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df371329
编写于
3月 01, 2017
作者:
Q
qingqing01
提交者:
GitHub
3月 01, 2017
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差异文件
Merge pull request #1482 from qingqing01/data_convert
Fix dataprovider_converter when using only one GPU
上级
91f13e48
566e5f1f
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
29 addition
and
7 deletion
+29
-7
paddle/api/PaddleAPI.h
paddle/api/PaddleAPI.h
+3
-0
paddle/api/Util.cpp
paddle/api/Util.cpp
+2
-0
paddle/py_paddle/dataprovider_converter.py
paddle/py_paddle/dataprovider_converter.py
+19
-6
python/paddle/v2/tests/test_data_feeder.py
python/paddle/v2/tests/test_data_feeder.py
+5
-1
未找到文件。
paddle/api/PaddleAPI.h
浏览文件 @
df371329
...
...
@@ -47,6 +47,9 @@ void setUseGpu(bool useGpu);
/// Return true if this py_paddle is compiled in GPU Version
bool
isGpuVersion
();
/// Return FLAGS_trainer_count
int
getTrainerCount
();
/// The Error of IO Operation. Such as file not found, etc.
class
IOError
{};
...
...
paddle/api/Util.cpp
浏览文件 @
df371329
...
...
@@ -54,5 +54,7 @@ bool isGpuVersion() {
#endif
}
int
getTrainerCount
()
{
return
FLAGS_trainer_count
;
}
static_assert
(
NUM_PARAMETER_TYPES
==
paddle
::
NUM_PARAMETER_TYPES
,
"The Parameter Type should be same in core/api and core/common"
);
paddle/py_paddle/dataprovider_converter.py
浏览文件 @
df371329
...
...
@@ -26,6 +26,15 @@ class IScanner(object):
if
not
isinstance
(
self
.
input_type
,
dp2
.
InputType
):
raise
ValueError
(
"input type should be dataprovider2.InputType"
)
self
.
pos
=
pos
# data_in_gpu is used to indicate whether to create argument on GPU
# or not in GPU mode. Now if using one thread (trainer_count=1),
# trainer uses NeuralNetwork which needs to create argument on GPU
# before calling forward function. So, set data_in_gpu to True.
# Otherwise, trainer uses MultiGradientMachine which will transfer
# data from CPU to GPU in the forward function, set data_in_gpu to
# False in this case.
self
.
data_in_gpu
=
swig_paddle
.
isUsingGpu
(
)
and
swig_paddle
.
getTrainerCount
()
==
1
def
scan
(
self
,
dat
):
pass
...
...
@@ -53,7 +62,8 @@ class DenseScanner(IScanner):
assert
isinstance
(
argument
,
swig_paddle
.
Arguments
)
if
self
.
__mat__
.
dtype
!=
numpy
.
float32
:
self
.
__mat__
=
self
.
__mat__
.
astype
(
numpy
.
float32
)
m
=
swig_paddle
.
Matrix
.
createDenseFromNumpy
(
self
.
__mat__
,
True
,
False
)
m
=
swig_paddle
.
Matrix
.
createDenseFromNumpy
(
self
.
__mat__
,
True
,
self
.
data_in_gpu
)
argument
.
setSlotValue
(
self
.
pos
,
m
)
...
...
@@ -75,10 +85,13 @@ class SparseBinaryScanner(IScanner):
def
finish_scan
(
self
,
argument
):
assert
isinstance
(
argument
,
swig_paddle
.
Arguments
)
m
=
swig_paddle
.
Matrix
.
createSparse
(
self
.
__height__
,
self
.
input_type
.
dim
,
len
(
self
.
__cols__
),
len
(
self
.
__value__
)
==
0
)
m
=
swig_paddle
.
Matrix
.
createSparse
(
self
.
__height__
,
self
.
input_type
.
dim
,
len
(
self
.
__cols__
),
len
(
self
.
__value__
)
==
0
,
False
,
# trans
False
)
# TODO supoort GPU
assert
isinstance
(
m
,
swig_paddle
.
Matrix
)
m
.
sparseCopyFrom
(
self
.
__rows__
,
self
.
__cols__
,
self
.
__value__
)
argument
.
setSlotValue
(
self
.
pos
,
m
)
...
...
@@ -102,7 +115,7 @@ class IndexScanner(IScanner):
self
.
__ids__
.
append
(
dat
)
def
finish_scan
(
self
,
argument
):
ids
=
swig_paddle
.
IVector
.
create
(
self
.
__ids__
)
ids
=
swig_paddle
.
IVector
.
create
(
self
.
__ids__
,
self
.
data_in_gpu
)
assert
isinstance
(
argument
,
swig_paddle
.
Arguments
)
argument
.
setSlotIds
(
self
.
pos
,
ids
)
...
...
python/paddle/v2/tests/test_data_feeder.py
浏览文件 @
df371329
...
...
@@ -235,4 +235,8 @@ class DataFeederTest(unittest.TestCase):
if
__name__
==
'__main__'
:
api
.
initPaddle
(
"--use_gpu=0"
)
unittest
.
main
()
suite
=
unittest
.
TestLoader
().
loadTestsFromTestCase
(
DataFeederTest
)
unittest
.
TextTestRunner
().
run
(
suite
)
if
api
.
isGpuVersion
():
api
.
setUseGpu
(
True
)
unittest
.
main
()
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