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杨迪
NiuTrans.Tensor
Commits
54adb703
Commit
54adb703
authored
Aug 02, 2019
by
linye
Browse files
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update test of multiply, softmax, unsqueeze, crossentropy
parent
39fa0d25
全部展开
隐藏空白字符变更
内嵌
并排
正在显示
5 个修改的文件
包含
804 行增加
和
6 行删除
+804
-6
source/tensor/test/TCrossEntropy.cpp
+360
-0
source/tensor/test/TMultiply.cpp
+123
-0
source/tensor/test/TSoftmax.cpp
+182
-0
source/tensor/test/TUnsqueeze.cpp
+133
-0
source/tensor/test/Test.cpp
+6
-6
没有找到文件。
source/tensor/test/TCrossEntropy.cpp
查看文件 @
54adb703
差异被折叠。
点击展开。
source/tensor/test/TMultiply.cpp
查看文件 @
54adb703
...
@@ -20,6 +20,7 @@
...
@@ -20,6 +20,7 @@
*/
*/
#include "TMultiply.h"
#include "TMultiply.h"
#include "../core/getandset/ConvertDataType.h"
namespace
nts
{
// namespace nts(NiuTrans.Tensor)
namespace
nts
{
// namespace nts(NiuTrans.Tensor)
...
@@ -148,6 +149,118 @@ bool TestMultiply1()
...
@@ -148,6 +149,118 @@ bool TestMultiply1()
#endif // USE_CUDA
#endif // USE_CUDA
}
}
/*
case 2: float16 element-wise product of two tensors
c(i) = a(i)*b(i) + \alpha * c(i)
In this case, (2, 2) (2, 2) -> (2, 2), leadingDim=0, alpha=0.
*/
bool
TestMultiply2
()
{
/* a source tensor of size (2, 2) */
int
sOrder1
=
2
;
int
*
sDimSize1
=
new
int
[
sOrder1
];
sDimSize1
[
0
]
=
2
;
sDimSize1
[
1
]
=
2
;
int
sUnitNum1
=
1
;
for
(
int
i
=
0
;
i
<
sOrder1
;
i
++
)
sUnitNum1
*=
sDimSize1
[
i
];
/* a source tensor of size (2, 2) */
int
sOrder2
=
2
;
int
*
sDimSize2
=
new
int
[
sOrder2
];
sDimSize2
[
0
]
=
2
;
sDimSize2
[
1
]
=
2
;
int
sUnitNum2
=
1
;
for
(
int
i
=
0
;
i
<
sOrder2
;
i
++
)
sUnitNum2
*=
sDimSize2
[
i
];
/* a target tensor of size (2, 2) */
int
tOrder
=
2
;
int
*
tDimSize
=
new
int
[
tOrder
];
tDimSize
[
0
]
=
2
;
tDimSize
[
1
]
=
2
;
int
tUnitNum
=
1
;
for
(
int
i
=
0
;
i
<
tOrder
;
i
++
)
tUnitNum
*=
tDimSize
[
i
];
DTYPE
sData1
[
2
][
2
]
=
{
{
0.0
F
,
1.0
F
},
{
2.0
F
,
3.0
F
}
};
DTYPE
sData2
[
2
][
2
]
=
{
{
0.0
F
,
1.0
F
},
{
2.0
F
,
3.0
F
}
};
DTYPE
answer
[
2
][
2
]
=
{
{
0.0
F
,
1.0
F
},
{
4.0
F
,
9.0
F
}
};
/* CPU test */
bool
cpuTest
=
true
;
#ifdef USE_CUDA
/* GPU test */
bool
gpuTest
=
true
;
/* create tensor */
XTensor
*
sGPU1
=
NewTensor
(
sOrder1
,
sDimSize1
,
X_FLOAT
,
1.0
F
,
0
);
XTensor
*
sGPU2
=
NewTensor
(
sOrder2
,
sDimSize2
,
X_FLOAT
,
1.0
F
,
0
);
XTensor
*
tGPU
=
NewTensor
(
tOrder
,
tDimSize
,
X_FLOAT
,
1.0
F
,
0
);
XTensor
*
tMeGPU
=
NewTensor
(
tOrder
,
tDimSize
,
X_FLOAT
,
1.0
F
,
0
);
XTensor
tUserGPU
;
/* create float16 tensor */
XTensor
sHalfGPU1
;
XTensor
sHalfGPU2
;
XTensor
tHalfGPU
;
XTensor
tMeHalfGPU
;
XTensor
tUserHalfGPU
;
/* Initialize variables */
sGPU1
->
SetData
(
sData1
,
sUnitNum1
);
tMeGPU
->
SetData
(
sData1
,
sUnitNum1
);
sGPU2
->
SetData
(
sData2
,
sUnitNum2
);
tGPU
->
SetZeroAll
();
/* convert data type from float to float16 */
sHalfGPU1
=
ConvertDataType
(
*
sGPU1
,
X_FLOAT16
);
sHalfGPU2
=
ConvertDataType
(
*
sGPU2
,
X_FLOAT16
);
tHalfGPU
=
ConvertDataType
(
*
tGPU
,
X_FLOAT16
);
tMeHalfGPU
=
ConvertDataType
(
*
tMeGPU
,
X_FLOAT16
);
/* call multiply function */
_Multiply
(
&
sHalfGPU1
,
&
sHalfGPU2
,
&
tHalfGPU
,
0
,
0
);
_MultiplyMe
(
&
tMeHalfGPU
,
&
sHalfGPU2
,
0
,
0
);
tUserHalfGPU
=
Multiply
(
sHalfGPU1
,
sHalfGPU2
,
0
);
/* convert data type from float16 to float */
_ConvertDataType
(
&
tHalfGPU
,
tGPU
);
_ConvertDataType
(
&
tMeHalfGPU
,
tMeGPU
);
tUserGPU
=
ConvertDataType
(
tUserHalfGPU
,
X_FLOAT
);
/* check results */
gpuTest
=
tGPU
->
CheckData
(
answer
,
tUnitNum
)
&&
tMeGPU
->
CheckData
(
answer
,
tUnitNum
)
&&
tUserGPU
.
CheckData
(
answer
,
tUnitNum
);
/* destroy variables */
delete
sGPU1
;
delete
sGPU2
;
delete
tGPU
;
delete
tMeGPU
;
delete
[]
sDimSize1
;
delete
[]
sDimSize2
;
delete
[]
tDimSize
;
return
cpuTest
&&
gpuTest
;
#else
/* destroy variables */
delete
[]
sDimSize1
;
delete
[]
sDimSize2
;
delete
[]
tDimSize
;
return
cpuTest
;
#endif // USE_CUDA
}
/* other cases */
/* other cases */
/*
/*
TODO!!
TODO!!
...
@@ -169,6 +282,16 @@ bool TestMultiply()
...
@@ -169,6 +282,16 @@ bool TestMultiply()
else
else
XPRINT
(
0
,
stdout
,
">> case 1 passed!
\n
"
);
XPRINT
(
0
,
stdout
,
">> case 1 passed!
\n
"
);
/* case 2 test */
caseFlag
=
TestMultiply2
();
if
(
!
caseFlag
)
{
returnFlag
=
false
;
XPRINT
(
0
,
stdout
,
">> case 2 failed!
\n
"
);
}
else
XPRINT
(
0
,
stdout
,
">> case 2 passed!
\n
"
);
/* other cases test */
/* other cases test */
/*
/*
TODO!!
TODO!!
...
...
source/tensor/test/TSoftmax.cpp
查看文件 @
54adb703
...
@@ -22,6 +22,7 @@
...
@@ -22,6 +22,7 @@
#include "../XTensor.h"
#include "../XTensor.h"
#include "../XUtility.h"
#include "../XUtility.h"
#include "TSoftmax.h"
#include "TSoftmax.h"
#include "../core/getandset/ConvertDataType.h"
namespace
nts
{
// namespace nts(NiuTrans.Tensor)
namespace
nts
{
// namespace nts(NiuTrans.Tensor)
...
@@ -207,6 +208,167 @@ bool TestSoftmax2()
...
@@ -207,6 +208,167 @@ bool TestSoftmax2()
#endif // USE_CUDA
#endif // USE_CUDA
}
}
/*
case 3: float16 test Softmax function.
softmax function: y = e^x / \sum_{i} e^{x_i}
*/
bool
TestSoftmax3
()
{
/* a tensor of size (2, 3) */
int
order
=
2
;
int
*
dimSize
=
new
int
[
order
];
dimSize
[
0
]
=
2
;
dimSize
[
1
]
=
3
;
int
unitNum
=
1
;
for
(
int
i
=
0
;
i
<
order
;
i
++
)
unitNum
*=
dimSize
[
i
];
DTYPE
xData
[
2
][
3
]
=
{
{
0.0
F
,
1.0
F
,
2.0
F
},
{
0.5
F
,
0.7
F
,
1.4
F
}
};
DTYPE
answer
[
2
][
3
]
=
{
{
0.0900
F
,
0.2447
F
,
0.6652
F
},
{
0.2136
F
,
0.2609
F
,
0.5254
F
}
};
/* CPU test */
bool
cpuTest
=
true
;
#ifdef USE_CUDA
/* GPU test */
bool
gpuTest
=
true
;
/* create tensors */
XTensor
*
xGPU
=
NewTensor
(
order
,
dimSize
,
X_FLOAT
,
1.0
F
,
0
);
XTensor
*
yGPU
=
NewTensor
(
order
,
dimSize
,
X_FLOAT
,
1.0
F
,
0
);
XTensor
yUserGPU
;
/* create float16 tensors */
XTensor
xHalfGPU
;
XTensor
yHalfGPU
;
XTensor
yUserHalfGPU
;
/* initialize variables */
xGPU
->
SetData
(
xData
,
unitNum
);
yGPU
->
SetZeroAll
();
/* convert data type from float to float16 */
xHalfGPU
=
ConvertDataType
(
*
xGPU
,
X_FLOAT16
);
yHalfGPU
=
ConvertDataType
(
*
yGPU
,
X_FLOAT16
);
/* call softmax function */
_Softmax
(
&
xHalfGPU
,
&
yHalfGPU
,
1
);
yUserHalfGPU
=
Softmax
(
xHalfGPU
,
1
);
/* convert data type from float16 to float */
_ConvertDataType
(
&
yHalfGPU
,
yGPU
);
yUserGPU
=
ConvertDataType
(
yUserHalfGPU
,
X_FLOAT
);
/* check result */
gpuTest
=
yGPU
->
CheckData
(
answer
,
unitNum
,
1e-3
F
)
&&
yUserGPU
.
CheckData
(
answer
,
unitNum
,
1e-3
F
);
/* destroy variables */
delete
xGPU
;
delete
yGPU
;
delete
[]
dimSize
;
return
cpuTest
&&
gpuTest
;
#else
/* destroy variables */
delete
[]
dimSize
;
return
cpuTest
;
#endif // USE_CUDA
}
/*
case 4: float16 test SoftmaxBackward function.
SoftmaxBackward function: dE/dx_j = -gold_j + y_j
In this case, LossName=CROSSENTROPY.
*/
bool
TestSoftmax4
()
{
/* a input tensor of size (2, 3) */
int
order
=
2
;
int
*
dimSize
=
new
int
[
order
];
dimSize
[
0
]
=
1
;
dimSize
[
1
]
=
3
;
int
unitNum
=
1
;
for
(
int
i
=
0
;
i
<
order
;
i
++
)
unitNum
*=
dimSize
[
i
];
DTYPE
xData
[
1
][
3
]
=
{
{
0.0
F
,
1.0
F
,
2.0
F
}
};
DTYPE
gData
[
1
][
3
]
=
{
{
0.0
F
,
0.0
F
,
1.0
F
}
};
DTYPE
yAnswer
[
1
][
3
]
=
{
{
0.0900
F
,
0.2447
F
,
0.6652
F
}
};
DTYPE
dedxAnswer
[
1
][
3
]
=
{
0.0900
F
,
0.2447
F
,
-
0.3347
F
};
/* CPU test */
bool
cpuTest
=
true
;
#ifdef USE_CUDA
/* GPU test */
bool
gpuTest
=
true
;
/* create tensors */
XTensor
*
xGPU
=
NewTensor
(
order
,
dimSize
,
X_FLOAT
,
1.0
F
,
0
);
XTensor
*
yGPU
=
NewTensor
(
order
,
dimSize
,
X_FLOAT
,
1.0
F
,
0
);
XTensor
*
gGPU
=
NewTensor
(
order
,
dimSize
,
X_FLOAT
,
1.0
F
,
0
);
XTensor
*
dedyGPU
=
NewTensor
(
order
,
dimSize
,
X_FLOAT
,
1.0
F
,
0
);
XTensor
*
dedxGPU
=
NewTensor
(
order
,
dimSize
,
X_FLOAT
,
1.0
F
,
0
);
/* create float16 tensors */
XTensor
xHalfGPU
;
XTensor
yHalfGPU
;
XTensor
gHalfGPU
;
XTensor
dedyHalfGPU
;
XTensor
dedxHalfGPU
;
/* initialize variables */
xGPU
->
SetData
(
xData
,
unitNum
);
gGPU
->
SetData
(
gData
,
unitNum
);
yGPU
->
SetZeroAll
();
dedxGPU
->
SetZeroAll
();
dedyGPU
->
SetZeroAll
();
/* convert data type from float to float16 */
xHalfGPU
=
ConvertDataType
(
*
xGPU
,
X_FLOAT16
);
yHalfGPU
=
ConvertDataType
(
*
yGPU
,
X_FLOAT16
);
gHalfGPU
=
ConvertDataType
(
*
gGPU
,
X_FLOAT16
);
dedxHalfGPU
=
ConvertDataType
(
*
dedxGPU
,
X_FLOAT16
);
dedyHalfGPU
=
ConvertDataType
(
*
dedyGPU
,
X_FLOAT16
);
/* call softmax function */
_Softmax
(
&
xHalfGPU
,
&
yHalfGPU
,
1
);
/* call SoftmaxBackward function */
_SoftmaxBackward
(
&
gHalfGPU
,
&
yHalfGPU
,
&
xHalfGPU
,
&
dedyHalfGPU
,
&
dedxHalfGPU
,
NULL
,
1
,
CROSSENTROPY
);
/* convert data type from float to float16 */
_ConvertDataType
(
&
yHalfGPU
,
yGPU
);
_ConvertDataType
(
&
dedxHalfGPU
,
dedxGPU
);
/* check result */
gpuTest
=
yGPU
->
CheckData
(
yAnswer
,
unitNum
,
1e-3
F
)
&&
dedxGPU
->
CheckData
(
dedxAnswer
,
unitNum
,
1e-3
F
);
/* destroy variables */
delete
xGPU
;
delete
yGPU
;
delete
gGPU
;
delete
dedxGPU
;
delete
dedyGPU
;
delete
[]
dimSize
;
return
cpuTest
&&
gpuTest
;
#else
/* destroy variables */
delete
[]
dimSize
;
return
cpuTest
;
#endif // USE_CUDA
}
/* other cases */
/* other cases */
/*
/*
TODO!!
TODO!!
...
@@ -238,6 +400,26 @@ bool TestSoftmax()
...
@@ -238,6 +400,26 @@ bool TestSoftmax()
else
else
XPRINT
(
0
,
stdout
,
">> case 2 passed!
\n
"
);
XPRINT
(
0
,
stdout
,
">> case 2 passed!
\n
"
);
/* case 3 test */
caseFlag
=
TestSoftmax3
();
if
(
!
caseFlag
)
{
returnFlag
=
false
;
XPRINT
(
0
,
stdout
,
">> case 3 failed!
\n
"
);
}
else
XPRINT
(
0
,
stdout
,
">> case 3 passed!
\n
"
);
/* case 4 test */
caseFlag
=
TestSoftmax4
();
if
(
!
caseFlag
)
{
returnFlag
=
false
;
XPRINT
(
0
,
stdout
,
">> case 4 failed!
\n
"
);
}
else
XPRINT
(
0
,
stdout
,
">> case 4 passed!
\n
"
);
/* other cases test */
/* other cases test */
/*
/*
TODO!!
TODO!!
...
...
source/tensor/test/TUnsqueeze.cpp
查看文件 @
54adb703
...
@@ -21,6 +21,7 @@
...
@@ -21,6 +21,7 @@
#include "../XList.h"
#include "../XList.h"
#include "TUnsqueeze.h"
#include "TUnsqueeze.h"
#include "../core/getandset/ConvertDataType.h"
namespace
nts
{
// namespace nts(NiuTrans.Tensor)
namespace
nts
{
// namespace nts(NiuTrans.Tensor)
...
@@ -153,6 +154,128 @@ bool TestUnsqueeze1()
...
@@ -153,6 +154,128 @@ bool TestUnsqueeze1()
#endif // USE_CUDA
#endif // USE_CUDA
}
}
/*
case 2: float16 insert a dimension by copying the blocks for x times (where x is the size of the inerted dimension)
In this case,
(2, 3) -> (2, 2, 3), dim=1, dSize=2
(2, 3) -> (2, 3, 2), dim=2, dSize=2
*/
bool
TestUnsqueeze2
()
{
/* a source tensor of size (2, 3) */
int
sOrder
=
2
;
int
*
sDimSize
=
new
int
[
sOrder
];
sDimSize
[
0
]
=
2
;
sDimSize
[
1
]
=
3
;
int
sUnitNum
=
1
;
for
(
int
i
=
0
;
i
<
sOrder
;
i
++
)
sUnitNum
*=
sDimSize
[
i
];
/* a target tensor of size (2, 2, 3) */
int
tOrder1
=
3
;
int
*
tDimSize1
=
new
int
[
tOrder1
];
tDimSize1
[
0
]
=
2
;
tDimSize1
[
1
]
=
2
;
tDimSize1
[
2
]
=
3
;
int
tUnitNum1
=
1
;
for
(
int
i
=
0
;
i
<
tOrder1
;
i
++
)
tUnitNum1
*=
tDimSize1
[
i
];
/* a target tensor of size (2, 3, 2) */
int
tOrder2
=
3
;
int
*
tDimSize2
=
new
int
[
tOrder2
];
tDimSize2
[
0
]
=
2
;
tDimSize2
[
1
]
=
3
;
tDimSize2
[
2
]
=
2
;
int
tUnitNum2
=
1
;
for
(
int
i
=
0
;
i
<
tOrder2
;
i
++
)
tUnitNum2
*=
tDimSize2
[
i
];
DTYPE
sData
[
2
][
3
]
=
{
{
0.0
F
,
1.0
F
,
2.0
F
},
{
3.0
F
,
4.0
F
,
5.0
F
}
};
DTYPE
answer1
[
2
][
2
][
3
]
=
{
{
{
0.0
F
,
1.0
F
,
2.0
F
},
{
0.0
F
,
1.0
F
,
2.0
F
}
},
{
{
3.0
F
,
4.0
F
,
5.0
F
},
{
3.0
F
,
4.0
F
,
5.0
F
}
}
};
DTYPE
answer2
[
2
][
3
][
2
]
=
{
{
{
0.0
F
,
0.0
F
},
{
1.0
F
,
1.0
F
},
{
2.0
F
,
2.0
F
}
},
{
{
3.0
F
,
3.0
F
},
{
4.0
F
,
4.0
F
},
{
5.0
F
,
5.0
F
}
}
};
/* CPU test */
bool
cpuTest
=
true
;
#ifdef USE_CUDA
/* GPU test */
bool
gpuTest
=
true
;
/* create tensor */
XTensor
*
sGPU
=
NewTensor
(
sOrder
,
sDimSize
,
X_FLOAT
,
1.0
F
,
0
);
XTensor
*
tGPU1
=
NewTensor
(
tOrder1
,
tDimSize1
,
X_FLOAT
,
1.0
F
,
0
);
XTensor
*
tGPU2
=
NewTensor
(
tOrder2
,
tDimSize2
,
X_FLOAT
,
1.0
F
,
0
);
XTensor
tUserGPU1
;
XTensor
tUserGPU2
;
/* create float16 tensor */
XTensor
sHalfGPU
;
XTensor
tHalfGPU1
;
XTensor
tHalfGPU2
;
XTensor
tUserHalfGPU1
;
XTensor
tUserHalfGPU2
;
/* Initialize variables */
sGPU
->
SetData
(
sData
,
sUnitNum
);
tGPU1
->
SetZeroAll
();
tGPU2
->
SetZeroAll
();
/* convert data type from float to float16 */
sHalfGPU
=
ConvertDataType
(
*
sGPU
,
X_FLOAT16
);
tHalfGPU1
=
ConvertDataType
(
*
tGPU1
,
X_FLOAT16
);
tHalfGPU2
=
ConvertDataType
(
*
tGPU2
,
X_FLOAT16
);
/* call unsqueeze function */
_Unsqueeze
(
&
sHalfGPU
,
&
tHalfGPU1
,
1
,
2
);
_Unsqueeze
(
&
sHalfGPU
,
&
tHalfGPU2
,
2
,
2
);
tUserHalfGPU1
=
Unsqueeze
(
sHalfGPU
,
1
,
2
);
tUserHalfGPU2
=
Unsqueeze
(
sHalfGPU
,
2
,
2
);
/* convert data type from float16 to float */
_ConvertDataType
(
&
tHalfGPU1
,
tGPU1
);
_ConvertDataType
(
&
tHalfGPU2
,
tGPU2
);
tUserGPU1
=
ConvertDataType
(
tUserHalfGPU1
,
X_FLOAT
);
tUserGPU2
=
ConvertDataType
(
tUserHalfGPU2
,
X_FLOAT
);
/* check results */
gpuTest
=
tGPU1
->
CheckData
(
answer1
,
tUnitNum1
)
&&
tUserGPU1
.
CheckData
(
answer1
,
tUnitNum1
)
&&
tGPU2
->
CheckData
(
answer2
,
tUnitNum2
)
&&
tUserGPU2
.
CheckData
(
answer2
,
tUnitNum2
);
/* destroy variables */
delete
sGPU
;
delete
tGPU1
;
delete
tGPU2
;
delete
[]
sDimSize
;
delete
[]
tDimSize1
;
delete
[]
tDimSize2
;
return
cpuTest
&&
gpuTest
;
#else
/* destroy variables */
delete
[]
sDimSize
;
delete
[]
tDimSize1
;
delete
[]
tDimSize2
;
return
cpuTest
;
#endif // USE_CUDA
}
/* other cases */
/* other cases */
/*
/*
TODO!!
TODO!!
...
@@ -174,6 +297,16 @@ bool TestUnsqueeze()
...
@@ -174,6 +297,16 @@ bool TestUnsqueeze()
else
else
XPRINT
(
0
,
stdout
,
">> case 1 passed!
\n
"
);
XPRINT
(
0
,
stdout
,
">> case 1 passed!
\n
"
);
/* case 2 test */
caseFlag
=
TestUnsqueeze2
();
if
(
!
caseFlag
)
{
returnFlag
=
false
;
XPRINT
(
0
,
stdout
,
">> case 2 failed!
\n
"
);
}
else
XPRINT
(
0
,
stdout
,
">> case 2 passed!
\n
"
);
/* other cases test */
/* other cases test */
/*
/*
TODO!!
TODO!!
...
...
source/tensor/test/Test.cpp
查看文件 @
54adb703
...
@@ -48,9 +48,9 @@ bool Test()
...
@@ -48,9 +48,9 @@ bool Test()
//wrong = !TestMatrixMul2DParallel() || wrong;
//wrong = !TestMatrixMul2DParallel() || wrong;
//wrong = !TestMatrixMulBatched() || wrong;
//wrong = !TestMatrixMulBatched() || wrong;
//wrong = !TestMerge() || wrong;
//wrong = !TestMerge() || wrong;
//
wrong = !TestMultiply() || wrong;
wrong
=
!
TestMultiply
()
||
wrong
;
//wrong = !TestMultiplyDim() || wrong;
//wrong = !TestMultiplyDim() || wrong;
wrong
=
!
TestNegate
()
||
wrong
;
//
wrong = !TestNegate() || wrong;
//wrong = !TestNormalize() || wrong;
//wrong = !TestNormalize() || wrong;
//wrong = !TestPower() || wrong;
//wrong = !TestPower() || wrong;
//wrong = !TestReduceMax() || wrong;
//wrong = !TestReduceMax() || wrong;
...
@@ -64,7 +64,7 @@ bool Test()
...
@@ -64,7 +64,7 @@ bool Test()
//wrong = !TestSelect() || wrong;
//wrong = !TestSelect() || wrong;
//wrong = !TestSetAscendingOrder() || wrong;
//wrong = !TestSetAscendingOrder() || wrong;
//wrong = !TestSetData() || wrong;
//wrong = !TestSetData() || wrong;
wrong
=
!
TestSign
()
||
wrong
;
//
wrong = !TestSign() || wrong;
//wrong = !TestSin() || wrong;
//wrong = !TestSin() || wrong;
//wrong = !TestSort() || wrong;
//wrong = !TestSort() || wrong;
//wrong = !TestSplit() || wrong;
//wrong = !TestSplit() || wrong;
...
@@ -76,10 +76,10 @@ bool Test()
...
@@ -76,10 +76,10 @@ bool Test()
//wrong = !TestTan() || wrong;
//wrong = !TestTan() || wrong;
//wrong = !TestTranspose() || wrong;
//wrong = !TestTranspose() || wrong;
//wrong = !TestTopK() || wrong;
//wrong = !TestTopK() || wrong;
//
wrong = !TestUnsqueeze() || wrong;
wrong
=
!
TestUnsqueeze
()
||
wrong
;
//wrong = !TestXMem() || wrong;
//wrong = !TestXMem() || wrong;
//
//
//
wrong = !TestCrossEntropy() || wrong;
wrong
=
!
TestCrossEntropy
()
||
wrong
;
//wrong = !TestDropout() || wrong;
//wrong = !TestDropout() || wrong;
//wrong = !TestHardTanH() || wrong;
//wrong = !TestHardTanH() || wrong;
//wrong = !TestIdentity() || wrong;
//wrong = !TestIdentity() || wrong;
...
@@ -87,7 +87,7 @@ bool Test()
...
@@ -87,7 +87,7 @@ bool Test()
//wrong = !TestLoss() || wrong;
//wrong = !TestLoss() || wrong;
//wrong = !TestRectify() || wrong;
//wrong = !TestRectify() || wrong;
//wrong = !TestSigmoid() || wrong;
//wrong = !TestSigmoid() || wrong;
//
wrong = !TestSoftmax() || wrong;
wrong
=
!
TestSoftmax
()
||
wrong
;
/* other test */
/* other test */
/*
/*
...
...
编写
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