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d3a66473
编写于
1月 14, 2020
作者:
W
Wojciech Uss
提交者:
Tao Luo
1月 14, 2020
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
improve placement pass tests code coverage (#22197)
上级
f5262865
变更
5
隐藏空白更改
内联
并排
Showing
5 changed file
with
191 addition
and
156 deletion
+191
-156
paddle/fluid/framework/ir/cudnn_placement_pass.h
paddle/fluid/framework/ir/cudnn_placement_pass.h
+3
-3
paddle/fluid/framework/ir/cudnn_placement_pass_tester.cc
paddle/fluid/framework/ir/cudnn_placement_pass_tester.cc
+84
-70
paddle/fluid/framework/ir/mkldnn/mkldnn_placement_pass.h
paddle/fluid/framework/ir/mkldnn/mkldnn_placement_pass.h
+3
-3
paddle/fluid/framework/ir/mkldnn/mkldnn_placement_pass_tester.cc
...fluid/framework/ir/mkldnn/mkldnn_placement_pass_tester.cc
+97
-80
paddle/fluid/framework/ir/placement_pass_base.h
paddle/fluid/framework/ir/placement_pass_base.h
+4
-0
未找到文件。
paddle/fluid/framework/ir/cudnn_placement_pass.h
浏览文件 @
d3a66473
...
...
@@ -27,11 +27,11 @@ namespace ir {
*/
class
CUDNNPlacementPass
:
public
PlacementPassBase
{
private:
const
std
::
string
GetPlacementName
()
const
{
return
"cuDNN"
;
}
const
std
::
string
GetPlacementName
()
const
override
{
return
"cuDNN"
;
}
const
std
::
string
GetAttrName
()
const
{
return
"use_cudnn"
;
}
const
std
::
string
GetAttrName
()
const
override
{
return
"use_cudnn"
;
}
const
std
::
unordered_set
<
std
::
string
>
GetOpTypesList
()
const
{
const
std
::
unordered_set
<
std
::
string
>
GetOpTypesList
()
const
override
{
return
Get
<
std
::
unordered_set
<
std
::
string
>>
(
"cudnn_enabled_op_types"
);
}
};
...
...
paddle/fluid/framework/ir/cudnn_placement_pass_tester.cc
浏览文件 @
d3a66473
...
...
@@ -22,94 +22,108 @@ namespace paddle {
namespace
framework
{
namespace
ir
{
void
RegisterOpKernel
()
{
static
bool
is_registered
=
false
;
if
(
!
is_registered
)
{
auto
&
all_kernels
=
OperatorWithKernel
::
AllOpKernels
();
platform
::
CUDAPlace
place
=
platform
::
CUDAPlace
(
0
);
OpKernelType
plain_kernel_type
=
OpKernelType
(
proto
::
VarType
::
FP32
,
place
,
DataLayout
::
kAnyLayout
,
LibraryType
::
kPlain
);
OpKernelType
cudnn_kernel_type
=
OpKernelType
(
proto
::
VarType
::
FP32
,
place
,
DataLayout
::
kAnyLayout
,
LibraryType
::
kCUDNN
);
auto
fake_kernel_func
=
[](
const
ExecutionContext
&
)
->
void
{
static
int
num_calls
=
0
;
num_calls
++
;
};
all_kernels
[
"conv2d"
][
cudnn_kernel_type
]
=
fake_kernel_func
;
all_kernels
[
"pool2d"
][
cudnn_kernel_type
]
=
fake_kernel_func
;
all_kernels
[
"depthwise_conv2d"
][
plain_kernel_type
]
=
fake_kernel_func
;
all_kernels
[
"relu"
][
plain_kernel_type
]
=
fake_kernel_func
;
is_registered
=
true
;
class
PlacementPassTest
{
private:
void
RegisterOpKernel
()
{
static
bool
is_registered
=
false
;
if
(
!
is_registered
)
{
auto
&
all_kernels
=
OperatorWithKernel
::
AllOpKernels
();
platform
::
CUDAPlace
place
=
platform
::
CUDAPlace
(
0
);
OpKernelType
plain_kernel_type
=
OpKernelType
(
proto
::
VarType
::
FP32
,
place
,
DataLayout
::
kAnyLayout
,
LibraryType
::
kPlain
);
OpKernelType
cudnn_kernel_type
=
OpKernelType
(
proto
::
VarType
::
FP32
,
place
,
DataLayout
::
kAnyLayout
,
LibraryType
::
kCUDNN
);
auto
fake_kernel_func
=
[](
const
ExecutionContext
&
)
->
void
{
static
int
num_calls
=
0
;
num_calls
++
;
};
all_kernels
[
"conv2d"
][
cudnn_kernel_type
]
=
fake_kernel_func
;
all_kernels
[
"pool2d"
][
cudnn_kernel_type
]
=
fake_kernel_func
;
all_kernels
[
"depthwise_conv2d"
][
plain_kernel_type
]
=
fake_kernel_func
;
all_kernels
[
"relu"
][
plain_kernel_type
]
=
fake_kernel_func
;
is_registered
=
true
;
}
}
}
void
MainTest
(
std
::
initializer_list
<
std
::
string
>
cudnn_enabled_op_types
,
unsigned
expected_use_cudnn_true_count
)
{
// operator use_cudnn
// --------------------------------------------------
// (a,b)->concat->c -
// (c,weights,bias)->conv2d->f false
// f->relu->g -
// g->pool2d->h false
// (h,weights2,bias2)->depthwise_conv2d->k false
// k->relu->l -
Layers
layers
;
VarDesc
*
a
=
layers
.
data
(
"a"
);
VarDesc
*
b
=
layers
.
data
(
"b"
);
VarDesc
*
c
=
layers
.
concat
(
std
::
vector
<
VarDesc
*>
({
a
,
b
}));
VarDesc
*
weights_0
=
layers
.
data
(
"weights_0"
);
VarDesc
*
bias_0
=
layers
.
data
(
"bias_0"
);
VarDesc
*
f
=
layers
.
conv2d
(
c
,
weights_0
,
bias_0
,
false
);
VarDesc
*
g
=
layers
.
relu
(
f
);
VarDesc
*
h
=
layers
.
pool2d
(
g
,
false
);
VarDesc
*
weights_1
=
layers
.
data
(
"weights_1"
);
VarDesc
*
bias_1
=
layers
.
data
(
"bias_1"
);
VarDesc
*
k
=
layers
.
depthwise_conv2d
(
h
,
weights_1
,
bias_1
,
false
);
layers
.
relu
(
k
);
RegisterOpKernel
();
std
::
unique_ptr
<
ir
::
Graph
>
graph
(
new
ir
::
Graph
(
layers
.
main_program
()));
auto
pass
=
PassRegistry
::
Instance
().
Get
(
"cudnn_placement_pass"
);
pass
->
Set
(
"cudnn_enabled_op_types"
,
new
std
::
unordered_set
<
std
::
string
>
(
cudnn_enabled_op_types
));
graph
.
reset
(
pass
->
Apply
(
graph
.
release
()));
unsigned
use_cudnn_true_count
=
0
;
for
(
auto
*
node
:
graph
->
Nodes
())
{
if
(
node
->
IsOp
()
&&
node
->
Op
())
{
auto
*
op
=
node
->
Op
();
if
(
op
->
HasAttr
(
"use_cudnn"
)
&&
boost
::
get
<
bool
>
(
op
->
GetAttr
(
"use_cudnn"
)))
{
++
use_cudnn_true_count
;
public:
void
MainTest
(
std
::
initializer_list
<
std
::
string
>
cudnn_enabled_op_types
,
unsigned
expected_use_cudnn_true_count
)
{
// operator use_cudnn
// --------------------------------------------------
// (a,b)->concat->c -
// (c,weights,bias)->conv2d->f false
// f->relu->g -
// g->pool2d->h false
// (h,weights2,bias2)->depthwise_conv2d->k false
// k->relu->l -
Layers
layers
;
VarDesc
*
a
=
layers
.
data
(
"a"
);
VarDesc
*
b
=
layers
.
data
(
"b"
);
VarDesc
*
c
=
layers
.
concat
(
std
::
vector
<
VarDesc
*>
({
a
,
b
}));
VarDesc
*
weights_0
=
layers
.
data
(
"weights_0"
);
VarDesc
*
bias_0
=
layers
.
data
(
"bias_0"
);
VarDesc
*
f
=
layers
.
conv2d
(
c
,
weights_0
,
bias_0
,
false
);
VarDesc
*
g
=
layers
.
relu
(
f
);
VarDesc
*
h
=
layers
.
pool2d
(
g
,
false
);
VarDesc
*
weights_1
=
layers
.
data
(
"weights_1"
);
VarDesc
*
bias_1
=
layers
.
data
(
"bias_1"
);
VarDesc
*
k
=
layers
.
depthwise_conv2d
(
h
,
weights_1
,
bias_1
,
false
);
layers
.
relu
(
k
);
RegisterOpKernel
();
std
::
unique_ptr
<
ir
::
Graph
>
graph
(
new
ir
::
Graph
(
layers
.
main_program
()));
auto
pass
=
PassRegistry
::
Instance
().
Get
(
"cudnn_placement_pass"
);
pass
->
Set
(
"cudnn_enabled_op_types"
,
new
std
::
unordered_set
<
std
::
string
>
(
cudnn_enabled_op_types
));
graph
.
reset
(
pass
->
Apply
(
graph
.
release
()));
unsigned
use_cudnn_true_count
=
0
;
for
(
auto
*
node
:
graph
->
Nodes
())
{
if
(
node
->
IsOp
()
&&
node
->
Op
())
{
auto
*
op
=
node
->
Op
();
if
(
op
->
HasAttr
(
"use_cudnn"
)
&&
boost
::
get
<
bool
>
(
op
->
GetAttr
(
"use_cudnn"
)))
{
++
use_cudnn_true_count
;
}
}
}
EXPECT_EQ
(
use_cudnn_true_count
,
expected_use_cudnn_true_count
);
}
EXPECT_EQ
(
use_cudnn_true_count
,
expected_use_cudnn_true_count
);
}
void
PlacementNameTest
()
{
auto
pass
=
PassRegistry
::
Instance
().
Get
(
"cudnn_placement_pass"
);
EXPECT_EQ
(
static_cast
<
PlacementPassBase
*>
(
pass
.
get
())
->
GetPlacementName
(),
"cuDNN"
);
}
};
TEST
(
CUDNNPlacementPass
,
enable_conv2d
)
{
// 1 conv2d
MainTest
({
"conv2d"
},
1
);
PlacementPassTest
().
MainTest
({
"conv2d"
},
1
);
}
TEST
(
CUDNNPlacementPass
,
enable_relu_pool
)
{
// 1 conv2d + 1 pool2d
MainTest
({
"conv2d"
,
"pool2d"
},
2
);
PlacementPassTest
().
MainTest
({
"conv2d"
,
"pool2d"
},
2
);
}
TEST
(
CUDNNPlacementPass
,
enable_all
)
{
// 1 conv2d + 1 pool2d
// depthwise_conv2d doesnot have CUDNN kernel.
MainTest
({},
2
);
PlacementPassTest
().
MainTest
({},
2
);
}
TEST
(
CUDNNPlacementPass
,
placement_name
)
{
PlacementPassTest
().
PlacementNameTest
();
}
}
// namespace ir
...
...
paddle/fluid/framework/ir/mkldnn/mkldnn_placement_pass.h
浏览文件 @
d3a66473
...
...
@@ -27,11 +27,11 @@ namespace ir {
*/
class
MKLDNNPlacementPass
:
public
PlacementPassBase
{
private:
const
std
::
string
GetPlacementName
()
const
{
return
"MKLDNN"
;
}
const
std
::
string
GetPlacementName
()
const
override
{
return
"MKLDNN"
;
}
const
std
::
string
GetAttrName
()
const
{
return
"use_mkldnn"
;
}
const
std
::
string
GetAttrName
()
const
override
{
return
"use_mkldnn"
;
}
const
std
::
unordered_set
<
std
::
string
>
GetOpTypesList
()
const
{
const
std
::
unordered_set
<
std
::
string
>
GetOpTypesList
()
const
override
{
return
Get
<
std
::
unordered_set
<
std
::
string
>>
(
"mkldnn_enabled_op_types"
);
}
};
...
...
paddle/fluid/framework/ir/mkldnn/mkldnn_placement_pass_tester.cc
浏览文件 @
d3a66473
...
...
@@ -21,112 +21,129 @@ 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
,
boost
::
tribool
use_mkldnn
)
{
auto
*
op
=
prog
->
MutableBlock
(
0
)
->
AppendOp
();
op
->
SetType
(
type
);
if
(
!
boost
::
indeterminate
(
use_mkldnn
))
op
->
SetAttr
(
"use_mkldnn"
,
use_mkldnn
);
if
(
type
==
"conv2d"
)
{
op
->
SetAttr
(
"name"
,
name
);
op
->
SetInput
(
"Input"
,
{
inputs
[
0
]});
op
->
SetInput
(
"Filter"
,
{
inputs
[
1
]});
op
->
SetInput
(
"Bias"
,
{
inputs
[
2
]});
}
else
if
(
type
==
"relu"
)
{
op
->
SetInput
(
"X"
,
inputs
);
}
else
if
(
type
==
"concat"
)
{
op
->
SetAttr
(
"axis"
,
1
);
op
->
SetInput
(
"X"
,
{
inputs
[
0
],
inputs
[
1
]});
}
else
if
(
type
==
"pool2d"
)
{
op
->
SetInput
(
"X"
,
{
inputs
[
0
]});
}
else
{
FAIL
()
<<
"Unexpected operator type."
;
class
PlacementPassTest
{
private:
void
SetOp
(
ProgramDesc
*
prog
,
const
std
::
string
&
type
,
const
std
::
string
&
name
,
const
std
::
vector
<
std
::
string
>&
inputs
,
const
std
::
vector
<
std
::
string
>&
outputs
,
boost
::
tribool
use_mkldnn
)
{
auto
*
op
=
prog
->
MutableBlock
(
0
)
->
AppendOp
();
op
->
SetType
(
type
);
if
(
!
boost
::
indeterminate
(
use_mkldnn
))
op
->
SetAttr
(
"use_mkldnn"
,
use_mkldnn
);
if
(
type
==
"conv2d"
)
{
op
->
SetAttr
(
"name"
,
name
);
op
->
SetInput
(
"Input"
,
{
inputs
[
0
]});
op
->
SetInput
(
"Filter"
,
{
inputs
[
1
]});
op
->
SetInput
(
"Bias"
,
{
inputs
[
2
]});
}
else
if
(
type
==
"relu"
)
{
op
->
SetInput
(
"X"
,
inputs
);
}
else
if
(
type
==
"concat"
)
{
op
->
SetAttr
(
"axis"
,
1
);
op
->
SetInput
(
"X"
,
{
inputs
[
0
],
inputs
[
1
]});
}
else
if
(
type
==
"pool2d"
)
{
op
->
SetInput
(
"X"
,
{
inputs
[
0
]});
}
else
{
FAIL
()
<<
"Unexpected operator type."
;
}
op
->
SetOutput
(
"Out"
,
{
outputs
[
0
]});
}
op
->
SetOutput
(
"Out"
,
{
outputs
[
0
]});
}
// operator use_mkldnn
// ---------------------------------------
// (a,b)->concat->c none
// (c,weights,bias)->conv->f none
// f->relu->g false
// g->pool->h false
// (h,weights2,bias2)->conv->k true
// k->relu->l true
ProgramDesc
BuildProgramDesc
()
{
ProgramDesc
prog
;
for
(
auto
&
v
:
std
::
vector
<
std
::
string
>
({
"a"
,
"b"
,
"c"
,
"weights"
,
"bias"
,
"f"
,
"g"
,
"h"
,
"weights2"
,
"bias2"
,
"k"
,
"l"
}))
{
auto
*
var
=
prog
.
MutableBlock
(
0
)
->
Var
(
v
);
var
->
SetType
(
proto
::
VarType
::
SELECTED_ROWS
);
if
(
v
==
"weights"
||
v
==
"bias"
)
{
var
->
SetPersistable
(
true
);
// operator use_mkldnn
// ---------------------------------------
// (a,b)->concat->c none
// (c,weights,bias)->conv->f none
// f->relu->g false
// g->pool->h false
// (h,weights2,bias2)->conv->k true
// k->relu->l true
ProgramDesc
BuildProgramDesc
()
{
ProgramDesc
prog
;
for
(
auto
&
v
:
std
::
vector
<
std
::
string
>
({
"a"
,
"b"
,
"c"
,
"weights"
,
"bias"
,
"f"
,
"g"
,
"h"
,
"weights2"
,
"bias2"
,
"k"
,
"l"
}))
{
auto
*
var
=
prog
.
MutableBlock
(
0
)
->
Var
(
v
);
var
->
SetType
(
proto
::
VarType
::
SELECTED_ROWS
);
if
(
v
==
"weights"
||
v
==
"bias"
)
{
var
->
SetPersistable
(
true
);
}
}
SetOp
(
&
prog
,
"concat"
,
"concat1"
,
std
::
vector
<
std
::
string
>
({
"a"
,
"b"
}),
std
::
vector
<
std
::
string
>
({
"c"
}),
boost
::
indeterminate
);
SetOp
(
&
prog
,
"conv2d"
,
"conv1"
,
std
::
vector
<
std
::
string
>
({
"c"
,
"weights"
,
"bias"
}),
std
::
vector
<
std
::
string
>
({
"f"
}),
boost
::
indeterminate
);
SetOp
(
&
prog
,
"relu"
,
"relu1"
,
std
::
vector
<
std
::
string
>
({
"f"
}),
std
::
vector
<
std
::
string
>
({
"g"
}),
false
);
SetOp
(
&
prog
,
"pool2d"
,
"pool1"
,
std
::
vector
<
std
::
string
>
({
"g"
}),
std
::
vector
<
std
::
string
>
({
"h"
}),
false
);
SetOp
(
&
prog
,
"conv2d"
,
"conv2"
,
std
::
vector
<
std
::
string
>
({
"h"
,
"weights2"
,
"bias2"
}),
std
::
vector
<
std
::
string
>
({
"k"
}),
true
);
SetOp
(
&
prog
,
"relu"
,
"relu2"
,
std
::
vector
<
std
::
string
>
({
"k"
}),
std
::
vector
<
std
::
string
>
({
"l"
}),
true
);
return
prog
;
}
SetOp
(
&
prog
,
"concat"
,
"concat1"
,
std
::
vector
<
std
::
string
>
({
"a"
,
"b"
}),
std
::
vector
<
std
::
string
>
({
"c"
}),
boost
::
indeterminate
);
SetOp
(
&
prog
,
"conv2d"
,
"conv1"
,
std
::
vector
<
std
::
string
>
({
"c"
,
"weights"
,
"bias"
}),
std
::
vector
<
std
::
string
>
({
"f"
}),
boost
::
indeterminate
);
SetOp
(
&
prog
,
"relu"
,
"relu1"
,
std
::
vector
<
std
::
string
>
({
"f"
}),
std
::
vector
<
std
::
string
>
({
"g"
}),
false
);
SetOp
(
&
prog
,
"pool2d"
,
"pool1"
,
std
::
vector
<
std
::
string
>
({
"g"
}),
std
::
vector
<
std
::
string
>
({
"h"
}),
false
);
SetOp
(
&
prog
,
"conv2d"
,
"conv2"
,
std
::
vector
<
std
::
string
>
({
"h"
,
"weights2"
,
"bias2"
}),
std
::
vector
<
std
::
string
>
({
"k"
}),
true
);
SetOp
(
&
prog
,
"relu"
,
"relu2"
,
std
::
vector
<
std
::
string
>
({
"k"
}),
std
::
vector
<
std
::
string
>
({
"l"
}),
true
);
return
prog
;
}
public:
void
MainTest
(
std
::
initializer_list
<
std
::
string
>
mkldnn_enabled_op_types
,
unsigned
expected_use_mkldnn_true_count
)
{
auto
prog
=
BuildProgramDesc
();
void
MainTest
(
std
::
initializer_list
<
std
::
string
>
mkldnn_enabled_op_types
,
unsigned
expected_use_mkldnn_true_count
)
{
auto
prog
=
BuildProgramDesc
();
std
::
unique_ptr
<
ir
::
Graph
>
graph
(
new
ir
::
Graph
(
prog
));
std
::
unique_ptr
<
ir
::
Graph
>
graph
(
new
ir
::
Graph
(
prog
)
);
auto
pass
=
PassRegistry
::
Instance
().
Get
(
"mkldnn_placement_pass"
);
auto
pass
=
PassRegistry
::
Instance
().
Get
(
"mkldnn_placement_pass"
);
pass
->
Set
(
"mkldnn_enabled_op_types"
,
new
std
::
unordered_set
<
std
::
string
>
(
mkldnn_enabled_op_types
));
pass
->
Set
(
"mkldnn_enabled_op_types"
,
new
std
::
unordered_set
<
std
::
string
>
(
mkldnn_enabled_op_types
));
graph
.
reset
(
pass
->
Apply
(
graph
.
release
()));
graph
.
reset
(
pass
->
Apply
(
graph
.
release
()));
unsigned
use_mkldnn_true_count
=
0
;
unsigned
use_mkldnn_true_count
=
0
;
for
(
auto
*
node
:
graph
->
Nodes
())
{
if
(
node
->
IsOp
())
{
auto
*
op
=
node
->
Op
();
if
(
op
->
HasAttr
(
"use_mkldnn"
)
&&
boost
::
get
<
bool
>
(
op
->
GetAttr
(
"use_mkldnn"
)))
{
++
use_mkldnn_true_count
;
for
(
auto
*
node
:
graph
->
Nodes
())
{
if
(
node
->
IsOp
())
{
auto
*
op
=
node
->
Op
();
if
(
op
->
HasAttr
(
"use_mkldnn"
)
&&
boost
::
get
<
bool
>
(
op
->
GetAttr
(
"use_mkldnn"
)))
{
++
use_mkldnn_true_count
;
}
}
}
EXPECT_EQ
(
use_mkldnn_true_count
,
expected_use_mkldnn_true_count
);
}
EXPECT_EQ
(
use_mkldnn_true_count
,
expected_use_mkldnn_true_count
);
}
void
PlacementNameTest
()
{
auto
pass
=
PassRegistry
::
Instance
().
Get
(
"mkldnn_placement_pass"
);
EXPECT_EQ
(
static_cast
<
PlacementPassBase
*>
(
pass
.
get
())
->
GetPlacementName
(),
"MKLDNN"
);
}
};
TEST
(
MKLDNNPlacementPass
,
enable_conv_relu
)
{
// 1 conv (1 conv is always true) + 2 relu (1 relu is always true) + 0 pool
MainTest
({
"conv2d"
,
"relu"
},
3
);
PlacementPassTest
().
MainTest
({
"conv2d"
,
"relu"
},
3
);
}
TEST
(
MKLDNNPlacementPass
,
enable_relu_pool
)
{
// 1 conv (1 conv is always true) + 2 relu (1 relu is always true) + 1 pool
MainTest
({
"relu"
,
"pool2d"
},
4
);
PlacementPassTest
().
MainTest
({
"relu"
,
"pool2d"
},
4
);
}
TEST
(
MKLDNNPlacementPass
,
enable_all
)
{
// 1 conv (1 conv is always true) + 2 relu (1 relu is always true) + 1 pool
MainTest
({},
4
);
PlacementPassTest
().
MainTest
({},
4
);
}
TEST
(
MKLDNNPlacementPass
,
placement_name
)
{
PlacementPassTest
().
PlacementNameTest
();
}
}
// namespace ir
...
...
paddle/fluid/framework/ir/placement_pass_base.h
浏览文件 @
d3a66473
...
...
@@ -35,6 +35,10 @@ class PlacementPassBase : public Pass {
private:
bool
IsSupport
(
const
std
::
string
&
op_type
)
const
;
#if PADDLE_WITH_TESTING
friend
class
PlacementPassTest
;
#endif
};
}
// namespace ir
...
...
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