({
conv_out_var
}).
LinksTo
({
activation_out_var
});
return
activation_out_var
;
}
PDNode
*
patterns
::
ConvReLU
::
operator
()(
paddle
::
framework
::
ir
::
PDNode
*
conv_input
)
{
// Create Operators
...
...
paddle/fluid/framework/ir/graph_pattern_detector.h
浏览文件 @
b837689e
...
...
@@ -431,6 +431,28 @@ struct ConvBN : public PatternBase {
PATTERN_DECL_NODE
(
bn_saved_variance
);
};
// Conv with Activation
// op: conv + activation
// named nodes:
// conv_input, conv_weight,
// conv_out, conv,
// activation_out, activation
struct
ConvActivation
:
public
PatternBase
{
ConvActivation
(
PDPattern
*
pattern
,
const
std
::
string
&
name_scope
)
:
PatternBase
(
pattern
,
name_scope
,
"conv_activation"
)
{}
PDNode
*
operator
()(
PDNode
*
conv_input
,
std
::
string
conv_type
=
"conv2d"
,
std
::
string
activation_type
=
"relu"
);
// declare operator node's name
PATTERN_DECL_NODE
(
conv
);
PATTERN_DECL_NODE
(
activation
);
// declare variable node's name
PATTERN_DECL_NODE
(
conv_weight
);
PATTERN_DECL_NODE
(
conv_out
);
PATTERN_DECL_NODE
(
activation_out
);
};
// CONV with ReLU
// op: conv + relu
// named nodes:
...
...
paddle/fluid/framework/ir/mkldnn/conv_activation_mkldnn_fuse_pass.cc
0 → 100644
浏览文件 @
b837689e
// 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/mkldnn/conv_activation_mkldnn_fuse_pass.h"
#include <string>
#include <vector>
#include "paddle/fluid/platform/enforce.h"
namespace
paddle
{
namespace
framework
{
namespace
ir
{
void
ConvActivationFusePass
::
ApplyImpl
(
ir
::
Graph
*
graph
)
const
{
PADDLE_ENFORCE_NOT_NULL
(
graph
,
"graph cannot be nullptr."
);
FusePassBase
::
Init
(
"conv_activation_mkldnn_fuse"
,
graph
);
GraphPatternDetector
gpd
;
auto
*
conv_input
=
gpd
.
mutable_pattern
()
->
NewNode
(
"conv_activation_mkldnn_fuse/conv_input"
)
->
AsInput
()
->
assert_is_op_input
(
conv_type
(),
"Input"
);
patterns
::
ConvActivation
conv_activation_pattern
(
gpd
.
mutable_pattern
(),
"conv_activation_mkldnn_fuse"
);
conv_activation_pattern
(
conv_input
,
conv_type
(),
activation_type
());
int
found_conv_activation_count
=
0
;
auto
handler
=
[
&
](
const
GraphPatternDetector
::
subgraph_t
&
subgraph
,
Graph
*
g
)
{
VLOG
(
4
)
<<
"handle "
+
conv_type
()
+
"+"
+
activation_type
()
+
" fuse"
;
GET_IR_NODE_FROM_SUBGRAPH
(
conv_weight
,
conv_weight
,
conv_activation_pattern
);
// Filter
GET_IR_NODE_FROM_SUBGRAPH
(
conv_out
,
conv_out
,
conv_activation_pattern
);
// tmp
GET_IR_NODE_FROM_SUBGRAPH
(
conv
,
conv
,
conv_activation_pattern
);
// CONV op
GET_IR_NODE_FROM_SUBGRAPH
(
activation_out
,
activation_out
,
conv_activation_pattern
);
// Out
GET_IR_NODE_FROM_SUBGRAPH
(
activation
,
activation
,
conv_activation_pattern
);
// Activation op
// Transform Conv node into ConvActivation node.
OpDesc
*
desc
=
conv
->
Op
();
desc
->
SetOutput
(
"Output"
,
std
::
vector
<
std
::
string
>
({
activation_out
->
Name
()}));
desc
->
SetAttr
(
"fuse_activation"
,
activation_type
());
// MKLDNN ops use alpha and beta as activation parameters but paddle ops are
// not generalized
if
(
activation_type
()
==
"relu6"
)
{
desc
->
SetAttr
(
"fuse_alpha"
,
boost
::
get
<
float
>
(
activation
->
Op
()
->
GetAttr
(
"threshold"
)));
}
else
{
desc
->
SetAttr
(
"fuse_alpha"
,
activation
->
Op
()
->
HasAttr
(
"alpha"
)
?
boost
::
get
<
float
>
(
activation
->
Op
()
->
GetAttr
(
"alpha"
))
:
0.0
f
);
}
desc
->
SetAttr
(
"fuse_beta"
,
activation
->
Op
()
->
HasAttr
(
"beta"
)
?
boost
::
get
<
float
>
(
activation
->
Op
()
->
GetAttr
(
"beta"
))
:
0.0
f
);
GraphSafeRemoveNodes
(
graph
,
{
activation
,
conv_out
});
PADDLE_ENFORCE_GT
(
subgraph
.
count
(
conv_input
),
0UL
,
"subgraph has to contain conv_input node."
);
IR_NODE_LINK_TO
(
conv
,
activation_out
);
found_conv_activation_count
++
;
};
gpd
(
graph
,
handler
);
AddStatis
(
found_conv_activation_count
);
}
}
// namespace ir
}
// namespace framework
}
// namespace paddle
REGISTER_PASS
(
conv_activation_mkldnn_fuse_pass
,
paddle
::
framework
::
ir
::
ConvActivationFusePass
);
REGISTER_PASS
(
conv_relu_mkldnn_fuse_pass
,
paddle
::
framework
::
ir
::
ConvActivationFusePass
);
REGISTER_PASS
(
conv_leaky_relu_mkldnn_fuse_pass
,
paddle
::
framework
::
ir
::
Conv2DLeakyReLUFusePass
);
REGISTER_PASS
(
conv_relu6_mkldnn_fuse_pass
,
paddle
::
framework
::
ir
::
Conv2DReLU6FusePass
);
paddle/fluid/framework/ir/mkldnn/conv_activation_mkldnn_fuse_pass.h
0 → 100644
浏览文件 @
b837689e
// 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.
#pragma once
#include <string>
#include "paddle/fluid/framework/ir/fuse_pass_base.h"
#include "paddle/fluid/framework/ir/graph.h"
#include "paddle/fluid/framework/ir/graph_pattern_detector.h"
#include "paddle/fluid/framework/ir/pass.h"
namespace
paddle
{
namespace
framework
{
namespace
ir
{
/*
* Fuse Conv and Activation base class.
*/
class
ConvActivationFusePass
:
public
FusePassBase
{
public:
virtual
~
ConvActivationFusePass
()
{}
virtual
std
::
string
conv_type
()
const
{
return
"conv2d"
;
}
virtual
std
::
string
activation_type
()
const
{
return
"relu"
;
}
protected:
void
ApplyImpl
(
ir
::
Graph
*
graph
)
const
override
;
const
std
::
string
name_scope_
{
"conv_activation_mkldnn_fuse"
};
};
/*
* Fuse Conv and LeakyReLU class
*/
class
Conv2DLeakyReLUFusePass
:
public
ConvActivationFusePass
{
public:
std
::
string
activation_type
()
const
{
return
"leaky_relu"
;
}
};
/*
* Fuse Conv and BoundedReLU class
*/
class
Conv2DReLU6FusePass
:
public
ConvActivationFusePass
{
public:
std
::
string
activation_type
()
const
{
return
"relu6"
;
}
};
}
// namespace ir
}
// namespace framework
}
// namespace paddle
paddle/fluid/framework/ir/mkldnn/conv_activation_mkldnn_fuse_pass_tester.cc
0 → 100644
浏览文件 @
b837689e
// 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/mkldnn/conv_activation_mkldnn_fuse_pass.h"
#include <gtest/gtest.h>
#include "paddle/fluid/framework/op_proto_maker.h"
namespace
paddle
{
namespace
framework
{
namespace
ir
{
void
SetOp
(
ProgramDesc
*
prog
,
const
std
::
string
&
type
,
const
std
::
string
&
name
,
const
std
::
vector
<
std
::
string
>&
inputs
,
const
std
::
vector
<
std
::
string
>&
outputs
,
bool
is_activation
=
false
,
bool
use_mkldnn
=
false
)
{
auto
*
op
=
prog
->
MutableBlock
(
0
)
->
AppendOp
();
op
->
SetType
(
type
);
op
->
SetAttr
(
"name"
,
name
);
if
(
type
==
"conv2d"
)
{
op
->
SetAttr
(
"use_mkldnn"
,
use_mkldnn
);
op
->
SetInput
(
"Input"
,
{
inputs
[
0
]});
op
->
SetInput
(
"Filter"
,
{
inputs
[
1
]});
op
->
SetInput
(
"Bias"
,
{
inputs
[
2
]});
}
else
if
(
is_activation
)
{
op
->
SetAttr
(
"use_mkldnn"
,
use_mkldnn
);
op
->
SetInput
(
"X"
,
inputs
);
if
(
type
==
"leaky_relu"
)
{
op
->
SetAttr
(
"alpha"
,
0.02
f
);
}
else
if
(
type
==
"relu6"
)
{
op
->
SetAttr
(
"threshold"
,
6.0
f
);
}
}
op
->
SetOutput
(
"Out"
,
outputs
);
op
->
SetAttr
(
OpProtoAndCheckerMaker
::
OpRoleAttrName
(),
static_cast
<
int
>
(
OpRole
::
kForward
));
}
// a->OP0->b
// b->OP1->c
// (c, weights, bias)->conv->f
// (f)->activation->g
ProgramDesc
BuildProgramDesc
(
std
::
string
activation
)
{
ProgramDesc
prog
;
for
(
auto
&
v
:
std
::
vector
<
std
::
string
>
({
"a"
,
"b"
,
"c"
,
"weights"
,
"bias"
,
"f"
,
"g"
,
"h"
,
"weights2"
,
"bias2"
,
"k"
,
"l"
,
"m"
}))
{
auto
*
var
=
prog
.
MutableBlock
(
0
)
->
Var
(
v
);
var
->
SetType
(
proto
::
VarType
::
SELECTED_ROWS
);
if
(
v
==
"weights"
||
v
==
"bias"
||
v
==
"weights2"
||
v
==
"bias2"
)
{
var
->
SetPersistable
(
true
);
}
}
SetOp
(
&
prog
,
"OP0"
,
"op0"
,
std
::
vector
<
std
::
string
>
({
"a"
}),
std
::
vector
<
std
::
string
>
({
"b"
}));
SetOp
(
&
prog
,
"OP1"
,
"op1"
,
std
::
vector
<
std
::
string
>
({
"b"
}),
std
::
vector
<
std
::
string
>
({
"c"
}));
// conv+activation, both with MKL-DNN
SetOp
(
&
prog
,
"conv2d"
,
"conv1"
,
std
::
vector
<
std
::
string
>
({
"c"
,
"weights"
,
"bias"
}),
std
::
vector
<
std
::
string
>
({
"f"
}),
false
,
true
);
SetOp
(
&
prog
,
activation
,
"activation1"
,
std
::
vector
<
std
::
string
>
({
"f"
}),
std
::
vector
<
std
::
string
>
({
"g"
}),
true
,
true
);
SetOp
(
&
prog
,
"OP3"
,
"op3"
,
std
::
vector
<
std
::
string
>
({
"g"
}),
std
::
vector
<
std
::
string
>
({
"h"
}));
// conv+activation, only one with MKL-DNN
SetOp
(
&
prog
,
"conv2d"
,
"conv2"
,
std
::
vector
<
std
::
string
>
({
"h"
,
"weights2"
,
"bias2"
}),
std
::
vector
<
std
::
string
>
({
"k"
}),
false
,
true
);
SetOp
(
&
prog
,
"activation"
,
"activation2"
,
std
::
vector
<
std
::
string
>
({
"k"
}),
std
::
vector
<
std
::
string
>
({
"l"
}),
true
,
false
);
SetOp
(
&
prog
,
"OP4"
,
"op4"
,
std
::
vector
<
std
::
string
>
({
"l"
}),
std
::
vector
<
std
::
string
>
({
"m"
}));
return
prog
;
}
void
MainTest
(
std
::
string
activation
)
{
auto
prog
=
BuildProgramDesc
(
activation
);
std
::
unique_ptr
<
ir
::
Graph
>
graph
(
new
ir
::
Graph
(
prog
));
auto
pass
=
PassRegistry
::
Instance
().
Get
(
"conv_"
+
activation
+
"_mkldnn_fuse_pass"
);
int
original_nodes_num
=
graph
->
Nodes
().
size
();
graph
.
reset
(
pass
->
Apply
(
graph
.
release
()));
int
current_nodes_num
=
graph
->
Nodes
().
size
();
// Remove 3 Nodes: CONV, activation, conv_out
// Add 1 Node: ConvActivation
EXPECT_EQ
(
original_nodes_num
-
2
,
current_nodes_num
);
// Assert conv_activation op in newly generated graph
int
conv_activation_count
=
0
;
for
(
auto
*
node
:
graph
->
Nodes
())
{
if
(
node
->
IsOp
()
&&
node
->
Op
()
->
Type
()
==
"conv2d"
)
{
auto
*
op
=
node
->
Op
();
ASSERT_TRUE
(
op
->
HasAttr
(
"use_mkldnn"
));
EXPECT_TRUE
(
boost
::
get
<
bool
>
(
op
->
GetAttr
(
"use_mkldnn"
)));
auto
op_name
=
boost
::
get
<
std
::
string
>
(
op
->
GetAttr
(
"name"
));
std
::
string
fuse_activation
=
op
->
HasAttr
(
"fuse_activation"
)
?
boost
::
get
<
std
::
string
>
(
op
->
GetAttr
(
"fuse_activation"
))
:
""
;
if
(
fuse_activation
==
activation
)
{
++
conv_activation_count
;
}
// check if only "conv1" convolution is fused
if
(
op_name
==
"conv1"
)
{
ASSERT_TRUE
(
op
->
HasAttr
(
"fuse_activation"
));
}
else
if
(
op_name
==
"conv2"
)
{
ASSERT_FALSE
(
op
->
HasAttr
(
"fuse_activation"
));
}
}
}
EXPECT_EQ
(
conv_activation_count
,
1
);
}
TEST
(
ConvActivationFusePass
,
conv_relu_fuse_pass
)
{
MainTest
(
"relu"
);
}
TEST
(
ConvActivationFusePass
,
conv_leaky_relu_fuse_pass
)
{
MainTest
(
"leaky_relu"
);
}
TEST
(
ConvActivationFusePass
,
conv_relu6_fuse_pass
)
{
MainTest
(
"relu6"
);
}
}
// namespace ir
}
// namespace framework
}
// namespace paddle
USE_PASS
(
conv_activation_mkldnn_fuse_pass
);
paddle/fluid/framework/ir/mkldnn/conv_concat_relu_mkldnn_fuse_pass.cc
浏览文件 @
b837689e
...
...
@@ -83,7 +83,7 @@ void ConvConcatReLUFusePass::FuseConvConcatReLU(
// Transform Conv node into ConvReLU node.
OpDesc
*
conv_desc
=
conv_op
->
Op
();
conv_desc
->
SetAttr
(
"fuse_
relu"
,
true
);
conv_desc
->
SetAttr
(
"fuse_
activation"
,
std
::
string
(
"relu"
)
);
// Remove ReLU when all Convs were transformed.
auto
number_of_unfused_convs_left
=
...
...
paddle/fluid/framework/ir/mkldnn/conv_concat_relu_mkldnn_fuse_pass_tester.cc
浏览文件 @
b837689e
...
...
@@ -28,7 +28,7 @@ void SetOp(ProgramDesc* prog, const std::string& type,
op
->
SetType
(
type
);
if
(
type
==
"conv2d"
)
{
op
->
SetAttr
(
"use_mkldnn"
,
use_mkldnn
);
op
->
SetAttr
(
"fuse_
relu"
,
false
);
op
->
SetAttr
(
"fuse_
activation"
,
std
::
string
(
""
)
);
op
->
SetInput
(
"Input"
,
{
inputs
[
0
]});
op
->
SetInput
(
"Filter"
,
{
inputs
[
1
]});
if
(
inputs
.
size
()
>
2
)
{
...
...
@@ -109,8 +109,9 @@ void MainTest(const ProgramDesc& prog, bool fuse_relu) {
if
(
node
->
IsOp
())
{
auto
*
op
=
node
->
Op
();
if
(
op
->
Type
()
==
"conv2d"
)
{
ASSERT_TRUE
(
op
->
HasAttr
(
"fuse_relu"
));
bool
fuse_relu_attr
=
boost
::
get
<
bool
>
(
op
->
GetAttr
(
"fuse_relu"
));
ASSERT_TRUE
(
op
->
HasAttr
(
"fuse_activation"
));
bool
fuse_relu_attr
=
(
boost
::
get
<
std
::
string
>
(
op
->
GetAttr
(
"fuse_activation"
))
==
"relu"
);
EXPECT_EQ
(
fuse_relu
,
fuse_relu_attr
);
}
else
if
(
op
->
Type
()
==
"relu"
)
{
relu_count
++
;
...
...
paddle/fluid/framework/ir/mkldnn/conv_elementwise_add_mkldnn_fuse_pass.cc
浏览文件 @
b837689e
...
...
@@ -109,8 +109,11 @@ void ResidualConnectionMKLDNNFusePass::IdentityFuseHandle::operator()(
if
(
!
IsReachable
(
graph
,
elementwise_add_identity
,
conv_output
))
return
;
auto
fuse_relu
=
HasAttribute
<
bool
>
(
*
conv_op
,
"fuse_relu"
);
if
(
fuse_relu
&&
*
fuse_relu
)
return
;
std
::
string
fuse_activation
=
conv_op
->
Op
()
->
HasAttr
(
"fuse_activation"
)
?
boost
::
get
<
std
::
string
>
(
conv_op
->
Op
()
->
GetAttr
(
"fuse_activation"
))
:
""
;
if
(
fuse_activation
==
"relu"
||
fuse_activation
==
"relu6"
)
return
;
conv_op
->
Op
()
->
SetInput
(
"ResidualData"
,
{
elementwise_add_identity
->
Name
()});
conv_op
->
Op
()
->
SetOutput
(
"Output"
,
{
elementwise_add_out
->
Name
()});
...
...
@@ -179,8 +182,12 @@ void ResidualConnectionMKLDNNFusePass::ProjectionFuseHandle::operator()(
return
;
}
auto
fuse_relu
=
HasAttribute
<
bool
>
(
*
residual_conv_op
,
"fuse_relu"
);
if
(
fuse_relu
&&
*
fuse_relu
)
return
;
std
::
string
fuse_activation
=
residual_conv_op
->
Op
()
->
HasAttr
(
"fuse_activation"
)
?
boost
::
get
<
std
::
string
>
(
residual_conv_op
->
Op
()
->
GetAttr
(
"fuse_activation"
))
:
""
;
if
(
fuse_activation
==
"relu"
||
fuse_activation
==
"relu6"
)
return
;
residual_conv_op
->
Op
()
->
SetInput
(
"ResidualData"
,
{
projection_node
->
Name
()});
residual_conv_op
->
Op
()
->
SetOutput
(
"Output"
,
{
elementwise_add_out
->
Name
()});
...
...
paddle/fluid/inference/api/mkldnn_quantizer.cc
浏览文件 @
b837689e
...
...
@@ -68,10 +68,13 @@ bool AnalysisPredictor::MkldnnQuantizer::CalculateScales() {
if
(
is_output
)
{
if
(
op
->
Type
()
==
"conv2d"
)
{
// output of conv2d with relu must be unsigned
is_unsigned
=
(
op
->
HasAttr
(
"fuse_relu"
)
&&
boost
::
get
<
bool
>
(
op
->
GetAttr
(
"fuse_relu"
)))
||
(
op
->
HasAttr
(
"fuse_brelu"
)
&&
boost
::
get
<
bool
>
(
op
->
GetAttr
(
"fuse_brelu"
)));
std
::
string
fuse_activation
=
op
->
HasAttr
(
"fuse_activation"
)
?
boost
::
get
<
std
::
string
>
(
op
->
GetAttr
(
"fuse_activation"
))
:
""
;
is_unsigned
=
(
fuse_activation
==
"relu"
||
fuse_activation
==
"relu6"
);
}
else
if
(
op
->
Type
()
==
"relu"
)
{
is_unsigned
=
true
;
}
else
if
(
op
->
Type
()
==
"transpose2"
||
...
...
paddle/fluid/inference/api/paddle_pass_builder.cc
浏览文件 @
b837689e
...
...
@@ -180,8 +180,9 @@ void CpuPassStrategy::EnableMKLDNN() {
"conv3d_bias_mkldnn_fuse_pass"
,
//
"conv_elementwise_add_mkldnn_fuse_pass"
,
"conv_concat_relu_mkldnn_fuse_pass"
,
"conv_relu_mkldnn_fuse_pass"
,
//
"conv_brelu_mkldnn_fuse_pass"
,
//
"conv_relu_mkldnn_fuse_pass"
,
//
"conv_leaky_relu_mkldnn_fuse_pass"
,
//
"conv_relu6_mkldnn_fuse_pass"
,
//
// Disabled due to topology-dependent speed-up
// "fc_mkldnn_pass"
}))
{
...
...
paddle/fluid/operators/conv_op.cc
浏览文件 @
b837689e
...
...
@@ -215,6 +215,14 @@ void Conv2DOpMaker::Make() {
AddAttr
<
float
>
(
"fuse_brelu_threshold"
,
"(float, default false 6.0) Only used in mkldnn kernel"
)
.
SetDefault
(
6.0
f
);
AddAttr
<
std
::
string
>
(
"fuse_activation"
,
"(string, default
\"\"
) Only used in mkldnn kernel"
)
.
SetDefault
(
""
);
AddAttr
<
float
>
(
"fuse_alpha"
,
"(float, default 0.0) Only used in mkldnn kernel"
)
.
SetDefault
(
0.0
f
);
AddAttr
<
float
>
(
"fuse_beta"
,
"(float, default 0.0) Only used in mkldnn kernel"
)
.
SetDefault
(
0.0
f
);
AddAttr
<
bool
>
(
"fuse_residual_connection"
,
"(bool, default false) Only used in mkldnn kernel. Used "
"whenever convolution output is as an input to residual "
...
...
@@ -352,6 +360,14 @@ void Conv3DOpMaker::Make() {
.
SetDefault
(
false
);
AddAttr
<
bool
>
(
"fuse_relu"
,
"(bool, default false) Only used in mkldnn kernel"
)
.
SetDefault
(
false
);
AddAttr
<
std
::
string
>
(
"fuse_activation"
,
"(string, default
\"\"
) Only used in mkldnn kernel"
)
.
SetDefault
(
""
);
AddAttr
<
float
>
(
"fuse_alpha"
,
"(float, default 0.0) Only used in mkldnn kernel"
)
.
SetDefault
(
0.0
f
);
AddAttr
<
float
>
(
"fuse_beta"
,
"(float, default 0.0) Only used in mkldnn kernel"
)
.
SetDefault
(
0.0
f
);
AddAttr
<
bool
>
(
"fuse_residual_connection"
,
"(bool, default false) Only used in mkldnn kernel. Used "
"whenever convolution output is as an input to residual "
...
...
paddle/fluid/operators/conv_transpose_op.cc
浏览文件 @
b837689e
...
...
@@ -170,6 +170,14 @@ void Conv2DTransposeOpMaker::Make() {
.
SetDefault
(
false
);
AddAttr
<
bool
>
(
"fuse_relu"
,
"(bool, default false) Only used in mkldnn kernel"
)
.
SetDefault
(
false
);
AddAttr
<
std
::
string
>
(
"fuse_activation"
,
"(string, default
\"\"
) Only used in mkldnn kernel"
)
.
SetDefault
(
""
);
AddAttr
<
float
>
(
"fuse_alpha"
,
"(float, default 0.0) Only used in mkldnn kernel"
)
.
SetDefault
(
0.0
f
);
AddAttr
<
float
>
(
"fuse_beta"
,
"(float, default 0.0) Only used in mkldnn kernel"
)
.
SetDefault
(
0.0
f
);
AddAttr
<
std
::
string
>
(
"data_format"
,
"(string, default NCHW) Only used in "
...
...
paddle/fluid/operators/mkldnn/conv_mkldnn_op.cc
浏览文件 @
b837689e
...
...
@@ -71,13 +71,14 @@ inline mkldnn::memory::format GetWeightsFormat(mkldnn::memory::format format,
static
mkldnn
::
memory
::
data_type
GetDstType
(
bool
is_int8
,
bool
force_fp32_output
,
bool
fuse_relu
,
bool
fuse_brelu
,
std
::
string
fuse_activation
,
bool
fuse_residual_conn
,
const
Tensor
*
residual_param
)
{
auto
dst_dt
=
mkldnn
::
memory
::
data_type
::
f32
;
// uint8_t, int8_t, float
if
(
is_int8
)
{
dst_dt
=
(
fuse_relu
||
fuse_brelu
)
?
mkldnn
::
memory
::
data_type
::
u8
:
mkldnn
::
memory
::
data_type
::
s8
;
dst_dt
=
(
fuse_activation
==
"relu"
||
fuse_activation
==
"relu6"
)
?
mkldnn
::
memory
::
data_type
::
u8
:
mkldnn
::
memory
::
data_type
::
s8
;
if
(
force_fp32_output
)
{
dst_dt
=
mkldnn
::
memory
::
data_type
::
f32
;
}
...
...
@@ -100,12 +101,11 @@ class ConvMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
if
(
!
is_INT8
)
{
ComputeFP32
(
ctx
);
}
else
{
bool
fuse_relu
=
ctx
.
Attr
<
bool
>
(
"fuse_relu
"
);
std
::
string
fuse_activation
=
ctx
.
Attr
<
std
::
string
>
(
"fuse_activation
"
);
bool
fuse_residual_conn
=
ctx
.
Attr
<
bool
>
(
"fuse_residual_connection"
);
bool
fuse_brelu
=
ctx
.
Attr
<
bool
>
(
"fuse_brelu"
);
bool
force_fp32_output
=
ctx
.
Attr
<
bool
>
(
"force_fp32_output"
);
auto
residual_param
=
ctx
.
Input
<
Tensor
>
(
"ResidualData"
);
auto
dst_dt
=
GetDstType
(
true
,
force_fp32_output
,
fuse_
relu
,
fuse_brelu
,
auto
dst_dt
=
GetDstType
(
true
,
force_fp32_output
,
fuse_
activation
,
fuse_residual_conn
,
residual_param
);
if
(
dst_dt
==
mkldnn
::
memory
::
data_type
::
f32
)
{
ComputeINT8
<
float
>
(
ctx
);
...
...
@@ -150,16 +150,13 @@ class ConvMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
std
::
vector
<
int
>
strides
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"strides"
);
std
::
vector
<
int
>
paddings
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"paddings"
);
std
::
vector
<
int
>
dilations
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"dilations"
);
bool
fuse_relu
=
ctx
.
Attr
<
bool
>
(
"fuse_relu"
);
std
::
string
fuse_activation
=
ctx
.
Attr
<
std
::
string
>
(
"fuse_activation"
);
float
fuse_alpha
=
ctx
.
Attr
<
float
>
(
"fuse_alpha"
);
float
fuse_beta
=
ctx
.
Attr
<
float
>
(
"fuse_beta"
);
bool
fuse_residual_conn
=
ctx
.
Attr
<
bool
>
(
"fuse_residual_connection"
);
bool
fuse_brelu
=
false
;
float
fuse_brelu_threshold
=
6.0
;
int
groups
=
ctx
.
Attr
<
int
>
(
"groups"
);
bool
is_conv3d
=
strides
.
size
()
==
3U
;
if
(
!
is_conv3d
)
{
fuse_brelu
=
ctx
.
Attr
<
bool
>
(
"fuse_brelu"
);
fuse_brelu_threshold
=
ctx
.
Attr
<
float
>
(
"fuse_brelu_threshold"
);
}
// TODO(tpatejko): add support for dilation
PADDLE_ENFORCE
(
is_conv3d
...
...
@@ -180,7 +177,7 @@ class ConvMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
// Get unique name for storing MKLDNN primitives
const
std
::
string
key
=
platform
::
ConvMKLDNNHandler
::
GetHash
(
src_tz
,
weights_tz
,
fuse_
relu
,
fuse_brelu
,
strides
,
paddings
,
dilations
,
src_tz
,
weights_tz
,
fuse_
activation
,
strides
,
paddings
,
dilations
,
groups
,
ctx
.
op
().
Input
(
"Input"
)
+
ctx
.
op
().
Input
(
"Filter"
));
std
::
vector
<
primitive
>
pipeline
;
...
...
@@ -232,13 +229,13 @@ class ConvMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
bias_tz
,
platform
::
MKLDNNGetDataType
<
T
>
(),
memory
::
format
::
x
);
conv_pd
=
handler
.
AcquireConvolutionPrimitiveDescriptor
(
src_md
,
weights_md
,
bias_md
,
dst_md
,
strides
,
paddings
,
mkldnn_engine
,
fuse_
relu
,
fuse_residual_conn
,
fuse_brelu
,
fuse_brelu_threshold
,
fuse_
activation
,
fuse_alpha
,
fuse_beta
,
fuse_residual_conn
,
fwd_prop_kind
);
}
else
{
conv_pd
=
handler
.
AcquireConvolutionPrimitiveDescriptor
(
src_md
,
weights_md
,
boost
::
none
,
dst_md
,
strides
,
paddings
,
mkldnn_engine
,
fuse_
relu
,
fuse_residual_conn
,
fuse_brelu
,
fuse_
brelu_threshold
,
fwd_prop_kind
);
mkldnn_engine
,
fuse_
activation
,
fuse_alpha
,
fuse_beta
,
fuse_
residual_conn
,
fwd_prop_kind
);
}
// create mkldnn memory from input tensors (data/weights)
...
...
@@ -355,12 +352,13 @@ class ConvMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
std
::
vector
<
int
>
paddings
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"paddings"
);
std
::
vector
<
int
>
dilations
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"dilations"
);
int
groups
=
ctx
.
Attr
<
int
>
(
"groups"
);
bool
fuse_relu
=
ctx
.
Attr
<
bool
>
(
"fuse_relu"
);
std
::
string
fuse_activation
=
ctx
.
Attr
<
std
::
string
>
(
"fuse_activation"
);
float
fuse_alpha
=
ctx
.
Attr
<
float
>
(
"fuse_alpha"
);
float
fuse_beta
=
ctx
.
Attr
<
float
>
(
"fuse_beta"
);
bool
fuse_residual_conn
=
ctx
.
Attr
<
bool
>
(
"fuse_residual_connection"
);
bool
fuse_brelu
=
ctx
.
Attr
<
bool
>
(
"fuse_brelu"
);
float
fuse_brelu_threshold
=
ctx
.
Attr
<
float
>
(
"fuse_brelu_threshold"
);
bool
force_fp32_output
=
ctx
.
Attr
<
bool
>
(
"force_fp32_output"
);
bool
unsigned_output
=
fuse_relu
||
fuse_brelu
;
bool
unsigned_output
=
(
fuse_activation
==
"relu"
||
fuse_activation
==
"relu6"
);
PADDLE_ENFORCE
(
!
fuse_residual_conn
||
!
force_fp32_output
,
"residual fusion does not support force output with fp32"
);
...
...
@@ -394,7 +392,7 @@ class ConvMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
key
.
reserve
(
MaxKeyLength
);
platform
::
ConvMKLDNNHandler
::
AppendKey
(
&
key
,
src_tz
,
weights_tz
,
strides
,
paddings
,
dilations
,
groups
,
src_dt
,
input
->
format
(),
fuse_
relu
,
fuse_residual_conn
,
fuse_brelu
,
input
->
format
(),
fuse_
activation
,
fuse_residual_conn
,
ctx
.
op
().
Input
(
"Input"
)
+
ctx
.
op
().
Input
(
"Filter"
));
const
std
::
string
key_conv_pd
=
key
+
"@conv_pd"
;
...
...
@@ -484,6 +482,14 @@ class ConvMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
handler
.
reset
(
new
platform
::
ConvMKLDNNHandler
(
dev_ctx
,
mkldnn_engine
,
key
));
// create a conv primitive descriptor and save it for usage in backward
// TODO(grygielski) if INT8 brelu post-op will be available, just delete
// whole if statement
if
(
fuse_activation
==
"relu6"
)
{
fuse_activation
=
"relu"
;
fuse_alpha
=
0.0
f
;
}
auto
propagation
=
is_test
?
mkldnn
::
prop_kind
::
forward_scoring
:
mkldnn
::
prop_kind
::
forward_training
;
...
...
@@ -493,13 +499,13 @@ class ConvMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
mkldnn
::
memory
::
format
::
x
);
conv_pd
=
handler
->
AcquireConvolutionPrimitiveDescriptor
(
src_md
,
weights_md
,
bias_md
,
dst_md
,
strides
,
paddings
,
mkldnn_engine
,
fuse_
relu
,
fuse_residual_conn
,
fuse_brelu
,
fuse_
brelu_threshold
,
propagation
,
output_shift_scale
,
sum_scale
);
mkldnn_engine
,
fuse_
activation
,
fuse_alpha
,
fuse_beta
,
fuse_
residual_conn
,
propagation
,
output_shift_scale
,
sum_scale
);
}
else
{
conv_pd
=
handler
->
AcquireConvolutionPrimitiveDescriptor
(
src_md
,
weights_md
,
boost
::
none
,
dst_md
,
strides
,
paddings
,
mkldnn_engine
,
fuse_
relu
,
fuse_residual_conn
,
fuse_brelu
,
fuse_
brelu_threshold
,
propagation
,
output_shift_scale
,
sum_scale
);
mkldnn_engine
,
fuse_
activation
,
fuse_alpha
,
fuse_beta
,
fuse_
residual_conn
,
propagation
,
output_shift_scale
,
sum_scale
);
}
// create mkldnn memory from input tensors (data/weights)
...
...
@@ -681,11 +687,6 @@ class ConvMKLDNNGradOpKernel : public paddle::framework::OpKernel<T> {
GetWeightsTz
(
weights_tz
,
g
,
is_conv3d
);
std
::
vector
<
int
>
dst_tz
=
paddle
::
framework
::
vectorize2int
(
output_grad
->
dims
());
bool
fuse_relu
=
ctx
.
Attr
<
bool
>
(
"fuse_relu"
);
bool
fuse_brelu
=
false
;
if
(
!
is_conv3d
)
{
fuse_brelu
=
ctx
.
Attr
<
bool
>
(
"fuse_brelu"
);
}
auto
src_format
=
input
->
format
();
mkldnn
::
memory
::
format
weights_format
=
GetWeightsFormat
(
filter
->
format
(),
g
,
is_conv3d
);
...
...
@@ -694,8 +695,8 @@ class ConvMKLDNNGradOpKernel : public paddle::framework::OpKernel<T> {
// as well as attributes of primitive to be created
// This name will be used as key when saving info into device context
const
std
::
string
key
=
platform
::
ConvMKLDNNHandler
::
GetHash
(
src_tz
,
weights_tz
,
fuse_relu
,
fuse_brelu
,
strides
,
paddings
,
dilation
s
,
groups
,
ctx
.
op
().
Input
(
"Input"
)
+
ctx
.
op
().
Input
(
"Filter"
));
src_tz
,
weights_tz
,
""
,
strides
,
paddings
,
dilations
,
group
s
,
ctx
.
op
().
Input
(
"Input"
)
+
ctx
.
op
().
Input
(
"Filter"
));
const
std
::
string
key_conv_pd
=
key
+
"@conv_pd"
;
std
::
vector
<
primitive
>
pipeline
;
...
...
paddle/fluid/operators/mkldnn/conv_transpose_mkldnn_op.cc
浏览文件 @
b837689e
...
...
@@ -142,7 +142,9 @@ class ConvTransposeMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
std
::
string
data_format
=
ctx
.
Attr
<
std
::
string
>
(
"data_format"
);
auto
chosen_memory_format
=
platform
::
data_format_to_memory_format
(
data_format
);
bool
fuse_relu
=
ctx
.
Attr
<
bool
>
(
"fuse_relu"
);
std
::
string
fuse_activation
=
ctx
.
Attr
<
std
::
string
>
(
"fuse_activation"
);
float
fuse_alpha
=
ctx
.
Attr
<
float
>
(
"fuse_alpha"
);
float
fuse_beta
=
ctx
.
Attr
<
float
>
(
"fuse_beta"
);
auto
src_md
=
platform
::
MKLDNNMemDesc
(
src_tz
,
platform
::
MKLDNNGetDataType
<
T
>
(),
chosen_memory_format
);
...
...
@@ -166,11 +168,12 @@ class ConvTransposeMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
bias_tz
,
platform
::
MKLDNNGetDataType
<
T
>
(),
mkldnn
::
memory
::
format
::
x
);
conv_transpose_pd
=
handler
.
AcquireConvolutionPrimitiveDescriptor
(
src_md
,
weights_md
,
bias_md
,
dst_md
,
strides
,
paddings
,
mkldnn_engine
,
fuse_
relu
,
false
,
false
,
0.0
,
fwd_prop_kind
);
fuse_
activation
,
fuse_alpha
,
fuse_beta
,
false
,
fwd_prop_kind
);
}
else
{
conv_transpose_pd
=
handler
.
AcquireConvolutionPrimitiveDescriptor
(
src_md
,
weights_md
,
boost
::
none
,
dst_md
,
strides
,
paddings
,
mkldnn_engine
,
fuse_relu
,
false
,
false
,
0.0
,
fwd_prop_kind
);
mkldnn_engine
,
fuse_activation
,
fuse_alpha
,
fuse_beta
,
false
,
fwd_prop_kind
);
}
// create mkldnn memory from input tensors (data/weights)
...
...
paddle/fluid/platform/mkldnn_reuse.h
浏览文件 @
b837689e
...
...
@@ -217,8 +217,8 @@ class MKLDNNHandler {
const
mkldnn
::
memory
::
dims
&
weights_dims
,
const
std
::
vector
<
int
>&
strides
,
const
std
::
vector
<
int
>&
paddings
,
const
std
::
vector
<
int
>&
dilations
,
const
int
&
groups
,
const
mkldnn
::
memory
::
data_type
&
srcdt
,
const
mkldnn
::
memory
::
format
&
format
,
const
bool
&
relu
,
const
bool
&
residual
,
const
bool
&
brelu
,
const
std
::
string
&
suffix
)
{
const
mkldnn
::
memory
::
format
&
format
,
const
std
::
string
&
fuse_activation
,
const
bool
&
residual
,
const
std
::
string
&
suffix
)
{
AppendKeyDims
(
key
,
input_dims
);
AppendKeyDims
(
key
,
weights_dims
);
...
...
@@ -232,9 +232,8 @@ class MKLDNNHandler {
AppendKey
(
key
,
std
::
to_string
(
groups
));
AppendKey
(
key
,
std
::
to_string
(
srcdt
));
AppendKey
(
key
,
std
::
to_string
(
format
));
AppendKey
(
key
,
std
::
to_string
(
relu
)
);
AppendKey
(
key
,
fuse_activation
);
AppendKey
(
key
,
std
::
to_string
(
residual
));
AppendKey
(
key
,
std
::
to_string
(
brelu
));
AppendKey
(
key
,
suffix
);
}
...
...
@@ -1179,9 +1178,8 @@ class ConvMKLDNNTemplateHandler : public MKLDNNHandler {
}
mkldnn
::
primitive_attr
CreatePostOps
(
bool
fuse_relu
,
bool
fuse_residual_conn
,
bool
fuse_brelu
,
float
fuse_brelu_threshold
,
const
std
::
vector
<
float
>
output_shift_scale
=
{},
std
::
string
fuse_activation
,
float
fuse_alpha
,
float
fuse_beta
,
bool
fuse_residual_conn
,
const
std
::
vector
<
float
>
output_shift_scale
=
{},
float
sum_scale
=
1.0
f
)
const
{
mkldnn
::
primitive_attr
conv_attr
;
mkldnn
::
post_ops
post_operations
;
...
...
@@ -1199,20 +1197,17 @@ class ConvMKLDNNTemplateHandler : public MKLDNNHandler {
}
// Fusion with ReLU layer is executed through the PostOps feature. Create a
// PostOps object and configure it to execute an eltwise relu operation.
if
(
fuse_
relu
)
{
if
(
fuse_
activation
==
"relu"
||
fuse_activation
==
"leaky_relu"
)
{
constexpr
float
scale
=
1.0
f
;
constexpr
float
negative_slope
=
0.0
f
;
constexpr
float
placeholder
=
0.0
f
;
post_operations
.
append_eltwise
(
scale
,
mkldnn
::
algorithm
::
eltwise_relu
,
negative_slope
,
placeholder
);
fuse_alpha
,
fuse_beta
);
}
if
(
fuse_
brelu
)
{
if
(
fuse_
activation
==
"relu6"
)
{
constexpr
float
scale
=
1.0
f
;
constexpr
float
placeholder
=
0.0
f
;
post_operations
.
append_eltwise
(
scale
,
mkldnn
::
algorithm
::
eltwise_bounded_relu
,
fuse_
brelu_threshold
,
placeholder
);
fuse_
alpha
,
fuse_beta
);
}
conv_attr
.
set_post_ops
(
post_operations
);
return
conv_attr
;
...
...
@@ -1224,9 +1219,8 @@ class ConvMKLDNNTemplateHandler : public MKLDNNHandler {
boost
::
optional
<
const
mkldnn
::
memory
::
desc
&>
bias
,
const
mkldnn
::
memory
::
desc
&
dst
,
const
std
::
vector
<
int
>&
strides
,
const
std
::
vector
<
int
>&
paddings
,
const
mkldnn
::
engine
&
engine
,
const
bool
fuse_relu
,
const
bool
fuse_residual_conn
,
const
bool
fuse_brelu
,
const
float
fuse_brelu_threshold
,
mkldnn
::
prop_kind
fwd_prop_kind
,
const
std
::
string
&
fuse_activation
,
float
fuse_alpha
,
float
fuse_beta
,
const
bool
fuse_residual_conn
,
mkldnn
::
prop_kind
fwd_prop_kind
,
const
std
::
vector
<
float
>
output_shift_scale
=
{},
const
float
sum_scale
=
1.0
f
)
{
// Conv PD has to be passed to Grad op that
...
...
@@ -1259,8 +1253,8 @@ class ConvMKLDNNTemplateHandler : public MKLDNNHandler {
padding_dims
,
mkldnn
::
padding_kind
::
zero
);
mkldnn
::
primitive_attr
conv_attr
=
CreatePostOps
(
fuse_
relu
,
fuse_residual_conn
,
fuse_brelu
,
fuse_
brelu_threshold
,
output_shift_scale
,
sum_scale
);
CreatePostOps
(
fuse_
activation
,
fuse_alpha
,
fuse_beta
,
fuse_
residual_conn
,
output_shift_scale
,
sum_scale
);
conv_pd_
.
reset
(
new
typename
forward_t
::
primitive_desc
(
conv_desc
,
conv_attr
,
engine
));
...
...
@@ -1343,14 +1337,12 @@ class ConvMKLDNNTemplateHandler : public MKLDNNHandler {
// TODO(jczaja): Make hashing function more optimial
static
std
::
string
GetHash
(
mkldnn
::
memory
::
dims
&
input_dims
,
// NOLINT
mkldnn
::
memory
::
dims
&
weights_dims
,
// NOLINT
const
bool
&
fuse_relu
,
// NOLINT
const
bool
&
fuse_brelu
,
// NOLINT
const
std
::
string
&
fuse_activation
,
// NOLINT
std
::
vector
<
int
>&
strides
,
// NOLINT
std
::
vector
<
int
>&
paddings
,
// NOLINT
std
::
vector
<
int
>&
dilations
,
// NOLINT
int
groups
,
const
std
::
string
&
suffix
)
{
return
dims2str
(
input_dims
)
+
dims2str
(
weights_dims
)
+
std
::
to_string
(
fuse_relu
)
+
std
::
to_string
(
fuse_brelu
)
+
return
dims2str
(
input_dims
)
+
dims2str
(
weights_dims
)
+
fuse_activation
+
dims2str
(
strides
)
+
dims2str
(
paddings
)
+
dims2str
(
dilations
)
+
std
::
to_string
(
groups
)
+
suffix
;
}
...
...
python/paddle/fluid/tests/unittests/mkldnn/test_conv2d_int8_mkldnn_op.py
浏览文件 @
b837689e
...
...
@@ -83,12 +83,12 @@ class TestConv2dInt8Op(TestConv2dOp):
input_residual
,
self
.
input_residual_size
).
astype
(
self
.
srctype
)
*
(
self
.
scale_out
/
self
.
scale_in_eltwise
))
if
self
.
fuse_
relu
:
if
self
.
fuse_
activation
==
"relu"
:
output
=
np
.
maximum
(
output_tmp
,
0
).
astype
(
self
.
dsttype
)
else
:
output
=
output_tmp
.
astype
(
self
.
dsttype
)
else
:
if
self
.
fuse_
relu
:
if
self
.
fuse_
activation
==
"relu"
:
output
=
np
.
maximum
(
np
.
round
(
output1
-
output2
),
0
).
astype
(
self
.
dsttype
)
else
:
...
...
@@ -113,12 +113,12 @@ class TestConv2dInt8Op(TestConv2dOp):
input_residual
,
self
.
input_residual_size
).
astype
(
np
.
int32
)
*
(
self
.
scale_out
/
self
.
scale_in_eltwise
))
if
self
.
fuse_
relu
:
if
self
.
fuse_
activation
==
"relu"
:
output
=
np
.
maximum
(
output_tmp_res
,
0
).
astype
(
self
.
dsttype
)
else
:
output
=
output_tmp_res
.
astype
(
self
.
dsttype
)
else
:
if
self
.
fuse_
relu
:
if
self
.
fuse_
activation
==
"relu"
:
output
=
np
.
maximum
(
output1_tmp
,
0
).
astype
(
self
.
dsttype
)
else
:
output
=
output1_tmp
.
astype
(
self
.
dsttype
)
...
...
@@ -145,7 +145,7 @@ class TestConv2dInt8Op(TestConv2dOp):
'Scale_out'
:
self
.
scale_out
,
'Scale_weights'
:
self
.
scale_weights
,
'Scale_in_eltwise'
:
self
.
scale_in_eltwise
,
'fuse_
relu'
:
self
.
fuse_relu
,
'fuse_
activation'
:
self
.
fuse_activation
,
'fuse_residual_connection'
:
self
.
fuse_residual
}
self
.
outputs
=
{
'Output'
:
output
}
...
...
@@ -178,7 +178,7 @@ class TestConv2dInt8Op(TestConv2dOp):
self
.
dsttype
=
np
.
int8
def
init_fuse_relu
(
self
):
self
.
fuse_
relu
=
True
self
.
fuse_
activation
=
"relu"
def
init_fuse_residual
(
self
):
self
.
fuse_residual
=
True
...
...
@@ -262,11 +262,11 @@ class TestWithInput1x1Filter1x1(TestConv2dInt8Op):
self
.
groups
=
3
def
init_data_type_with_fusion
(
self
,
input_dt
,
fuse_
relu
,
fuse_residual
):
def
init_data_type_with_fusion
(
self
,
input_dt
,
fuse_
activation
,
fuse_residual
):
self
.
srctype
=
input_dt
self
.
dsttype
=
np
.
uint8
if
fuse_
relu
else
np
.
int8
self
.
dsttype
=
np
.
uint8
if
fuse_
activation
==
"relu"
else
np
.
int8
self
.
fuse_
relu
=
fuse_relu
self
.
fuse_
activation
=
fuse_activation
self
.
fuse_residual
=
fuse_residual
...
...
@@ -277,43 +277,43 @@ def create_test_int8_class(parent):
class
TestS8U8Case
(
parent
):
def
init_data_type
(
self
):
init_data_type_with_fusion
(
self
,
np
.
int8
,
True
,
False
)
init_data_type_with_fusion
(
self
,
np
.
int8
,
"relu"
,
False
)
#--------------------test conv2d s8 in and s8 out--------------------
class
TestS8S8Case
(
parent
):
def
init_data_type
(
self
):
init_data_type_with_fusion
(
self
,
np
.
int8
,
False
,
False
)
init_data_type_with_fusion
(
self
,
np
.
int8
,
""
,
False
)
#--------------------test conv2d u8 in and s8 out--------------------
class
TestU8S8Case
(
parent
):
def
init_data_type
(
self
):
init_data_type_with_fusion
(
self
,
np
.
uint8
,
False
,
False
)
init_data_type_with_fusion
(
self
,
np
.
uint8
,
""
,
False
)
#--------------------test conv2d u8 in and u8 out without residual fuse--------------------
class
TestU8U8Case
(
parent
):
def
init_data_type
(
self
):
init_data_type_with_fusion
(
self
,
np
.
uint8
,
True
,
False
)
init_data_type_with_fusion
(
self
,
np
.
uint8
,
"relu"
,
False
)
#--------------------test conv2d s8 in and u8 out with residual fuse--------------------
class
TestS8U8ResCase
(
parent
):
def
init_data_type
(
self
):
init_data_type_with_fusion
(
self
,
np
.
int8
,
True
,
True
)
init_data_type_with_fusion
(
self
,
np
.
int8
,
"relu"
,
True
)
#--------------------test conv2d s8 in and s8 out with residual fuse--------------------
class
TestS8S8ResCase
(
parent
):
def
init_data_type
(
self
):
init_data_type_with_fusion
(
self
,
np
.
int8
,
False
,
True
)
init_data_type_with_fusion
(
self
,
np
.
int8
,
""
,
True
)
#--------------------test conv2d u8 in and s8 out with residual fuse--------------------
class
TestU8S8ResCase
(
parent
):
def
init_data_type
(
self
):
init_data_type_with_fusion
(
self
,
np
.
uint8
,
False
,
True
)
init_data_type_with_fusion
(
self
,
np
.
uint8
,
""
,
True
)
cls_name_s8u8
=
"{0}_relu_{1}_residual_0"
.
format
(
parent
.
__name__
,
"1"
)
cls_name_s8s8
=
"{0}_relu_{1}_residual_0"
.
format
(
parent
.
__name__
,
"0"
)
...
...
python/paddle/fluid/tests/unittests/mkldnn/test_conv2d_mkldnn_op.py
浏览文件 @
b837689e
...
...
@@ -56,8 +56,9 @@ class TestConv2dMKLDNNOp(TestConv2dOp):
def
setUp
(
self
):
self
.
fuse_bias
=
False
self
.
bias_size
=
None
self
.
fuse_relu
=
False
self
.
fuse_brelu
=
False
self
.
fuse_activation
=
""
self
.
fuse_alpha
=
0
self
.
fuse_beta
=
0
self
.
fuse_brelu_threshold
=
6.0
self
.
fuse_residual_connection
=
False
self
.
input_residual_size
=
None
...
...
@@ -83,18 +84,18 @@ class TestConv2dMKLDNNOp(TestConv2dOp):
self
.
inputs
[
'ResidualData'
]
=
OpTest
.
np_dtype_to_fluid_dtype
(
input_residual
)
if
self
.
fuse_
relu
:
if
self
.
fuse_
activation
==
"relu"
:
output
=
np
.
maximum
(
output
,
0
).
astype
(
self
.
dsttype
)
if
self
.
fuse_brelu
:
output
=
np
.
minimum
(
np
.
maximum
(
output
,
0
),
self
.
fuse_brelu_threshold
).
astype
(
self
.
dsttype
)
if
self
.
fuse_activation
==
"relu6"
:
output
=
np
.
minimum
(
np
.
maximum
(
output
,
0
),
self
.
fuse_alpha
).
astype
(
self
.
dsttype
)
output
=
output
.
astype
(
self
.
dtype
)
self
.
attrs
[
'fuse_bias'
]
=
self
.
fuse_bias
self
.
attrs
[
'fuse_relu'
]
=
self
.
fuse_relu
self
.
attrs
[
'fuse_brelu'
]
=
self
.
fuse_brelu
self
.
attrs
[
'fuse_activation'
]
=
self
.
fuse_activation
self
.
attrs
[
'fuse_alpha'
]
=
self
.
fuse_alpha
self
.
attrs
[
'fuse_beta'
]
=
self
.
fuse_beta
self
.
attrs
[
'fuse_brelu_threshold'
]
=
self
.
fuse_brelu_threshold
self
.
attrs
[
'fuse_residual_connection'
]
=
self
.
fuse_residual_connection
...
...
@@ -104,8 +105,8 @@ class TestConv2dMKLDNNOp(TestConv2dOp):
class
TestWithbreluFusion
(
TestConv2dMKLDNNOp
):
def
init_test_case
(
self
):
TestConv2dMKLDNNOp
.
init_test_case
(
self
)
self
.
fuse_
brelu
=
True
self
.
fuse_
brelu_threshold
=
6.0
self
.
fuse_
activation
=
"relu6"
self
.
fuse_
alpha
=
6.0
self
.
dsttype
=
np
.
float32
def
test_check_grad
(
self
):
...
...
python/paddle/fluid/tests/unittests/mkldnn/test_conv2d_transpose_mkldnn_op.py
浏览文件 @
b837689e
...
...
@@ -51,7 +51,9 @@ class TestConv2dTransposeMKLDNNOp(TestConv2dTransposeOp):
self
.
pad
=
[
0
,
0
]
self
.
fuse_bias
=
False
self
.
bias_size
=
None
self
.
fuse_relu
=
False
self
.
fuse_activation
=
""
self
.
fuse_alpha
=
0.0
self
.
fuse_beta
=
0.0
self
.
stride
=
[
1
,
1
]
self
.
dilations
=
[
1
,
1
]
self
.
input_size
=
[
2
,
3
,
5
,
5
]
# NCHW
...
...
@@ -71,11 +73,13 @@ class TestConv2dTransposeMKLDNNOp(TestConv2dTransposeOp):
self
.
attrs
[
'fuse_bias'
]
=
self
.
fuse_bias
self
.
inputs
[
'Bias'
]
=
OpTest
.
np_dtype_to_fluid_dtype
(
bias
)
if
self
.
fuse_
relu
:
if
self
.
fuse_
activation
==
"relu"
:
output
=
np
.
maximum
(
output
,
0
).
astype
(
self
.
dtype
)
output
=
output
.
astype
(
self
.
dtype
)
self
.
attrs
[
'fuse_bias'
]
=
self
.
fuse_bias
self
.
attrs
[
'fuse_relu'
]
=
self
.
fuse_relu
self
.
attrs
[
'fuse_activation'
]
=
self
.
fuse_activation
self
.
attrs
[
'fuse_alpha'
]
=
self
.
fuse_alpha
self
.
attrs
[
'fuse_beta'
]
=
self
.
fuse_beta
self
.
outputs
[
'Output'
]
=
output
...
...
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