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24181fdc
编写于
1月 04, 2018
作者:
Y
Yang Yu
浏览文件
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差异文件
Merge branch 'develop' of github.com:baidu/Paddle into feature/async_drop_kid
上级
8ae84a57
cd5fad13
变更
8
隐藏空白更改
内联
并排
Showing
8 changed file
with
49 addition
and
18 deletion
+49
-18
paddle/framework/init.cc
paddle/framework/init.cc
+5
-0
paddle/framework/init.h
paddle/framework/init.h
+2
-0
paddle/framework/lod_tensor.cc
paddle/framework/lod_tensor.cc
+3
-0
paddle/framework/threadpool.h
paddle/framework/threadpool.h
+5
-6
paddle/operators/activation_op.h
paddle/operators/activation_op.h
+11
-6
paddle/pybind/pybind.cc
paddle/pybind/pybind.cc
+1
-0
python/paddle/v2/fluid/__init__.py
python/paddle/v2/fluid/__init__.py
+3
-2
python/paddle/v2/fluid/layers/ops.py
python/paddle/v2/fluid/layers/ops.py
+19
-4
未找到文件。
paddle/framework/init.cc
浏览文件 @
24181fdc
...
...
@@ -75,5 +75,10 @@ bool InitDevices(const std::vector<std::string> &devices) {
return
true
;
}
void
InitGLOG
(
const
std
::
string
&
prog_name
)
{
google
::
InitGoogleLogging
(
prog_name
.
c_str
());
google
::
InstallFailureSignalHandler
();
}
}
// namespace framework
}
// namespace paddle
paddle/framework/init.h
浏览文件 @
24181fdc
...
...
@@ -22,6 +22,8 @@ namespace framework {
void
InitGflags
(
std
::
vector
<
std
::
string
>
&
argv
);
void
InitGLOG
(
const
std
::
string
&
prog_name
);
bool
InitDevices
(
const
std
::
vector
<
std
::
string
>
&
devices
);
}
// namespace framework
...
...
paddle/framework/lod_tensor.cc
浏览文件 @
24181fdc
...
...
@@ -177,6 +177,9 @@ void AppendLoD(LoD *lod, const LoD &lod_length) {
lod
->
empty
()
||
lod
->
size
()
==
lod_length
.
size
(),
"The lod_length should has the same size with the appended lod."
);
if
(
lod
->
empty
())
{
for
(
size_t
i
=
0
;
i
<
lod_length
.
size
();
++
i
)
{
lod
->
emplace_back
(
1
,
0
);
// size = 1, value = 0;
}
*
lod
=
LoD
(
lod_length
.
size
(),
std
::
vector
<
size_t
>
({
0
}));
}
for
(
size_t
i
=
0
;
i
<
lod
->
size
();
++
i
)
{
...
...
paddle/framework/threadpool.h
浏览文件 @
24181fdc
...
...
@@ -29,7 +29,6 @@ namespace framework {
class
ThreadPool
{
public:
typedef
std
::
packaged_task
<
void
()
>
Task
;
typedef
std
::
function
<
void
()
>
Fun
;
/**
* @brief Get a instance of threadpool, the thread number will
...
...
@@ -67,7 +66,8 @@ class ThreadPool {
* @return std::future<void>, we could wait for the task finished by
* f.wait().
*/
std
::
future
<
void
>
Run
(
const
Fun
&
fn
)
{
template
<
typename
Callback
>
std
::
future
<
void
>
Run
(
Callback
fn
)
{
std
::
unique_lock
<
std
::
mutex
>
lock
(
mutex_
);
Task
task
(
std
::
bind
(
fn
));
std
::
future
<
void
>
f
=
task
.
get_future
();
...
...
@@ -162,10 +162,9 @@ class ThreadPool {
// Run a function asynchronously.
// NOTE: The function must return void. If the function need to return a value,
// you can use lambda to capture a value pointer.
template
<
typename
Callback
,
typename
ARGS
>
std
::
future
<
void
>
Async
(
Callback
callback
,
ARGS
...
args
)
{
return
ThreadPool
::
GetInstance
()
->
Run
(
[
&
]
{
callback
(
std
::
forward
(
args
)...);
});
template
<
typename
Callback
>
std
::
future
<
void
>
Async
(
Callback
callback
)
{
return
ThreadPool
::
GetInstance
()
->
Run
(
callback
);
};
}
// namespace framework
...
...
paddle/operators/activation_op.h
浏览文件 @
24181fdc
...
...
@@ -15,6 +15,7 @@ limitations under the License. */
#pragma once
#include "paddle/framework/eigen.h"
#include "paddle/framework/op_registry.h"
#include "paddle/operators/detail/safe_ref.h"
namespace
paddle
{
namespace
operators
{
...
...
@@ -26,12 +27,16 @@ class ActivationKernel
using
T
=
typename
Functor
::
ELEMENT_TYPE
;
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
auto
*
X
=
context
.
Input
<
framework
::
Tensor
>
(
"X"
);
auto
*
Out
=
context
.
Output
<
framework
::
Tensor
>
(
"Out"
);
Out
->
mutable_data
<
T
>
(
context
.
GetPlace
());
auto
x
=
framework
::
EigenVector
<
T
>::
Flatten
(
*
X
);
auto
out
=
framework
::
EigenVector
<
T
>::
Flatten
(
*
Out
);
auto
&
X
=
detail
::
Ref
(
context
.
Input
<
framework
::
Tensor
>
(
"X"
),
"Cannot get input tensor X, variable name = %s"
,
context
.
op
().
Input
(
"X"
));
auto
&
Out
=
detail
::
Ref
(
context
.
Output
<
framework
::
Tensor
>
(
"Out"
),
"Cannot get output tensor Out, variable name = %s"
,
context
.
op
().
Output
(
"Out"
));
Out
.
mutable_data
<
T
>
(
context
.
GetPlace
());
auto
x
=
framework
::
EigenVector
<
T
>::
Flatten
(
X
);
auto
out
=
framework
::
EigenVector
<
T
>::
Flatten
(
Out
);
auto
*
place
=
context
.
template
device_context
<
DeviceContext
>().
eigen_device
();
Functor
functor
;
...
...
paddle/pybind/pybind.cc
浏览文件 @
24181fdc
...
...
@@ -427,6 +427,7 @@ All parameter, weight, gradient are variables in Paddle.
m
.
def
(
"unique_integer"
,
UniqueIntegerGenerator
);
m
.
def
(
"init_gflags"
,
framework
::
InitGflags
);
m
.
def
(
"init_glog"
,
framework
::
InitGLOG
);
m
.
def
(
"init_devices"
,
&
framework
::
InitDevices
);
m
.
def
(
"is_compile_gpu"
,
IsCompileGPU
);
...
...
python/paddle/v2/fluid/__init__.py
浏览文件 @
24181fdc
...
...
@@ -27,7 +27,7 @@ __all__ = framework.__all__ + executor.__all__ + [
]
def
__
read_gflags_from_env
__
():
def
__
bootstrap
__
():
"""
Enable reading gflags from environment variables.
...
...
@@ -41,6 +41,7 @@ def __read_gflags_from_env__():
read_env_flags
.
append
(
'fraction_of_gpu_memory_to_use'
)
core
.
init_gflags
([
sys
.
argv
[
0
]]
+
[
"--tryfromenv="
+
","
.
join
(
read_env_flags
)])
core
.
init_glog
(
sys
.
argv
[
0
])
if
core
.
is_compile_gpu
():
core
.
init_devices
([
"CPU"
,
"GPU:0"
])
...
...
@@ -48,4 +49,4 @@ def __read_gflags_from_env__():
core
.
init_devices
([
"CPU"
])
__
read_gflags_from_env
__
()
__
bootstrap
__
()
python/paddle/v2/fluid/layers/ops.py
浏览文件 @
24181fdc
from
..registry
import
register_layer
__all__
=
[
'mean'
,
'mul'
,
'dropout'
,
'reshape'
,
'sigmoid'
,
'scale'
,
'transpose'
,
'sigmoid_cross_entropy_with_logits'
,
'elementwise_add'
,
'elementwise_div'
,
'elementwise_sub'
,
'elementwise_mul'
,
'clip'
,
'abs'
,
'sequence_softmax'
__activations__
=
[
'abs'
,
'tanh'
,
'sigmoid'
,
'relu'
,
'sqrt'
,
'ceil'
,
'floor'
,
'log'
,
'round'
]
__all__
=
[
'mean'
,
'mul'
,
'dropout'
,
'reshape'
,
'scale'
,
'transpose'
,
'sigmoid_cross_entropy_with_logits'
,
'elementwise_add'
,
'elementwise_div'
,
'elementwise_sub'
,
'elementwise_mul'
,
'clip'
,
'sequence_softmax'
,
]
+
__activations__
for
_OP
in
set
(
__all__
):
globals
()[
_OP
]
=
register_layer
(
_OP
)
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