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体验新版 GitCode,发现更多精彩内容 >>
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a42f8f4f
编写于
1月 07, 2019
作者:
M
mozga-intel
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
Enable element_wise_add operator for a ngraph
test=develop
上级
9c027651
变更
7
隐藏空白更改
内联
并排
Showing
7 changed file
with
364 addition
and
10 deletion
+364
-10
paddle/fluid/framework/ngraph_bridge.cc
paddle/fluid/framework/ngraph_bridge.cc
+3
-0
paddle/fluid/operators/ngraph/ngraph_ops.h
paddle/fluid/operators/ngraph/ngraph_ops.h
+1
-0
paddle/fluid/operators/ngraph/ops/elementwise_add_op.h
paddle/fluid/operators/ngraph/ops/elementwise_add_op.h
+89
-0
paddle/fluid/operators/ngraph/ops/elementwise_binary_prepare_node.h
...id/operators/ngraph/ops/elementwise_binary_prepare_node.h
+78
-0
paddle/fluid/operators/ngraph/ops/elementwise_node.h
paddle/fluid/operators/ngraph/ops/elementwise_node.h
+65
-0
paddle/fluid/platform/ngraph_helper.h
paddle/fluid/platform/ngraph_helper.h
+41
-10
python/paddle/fluid/tests/unittests/ngraph/test_elementwise_add_ngraph_op.py
.../tests/unittests/ngraph/test_elementwise_add_ngraph_op.py
+87
-0
未找到文件。
paddle/fluid/framework/ngraph_bridge.cc
浏览文件 @
a42f8f4f
...
...
@@ -26,11 +26,14 @@ limitations under the License. */
namespace
paddle
{
namespace
framework
{
namespace
NG_OPS
=
paddle
::
operators
::
ngraphs
;
std
::
map
<
std
::
string
,
std
::
function
<
void
(
const
std
::
shared_ptr
<
OperatorBase
>&
,
std
::
shared_ptr
<
std
::
unordered_map
<
std
::
string
,
std
::
shared_ptr
<
ngraph
::
Node
>>>
)
>>
NgraphBridge
::
NG_NODE_MAP
=
{
{
"elementwise_add"
,
NG_OPS
::
BuildElementwiseAddNode
},
{
"elementwise_add_grad"
,
NG_OPS
::
BuildElementwiseAddGradNode
},
{
"fill_constant"
,
paddle
::
operators
::
ngraphs
::
BuildFillConstantNode
},
{
"mean"
,
paddle
::
operators
::
ngraphs
::
BuildMeanNode
},
{
"mean_grad"
,
paddle
::
operators
::
ngraphs
::
BuildMeanGradNode
},
...
...
paddle/fluid/operators/ngraph/ngraph_ops.h
浏览文件 @
a42f8f4f
...
...
@@ -22,6 +22,7 @@ limitations under the License. */
#pragma once
#include "ops/binary_unnary_op.h"
#include "ops/elementwise_add_op.h"
#include "ops/fill_constant_op.h"
#include "ops/mean_op.h"
#include "ops/mul_op.h"
...
...
paddle/fluid/operators/ngraph/ops/elementwise_add_op.h
0 → 100644
浏览文件 @
a42f8f4f
/*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. */
#ifdef PADDLE_WITH_NGRAPH
#pragma once
#include <string>
#include <vector>
#include "ngraph/ngraph.hpp"
#include "paddle/fluid/operators/ngraph/ops/elementwise_node.h"
#include "paddle/fluid/platform/ngraph_helper.h"
namespace
paddle
{
namespace
operators
{
namespace
ngraphs
{
void
BuildElementwiseAddNode
(
const
std
::
shared_ptr
<
paddle
::
framework
::
OperatorBase
>&
op
,
std
::
shared_ptr
<
std
::
unordered_map
<
std
::
string
,
std
::
shared_ptr
<
ngraph
::
Node
>>>
ngb_node_map
)
{
BuildElementwiseBinaryNode
<
ngraph
::
op
::
Add
>
(
op
,
ngb_node_map
);
}
void
BuildElementwiseAddGradNode
(
const
std
::
shared_ptr
<
paddle
::
framework
::
OperatorBase
>&
op
,
std
::
shared_ptr
<
std
::
unordered_map
<
std
::
string
,
std
::
shared_ptr
<
ngraph
::
Node
>>>
ngb_node_map
)
{
auto
op_attrs
=
paddle
::
framework
::
AttrReader
(
op
->
Attrs
());
int
axis
=
op_attrs
.
Get
<
int
>
(
"axis"
);
auto
dout
=
paddle
::
platform
::
GetInputNode
(
op
,
"Out@GRAD"
,
ngb_node_map
);
auto
y
=
paddle
::
platform
::
GetInputNode
(
op
,
"Y"
,
ngb_node_map
);
auto
dout_shape
=
dout
->
get_shape
();
auto
y_shape
=
y
->
get_shape
();
if
(
dout_shape
==
y_shape
)
{
paddle
::
platform
::
SetOutputNode
(
op
,
"X@GRAD"
,
dout
,
ngb_node_map
);
paddle
::
platform
::
SetOutputNode
(
op
,
"Y@GRAD"
,
dout
,
ngb_node_map
);
}
else
{
axis
=
(
axis
==
-
1
?
dout_shape
.
size
()
-
y_shape
.
size
()
:
axis
);
paddle
::
platform
::
TrimTrailingSingularDims
(
&
y_shape
);
axis
=
(
y_shape
.
size
()
==
0
?
dout_shape
.
size
()
:
axis
);
int
pre
,
n
,
post
;
paddle
::
platform
::
GetMidDims
(
dout_shape
,
y_shape
,
axis
,
&
pre
,
&
n
,
&
post
);
ngraph
::
Shape
lhs_shape
{};
lhs_shape
.
push_back
(
pre
);
lhs_shape
.
push_back
(
n
);
if
(
post
!=
1
)
{
lhs_shape
.
push_back
(
post
);
}
std
::
vector
<
size_t
>
lhs_order
(
dout_shape
.
size
());
std
::
iota
(
std
::
begin
(
lhs_order
),
std
::
end
(
lhs_order
),
0
);
auto
dout_reshape
=
std
::
make_shared
<
ngraph
::
op
::
Reshape
>
(
dout
,
ngraph
::
AxisVector
(
lhs_order
),
lhs_shape
);
ngraph
::
AxisSet
axis_set
{
0
};
if
(
post
!=
1
)
{
axis_set
.
insert
(
2
);
}
auto
dout_sum
=
std
::
make_shared
<
ngraph
::
op
::
Sum
>
(
dout_reshape
,
axis_set
);
auto
dy
=
std
::
make_shared
<
ngraph
::
op
::
Reshape
>
(
dout_sum
,
ngraph
::
AxisVector
{
0
},
y
->
get_shape
());
paddle
::
platform
::
SetOutputNode
(
op
,
"X@GRAD"
,
dout
,
ngb_node_map
);
paddle
::
platform
::
SetOutputNode
(
op
,
"Y@GRAD"
,
dy
,
ngb_node_map
);
}
}
}
// namespace ngraphs
}
// namespace operators
}
// namespace paddle
#endif
paddle/fluid/operators/ngraph/ops/elementwise_binary_prepare_node.h
0 → 100644
浏览文件 @
a42f8f4f
/*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. */
#ifdef PADDLE_WITH_NGRAPH
#pragma once
#include <string>
#include <vector>
#include "ngraph/ngraph.hpp"
#include "paddle/fluid/platform/ngraph_helper.h"
namespace
paddle
{
namespace
operators
{
namespace
ngraphs
{
ngraph
::
NodeVector
ElementwiseBinaryNodePrepare
(
const
std
::
shared_ptr
<
paddle
::
framework
::
OperatorBase
>&
op
,
std
::
shared_ptr
<
std
::
unordered_map
<
std
::
string
,
std
::
shared_ptr
<
ngraph
::
Node
>>>
ngb_node_map
)
{
auto
op_attrs
=
paddle
::
framework
::
AttrReader
(
op
->
Attrs
());
int
axis
=
op_attrs
.
Get
<
int
>
(
"axis"
);
auto
lhs
=
paddle
::
platform
::
GetInputNode
(
op
,
"X"
,
ngb_node_map
);
auto
rhs
=
paddle
::
platform
::
GetInputNode
(
op
,
"Y"
,
ngb_node_map
);
auto
lhs_shape
=
lhs
->
get_shape
();
auto
rhs_shape
=
rhs
->
get_shape
();
PADDLE_ENFORCE_GE
(
lhs_shape
.
size
(),
rhs_shape
.
size
(),
"Rank of first input must >= rank of second input."
);
if
(
lhs_shape
==
rhs_shape
)
{
return
ngraph
::
NodeVector
{
lhs
,
rhs
};
}
axis
=
(
axis
==
-
1
?
lhs_shape
.
size
()
-
rhs_shape
.
size
()
:
axis
);
PADDLE_ENFORCE
(
axis
>=
0
&&
axis
<
(
int
)(
lhs_shape
.
size
()),
"Axis should be in range [0, lhs_shape)"
);
paddle
::
platform
::
TrimTrailingSingularDims
(
&
rhs_shape
);
axis
=
(
rhs_shape
.
size
()
==
0
)
?
lhs_shape
.
size
()
:
axis
;
int
pre
,
n
,
post
;
paddle
::
platform
::
GetMidDims
(
lhs_shape
,
rhs_shape
,
axis
,
&
pre
,
&
n
,
&
post
);
ngraph
::
Shape
l_shape
{};
l_shape
.
push_back
(
pre
);
l_shape
.
push_back
(
n
);
l_shape
.
push_back
(
post
);
std
::
vector
<
size_t
>
rhs_order
(
rhs
->
get_shape
().
size
());
std
::
iota
(
std
::
begin
(
rhs_order
),
std
::
end
(
rhs_order
),
0
);
ngraph
::
Shape
r_shape
{};
r_shape
.
push_back
(
n
);
auto
rhs_reshape
=
std
::
make_shared
<
ngraph
::
op
::
Reshape
>
(
rhs
,
ngraph
::
AxisVector
(
rhs_order
),
r_shape
);
auto
rhs_bcast
=
std
::
make_shared
<
ngraph
::
op
::
Broadcast
>
(
rhs_reshape
,
l_shape
,
ngraph
::
AxisSet
{
0
,
2
});
std
::
vector
<
size_t
>
bcast_order
(
rhs_bcast
->
get_shape
().
size
());
std
::
iota
(
std
::
begin
(
bcast_order
),
std
::
end
(
bcast_order
),
0
);
std
::
shared_ptr
<
ngraph
::
Node
>
rhs_bcast_reshape
=
std
::
make_shared
<
ngraph
::
op
::
Reshape
>
(
rhs_bcast
,
ngraph
::
AxisVector
(
bcast_order
),
lhs_shape
);
return
ngraph
::
NodeVector
{
lhs
,
rhs_bcast_reshape
};
}
}
// namespace ngraphs
}
// namespace operators
}
// namespace paddle
#endif
paddle/fluid/operators/ngraph/ops/elementwise_node.h
0 → 100644
浏览文件 @
a42f8f4f
/*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. */
#ifdef PADDLE_WITH_NGRAPH
#pragma once
#include <string>
#include "ngraph/ngraph.hpp"
#include "paddle/fluid/operators/ngraph/ops/elementwise_binary_prepare_node.h"
#include "paddle/fluid/platform/ngraph_helper.h"
namespace
paddle
{
namespace
operators
{
namespace
ngraphs
{
template
<
typename
T
>
void
BuildElementwiseBinaryNode
(
const
std
::
shared_ptr
<
paddle
::
framework
::
OperatorBase
>&
op
,
std
::
shared_ptr
<
std
::
unordered_map
<
std
::
string
,
std
::
shared_ptr
<
ngraph
::
Node
>>>
ngb_node_map
)
{
auto
nodes
=
ElementwiseBinaryNodePrepare
(
op
,
ngb_node_map
);
std
::
shared_ptr
<
ngraph
::
Node
>&
x
=
nodes
.
at
(
0
);
std
::
shared_ptr
<
ngraph
::
Node
>&
y
=
nodes
.
at
(
1
);
if
(
x
->
get_element_type
()
!=
y
->
get_element_type
())
{
y
=
std
::
make_shared
<
ngraph
::
op
::
Convert
>
(
y
,
x
->
get_element_type
());
}
auto
out
=
std
::
make_shared
<
T
>
(
x
,
y
);
paddle
::
platform
::
SetOutputNode
(
op
,
"Out"
,
out
,
ngb_node_map
);
}
template
<
typename
T
>
void
BuildElementwiseCompareNode
(
const
std
::
shared_ptr
<
paddle
::
framework
::
OperatorBase
>&
op
,
std
::
shared_ptr
<
std
::
unordered_map
<
std
::
string
,
std
::
shared_ptr
<
ngraph
::
Node
>>>
ngb_node_map
)
{
auto
nodes
=
ElementwiseBinaryNodePrepare
(
op
,
ngb_node_map
);
std
::
shared_ptr
<
ngraph
::
Node
>&
x
=
nodes
.
at
(
0
);
std
::
shared_ptr
<
ngraph
::
Node
>&
y
=
nodes
.
at
(
1
);
if
(
x
->
get_element_type
()
!=
y
->
get_element_type
())
{
x
=
std
::
make_shared
<
ngraph
::
op
::
Convert
>
(
x
,
ngraph
::
element
::
f64
);
y
=
std
::
make_shared
<
ngraph
::
op
::
Convert
>
(
y
,
ngraph
::
element
::
f64
);
}
auto
out
=
std
::
make_shared
<
T
>
(
x
,
y
);
paddle
::
platform
::
SetOutputNode
(
op
,
"Out"
,
out
,
ngb_node_map
);
}
}
// namespace ngraphs
}
// namespace operators
}
// namespace paddle
#endif
paddle/fluid/platform/ngraph_helper.h
浏览文件 @
a42f8f4f
...
...
@@ -23,7 +23,7 @@ limitations under the License. */
namespace
paddle
{
namespace
platform
{
static
ngraph
::
Shape
FlattenTo2d
(
ngraph
::
Shape
sh
,
int
num
)
{
ngraph
::
Shape
FlattenTo2d
(
ngraph
::
Shape
sh
,
int
num
)
{
auto
x1
=
std
::
accumulate
(
std
::
begin
(
sh
),
std
::
begin
(
sh
)
+
num
,
1
,
std
::
multiplies
<
size_t
>
());
auto
x2
=
std
::
accumulate
(
std
::
begin
(
sh
)
+
num
,
std
::
end
(
sh
),
1
,
...
...
@@ -33,15 +33,15 @@ static ngraph::Shape FlattenTo2d(ngraph::Shape sh, int num) {
return
ngraph
::
Shape
{
x1_l
,
x2_l
};
}
st
atic
std
::
shared_ptr
<
ngraph
::
Node
>
NgReshaper
(
std
::
shared_ptr
<
ngraph
::
Node
>
input
,
ngraph
::
Shape
shape
)
{
st
d
::
shared_ptr
<
ngraph
::
Node
>
NgReshaper
(
std
::
shared_ptr
<
ngraph
::
Node
>
input
,
ngraph
::
Shape
shape
)
{
std
::
vector
<
size_t
>
input_order
(
input
->
get_shape
().
size
());
std
::
iota
(
std
::
begin
(
input_order
),
std
::
end
(
input_order
),
0
);
return
std
::
make_shared
<
ngraph
::
op
::
Reshape
>
(
input
,
ngraph
::
AxisVector
(
input_order
),
shape
);
}
st
atic
st
d
::
shared_ptr
<
ngraph
::
Node
>
GetNode
(
std
::
shared_ptr
<
ngraph
::
Node
>
GetNode
(
const
std
::
shared_ptr
<
paddle
::
framework
::
OperatorBase
>&
op
,
const
std
::
string
prm
,
const
paddle
::
framework
::
VariableNameMap
&
var_map
,
std
::
shared_ptr
<
...
...
@@ -57,7 +57,7 @@ static std::shared_ptr<ngraph::Node> GetNode(
}
}
st
atic
st
d
::
shared_ptr
<
ngraph
::
Node
>
GetInputNode
(
std
::
shared_ptr
<
ngraph
::
Node
>
GetInputNode
(
const
std
::
shared_ptr
<
paddle
::
framework
::
OperatorBase
>&
op
,
const
std
::
string
prm
,
std
::
shared_ptr
<
...
...
@@ -66,7 +66,7 @@ static std::shared_ptr<ngraph::Node> GetInputNode(
return
GetNode
(
op
,
prm
,
op
->
Inputs
(),
ngb_node_map
);
}
st
atic
st
d
::
shared_ptr
<
ngraph
::
Node
>
GetOutputNode
(
std
::
shared_ptr
<
ngraph
::
Node
>
GetOutputNode
(
const
std
::
shared_ptr
<
paddle
::
framework
::
OperatorBase
>&
op
,
const
std
::
string
prm
,
std
::
shared_ptr
<
...
...
@@ -75,7 +75,7 @@ static std::shared_ptr<ngraph::Node> GetOutputNode(
return
GetNode
(
op
,
prm
,
op
->
Outputs
(),
ngb_node_map
);
}
static
void
SetOutputNode
(
void
SetOutputNode
(
const
std
::
shared_ptr
<
paddle
::
framework
::
OperatorBase
>&
op
,
const
std
::
string
prm
,
std
::
shared_ptr
<
ngraph
::
Node
>
node
,
std
::
shared_ptr
<
...
...
@@ -91,14 +91,45 @@ static void SetOutputNode(
}
}
static
bool
HasOutput
(
const
std
::
shared_ptr
<
paddle
::
framework
::
OperatorBase
>&
op
,
const
std
::
string
prm
)
{
bool
HasOutput
(
const
std
::
shared_ptr
<
paddle
::
framework
::
OperatorBase
>&
op
,
const
std
::
string
prm
)
{
auto
&
outputs
=
op
->
Outputs
();
if
(
outputs
.
find
(
prm
)
==
outputs
.
end
())
return
false
;
return
outputs
.
at
(
prm
).
size
()
>
0
;
}
inline
void
GetMidDims
(
const
ngraph
::
Shape
&
x_shape
,
const
ngraph
::
Shape
&
y_shape
,
int
axis
,
int
*
pre
,
int
*
n
,
int
*
post
)
{
*
pre
=
1
;
*
n
=
1
;
*
post
=
1
;
for
(
int
i
=
0
;
i
<
axis
;
++
i
)
{
(
*
pre
)
*=
x_shape
[
i
];
}
for
(
size_t
i
=
0
;
i
<
y_shape
.
size
();
++
i
)
{
PADDLE_ENFORCE_EQ
(
x_shape
[
i
+
axis
],
y_shape
[
i
],
"Broadcast dimension mismatch."
);
(
*
n
)
*=
y_shape
[
i
];
}
for
(
size_t
i
=
axis
+
y_shape
.
size
();
i
<
x_shape
.
size
();
++
i
)
{
(
*
post
)
*=
x_shape
[
i
];
}
}
inline
void
TrimTrailingSingularDims
(
ngraph
::
Shape
*
shape
)
{
// Remove trailing dimensions of size 1 for y
auto
actual_shape_size
=
shape
->
size
();
for
(;
actual_shape_size
!=
0
;
--
actual_shape_size
)
{
if
((
*
shape
)[
actual_shape_size
-
1
]
!=
1
)
{
break
;
}
else
{
shape
->
pop_back
();
}
}
}
}
// namespace platform
}
// namespace paddle
...
...
python/paddle/fluid/tests/unittests/ngraph/test_elementwise_add_ngraph_op.py
0 → 100644
浏览文件 @
a42f8f4f
# 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.
from
__future__
import
print_function
import
unittest
from
paddle.fluid.tests.unittests.test_elementwise_add_op
import
*
class
TestNGRAPHElementwiseAddOp
(
TestElementwiseAddOp
):
def
init_input_output
(
self
):
super
(
TestNGRAPHElementwiseAddOp
,
self
).
init_input_output
()
class
TestNGRAPHElementwiseAddOp_scalar
(
TestElementwiseAddOp_scalar
):
def
init_input_output
(
self
):
super
(
TestNGRAPHElementwiseAddOp_scalar
,
self
).
init_input_output
()
class
TestNGRAPHElementwiseAddOp_scalar2
(
TestElementwiseAddOp_scalar2
):
def
init_input_output
(
self
):
super
(
TestNGRAPHElementwiseAddOp_scalar2
,
self
).
init_input_output
()
class
TestNGRAPHElementwiseAddOp_Vector
(
TestElementwiseAddOp_Vector
):
def
init_input_output
(
self
):
super
(
TestNGRAPHElementwiseAddOp_Vector
,
self
).
init_input_output
()
class
TesNGRAPHtElementwiseAddOp_broadcast_0
(
TestElementwiseAddOp_broadcast_0
):
def
init_input_output
(
self
):
super
(
TesNGRAPHtElementwiseAddOp_broadcast_0
,
self
).
init_input_output
()
class
TestNGRAPHElementwiseAddOp_broadcast_1
(
TestElementwiseAddOp_broadcast_1
):
def
init_input_output
(
self
):
super
(
TestNGRAPHElementwiseAddOp_broadcast_1
,
self
).
init_input_output
()
class
TestNGRAPHElementwiseAddOp_broadcast_2
(
TestElementwiseAddOp_broadcast_2
):
def
init_input_output
(
self
):
super
(
TestNGRAPHElementwiseAddOp_broadcast_2
,
self
).
init_input_output
()
class
TestNGRAPHElementwiseAddOp_broadcast_3
(
TestElementwiseAddOp_broadcast_3
):
def
init_input_output
(
self
):
super
(
TestNGRAPHElementwiseAddOp_broadcast_3
,
self
).
init_input_output
()
class
TestNGRAPHElementwiseAddOp_broadcast_4
(
TestElementwiseAddOp_broadcast_4
):
def
init_input_output
(
self
):
super
(
TestNGRAPHElementwiseAddOp_broadcast_4
,
self
).
init_input_output
()
class
TestNGRAPHElementwiseAddOp_rowwise_add_0
(
TestElementwiseAddOp_rowwise_add_0
):
def
init_input_output
(
self
):
super
(
TestNGRAPHElementwiseAddOp_rowwise_add_0
,
self
).
init_input_output
()
class
TestNGRAPHElementwiseAddOp_rowwise_add_1
(
TestElementwiseAddOp_rowwise_add_1
):
def
init_input_output
(
self
):
super
(
TestNGRAPHElementwiseAddOp_rowwise_add_1
,
self
).
init_input_output
()
class
TestNGRAPHElementwiseAddOp_channelwise_add
(
TestElementwiseAddOp_channelwise_add
):
def
init_input_output
(
self
):
super
(
TestNGRAPHElementwiseAddOp_channelwise_add
,
self
).
init_input_output
()
if
__name__
==
'__main__'
:
unittest
.
main
()
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