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体验新版 GitCode,发现更多精彩内容 >>
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2be3a747
编写于
11月 07, 2016
作者:
W
wangyang59
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
Modified API to use FLAGS_use_gpu as useGpu default value
上级
0ba0f02c
变更
5
隐藏空白更改
内联
并排
Showing
5 changed file
with
67 addition
and
10 deletion
+67
-10
paddle/api/Matrix.cpp
paddle/api/Matrix.cpp
+11
-0
paddle/api/Paddle.swig
paddle/api/Paddle.swig
+8
-1
paddle/api/PaddleAPI.h
paddle/api/PaddleAPI.h
+23
-8
paddle/api/Util.cpp
paddle/api/Util.cpp
+2
-0
paddle/api/Vector.cpp
paddle/api/Vector.cpp
+23
-1
未找到文件。
paddle/api/Matrix.cpp
浏览文件 @
2be3a747
...
...
@@ -52,6 +52,17 @@ Matrix* Matrix::createDense(const std::vector<float>& data, size_t height,
return
m
;
}
Matrix
*
Matrix
::
createDenseFromNumpy
(
float
*
data
,
int
dim1
,
int
dim2
,
bool
copy
,
bool
useGpu
)
{
if
(
useGpu
)
{
/// Gpu mode only supports copy=True
CHECK
(
copy
);
return
Matrix
::
createGpuDenseFromNumpy
(
data
,
dim1
,
dim2
);
}
else
{
return
Matrix
::
createCpuDenseFromNumpy
(
data
,
dim1
,
dim2
,
copy
);
}
}
Matrix
*
Matrix
::
createCpuDenseFromNumpy
(
float
*
data
,
int
dim1
,
int
dim2
,
bool
copy
)
{
auto
m
=
new
Matrix
();
...
...
paddle/api/Paddle.swig
浏览文件 @
2be3a747
...
...
@@ -133,14 +133,21 @@ namespace std {
%newobject Matrix::createZero;
%newobject Matrix::createSparse;
%newobject Matrix::createDense;
%newobject Matrix::createDenseFromNumpy;
%newobject Matrix::createCpuDenseFromNumpy;
%newobject Matrix::createGpuDenseFromNumpy;
%newobject Vector::createZero;
%newobject Vector::create;
%newobject Vector::createVectorFromNumpy;
%newobject Vector::createCpuVectorFromNumpy;
%newobject Vector::createGpuVectorFromNumpy;
%newobject IVector::createZero;
%newobject IVector::create;
%newobject IVector::createVectorFromNumpy;
%newobject IVector::createCpuVectorFromNumpy;
%newobject IVector::createGpuVectorFromNumpy;
%newobject Trainer::createByCommandLine;
%newobject Trainer::get
Network
Output;
%newobject Trainer::get
Forward
Output;
%newobject Trainer::getLayerOutput;
%newobject Arguments::getSlotValue;
%newobject Arguments::getSlotIds;
...
...
paddle/api/PaddleAPI.h
浏览文件 @
2be3a747
...
...
@@ -42,6 +42,9 @@ using namespace paddle::enumeration_wrapper; // NOLINT
*/
void
initPaddle
(
int
argc
,
char
**
argv
);
/// Return FLAGS_use_gpu
bool
isUseGpu
();
/// Return true if this py_paddle is compiled in GPU Version
bool
isGpuVersion
();
...
...
@@ -101,7 +104,8 @@ public:
/**
* Create A Matrix with height,width, which is filled by zero.
*/
static
Matrix
*
createZero
(
size_t
height
,
size_t
width
,
bool
useGpu
=
false
);
static
Matrix
*
createZero
(
size_t
height
,
size_t
width
,
bool
useGpu
=
isUseGpu
());
/**
* Create Sparse Matrix.
...
...
@@ -114,7 +118,7 @@ public:
*/
static
Matrix
*
createSparse
(
size_t
height
,
size_t
width
,
size_t
nnz
,
bool
isNonVal
=
true
,
bool
trans
=
false
,
bool
useGpu
=
false
);
bool
useGpu
=
isUseGpu
()
);
/**
* Create Dense Matrix.
...
...
@@ -123,7 +127,11 @@ public:
* @note the value will be copy into a new matrix.
*/
static
Matrix
*
createDense
(
const
std
::
vector
<
float
>&
data
,
size_t
height
,
size_t
width
,
bool
useGpu
=
false
);
size_t
width
,
bool
useGpu
=
isUseGpu
());
static
Matrix
*
createDenseFromNumpy
(
float
*
data
,
int
dim1
,
int
dim2
,
bool
copy
=
true
,
bool
useGpu
=
isUseGpu
());
/**
* Create Cpu Dense Matrix from numpy matrix, dtype=float32
...
...
@@ -221,15 +229,18 @@ public:
~
Vector
();
/// Create Vector filled with zero.
static
Vector
*
createZero
(
size_t
sz
,
bool
useGpu
=
false
);
static
Vector
*
createZero
(
size_t
sz
,
bool
useGpu
=
isUseGpu
()
);
/**
* Create Vector from list of float.
*
* It will create a new vector, and copy data into it.
*/
static
Vector
*
create
(
const
std
::
vector
<
float
>&
data
,
bool
useGpu
=
false
);
static
Vector
*
create
(
const
std
::
vector
<
float
>&
data
,
bool
useGpu
=
isUseGpu
());
static
Vector
*
createVectorFromNumpy
(
float
*
data
,
int
dim
,
bool
copy
=
true
,
bool
useGpu
=
isUseGpu
());
/**
* Create Cpu Vector from numpy array, which dtype=float32
*
...
...
@@ -279,13 +290,17 @@ class IVector {
public:
/// Create IVector filled with zero
static
IVector
*
createZero
(
size_t
sz
,
bool
useGpu
=
false
);
static
IVector
*
createZero
(
size_t
sz
,
bool
useGpu
=
isUseGpu
()
);
/**
* Create IVector from list of int.
* It will create a new vector, and copy data into it.
*/
static
IVector
*
create
(
const
std
::
vector
<
int
>&
data
,
bool
useGpu
=
false
);
static
IVector
*
create
(
const
std
::
vector
<
int
>&
data
,
bool
useGpu
=
isUseGpu
());
static
IVector
*
createVectorFromNumpy
(
int
*
data
,
int
dim
,
bool
copy
=
true
,
bool
useGpu
=
isUseGpu
());
/**
* Create Cpu IVector from numpy array, which dtype=int32
...
...
@@ -297,7 +312,7 @@ public:
/**
* Create Gpu IVector from numpy array, which dtype=int32
*/
static
IVector
*
createGpuVectorFromNumy
(
int
*
data
,
int
dim
);
static
IVector
*
createGpuVectorFromNum
p
y
(
int
*
data
,
int
dim
);
/// Cast to numpy array inplace.
void
toNumpyArrayInplace
(
int
**
view_data
,
int
*
dim1
)
throw
(
UnsupportError
);
...
...
paddle/api/Util.cpp
浏览文件 @
2be3a747
...
...
@@ -41,6 +41,8 @@ IntWithFloatArray::IntWithFloatArray(const float* v, const int* i, size_t l,
bool
f
)
:
valBuf
(
v
),
idxBuf
(
i
),
length
(
l
),
needFree
(
f
)
{}
bool
isUseGpu
()
{
return
FLAGS_use_gpu
;}
bool
isGpuVersion
()
{
#ifdef PADDLE_ONLY_CPU
return
false
;
...
...
paddle/api/Vector.cpp
浏览文件 @
2be3a747
...
...
@@ -39,6 +39,17 @@ IVector* IVector::create(const std::vector<int>& data, bool useGpu) {
return
v
;
}
IVector
*
IVector
::
createVectorFromNumpy
(
int
*
data
,
int
dim
,
bool
copy
,
bool
useGpu
)
{
if
(
useGpu
)
{
/// if use gpu only copy=true is supported
CHECK
(
copy
);
return
IVector
::
createGpuVectorFromNumpy
(
data
,
dim
);
}
else
{
return
IVector
::
createCpuVectorFromNumpy
(
data
,
dim
,
copy
);
}
}
IVector
*
IVector
::
createCpuVectorFromNumpy
(
int
*
data
,
int
dim
,
bool
copy
)
{
auto
v
=
new
IVector
();
if
(
copy
)
{
...
...
@@ -50,7 +61,7 @@ IVector* IVector::createCpuVectorFromNumpy(int* data, int dim, bool copy) {
return
v
;
}
IVector
*
IVector
::
createGpuVectorFromNumy
(
int
*
data
,
int
dim
)
{
IVector
*
IVector
::
createGpuVectorFromNum
p
y
(
int
*
data
,
int
dim
)
{
auto
v
=
new
IVector
();
v
->
m
->
vec
=
paddle
::
IVector
::
create
(
dim
,
true
);
v
->
m
->
vec
->
copyFrom
(
data
,
dim
);
...
...
@@ -188,6 +199,17 @@ Vector* Vector::createByPaddleVectorPtr(void* ptr) {
}
}
Vector
*
Vector
::
createVectorFromNumpy
(
float
*
data
,
int
dim
,
bool
copy
,
bool
useGpu
)
{
if
(
useGpu
)
{
/// if use gpu only copy=True is supported
CHECK
(
copy
);
return
Vector
::
createGpuVectorFromNumpy
(
data
,
dim
);
}
else
{
return
Vector
::
createCpuVectorFromNumpy
(
data
,
dim
,
copy
);
}
}
Vector
*
Vector
::
createCpuVectorFromNumpy
(
float
*
data
,
int
dim
,
bool
copy
)
{
CHECK_GT
(
dim
,
0
);
auto
retVec
=
new
Vector
();
...
...
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