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2608c485
编写于
6月 13, 2017
作者:
H
hedaoyuan
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电子邮件补丁
差异文件
Add test cases where the height and width (input, filter) are not equal.
上级
01d52ebf
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
88 addition
and
1 deletion
+88
-1
paddle/function/ConvOpTest.cpp
paddle/function/ConvOpTest.cpp
+87
-0
paddle/function/NaiveConvOp.cpp
paddle/function/NaiveConvOp.cpp
+1
-1
未找到文件。
paddle/function/ConvOpTest.cpp
浏览文件 @
2608c485
...
...
@@ -98,25 +98,112 @@ public:
}
};
// Mainly used to test cases where the height and width (input, filter)
// are not equal.
template
<
DeviceType
DType1
,
DeviceType
DType2
>
class
ConvolutionTest2
{
public:
ConvolutionTest2
(
const
std
::
string
&
conv1
,
const
std
::
string
&
conv2
,
TestType
type
,
std
::
string
algo
=
"auto"
)
{
for
(
size_t
batchSize
:
{
16
})
{
for
(
size_t
inputHeight
:
{
7
,
31
})
{
for
(
size_t
inputWidth
:
{
10
,
54
})
{
for
(
size_t
filterHeight
:
{
1
,
5
})
{
for
(
size_t
filterWidth
:
{
3
,
7
})
{
for
(
size_t
inputChannels
:
{
7
})
{
for
(
size_t
outputChannels
:
{
32
})
{
size_t
stride
=
1
;
size_t
padding
=
0
;
size_t
outputHeight
=
(
inputHeight
-
filterHeight
+
2
*
padding
+
stride
)
/
stride
;
size_t
outputWidth
=
(
inputWidth
-
filterWidth
+
2
*
padding
+
stride
)
/
stride
;
VLOG
(
3
)
<<
" batchSize="
<<
batchSize
<<
" inputChannels="
<<
inputChannels
<<
" inputHeight="
<<
inputHeight
<<
" inputWidth="
<<
inputWidth
<<
" outputChannels="
<<
outputChannels
<<
" filterHeight="
<<
filterHeight
<<
" filterWidth="
<<
filterWidth
<<
" outputHeight="
<<
outputHeight
<<
" outputWidth="
<<
outputWidth
<<
" stride="
<<
stride
<<
" padding="
<<
padding
;
std
::
vector
<
size_t
>
paddings
=
{
padding
,
padding
};
std
::
vector
<
size_t
>
strides
=
{
stride
,
stride
};
Compare2Function
<
DType1
,
DType2
>
test
(
conv1
,
conv2
,
FuncConfig
()
.
set
(
"paddings"
,
paddings
)
.
set
(
"strides"
,
strides
)
.
set
(
"groups"
,
(
size_t
)
1
)
.
set
(
"algo"
,
algo
));
TensorShape
input
{
batchSize
,
inputChannels
,
inputHeight
,
inputWidth
};
TensorShape
filter
{
outputChannels
,
inputChannels
,
filterHeight
,
filterWidth
};
TensorShape
output
{
batchSize
,
outputChannels
,
outputHeight
,
outputWidth
};
if
(
type
==
kForwardTest
)
{
test
.
addInputs
(
BufferArg
(
VALUE_TYPE_FLOAT
,
input
));
test
.
addInputs
(
BufferArg
(
VALUE_TYPE_FLOAT
,
filter
));
test
.
addOutputs
(
BufferArg
(
VALUE_TYPE_FLOAT
,
output
));
test
.
run
();
}
else
if
(
type
==
kBackwardInputTest
)
{
test
.
addInputs
(
BufferArg
(
VALUE_TYPE_FLOAT
,
output
));
test
.
addInputs
(
BufferArg
(
VALUE_TYPE_FLOAT
,
filter
));
test
.
addOutputs
(
BufferArg
(
VALUE_TYPE_FLOAT
,
input
),
ADD_TO
);
test
.
run
();
}
else
if
(
type
==
kBackwardFilterTest
)
{
test
.
addInputs
(
BufferArg
(
VALUE_TYPE_FLOAT
,
output
));
test
.
addInputs
(
BufferArg
(
VALUE_TYPE_FLOAT
,
input
));
test
.
addOutputs
(
BufferArg
(
VALUE_TYPE_FLOAT
,
filter
));
test
.
run
();
}
}
}
}
}
}
}
}
}
};
TEST
(
Forward
,
GEMM
)
{
ConvolutionTest
<
DEVICE_TYPE_CPU
,
DEVICE_TYPE_CPU
>
test
(
"NaiveConv-CPU"
,
"GemmConv-CPU"
,
kForwardTest
);
ConvolutionTest2
<
DEVICE_TYPE_CPU
,
DEVICE_TYPE_CPU
>
test2
(
"NaiveConv-CPU"
,
"GemmConv-CPU"
,
kForwardTest
);
}
#ifndef PADDLE_ONLY_CPU
TEST
(
Forward
,
GEMM2
)
{
ConvolutionTest
<
DEVICE_TYPE_CPU
,
DEVICE_TYPE_GPU
>
test
(
"GemmConv-CPU"
,
"GemmConv-GPU"
,
kForwardTest
);
ConvolutionTest2
<
DEVICE_TYPE_CPU
,
DEVICE_TYPE_GPU
>
test2
(
"GemmConv-CPU"
,
"GemmConv-GPU"
,
kForwardTest
);
}
TEST
(
BackwardInput
,
GEMM
)
{
ConvolutionTest
<
DEVICE_TYPE_CPU
,
DEVICE_TYPE_GPU
>
test
(
"GemmConvGradInput-CPU"
,
"GemmConvGradInput-GPU"
,
kBackwardInputTest
);
ConvolutionTest2
<
DEVICE_TYPE_CPU
,
DEVICE_TYPE_GPU
>
test2
(
"GemmConvGradInput-CPU"
,
"GemmConvGradInput-GPU"
,
kBackwardInputTest
);
}
TEST
(
BackwardFilter
,
GEMM
)
{
ConvolutionTest
<
DEVICE_TYPE_CPU
,
DEVICE_TYPE_GPU
>
test
(
"GemmConvGradFilter-CPU"
,
"GemmConvGradFilter-GPU"
,
kBackwardFilterTest
);
ConvolutionTest2
<
DEVICE_TYPE_CPU
,
DEVICE_TYPE_GPU
>
test2
(
"GemmConvGradFilter-CPU"
,
"GemmConvGradFilter-GPU"
,
kBackwardFilterTest
);
}
#endif
...
...
paddle/function/NaiveConvOp.cpp
浏览文件 @
2608c485
...
...
@@ -104,7 +104,7 @@ public:
size_t
inputHeight
=
inputs
[
0
].
shape
()[
2
];
size_t
inputWidth
=
inputs
[
0
].
shape
()[
3
];
size_t
filterHeight
=
inputs
[
1
].
shape
()[
2
];
size_t
filterWidth
=
inputs
[
1
].
shape
()[
2
];
size_t
filterWidth
=
inputs
[
1
].
shape
()[
3
];
size_t
outputChannels
=
outputs
[
0
].
shape
()[
1
];
size_t
outputHeight
=
outputs
[
0
].
shape
()[
2
];
size_t
outputWidth
=
outputs
[
0
].
shape
()[
3
];
...
...
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