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25fc2a1f
编写于
3月 19, 2021
作者:
J
Jacek Czaja
提交者:
GitHub
3月 19, 2021
浏览文件
操作
浏览文件
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电子邮件补丁
差异文件
[oneDNN] Added Elementwise Mul grad fp32/bf16 (#31647)
上级
878e117b
变更
7
隐藏空白更改
内联
并排
Showing
7 changed file
with
206 addition
and
15 deletion
+206
-15
paddle/fluid/operators/elementwise/elementwise_op.h
paddle/fluid/operators/elementwise/elementwise_op.h
+2
-3
paddle/fluid/operators/elementwise/mkldnn/elementwise_add_mkldnn_op.cc
...operators/elementwise/mkldnn/elementwise_add_mkldnn_op.cc
+11
-0
paddle/fluid/operators/elementwise/mkldnn/elementwise_mkldnn_op.h
...luid/operators/elementwise/mkldnn/elementwise_mkldnn_op.h
+0
-1
paddle/fluid/operators/elementwise/mkldnn/elementwise_mul_mkldnn_op.cc
...operators/elementwise/mkldnn/elementwise_mul_mkldnn_op.cc
+116
-0
paddle/fluid/platform/mkldnn_reuse.h
paddle/fluid/platform/mkldnn_reuse.h
+9
-1
python/paddle/fluid/tests/unittests/mkldnn/test_elementwise_mul_bf16_mkldnn_op.py
...s/unittests/mkldnn/test_elementwise_mul_bf16_mkldnn_op.py
+59
-7
python/paddle/fluid/tests/unittests/mkldnn/test_elementwise_mul_mkldnn_op.py
.../tests/unittests/mkldnn/test_elementwise_mul_mkldnn_op.py
+9
-3
未找到文件。
paddle/fluid/operators/elementwise/elementwise_op.h
浏览文件 @
25fc2a1f
...
@@ -276,7 +276,7 @@ class ElementwiseOpGrad : public framework::OperatorWithKernel {
...
@@ -276,7 +276,7 @@ class ElementwiseOpGrad : public framework::OperatorWithKernel {
#ifdef PADDLE_WITH_MKLDNN
#ifdef PADDLE_WITH_MKLDNN
// If broadcasting is needed, use native implementation
// If broadcasting is needed, use native implementation
auto
CanMKLDNNElementwise
Add
GradBeUsed
=
[
&
]()
{
auto
CanMKLDNNElementwiseGradBeUsed
=
[
&
]()
{
auto
dx_dims
=
ctx
.
Input
<
Tensor
>
(
"X"
)
->
dims
();
auto
dx_dims
=
ctx
.
Input
<
Tensor
>
(
"X"
)
->
dims
();
auto
dy_dims
=
ctx
.
Input
<
Tensor
>
(
"Y"
)
->
dims
();
auto
dy_dims
=
ctx
.
Input
<
Tensor
>
(
"Y"
)
->
dims
();
// No broadcast or broadcasting of data on inner dims is supported
// No broadcast or broadcasting of data on inner dims is supported
...
@@ -284,8 +284,7 @@ class ElementwiseOpGrad : public framework::OperatorWithKernel {
...
@@ -284,8 +284,7 @@ class ElementwiseOpGrad : public framework::OperatorWithKernel {
};
};
if
(
this
->
CanMKLDNNBeUsed
(
ctx
,
input_data_type
)
&&
if
(
this
->
CanMKLDNNBeUsed
(
ctx
,
input_data_type
)
&&
(
ctx
.
Type
()
!=
"elementwise_add_grad"
||
CanMKLDNNElementwiseGradBeUsed
())
{
CanMKLDNNElementwiseAddGradBeUsed
()))
{
return
framework
::
OpKernelType
(
input_data_type
,
ctx
.
GetPlace
(),
return
framework
::
OpKernelType
(
input_data_type
,
ctx
.
GetPlace
(),
framework
::
DataLayout
::
kMKLDNN
,
framework
::
DataLayout
::
kMKLDNN
,
framework
::
LibraryType
::
kMKLDNN
);
framework
::
LibraryType
::
kMKLDNN
);
...
...
paddle/fluid/operators/elementwise/mkldnn/elementwise_add_mkldnn_op.cc
浏览文件 @
25fc2a1f
...
@@ -61,6 +61,9 @@ class EltwiseAddMKLDNNGradKernel : public ElemwiseGradKernel<T> {
...
@@ -61,6 +61,9 @@ class EltwiseAddMKLDNNGradKernel : public ElemwiseGradKernel<T> {
platform
::
EventRole
::
kUniqueOp
);
platform
::
EventRole
::
kUniqueOp
);
reorder_p
->
execute
(
astream
,
*
reorder_src_memory_p
,
*
reorder_dst_memory_p
);
reorder_p
->
execute
(
astream
,
*
reorder_src_memory_p
,
*
reorder_dst_memory_p
);
astream
.
wait
();
astream
.
wait
();
dx
->
set_layout
(
DataLayout
::
kMKLDNN
);
dx
->
set_format
(
platform
::
GetMKLDNNFormat
(
*
reorder_dst_memory_p
));
}
}
if
(
dy
)
{
if
(
dy
)
{
...
@@ -75,6 +78,9 @@ class EltwiseAddMKLDNNGradKernel : public ElemwiseGradKernel<T> {
...
@@ -75,6 +78,9 @@ class EltwiseAddMKLDNNGradKernel : public ElemwiseGradKernel<T> {
reorder_p
->
execute
(
astream
,
*
reorder_src_memory_p
,
reorder_p
->
execute
(
astream
,
*
reorder_src_memory_p
,
*
reorder_dst_memory_p
);
*
reorder_dst_memory_p
);
astream
.
wait
();
astream
.
wait
();
dy
->
set_layout
(
DataLayout
::
kMKLDNN
);
dy
->
set_format
(
platform
::
GetMKLDNNFormat
(
*
reorder_dst_memory_p
));
}
else
{
}
else
{
// Broadcasting
// Broadcasting
platform
::
ReductionMKLDNNHandler
<
T
>
handler_sum
(
platform
::
ReductionMKLDNNHandler
<
T
>
handler_sum
(
...
@@ -86,6 +92,11 @@ class EltwiseAddMKLDNNGradKernel : public ElemwiseGradKernel<T> {
...
@@ -86,6 +92,11 @@ class EltwiseAddMKLDNNGradKernel : public ElemwiseGradKernel<T> {
reduction_p
->
execute
(
astream
,
{{
DNNL_ARG_SRC
,
*
reorder_src_memory_p
},
reduction_p
->
execute
(
astream
,
{{
DNNL_ARG_SRC
,
*
reorder_src_memory_p
},
{
DNNL_ARG_DST
,
*
dy_memory_p
}});
{
DNNL_ARG_DST
,
*
dy_memory_p
}});
astream
.
wait
();
astream
.
wait
();
dy
->
set_layout
(
DataLayout
::
kMKLDNN
);
dy
->
set_format
(
platform
::
GetMKLDNNFormat
(
dy_memory_p
->
get_desc
().
reshape
(
paddle
::
framework
::
vectorize
<
int64_t
>
(
dy
->
dims
()))));
}
}
}
}
}
}
...
...
paddle/fluid/operators/elementwise/mkldnn/elementwise_mkldnn_op.h
浏览文件 @
25fc2a1f
...
@@ -15,7 +15,6 @@
...
@@ -15,7 +15,6 @@
#pragma once
#pragma once
#include <string>
#include <string>
#include <unordered_map>
#include <unordered_map>
#include "paddle/fluid/memory/memcpy.h"
#include "paddle/fluid/operators/elementwise/elementwise_add_op.h"
#include "paddle/fluid/operators/elementwise/elementwise_add_op.h"
#include "paddle/fluid/operators/elementwise/elementwise_op_function.h"
#include "paddle/fluid/operators/elementwise/elementwise_op_function.h"
...
...
paddle/fluid/operators/elementwise/mkldnn/elementwise_mul_mkldnn_op.cc
浏览文件 @
25fc2a1f
...
@@ -14,6 +14,118 @@ limitations under the License. */
...
@@ -14,6 +14,118 @@ limitations under the License. */
#include "paddle/fluid/operators/elementwise/mkldnn/elementwise_mkldnn_op.h"
#include "paddle/fluid/operators/elementwise/mkldnn/elementwise_mkldnn_op.h"
namespace
paddle
{
namespace
framework
{
class
ExecutionContext
;
}
// namespace framework
namespace
platform
{
class
CPUDeviceContext
;
struct
CPUPlace
;
}
// namespace platform
}
// namespace paddle
namespace
paddle
{
namespace
operators
{
template
<
typename
T
>
class
EltwiseMulMKLDNNGradKernel
:
public
ElemwiseGradKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
ElemwiseGradKernel
<
T
>::
Compute
(
ctx
);
auto
&
dev_ctx
=
ctx
.
template
device_context
<
paddle
::
platform
::
MKLDNNDeviceContext
>();
const
auto
&
mkldnn_engine
=
dev_ctx
.
GetEngine
();
auto
*
x
=
ctx
.
Input
<
framework
::
Tensor
>
(
"X"
);
auto
*
y
=
ctx
.
Input
<
framework
::
Tensor
>
(
"Y"
);
auto
*
dout
=
ctx
.
Input
<
framework
::
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
auto
*
dx
=
ctx
.
Output
<
framework
::
Tensor
>
(
framework
::
GradVarName
(
"X"
));
auto
*
dy
=
ctx
.
Output
<
framework
::
Tensor
>
(
framework
::
GradVarName
(
"Y"
));
int
axis
=
ctx
.
Attr
<
int
>
(
"axis"
);
auto
&
astream
=
platform
::
MKLDNNDeviceContext
::
tls
().
get_stream
();
if
(
dx
)
{
// dx = dout*y
platform
::
BinaryMKLDNNHandler
<
T
>
handler
(
dnnl
::
algorithm
::
binary_mul
,
axis
,
dev_ctx
,
mkldnn_engine
,
ctx
.
GetPlace
(),
dout
,
y
,
dx
,
1.0
f
,
1.0
f
,
1.0
f
,
ctx
.
InputName
(
framework
::
GradVarName
(
"Out"
)));
const
auto
src_dout_memory
=
handler
.
AcquireSrcMemory
(
dout
);
const
auto
src_y_memory
=
handler
.
AcquireSecondSrcMemory
(
y
);
const
auto
dst_dx_memory
=
handler
.
AcquireDstMemory
(
dx
);
const
auto
binary_prim
=
handler
.
AcquireForwardPrimitive
();
const
std
::
unordered_map
<
int
,
dnnl
::
memory
>
args
=
{
{
DNNL_ARG_SRC_0
,
*
src_dout_memory
},
{
DNNL_ARG_SRC_1
,
*
src_y_memory
},
{
DNNL_ARG_DST
,
*
dst_dx_memory
}};
binary_prim
->
execute
(
astream
,
args
);
astream
.
wait
();
dx
->
set_layout
(
framework
::
DataLayout
::
kMKLDNN
);
dx
->
set_format
(
platform
::
GetMKLDNNFormat
(
*
dst_dx_memory
));
}
if
(
dy
)
{
// dy = dout*x
// Handler is having nullptr passed instead of output tensor as
// we want Dst buffer to be allocated by oneDNN not to use Tensor
platform
::
BinaryMKLDNNHandler
<
T
>
handler
(
dnnl
::
algorithm
::
binary_mul
,
axis
,
dev_ctx
,
mkldnn_engine
,
ctx
.
GetPlace
(),
dout
,
x
,
nullptr
,
1.0
f
,
1.0
f
,
1.0
f
,
ctx
.
InputName
(
framework
::
GradVarName
(
"Out"
)));
const
auto
src_dout_memory
=
handler
.
AcquireSrcMemory
(
dout
);
const
auto
src_x_memory
=
handler
.
AcquireSecondSrcMemory
(
x
);
// If broadcasting is in use then let's write to temporary
// buffer allocated by oneDNN
const
auto
dst_dy_memory
=
(
dout
->
dims
()
==
dy
->
dims
())
?
handler
.
AcquireDstMemory
(
dy
)
:
handler
.
AcquireDstMemory
();
const
auto
binary_prim
=
handler
.
AcquireForwardPrimitive
();
const
std
::
unordered_map
<
int
,
dnnl
::
memory
>
args
=
{
{
DNNL_ARG_SRC_0
,
*
src_dout_memory
},
{
DNNL_ARG_SRC_1
,
*
src_x_memory
},
{
DNNL_ARG_DST
,
*
dst_dy_memory
}};
binary_prim
->
execute
(
astream
,
args
);
astream
.
wait
();
dy
->
set_layout
(
framework
::
DataLayout
::
kMKLDNN
);
// Reduction is needed for broadcasting scenario
if
(
dout
->
dims
()
!=
dy
->
dims
())
{
platform
::
ReductionMKLDNNHandler
<
T
>
handler_sum
(
dnnl
::
algorithm
::
reduction_sum
,
0.0
f
,
0.0
f
,
dev_ctx
,
mkldnn_engine
,
ctx
.
GetPlace
(),
dout
,
dy
,
ctx
.
InputName
(
framework
::
GradVarName
(
"Out"
)));
auto
dy_memory_p
=
handler_sum
.
AcquireDstMemory
(
dy
);
auto
reduction_p
=
handler_sum
.
AcquireForwardPrimitive
();
// As source we use mem object with results from binary operation
reduction_p
->
execute
(
astream
,
{{
DNNL_ARG_SRC
,
*
dst_dy_memory
},
{
DNNL_ARG_DST
,
*
dy_memory_p
}});
astream
.
wait
();
dy
->
set_format
(
platform
::
GetMKLDNNFormat
(
dy_memory_p
->
get_desc
().
reshape
(
paddle
::
framework
::
vectorize
<
int64_t
>
(
dy
->
dims
()))));
}
else
{
dy
->
set_format
(
platform
::
GetMKLDNNFormat
(
*
dst_dy_memory
));
}
}
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
namespace
ops
=
paddle
::
operators
;
REGISTER_OP_KERNEL
(
REGISTER_OP_KERNEL
(
...
@@ -23,3 +135,7 @@ REGISTER_OP_KERNEL(
...
@@ -23,3 +135,7 @@ REGISTER_OP_KERNEL(
dnnl
::
algorithm
::
binary_mul
>
,
dnnl
::
algorithm
::
binary_mul
>
,
ops
::
EltwiseMKLDNNKernel
<
int8_t
,
dnnl
::
algorithm
::
binary_mul
>
,
ops
::
EltwiseMKLDNNKernel
<
int8_t
,
dnnl
::
algorithm
::
binary_mul
>
,
ops
::
EltwiseMKLDNNKernel
<
uint8_t
,
dnnl
::
algorithm
::
binary_mul
>
)
ops
::
EltwiseMKLDNNKernel
<
uint8_t
,
dnnl
::
algorithm
::
binary_mul
>
)
REGISTER_OP_KERNEL
(
elementwise_mul_grad
,
MKLDNN
,
::
paddle
::
platform
::
CPUPlace
,
ops
::
EltwiseMulMKLDNNGradKernel
<
paddle
::
platform
::
bfloat16
>
,
ops
::
EltwiseMulMKLDNNGradKernel
<
float
>
)
paddle/fluid/platform/mkldnn_reuse.h
浏览文件 @
25fc2a1f
...
@@ -87,6 +87,11 @@ class MKLDNNHandlerT {
...
@@ -87,6 +87,11 @@ class MKLDNNHandlerT {
"@dst_mem_p"
);
"@dst_mem_p"
);
}
}
template
<
typename
T_out
=
T
>
std
::
shared_ptr
<
mkldnn
::
memory
>
AcquireDstMemory
(
void
)
{
return
this
->
AcquireMemoryFromPrimitive
(
fwd_pd_
->
dst_desc
(),
"@dstt_mem_p"
);
}
template
<
typename
T_out
=
T
>
template
<
typename
T_out
=
T
>
std
::
shared_ptr
<
mkldnn
::
memory
>
AcquireDstMemory
(
std
::
shared_ptr
<
mkldnn
::
memory
>
AcquireDstMemory
(
const
framework
::
Tensor
*
output
)
{
const
framework
::
Tensor
*
output
)
{
...
@@ -561,7 +566,10 @@ class BinaryMKLDNNHandler : public platform::MKLDNNHandlerT<T, dnnl::binary> {
...
@@ -561,7 +566,10 @@ class BinaryMKLDNNHandler : public platform::MKLDNNHandlerT<T, dnnl::binary> {
const
auto
src_x_tz
=
framework
::
vectorize
(
x
->
dims
());
const
auto
src_x_tz
=
framework
::
vectorize
(
x
->
dims
());
const
auto
src_y_tz
=
framework
::
vectorize
(
y
->
dims
());
const
auto
src_y_tz
=
framework
::
vectorize
(
y
->
dims
());
const
auto
dst_tz
=
framework
::
vectorize
(
z
->
dims
());
// if output tensor(z) is nullptr then we are computing into oneDNN
// managed buffer
const
auto
dst_tz
=
(
z
==
nullptr
)
?
src_x_tz
:
framework
::
vectorize
(
z
->
dims
());
const
auto
src0_md
=
dnnl
::
memory
::
desc
(
const
auto
src0_md
=
dnnl
::
memory
::
desc
(
src_x_tz
,
platform
::
MKLDNNGetDataType
<
T
>
(),
x
->
format
());
src_x_tz
,
platform
::
MKLDNNGetDataType
<
T
>
(),
x
->
format
());
...
...
python/paddle/fluid/tests/unittests/mkldnn/test_elementwise_mul_bf16_mkldnn_op.py
浏览文件 @
25fc2a1f
...
@@ -30,10 +30,9 @@ class TestElementwiseMulBf16MklDNNOp(OpTest):
...
@@ -30,10 +30,9 @@ class TestElementwiseMulBf16MklDNNOp(OpTest):
self
.
axis
=
-
1
self
.
axis
=
-
1
self
.
generate_data
()
self
.
generate_data
()
self
.
inputs
=
{
self
.
x_bf16
=
convert_float_to_uint16
(
self
.
x
)
'X'
:
convert_float_to_uint16
(
self
.
x
),
self
.
y_bf16
=
convert_float_to_uint16
(
self
.
y
)
'Y'
:
convert_float_to_uint16
(
self
.
y
)
self
.
inputs
=
{
'X'
:
self
.
x_bf16
,
'Y'
:
self
.
y_bf16
}
}
self
.
attrs
=
{
'axis'
:
self
.
axis
,
'use_mkldnn'
:
self
.
use_mkldnn
}
self
.
attrs
=
{
'axis'
:
self
.
axis
,
'use_mkldnn'
:
self
.
use_mkldnn
}
self
.
outputs
=
{
'Out'
:
convert_float_to_uint16
(
self
.
out
)}
self
.
outputs
=
{
'Out'
:
convert_float_to_uint16
(
self
.
out
)}
...
@@ -46,13 +45,66 @@ class TestElementwiseMulBf16MklDNNOp(OpTest):
...
@@ -46,13 +45,66 @@ class TestElementwiseMulBf16MklDNNOp(OpTest):
self
.
check_output_with_place
(
core
.
CPUPlace
())
self
.
check_output_with_place
(
core
.
CPUPlace
())
def
test_check_grad_normal
(
self
):
def
test_check_grad_normal
(
self
):
pass
self
.
check_grad_with_place
(
core
.
CPUPlace
(),
[
"X"
,
"Y"
],
"Out"
,
check_dygraph
=
False
,
user_defined_grads
=
[
np
.
multiply
(
self
.
x
,
self
.
y
),
np
.
multiply
(
self
.
x
,
self
.
x
)
],
user_defined_grad_outputs
=
[
self
.
x_bf16
])
def
test_check_grad_ingore_x
(
self
):
def
test_check_grad_ingore_x
(
self
):
pass
self
.
check_grad_with_place
(
core
.
CPUPlace
(),
[
"Y"
],
"Out"
,
check_dygraph
=
False
,
user_defined_grads
=
[
np
.
multiply
(
self
.
y
,
self
.
x
)],
user_defined_grad_outputs
=
[
self
.
y_bf16
])
def
test_check_grad_ingore_y
(
self
):
def
test_check_grad_ingore_y
(
self
):
pass
self
.
check_grad_with_place
(
core
.
CPUPlace
(),
[
"X"
],
"Out"
,
check_dygraph
=
False
,
user_defined_grads
=
[
np
.
multiply
(
self
.
x
,
self
.
y
)],
user_defined_grad_outputs
=
[
self
.
x_bf16
])
class
TestElementwiseMulBroadcastingBf16MklDNNOp
(
TestElementwiseMulBf16MklDNNOp
):
def
generate_data
(
self
):
self
.
x
=
np
.
random
.
uniform
(
1
,
2
,
[
1
,
2
,
3
,
100
]).
astype
(
np
.
float32
)
self
.
y
=
np
.
random
.
uniform
(
1
,
2
,
[
100
]).
astype
(
np
.
float32
)
self
.
out
=
np
.
multiply
(
self
.
x
,
self
.
y
)
# Compute partial sums along all axes but last one
def
compute_reduced_gradients
(
self
,
out_grads
):
part_sum
=
np
.
add
.
reduceat
(
out_grads
,
[
0
],
axis
=
0
)
part_sum
=
np
.
add
.
reduceat
(
part_sum
,
[
0
],
axis
=
1
)
part_sum
=
np
.
add
.
reduceat
(
part_sum
,
[
0
],
axis
=
2
)
return
part_sum
.
flatten
()
def
test_check_grad_normal
(
self
):
self
.
check_grad_with_place
(
core
.
CPUPlace
(),
[
"X"
,
"Y"
],
"Out"
,
check_dygraph
=
False
,
user_defined_grads
=
[
np
.
multiply
(
self
.
x
,
self
.
y
),
self
.
compute_reduced_gradients
(
np
.
multiply
(
self
.
x
,
self
.
x
))
],
user_defined_grad_outputs
=
[
self
.
x_bf16
])
def
test_check_grad_ingore_x
(
self
):
self
.
check_grad_with_place
(
core
.
CPUPlace
(),
[
"Y"
],
"Out"
,
check_dygraph
=
False
,
user_defined_grads
=
[
self
.
compute_reduced_gradients
(
np
.
multiply
(
self
.
x
,
self
.
x
))
],
user_defined_grad_outputs
=
[
self
.
x_bf16
])
if
__name__
==
'__main__'
:
if
__name__
==
'__main__'
:
...
...
python/paddle/fluid/tests/unittests/mkldnn/test_elementwise_mul_mkldnn_op.py
浏览文件 @
25fc2a1f
...
@@ -17,6 +17,7 @@ import unittest
...
@@ -17,6 +17,7 @@ import unittest
import
numpy
as
np
import
numpy
as
np
from
paddle.fluid.tests.unittests.op_test
import
skip_check_grad_ci
from
paddle.fluid.tests.unittests.op_test
import
skip_check_grad_ci
from
paddle.fluid.tests.unittests.test_elementwise_mul_op
import
ElementwiseMulOp
from
paddle.fluid.tests.unittests.test_elementwise_mul_op
import
ElementwiseMulOp
from
paddle
import
enable_static
class
TestMKLDNNElementwiseMulOp
(
ElementwiseMulOp
):
class
TestMKLDNNElementwiseMulOp
(
ElementwiseMulOp
):
...
@@ -51,13 +52,17 @@ class TestMKLDNNElementwiseMulOp4(TestMKLDNNElementwiseMulOp):
...
@@ -51,13 +52,17 @@ class TestMKLDNNElementwiseMulOp4(TestMKLDNNElementwiseMulOp):
def
test_check_grad_normal
(
self
):
def
test_check_grad_normal
(
self
):
pass
pass
def
test_check_grad_ingore_x
(
self
):
pass
def
test_check_grad_ingore_y
(
self
):
def
test_check_grad_ingore_y
(
self
):
pass
pass
class
TestMKLDNNElementwiseMulOp5
(
TestMKLDNNElementwiseMulOp
):
def
init_input_output
(
self
):
self
.
x
=
np
.
random
.
uniform
(
1
,
2
,
[
2
,
3
,
4
,
100
]).
astype
(
self
.
dtype
)
self
.
y
=
np
.
random
.
uniform
(
1
,
2
,
[
100
]).
astype
(
self
.
dtype
)
self
.
out
=
np
.
multiply
(
self
.
x
,
self
.
y
)
''' INT8 Tests '''
''' INT8 Tests '''
...
@@ -140,4 +145,5 @@ class TestUint8Scales(TestInt8Scales):
...
@@ -140,4 +145,5 @@ class TestUint8Scales(TestInt8Scales):
if
__name__
==
'__main__'
:
if
__name__
==
'__main__'
:
enable_static
()
unittest
.
main
()
unittest
.
main
()
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