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85e0cd70
编写于
11月 28, 2016
作者:
H
hedaoyuan
浏览文件
操作
浏览文件
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电子邮件补丁
差异文件
move some BaseMatrix test from test_matrixCompare.cpp to test_BaseMatrix.cpp
上级
ff7b4284
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
300 addition
and
367 deletion
+300
-367
paddle/math/tests/TensorCheck.h
paddle/math/tests/TensorCheck.h
+42
-47
paddle/math/tests/TestUtils.h
paddle/math/tests/TestUtils.h
+44
-7
paddle/math/tests/test_BaseMatrix.cpp
paddle/math/tests/test_BaseMatrix.cpp
+214
-15
paddle/math/tests/test_matrixCompare.cpp
paddle/math/tests/test_matrixCompare.cpp
+0
-298
未找到文件。
paddle/math/tests/TensorCheck.h
浏览文件 @
85e0cd70
...
...
@@ -21,60 +21,29 @@ using namespace std; // NOLINT
namespace
autotest
{
class
Check
Equal
{
class
Assert
Equal
{
public:
inline
int
operator
()(
real
a
,
real
b
)
{
if
(
a
!=
b
)
{
return
1
;
}
return
0
;
}
};
AssertEqual
(
real
err
=
0
)
:
err_
(
err
)
{}
class
CheckWithErr
{
public:
CheckWithErr
()
{
#ifndef PADDLE_TYPE_DOUBLE
err_
=
1e-5
;
#else
err_
=
1e-10
;
#endif
}
inline
int
operator
()(
real
a
,
real
b
)
{
if
(
std
::
fabs
(
a
-
b
)
>
err_
)
{
if
((
std
::
fabs
(
a
-
b
)
/
std
::
fabs
(
a
))
>
(
err_
/
10.0
f
))
{
return
1
;
inline
bool
operator
()(
real
a
,
real
b
)
{
if
(
err_
==
0
)
{
if
(
a
!=
b
)
{
return
false
;
}
}
else
{
if
(
std
::
fabs
(
a
-
b
)
>
err_
)
{
if
((
std
::
fabs
(
a
-
b
)
/
std
::
fabs
(
a
))
>
(
err_
/
10.0
f
))
{
return
false
;
}
}
}
return
0
;
return
true
;
}
private:
real
err_
;
};
template
<
typename
Check
>
void
TensorCheck
(
Check
op
,
const
CpuMatrix
&
matrix1
,
const
CpuMatrix
&
matrix2
)
{
CHECK
(
matrix1
.
getHeight
()
==
matrix2
.
getHeight
());
CHECK
(
matrix1
.
getWidth
()
==
matrix2
.
getWidth
());
int
height
=
matrix1
.
getHeight
();
int
width
=
matrix1
.
getWidth
();
const
real
*
data1
=
matrix1
.
getData
();
const
real
*
data2
=
matrix2
.
getData
();
int
count
=
0
;
for
(
int
i
=
0
;
i
<
height
;
i
++
)
{
for
(
int
j
=
0
;
j
<
width
;
j
++
)
{
real
a
=
data1
[
i
*
width
+
j
];
real
b
=
data2
[
i
*
width
+
j
];
count
+=
op
(
a
,
b
);
}
}
EXPECT_EQ
(
count
,
0
)
<<
"There are "
<<
count
<<
" different element."
;
}
template
<
typename
Tensor
>
class
CopyToCpu
;
...
...
@@ -101,10 +70,36 @@ private:
CpuMatrix
arg_
;
};
template
<
typename
Tensor1
,
typename
Tensor2
>
extern
void
TensorCheckErr
(
const
Tensor1
&
tensor1
,
const
Tensor2
&
tensor2
)
{
template
<
typename
AssertEq
>
void
TensorCheck
(
AssertEq
compare
,
const
CpuMatrix
&
matrix1
,
const
CpuMatrix
&
matrix2
)
{
CHECK
(
matrix1
.
getHeight
()
==
matrix2
.
getHeight
());
CHECK
(
matrix1
.
getWidth
()
==
matrix2
.
getWidth
());
int
height
=
matrix1
.
getHeight
();
int
width
=
matrix1
.
getWidth
();
const
real
*
data1
=
matrix1
.
getData
();
const
real
*
data2
=
matrix2
.
getData
();
int
count
=
0
;
for
(
int
i
=
0
;
i
<
height
;
i
++
)
{
for
(
int
j
=
0
;
j
<
width
;
j
++
)
{
real
a
=
data1
[
i
*
width
+
j
];
real
b
=
data2
[
i
*
width
+
j
];
if
(
!
compare
(
a
,
b
))
{
count
++
;
}
}
}
EXPECT_EQ
(
count
,
0
)
<<
"There are "
<<
count
<<
" different element."
;
}
template
<
typename
AssertEq
,
typename
Tensor1
,
typename
Tensor2
>
extern
void
TensorCheck
(
AssertEq
compare
,
const
Tensor1
&
tensor1
,
const
Tensor2
&
tensor2
)
{
TensorCheck
(
CheckWithErr
()
,
compare
,
CopyToCpu
<
Tensor1
>
(
tensor1
).
copiedArg
(),
CopyToCpu
<
Tensor2
>
(
tensor2
).
copiedArg
());
}
...
...
paddle/math/tests/TestUtils.h
浏览文件 @
85e0cd70
...
...
@@ -107,12 +107,16 @@ R call(C& obj, R (FC::*f)(FArgs...), Args&&... args) {
return
(
obj
.
*
f
)(
args
...);
}
template
<
std
::
size_t
...
I
,
typename
C
,
typename
R
,
typename
...
Args
>
void
BaseMatrixCompare
(
R
(
C
::*
f
)(
Args
...))
{
template
<
bool
ApplyRow
,
bool
ApplyCol
,
std
::
size_t
...
I
,
typename
C
,
typename
R
,
typename
...
Args
,
typename
AssertEq
>
void
BaseMatrixCompare
(
R
(
C
::*
f
)(
Args
...),
AssertEq
compare
)
{
for
(
auto
height
:
{
1
,
11
,
73
,
128
,
200
,
330
})
{
for
(
auto
width
:
{
1
,
3
,
32
,
100
,
512
,
1000
,
3210
})
{
CpuMatrix
obj1
(
height
,
width
);
GpuMatrix
obj2
(
height
,
width
);
for
(
auto
width
:
{
1
,
3
,
32
,
100
,
512
,
1000
})
{
CpuMatrix
obj1
(
ApplyCol
?
1
:
height
,
ApplyRow
?
1
:
width
);
GpuMatrix
obj2
(
ApplyCol
?
1
:
height
,
ApplyRow
?
1
:
width
);
init
(
obj1
);
copy
(
obj2
,
obj1
);
...
...
@@ -132,7 +136,7 @@ void BaseMatrixCompare(R (C::*f)(Args...)) {
call
(
obj1
,
f
,
std
::
get
<
I
>
(
tuple1
)...);
call
(
obj2
,
f
,
std
::
get
<
I
>
(
tuple2
)...);
TensorCheck
Err
(
obj1
,
obj2
);
TensorCheck
(
compare
,
obj1
,
obj2
);
}
}
}
...
...
@@ -144,6 +148,39 @@ void BaseMatrixCompare(R (C::*f)(Args...)) {
static_assert
(
sizeof
...(
I
)
==
sizeof
...(
Args
),
"size of parameter packs are not equal"
);
autotest
::
BaseMatrixCompare
<
I
...
>
(
f
);
#ifndef PADDLE_TYPE_DOUBLE
autotest
::
AssertEqual
compare
(
1e-5
);
#else
autotest
::
AssertEqual
compare
(
1e-10
);
#endif
autotest
::
BaseMatrixCompare
<
false
,
false
,
I
...
>
(
f
,
compare
);
}
template
<
std
::
size_t
...
I
,
typename
C
,
typename
R
,
typename
...
Args
>
void
BaseMatrixApplyRow
(
R
(
C
::*
f
)(
Args
...))
{
static_assert
(
sizeof
...(
I
)
==
sizeof
...(
Args
),
"size of parameter packs are not equal"
);
#ifndef PADDLE_TYPE_DOUBLE
autotest
::
AssertEqual
compare
(
1e-3
);
#else
autotest
::
AssertEqual
compare
(
1e-8
);
#endif
autotest
::
BaseMatrixCompare
<
true
,
false
,
I
...
>
(
f
,
compare
);
}
template
<
std
::
size_t
...
I
,
typename
C
,
typename
R
,
typename
...
Args
>
void
BaseMatrixApplyCol
(
R
(
C
::*
f
)(
Args
...))
{
static_assert
(
sizeof
...(
I
)
==
sizeof
...(
Args
),
"size of parameter packs are not equal"
);
#ifndef PADDLE_TYPE_DOUBLE
autotest
::
AssertEqual
compare
(
1e-3
);
#else
autotest
::
AssertEqual
compare
(
1e-8
);
#endif
autotest
::
BaseMatrixCompare
<
false
,
true
,
I
...
>
(
f
,
compare
);
}
paddle/math/tests/test_BaseMatrix.cpp
浏览文件 @
85e0cd70
...
...
@@ -26,25 +26,224 @@ limitations under the License. */
using
namespace
paddle
;
// NOLINT
using
namespace
std
;
// NOLINT
TEST
(
BaseMatrix
,
apply
)
{
// member function with no argument
BaseMatrixCompare
(
&
BaseMatrix
::
neg
);
/**
* Test member functions which prototype is
* void (BaseMatrix::*)().
*/
TEST
(
BaseMatrix
,
void
)
{
typedef
void
(
BaseMatrix
::*
FunctionProto
)();
#define BASEMATRIXCOMPARE(function) \
BaseMatrixCompare(static_cast<FunctionProto>(&BaseMatrix::function));
BASEMATRIXCOMPARE
(
neg
);
BASEMATRIXCOMPARE
(
exp
);
BASEMATRIXCOMPARE
(
log
);
BASEMATRIXCOMPARE
(
sqrt
);
BASEMATRIXCOMPARE
(
square
);
BASEMATRIXCOMPARE
(
reciprocal
);
BASEMATRIXCOMPARE
(
abs
);
BASEMATRIXCOMPARE
(
sign
);
BASEMATRIXCOMPARE
(
zero
);
BASEMATRIXCOMPARE
(
one
);
#undef BASEMATRIXCOMPARE
}
/**
* Test member functions which prototype is
* void (BaseMatrix::*)(real).
*/
TEST
(
BaseMatrix
,
real
)
{
typedef
void
(
BaseMatrix
::*
FunctionProto
)(
real
);
#define BASEMATRIXCOMPARE(function) \
BaseMatrixCompare<0>(static_cast<FunctionProto>(&BaseMatrix::function));
BASEMATRIXCOMPARE
(
pow
);
BASEMATRIXCOMPARE
(
subScalar
);
BASEMATRIXCOMPARE
(
mulScalar
);
BASEMATRIXCOMPARE
(
divScalar
);
BASEMATRIXCOMPARE
(
assign
);
BASEMATRIXCOMPARE
(
add
);
BASEMATRIXCOMPARE
(
biggerThanScalar
);
BASEMATRIXCOMPARE
(
downClip
);
#undef BASEMATRIXCOMPARE
}
/**
* Test member functions which prototype is
* void (BaseMatrix::*)(real, real).
*/
TEST
(
BaseMatrix
,
real_real
)
{
typedef
void
(
BaseMatrix
::*
FunctionProto
)(
real
,
real
);
#define BASEMATRIXCOMPARE(function) \
BaseMatrixCompare<0, 1>(static_cast<FunctionProto>(&BaseMatrix::function));
BASEMATRIXCOMPARE
(
add
);
BASEMATRIXCOMPARE
(
clip
);
#undef BASEMATRIXCOMPARE
}
/**
* Test member functions which prototype is
* void (BaseMatrix::*)(BaseMatrix&).
*/
TEST
(
BaseMatrix
,
BaseMatrix
)
{
typedef
void
(
BaseMatrix
::*
FunctionProto
)(
BaseMatrix
&
);
#define BASEMATRIXCOMPARE(function) \
BaseMatrixCompare<0>(static_cast<FunctionProto>(&BaseMatrix::function));
BASEMATRIXCOMPARE
(
assign
);
BASEMATRIXCOMPARE
(
add
);
BASEMATRIXCOMPARE
(
relu
);
BASEMATRIXCOMPARE
(
reluDerivative
);
BASEMATRIXCOMPARE
(
softrelu
);
BASEMATRIXCOMPARE
(
softreluDerivative
);
BASEMATRIXCOMPARE
(
brelu
);
BASEMATRIXCOMPARE
(
breluDerivative
);
BASEMATRIXCOMPARE
(
square
);
BASEMATRIXCOMPARE
(
squareDerivative
);
BASEMATRIXCOMPARE
(
tanh
);
BASEMATRIXCOMPARE
(
tanhDerivative
);
BASEMATRIXCOMPARE
(
reciprocal
);
BASEMATRIXCOMPARE
(
reciprocalDerivative
);
BASEMATRIXCOMPARE
(
abs
);
BASEMATRIXCOMPARE
(
absDerivative
);
BASEMATRIXCOMPARE
(
sigmoid
);
BASEMATRIXCOMPARE
(
sigmoidDerivative
);
BASEMATRIXCOMPARE
(
expDerivative
);
BASEMATRIXCOMPARE
(
sign
);
BASEMATRIXCOMPARE
(
exp
);
BASEMATRIXCOMPARE
(
log
);
BASEMATRIXCOMPARE
(
sqrt
);
BASEMATRIXCOMPARE
(
dotMul
);
BASEMATRIXCOMPARE
(
dotMulSquare
);
BASEMATRIXCOMPARE
(
dotSquareMul
);
BASEMATRIXCOMPARE
(
addColVector
);
BASEMATRIXCOMPARE
(
addRowVector
);
BASEMATRIXCOMPARE
(
mulRowVector
);
BASEMATRIXCOMPARE
(
divRowVector
);
BASEMATRIXCOMPARE
(
addP2P
);
BASEMATRIXCOMPARE
(
invSqrt
);
#undef BASEMATRIXCOMPARE
}
/**
* Test member functions which prototype is
* void (BaseMatrix::*)(BaseMatrix&, real).
*/
TEST
(
BaseMatrix
,
BaseMatrix_real
)
{
typedef
void
(
BaseMatrix
::*
FunctionProto
)(
BaseMatrix
&
,
real
);
#define BASEMATRIXCOMPARE(function) \
BaseMatrixCompare<0, 1>(static_cast<FunctionProto>(&BaseMatrix::function));
// If the member function are overloaded, use static_cast to specify which
// member function need be test.
BaseMatrixCompare
(
static_cast
<
void
(
BaseMatrix
::*
)()
>
(
&
BaseMatrix
::
exp
));
BaseMatrixCompare
(
static_cast
<
void
(
BaseMatrix
::*
)()
>
(
&
BaseMatrix
::
sqrt
));
BASEMATRIXCOMPARE
(
addBias
);
BASEMATRIXCOMPARE
(
add
);
BASEMATRIXCOMPARE
(
sub
);
BASEMATRIXCOMPARE
(
pow
);
BASEMATRIXCOMPARE
(
addScalar
);
BASEMATRIXCOMPARE
(
subScalar
);
BASEMATRIXCOMPARE
(
mulScalar
);
BASEMATRIXCOMPARE
(
divScalar
);
BASEMATRIXCOMPARE
(
scalarDiv
);
BASEMATRIXCOMPARE
(
addSquare
);
BASEMATRIXCOMPARE
(
isEqualTo
);
#undef BASEMATRIXCOMPARE
}
/**
* Test member functions which prototype is
* void (BaseMatrix::*)(BaseMatrix&, BaseMatrix&).
*/
TEST
(
BaseMatrix
,
BaseMatrix_BaseMatrix
)
{
typedef
void
(
BaseMatrix
::*
FunctionProto
)(
BaseMatrix
&
,
BaseMatrix
&
);
#define BASEMATRIXCOMPARE(function) \
BaseMatrixCompare<0, 1>(static_cast<FunctionProto>(&BaseMatrix::function));
BASEMATRIXCOMPARE
(
softCrossEntropy
);
BASEMATRIXCOMPARE
(
softCrossEntropyBp
);
BASEMATRIXCOMPARE
(
binaryLabelCrossEntropy
);
BASEMATRIXCOMPARE
(
binaryLabelCrossEntropyBp
);
BASEMATRIXCOMPARE
(
sub
);
BASEMATRIXCOMPARE
(
add2
);
BASEMATRIXCOMPARE
(
dotMul
);
BASEMATRIXCOMPARE
(
dotDiv
);
BASEMATRIXCOMPARE
(
logisticRegressionLoss
);
BASEMATRIXCOMPARE
(
logisticRegressionLossBp
);
BASEMATRIXCOMPARE
(
biggerThan
);
BASEMATRIXCOMPARE
(
max
);
BASEMATRIXCOMPARE
(
dotMulSquare
);
BASEMATRIXCOMPARE
(
dotSquareSquare
);
#undef BASEMATRIXCOMPARE
}
/**
* Test aggregate member functions which prototype is
* void (BaseMatrix::*)(BaseMatrix&).
*/
TEST
(
Aggregate
,
BaseMatrix
)
{
typedef
void
(
BaseMatrix
::*
FunctionProto
)(
BaseMatrix
&
);
#define BASEMATRIXAPPLYROW(function) \
BaseMatrixApplyRow<0>(static_cast<FunctionProto>(&BaseMatrix::function));
#define BASEMATRIXAPPLYCOL(function) \
BaseMatrixApplyCol<0>(static_cast<FunctionProto>(&BaseMatrix::function));
BASEMATRIXAPPLYROW
(
maxRows
);
BASEMATRIXAPPLYROW
(
minRows
);
BASEMATRIXAPPLYCOL
(
sumCols
);
BASEMATRIXAPPLYCOL
(
maxCols
);
BASEMATRIXAPPLYCOL
(
minCols
);
#undef BASEMATRIXAPPLYROW
#undef BASEMATRIXAPPLYCOL
}
/**
* Test aggregate member functions which prototype is
* void (BaseMatrix::*)(BaseMatrix&, BaseMatrix&).
*/
TEST
(
Aggregate
,
BaseMatrix_BaseMatrix
)
{
typedef
void
(
BaseMatrix
::*
FunctionProto
)(
BaseMatrix
&
,
BaseMatrix
&
);
#define BASEMATRIXAPPLYROW(function) \
BaseMatrixApplyRow<0, 1>(static_cast<FunctionProto>(&BaseMatrix::function));
#define BASEMATRIXAPPLYCOL(function) \
BaseMatrixApplyCol<0, 1>(static_cast<FunctionProto>(&BaseMatrix::function));
BASEMATRIXAPPLYCOL
(
addDotMulVMM
);
#undef BASEMATRIXAPPLYROW
#undef BASEMATRIXAPPLYCOL
}
/**
* Test aggregate member functions which prototype is
* void (BaseMatrix::*)(BaseMatrix&, real, real).
*/
TEST
(
Aggregate
,
BaseMatrix_real_real
)
{
typedef
void
(
BaseMatrix
::*
FunctionProto
)(
BaseMatrix
&
,
real
,
real
);
#define BASEMATRIXAPPLYROW(function) \
BaseMatrixApplyRow<0, 1, 2>(\
static_cast<FunctionProto>(&BaseMatrix::function));
// member function with one argument
#define BASEMATRIXAPPLYCOL(function) \
BaseMatrixApplyCol<0, 1, 2>(\
static_cast<FunctionProto>(&BaseMatrix::function));
BaseMatrixCompare
<
0
>
(
&
BaseMatrix
::
tanh
);
BASEMATRIXAPPLYROW
(
sumRows
);
BASEMATRIXAPPLYCOL
(
sumCols
);
BaseMatrixCompare
<
0
>
(
static_cast
<
void
(
BaseMatrix
::*
)(
real
)
>
(
&
BaseMatrix
::
assign
));
BaseMatrixCompare
<
0
>
(
static_cast
<
void
(
BaseMatrix
::*
)(
real
)
>
(
&
BaseMatrix
::
pow
));
#undef BASEMATRIXAPPLYROW
#undef BASEMATRIXAPPLYCOL
}
int
main
(
int
argc
,
char
**
argv
)
{
...
...
paddle/math/tests/test_matrixCompare.cpp
浏览文件 @
85e0cd70
...
...
@@ -448,125 +448,6 @@ void testMatrixZeroAtOffset(int height, int width) {
MatrixCheckEqual
(
*
cpuA
,
*
cpuTest
);
}
void
testMatrixBinaryAdd
(
int
height
,
int
width
)
{
MatrixPtr
cpuA
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
width
);
MatrixPtr
cpuB
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
width
);
MatrixPtr
gpuA
=
std
::
make_shared
<
GpuMatrix
>
(
height
,
width
);
MatrixPtr
gpuB
=
std
::
make_shared
<
GpuMatrix
>
(
height
,
width
);
cpuA
->
randomizeUniform
();
cpuB
->
randomizeUniform
();
gpuA
->
copyFrom
(
*
cpuA
);
gpuB
->
copyFrom
(
*
cpuB
);
cpuA
->
add
(
*
cpuB
);
gpuA
->
add
(
*
gpuB
);
MatrixPtr
outputCheck
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
width
);
outputCheck
->
copyFrom
(
*
gpuA
);
MatrixCheckEqual
(
*
cpuA
,
*
outputCheck
);
}
void
testMatrixAssign
(
int
height
,
int
width
)
{
MatrixPtr
cpuA
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
width
);
MatrixPtr
gpuA
=
std
::
make_shared
<
GpuMatrix
>
(
height
,
width
);
cpuA
->
randomizeUniform
();
gpuA
->
copyFrom
(
*
cpuA
);
cpuA
->
assign
(
2.5
);
gpuA
->
assign
(
2.5
);
MatrixPtr
outputCheck
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
width
);
outputCheck
->
copyFrom
(
*
gpuA
);
MatrixCheckEqual
(
*
cpuA
,
*
outputCheck
);
}
void
testMatrixAdd
(
int
height
,
int
width
)
{
MatrixPtr
cpuA
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
width
);
MatrixPtr
gpuA
=
std
::
make_shared
<
GpuMatrix
>
(
height
,
width
);
cpuA
->
randomizeUniform
();
gpuA
->
copyFrom
(
*
cpuA
);
cpuA
->
add
(
2.5
);
gpuA
->
add
(
2.5
);
MatrixPtr
outputCheck
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
width
);
outputCheck
->
copyFrom
(
*
gpuA
);
MatrixCheckEqual
(
*
cpuA
,
*
outputCheck
);
}
void
testMatrixSqrt
(
int
height
,
int
width
)
{
MatrixPtr
cpuA
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
width
);
MatrixPtr
gpuA
=
std
::
make_shared
<
GpuMatrix
>
(
height
,
width
);
cpuA
->
randomizeUniform
();
gpuA
->
copyFrom
(
*
cpuA
);
cpuA
->
sqrt
();
gpuA
->
sqrt
();
MatrixPtr
outputCheck
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
width
);
outputCheck
->
copyFrom
(
*
gpuA
);
MatrixCheckErr
(
*
cpuA
,
*
outputCheck
);
}
void
testMatrixTanhDerivative
(
int
height
,
int
width
)
{
MatrixPtr
cpuA
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
width
);
MatrixPtr
cpuB
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
width
);
MatrixPtr
gpuA
=
std
::
make_shared
<
GpuMatrix
>
(
height
,
width
);
MatrixPtr
gpuB
=
std
::
make_shared
<
GpuMatrix
>
(
height
,
width
);
cpuA
->
randomizeUniform
();
cpuB
->
randomizeUniform
();
gpuA
->
copyFrom
(
*
cpuA
);
gpuB
->
copyFrom
(
*
cpuB
);
cpuA
->
tanhDerivative
(
*
cpuB
);
gpuA
->
tanhDerivative
(
*
gpuB
);
MatrixPtr
outputCheck
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
width
);
outputCheck
->
copyFrom
(
*
gpuA
);
MatrixCheckErr
(
*
cpuA
,
*
outputCheck
);
}
void
testMatrixTanh
(
int
height
,
int
width
)
{
MatrixPtr
cpuA
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
width
);
MatrixPtr
cpuB
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
width
);
MatrixPtr
gpuA
=
std
::
make_shared
<
GpuMatrix
>
(
height
,
width
);
MatrixPtr
gpuB
=
std
::
make_shared
<
GpuMatrix
>
(
height
,
width
);
cpuA
->
randomizeUniform
();
cpuB
->
randomizeUniform
();
gpuA
->
copyFrom
(
*
cpuA
);
gpuB
->
copyFrom
(
*
cpuB
);
cpuA
->
tanh
(
*
cpuB
);
gpuA
->
tanh
(
*
gpuB
);
MatrixPtr
outputCheck
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
width
);
outputCheck
->
copyFrom
(
*
gpuA
);
MatrixCheckErr
(
*
cpuA
,
*
outputCheck
);
}
void
testMatrixTernarySub
(
int
height
,
int
width
)
{
MatrixPtr
cpuA
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
width
);
MatrixPtr
cpuB
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
width
);
MatrixPtr
cpuC
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
width
);
MatrixPtr
gpuA
=
std
::
make_shared
<
GpuMatrix
>
(
height
,
width
);
MatrixPtr
gpuB
=
std
::
make_shared
<
GpuMatrix
>
(
height
,
width
);
MatrixPtr
gpuC
=
std
::
make_shared
<
GpuMatrix
>
(
height
,
width
);
cpuA
->
randomizeUniform
();
cpuB
->
randomizeUniform
();
cpuC
->
randomizeUniform
();
gpuA
->
copyFrom
(
*
cpuA
);
gpuB
->
copyFrom
(
*
cpuB
);
gpuC
->
copyFrom
(
*
cpuC
);
cpuA
->
sub
(
*
cpuB
,
*
cpuC
);
gpuA
->
sub
(
*
gpuB
,
*
gpuC
);
MatrixPtr
outputCheck
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
width
);
outputCheck
->
copyFrom
(
*
gpuA
);
MatrixCheckEqual
(
*
cpuA
,
*
outputCheck
);
}
void
testMatrixSumOfSquaresBp
(
int
height
,
int
width
)
{
MatrixPtr
cpuA
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
width
);
MatrixPtr
cpuB
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
width
);
...
...
@@ -789,18 +670,7 @@ TEST(Matrix, unary) {
for
(
auto
width
:
{
1
,
3
,
32
,
100
,
512
,
1000
,
3210
})
{
VLOG
(
3
)
<<
" height="
<<
height
<<
" width="
<<
width
;
// applyUnary
testMatrixAssign
(
height
,
width
);
testMatrixAdd
(
height
,
width
);
testMatrixSqrt
(
height
,
width
);
// applyBinary
testMatrixBinaryAdd
(
height
,
width
);
testMatrixTanh
(
height
,
width
);
testMatrixTanhDerivative
(
height
,
width
);
// applyTernary
testMatrixTernarySub
(
height
,
width
);
testMatrixSumOfSquaresBp
(
height
,
width
);
// asRowVector
...
...
@@ -931,165 +801,6 @@ TEST(Matrix, softmax) {
}
}
void
testMatrixAddDotMulVMM
(
int
height
,
int
width
,
int
endCol
=
0
)
{
MatrixPtr
cpuA
=
std
::
make_shared
<
CpuMatrix
>
(
1
,
width
);
MatrixPtr
cpuB
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
width
);
MatrixPtr
cpuC
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
width
);
MatrixPtr
gpuA
=
std
::
make_shared
<
GpuMatrix
>
(
1
,
width
);
MatrixPtr
gpuB
=
std
::
make_shared
<
GpuMatrix
>
(
height
,
width
);
MatrixPtr
gpuC
=
std
::
make_shared
<
GpuMatrix
>
(
height
,
width
);
MatrixPtr
cpuA1
=
std
::
make_shared
<
CpuMatrix
>
(
1
,
width
);
MatrixPtr
cpuB1
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
width
);
MatrixPtr
cpuC1
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
width
);
cpuA
->
randomizeUniform
();
cpuB
->
randomizeUniform
();
cpuC
->
randomizeUniform
();
gpuA
->
copyFrom
(
*
cpuA
);
gpuB
->
copyFrom
(
*
cpuB
);
gpuC
->
copyFrom
(
*
cpuC
);
cpuA1
->
copyFrom
(
*
cpuA
);
cpuB1
->
copyFrom
(
*
cpuB
);
cpuC1
->
copyFrom
(
*
cpuC
);
if
(
!
endCol
)
{
cpuA
->
addDotMulVMM
(
*
cpuB
,
*
cpuC
);
gpuA
->
addDotMulVMM
(
*
gpuB
,
*
gpuC
);
cpuA1
->
addDotMulVMM2
(
*
cpuB1
,
*
cpuC1
);
MatrixCheckErr
(
*
cpuA
,
*
cpuA1
);
}
else
{
MatrixPtr
subCpuA
=
cpuA
->
subColMatrix
(
0
,
endCol
);
MatrixPtr
subCpuB
=
cpuB
->
subColMatrix
(
0
,
endCol
);
MatrixPtr
subCpuC
=
cpuC
->
subColMatrix
(
0
,
endCol
);
MatrixPtr
subGpuA
=
gpuA
->
subColMatrix
(
0
,
endCol
);
MatrixPtr
subGpuB
=
gpuB
->
subColMatrix
(
0
,
endCol
);
MatrixPtr
subGpuC
=
gpuC
->
subColMatrix
(
0
,
endCol
);
subCpuA
->
addDotMulVMM
(
*
subCpuB
,
*
subCpuC
);
subGpuA
->
addDotMulVMM
(
*
subGpuB
,
*
subGpuC
);
}
MatrixPtr
outputCheck
=
std
::
make_shared
<
CpuMatrix
>
(
1
,
width
);
outputCheck
->
copyFrom
(
*
gpuA
);
MatrixCheckErr
(
*
cpuA
,
*
outputCheck
);
}
void
testMatrixRowSum
(
int
height
,
int
width
)
{
MatrixPtr
cpuA
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
1
);
MatrixPtr
cpuB
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
width
);
MatrixPtr
gpuA
=
std
::
make_shared
<
GpuMatrix
>
(
height
,
1
);
MatrixPtr
gpuB
=
std
::
make_shared
<
GpuMatrix
>
(
height
,
width
);
MatrixPtr
cpuA1
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
1
);
MatrixPtr
cpuB1
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
width
);
MatrixPtr
gpuA1
=
std
::
make_shared
<
GpuMatrix
>
(
height
,
1
);
MatrixPtr
gpuB1
=
std
::
make_shared
<
GpuMatrix
>
(
height
,
width
);
cpuA
->
randomizeUniform
();
cpuB
->
randomizeUniform
();
gpuA
->
copyFrom
(
*
cpuA
);
gpuB
->
copyFrom
(
*
cpuB
);
cpuA1
->
copyFrom
(
*
cpuA
);
cpuB1
->
copyFrom
(
*
cpuB
);
gpuA1
->
copyFrom
(
*
cpuA
);
gpuB1
->
copyFrom
(
*
cpuB
);
cpuA
->
colMerge
(
*
cpuB
);
gpuA
->
colMerge
(
*
gpuB
);
cpuB1
->
rowSum
(
*
cpuA1
);
gpuB1
->
rowSum
(
*
gpuA1
);
MatrixPtr
outputCheck
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
1
);
outputCheck
->
copyFrom
(
*
gpuA
);
MatrixCheckErr
(
*
cpuA
,
*
outputCheck
);
outputCheck
->
copyFrom
(
*
gpuA1
);
MatrixCheckErr
(
*
cpuA1
,
*
outputCheck
);
}
void
testMatrixRowMax
(
int
height
,
int
width
,
int
endCol
=
0
)
{
MatrixPtr
cpuA
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
1
);
MatrixPtr
cpuB
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
width
);
MatrixPtr
gpuA
=
std
::
make_shared
<
GpuMatrix
>
(
height
,
1
);
MatrixPtr
gpuB
=
std
::
make_shared
<
GpuMatrix
>
(
height
,
width
);
cpuA
->
randomizeUniform
();
cpuB
->
randomizeUniform
();
gpuA
->
copyFrom
(
*
cpuA
);
gpuB
->
copyFrom
(
*
cpuB
);
if
(
!
endCol
)
{
cpuB
->
rowMax
(
*
cpuA
);
gpuB
->
rowMax
(
*
gpuA
);
}
else
{
MatrixPtr
subCpuB
=
cpuB
->
subColMatrix
(
0
,
endCol
);
MatrixPtr
subGpuB
=
gpuB
->
subColMatrix
(
0
,
endCol
);
subCpuB
->
rowMax
(
*
cpuA
);
subGpuB
->
rowMax
(
*
gpuA
);
}
MatrixPtr
outputCheck
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
1
);
outputCheck
->
copyFrom
(
*
gpuA
);
MatrixCheckErr
(
*
cpuA
,
*
outputCheck
);
}
void
testMatrixColSum
(
int
height
,
int
width
,
int
endCol
=
0
)
{
MatrixPtr
cpuA
=
std
::
make_shared
<
CpuMatrix
>
(
1
,
width
);
MatrixPtr
cpuB
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
width
);
MatrixPtr
gpuA
=
std
::
make_shared
<
GpuMatrix
>
(
1
,
width
);
MatrixPtr
gpuB
=
std
::
make_shared
<
GpuMatrix
>
(
height
,
width
);
cpuA
->
randomizeUniform
();
cpuB
->
randomizeUniform
();
gpuA
->
copyFrom
(
*
cpuA
);
gpuB
->
copyFrom
(
*
cpuB
);
if
(
!
endCol
)
{
cpuA
->
accumulateColSum
(
*
cpuB
);
gpuA
->
accumulateColSum
(
*
gpuB
);
}
else
{
MatrixPtr
subCpuA
=
cpuA
->
subColMatrix
(
0
,
endCol
);
MatrixPtr
subGpuA
=
gpuA
->
subColMatrix
(
0
,
endCol
);
MatrixPtr
subCpuB
=
cpuB
->
subColMatrix
(
0
,
endCol
);
MatrixPtr
subGpuB
=
gpuB
->
subColMatrix
(
0
,
endCol
);
subCpuA
->
accumulateColSum
(
*
subCpuB
);
subGpuA
->
accumulateColSum
(
*
subGpuB
);
}
MatrixPtr
outputCheck
=
std
::
make_shared
<
CpuMatrix
>
(
1
,
width
);
outputCheck
->
copyFrom
(
*
gpuA
);
MatrixCheckErr
(
*
cpuA
,
*
outputCheck
);
}
void
testMatrixColMax
(
int
height
,
int
width
,
int
endCol
=
0
)
{
MatrixPtr
cpuA
=
std
::
make_shared
<
CpuMatrix
>
(
1
,
width
);
MatrixPtr
cpuB
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
width
);
MatrixPtr
gpuA
=
std
::
make_shared
<
GpuMatrix
>
(
1
,
width
);
MatrixPtr
gpuB
=
std
::
make_shared
<
GpuMatrix
>
(
height
,
width
);
cpuA
->
randomizeUniform
();
cpuB
->
randomizeUniform
();
gpuA
->
copyFrom
(
*
cpuA
);
gpuB
->
copyFrom
(
*
cpuB
);
if
(
!
endCol
)
{
cpuB
->
colMax
(
*
cpuA
);
gpuB
->
colMax
(
*
gpuA
);
}
else
{
MatrixPtr
subCpuA
=
cpuA
->
subColMatrix
(
0
,
endCol
);
MatrixPtr
subGpuA
=
gpuA
->
subColMatrix
(
0
,
endCol
);
MatrixPtr
subCpuB
=
cpuB
->
subColMatrix
(
0
,
endCol
);
MatrixPtr
subGpuB
=
gpuB
->
subColMatrix
(
0
,
endCol
);
subCpuB
->
colMax
(
*
subCpuA
);
subGpuB
->
colMax
(
*
subGpuA
);
}
MatrixPtr
outputCheck
=
std
::
make_shared
<
CpuMatrix
>
(
1
,
width
);
outputCheck
->
copyFrom
(
*
gpuA
);
MatrixCheckErr
(
*
cpuA
,
*
outputCheck
);
}
void
testMatrixCollectBias
(
int
height
,
int
width
)
{
MatrixPtr
cpuA
=
std
::
make_shared
<
CpuMatrix
>
(
1
,
width
);
MatrixPtr
cpuB
=
std
::
make_shared
<
CpuMatrix
>
(
height
,
width
);
...
...
@@ -1182,13 +893,8 @@ TEST(Matrix, aggregate) {
for
(
auto
height
:
{
1
,
11
,
16
,
32
,
64
,
73
,
128
,
200
,
1024
,
2345
})
{
for
(
auto
width
:
{
1
,
9
,
16
,
32
,
64
,
100
,
512
,
1000
,
1024
,
2453
})
{
VLOG
(
3
)
<<
" height="
<<
height
<<
" width="
<<
width
;
testMatrixRowSum
(
height
,
width
);
testMatrixRowMax
(
height
,
width
);
testMatrixColSum
(
height
,
width
);
testMatrixColMax
(
height
,
width
);
testMatrixCollectBias
(
height
,
width
);
testMatrixTernaryRowDotMul
(
height
,
width
);
testMatrixAddDotMulVMM
(
height
,
width
);
testMatrixSumOfSquares
(
height
,
width
);
testMatrixBinaryClassificationError
(
height
,
width
);
...
...
@@ -1203,11 +909,7 @@ TEST(Matrix, aggregate2) {
VLOG
(
3
)
<<
" height="
<<
height
<<
" width="
<<
width
;
int
endCol
=
rand
()
%
width
;
// NOLINT
testMatrixRowMax
(
height
,
width
,
endCol
);
testMatrixSumOfSquares
(
height
,
width
,
endCol
);
testMatrixColSum
(
height
,
width
,
endCol
);
testMatrixColMax
(
height
,
width
,
endCol
);
testMatrixAddDotMulVMM
(
height
,
width
,
endCol
);
}
}
}
...
...
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