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体验新版 GitCode,发现更多精彩内容 >>
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6540701f
编写于
8月 08, 2017
作者:
Y
Yu Yang
提交者:
GitHub
8月 08, 2017
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差异文件
Merge pull request #3293 from reyoung/feature/uniform_random_op
Add uniform random operator
上级
01c668e6
7c250810
变更
7
隐藏空白更改
内联
并排
Showing
7 changed file
with
201 addition
and
7 deletion
+201
-7
paddle/framework/CMakeLists.txt
paddle/framework/CMakeLists.txt
+8
-7
paddle/framework/pybind.cc
paddle/framework/pybind.cc
+1
-0
paddle/operators/CMakeLists.txt
paddle/operators/CMakeLists.txt
+2
-0
paddle/operators/uniform_random_op.cc
paddle/operators/uniform_random_op.cc
+84
-0
paddle/operators/uniform_random_op.cu
paddle/operators/uniform_random_op.cu
+70
-0
python/paddle/v2/framework/tests/CMakeLists.txt
python/paddle/v2/framework/tests/CMakeLists.txt
+1
-0
python/paddle/v2/framework/tests/test_uniform_random_op.py
python/paddle/v2/framework/tests/test_uniform_random_op.py
+35
-0
未找到文件。
paddle/framework/CMakeLists.txt
浏览文件 @
6540701f
...
...
@@ -40,11 +40,12 @@ if(WITH_PYTHON)
cc_library
(
paddle_pybind SHARED
SRCS pybind.cc
DEPS pybind python backward
fc_op
sgd_op
add_op
mean_op
cross_entropy_op
fill_zeros_like_op
recurrent_op
)
fc_op
sgd_op
add_op
mean_op
cross_entropy_op
recurrent_op
uniform_random_op
fill_zeros_like_op
)
endif
(
WITH_PYTHON
)
paddle/framework/pybind.cc
浏览文件 @
6540701f
...
...
@@ -42,6 +42,7 @@ USE_OP(softmax);
USE_OP
(
rowwise_add
);
USE_OP
(
fill_zeros_like
);
USE_OP_WITHOUT_KERNEL
(
recurrent_op
);
USE_OP
(
uniform_random
);
namespace
paddle
{
namespace
framework
{
template
<
typename
ClassType
>
...
...
paddle/operators/CMakeLists.txt
浏览文件 @
6540701f
...
...
@@ -66,3 +66,5 @@ op_library(fc_op
op_library
(
recurrent_op SRCS recurrent_op.cc rnn/recurrent_op_utils.cc
DEPS op_desc tensor op_registry operator net_op
)
cc_test
(
recurrent_op_test SRCS recurrent_op_test.cc DEPS recurrent_op gtest mul_op add_op
)
op_library
(
uniform_random_op
SRCS uniform_random_op.cc uniform_random_op.cu
)
paddle/operators/uniform_random_op.cc
0 → 100644
浏览文件 @
6540701f
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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 <random>
#include <type_traits>
#include "paddle/framework/op_registry.h"
#include "paddle/framework/operator.h"
namespace
paddle
{
namespace
operators
{
// It seems that Eigen::Tensor::random in GPU will SEGFAULT.
// Use std::random and thrust::random(thrust is a std library in CUDA) to
// implement uniform random.
template
<
typename
T
>
class
CPUUniformRandomKernel
:
public
framework
::
OpKernel
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
auto
*
tensor
=
context
.
Output
<
framework
::
Tensor
>
(
0
);
T
*
data
=
tensor
->
mutable_data
<
T
>
(
context
.
GetPlace
());
unsigned
int
seed
=
static_cast
<
unsigned
int
>
(
context
.
op_
.
GetAttr
<
int
>
(
"seed"
));
std
::
minstd_rand
engine
;
if
(
seed
==
0
)
{
seed
=
std
::
random_device
()();
}
engine
.
seed
(
seed
);
std
::
uniform_real_distribution
<
T
>
dist
(
static_cast
<
T
>
(
context
.
op_
.
GetAttr
<
float
>
(
"min"
)),
static_cast
<
T
>
(
context
.
op_
.
GetAttr
<
float
>
(
"max"
)));
for
(
ssize_t
i
=
0
;
i
<
framework
::
product
(
tensor
->
dims
());
++
i
)
{
data
[
i
]
=
dist
(
engine
);
}
}
};
class
UniformRandomOp
:
public
framework
::
OperatorWithKernel
{
protected:
void
InferShape
(
const
framework
::
InferShapeContext
&
ctx
)
const
override
{
PADDLE_ENFORCE
(
GetAttr
<
float
>
(
"min"
)
<
GetAttr
<
float
>
(
"max"
),
"uniform_random's min must less then max"
);
auto
*
tensor
=
ctx
.
Output
<
framework
::
Tensor
>
(
0
);
auto
dims
=
GetAttr
<
std
::
vector
<
int
>>
(
"dims"
);
tensor
->
Resize
(
framework
::
make_ddim
(
dims
));
}
};
class
UniformRandomOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
UniformRandomOpMaker
(
framework
::
OpProto
*
proto
,
framework
::
OpAttrChecker
*
op_checker
)
:
framework
::
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddOutput
(
"Out"
,
"The output tensor of uniform random op"
);
AddComment
(
R"DOC(Uniform random operator.
Used to initialize tensor with uniform random generator.
)DOC"
);
AddAttr
<
std
::
vector
<
int
>>
(
"dims"
,
"the dimension of random tensor"
);
AddAttr
<
float
>
(
"min"
,
"Minimum value of uniform random"
).
SetDefault
(
-
1.0
f
);
AddAttr
<
float
>
(
"max"
,
"Maximun value of uniform random"
).
SetDefault
(
1.0
f
);
AddAttr
<
int
>
(
"seed"
,
"Random seed of uniform random. "
"0 means generate a seed by system"
)
.
SetDefault
(
0
);
}
};
}
// namespace operators
}
// namespace paddle
REGISTER_OP
(
uniform_random
,
paddle
::
operators
::
UniformRandomOp
,
paddle
::
operators
::
UniformRandomOpMaker
);
REGISTER_OP_CPU_KERNEL
(
uniform_random
,
paddle
::
operators
::
CPUUniformRandomKernel
<
float
>
);
paddle/operators/uniform_random_op.cu
0 → 100644
浏览文件 @
6540701f
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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 <thrust/device_ptr.h>
#include <thrust/iterator/counting_iterator.h>
#include <thrust/random.h>
#include <thrust/transform.h>
#include "paddle/framework/op_registry.h"
#include "paddle/framework/operator.h"
namespace
paddle
{
namespace
operators
{
template
<
typename
T
>
struct
UniformGenerator
{
T
min_
,
max_
;
unsigned
int
seed_
;
__host__
__device__
UniformGenerator
(
T
min
,
T
max
,
int
seed
)
:
min_
(
min
),
max_
(
max
),
seed_
(
seed
)
{}
__host__
__device__
T
operator
()(
const
unsigned
int
n
)
const
{
thrust
::
minstd_rand
rng
;
rng
.
seed
(
seed_
);
thrust
::
uniform_real_distribution
<
T
>
dist
(
min_
,
max_
);
rng
.
discard
(
n
);
return
dist
(
rng
);
}
};
// It seems that Eigen::Tensor::random in GPU will SEGFAULT.
// Use std::random and thrust::random(thrust is a std library in CUDA) to
// implement uniform random.
template
<
typename
T
>
class
GPUUniformRandomKernel
:
public
framework
::
OpKernel
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
auto
*
tensor
=
context
.
Output
<
framework
::
Tensor
>
(
0
);
T
*
data
=
tensor
->
mutable_data
<
T
>
(
context
.
GetPlace
());
unsigned
int
seed
=
static_cast
<
unsigned
int
>
(
context
.
op_
.
GetAttr
<
int
>
(
"seed"
));
if
(
seed
==
0
)
{
seed
=
std
::
random_device
()();
}
T
min
=
static_cast
<
T
>
(
context
.
op_
.
GetAttr
<
float
>
(
"min"
));
T
max
=
static_cast
<
T
>
(
context
.
op_
.
GetAttr
<
float
>
(
"max"
));
thrust
::
counting_iterator
<
unsigned
int
>
index_sequence_begin
(
0
);
ssize_t
N
=
framework
::
product
(
tensor
->
dims
());
thrust
::
transform
(
index_sequence_begin
,
index_sequence_begin
+
N
,
thrust
::
device_ptr
<
T
>
(
data
),
UniformGenerator
<
T
>
(
min
,
max
,
seed
));
}
};
}
// namespace operators
}
// namespace paddle
REGISTER_OP_GPU_KERNEL
(
uniform_random
,
paddle
::
operators
::
GPUUniformRandomKernel
<
float
>
);
python/paddle/v2/framework/tests/CMakeLists.txt
浏览文件 @
6540701f
...
...
@@ -21,3 +21,4 @@ py_test(test_rowwise_add_op SRCS test_rowwise_add_op.py)
py_test
(
test_default_scope_funcs SRCS test_default_scope_funcs.py
)
py_test
(
test_operator SRCS test_operator.py
)
py_test
(
test_uniform_random_op SRCS test_uniform_random_op.py
)
python/paddle/v2/framework/tests/test_uniform_random_op.py
0 → 100644
浏览文件 @
6540701f
import
unittest
from
paddle.v2.framework.op
import
Operator
import
paddle.v2.framework.core
as
core
import
numpy
class
UniformRandomTest
(
unittest
.
TestCase
):
def
test_uniform_random_cpu
(
self
):
self
.
uniform_random_test
(
place
=
core
.
CPUPlace
())
def
test_uniform_random_gpu
(
self
):
if
core
.
is_compile_gpu
():
self
.
uniform_random_test
(
place
=
core
.
GPUPlace
(
0
))
def
uniform_random_test
(
self
,
place
):
scope
=
core
.
Scope
()
scope
.
new_var
(
"X"
).
get_tensor
()
op
=
Operator
(
"uniform_random"
,
Out
=
"X"
,
dims
=
[
1000
,
784
],
min
=-
5.0
,
max
=
10.0
,
seed
=
10
)
op
.
infer_shape
(
scope
)
ctx
=
core
.
DeviceContext
.
create
(
place
)
op
.
run
(
scope
,
ctx
)
tensor
=
numpy
.
array
(
scope
.
find_var
(
"X"
).
get_tensor
())
self
.
assertAlmostEqual
(
tensor
.
mean
(),
2.5
,
delta
=
0.1
)
if
__name__
==
'__main__'
:
unittest
.
main
()
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