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2d9113da
编写于
6月 28, 2017
作者:
H
hedaoyuan
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电子邮件补丁
差异文件
Add test for NNPACKConvFunc.
上级
7062be0f
变更
2
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2 changed file
with
99 addition
and
0 deletion
+99
-0
paddle/function/CMakeLists.txt
paddle/function/CMakeLists.txt
+3
-0
paddle/function/nnpack/NNPACKConvOpTest.cpp
paddle/function/nnpack/NNPACKConvOpTest.cpp
+96
-0
未找到文件。
paddle/function/CMakeLists.txt
浏览文件 @
2d9113da
...
...
@@ -13,6 +13,9 @@ endif()
if
(
USE_NNPACK
)
include
(
nnpack/nnpack.cmake
)
list
(
APPEND cpp_files nnpack/NNPACKConvOp.cpp
)
if
(
WITH_TESTING
)
add_unittest
(
NNPACKConvOpTest nnpack/NNPACKConvOpTest.cpp
)
endif
()
endif
()
add_library
(
paddle_function STATIC
${
cpp_files
}
${
cu_objs
}
)
...
...
paddle/function/nnpack/NNPACKConvOpTest.cpp
0 → 100644
浏览文件 @
2d9113da
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include <gtest/gtest.h>
#include "paddle/function/Function.h"
#include "paddle/function/FunctionTest.h"
DEFINE_string
(
algo
,
"auto"
,
"The algorithm (auto, ft8x8, ft16x16, wt8x8, "
"implicit-gemm, or direct) for computing convolution of NNPACK."
);
namespace
paddle
{
#define IS_NNPACK_SUPPORT(algo, filterSize, stride) \
if (algo == "direct" && filterSize != 1) continue; \
if (algo == "direct" && batchSize != 1) continue; \
if (algo == "wt8x8" && filterSize != 3) continue; \
if (algo == "implicit-gemm" && batchSize != 1) continue; \
if (algo != "auto" && algo != "implicit-gemm" && stride > 1) continue;
class
ConvolutionTest
{
public:
ConvolutionTest
(
const
std
::
string
&
conv1
,
const
std
::
string
&
conv2
,
std
::
string
algo
=
"auto"
)
{
for
(
size_t
batchSize
:
{
1
,
32
})
{
for
(
size_t
inputSize
:
{
7
,
14
,
54
})
{
for
(
size_t
filterSize
:
{
1
,
3
,
5
})
{
for
(
size_t
inputChannels
:
{
3
,
64
})
{
for
(
size_t
outputChannels
:
{
3
,
64
,
128
})
{
if
(
inputChannels
<
outputChannels
)
break
;
for
(
size_t
stride
:
{
1
,
2
})
{
// if batchSize > 1 NNPACKConv only supports stride = 1
if
(
batchSize
>
1
&&
stride
>
1
)
break
;
for
(
size_t
padding
:
{
0
,
1
})
{
if
(
padding
>=
filterSize
)
break
;
size_t
outputSize
=
(
inputSize
-
filterSize
+
2
*
padding
+
stride
)
/
stride
;
IS_NNPACK_SUPPORT
(
algo
,
filterSize
,
stride
);
LOG
(
INFO
)
<<
" batchSize="
<<
batchSize
<<
" inputChannels="
<<
inputChannels
<<
" inputHeight="
<<
inputSize
<<
" inputWidth="
<<
inputSize
<<
" outputChannels="
<<
outputChannels
<<
" filterHeight="
<<
filterSize
<<
" filterWidth="
<<
filterSize
<<
" outputHeight="
<<
outputSize
<<
" outputWidth="
<<
outputSize
<<
" stride="
<<
stride
<<
" padding="
<<
padding
;
Compare2Function
<
DEVICE_TYPE_CPU
,
DEVICE_TYPE_CPU
>
test
(
conv1
,
conv2
,
FuncConfig
()
.
set
(
"padding"
,
padding
)
.
set
(
"stride"
,
stride
)
.
set
(
"algo"
,
algo
));
TensorShape
shape0
{
batchSize
,
inputChannels
,
inputSize
,
inputSize
};
TensorShape
shape1
{
outputChannels
,
inputChannels
,
filterSize
,
filterSize
};
TensorShape
shape2
{
batchSize
,
outputChannels
,
outputSize
,
outputSize
};
test
.
addInputs
(
BufferArg
(
VALUE_TYPE_FLOAT
,
shape0
));
test
.
addInputs
(
BufferArg
(
VALUE_TYPE_FLOAT
,
shape1
));
test
.
addOutputs
(
BufferArg
(
VALUE_TYPE_FLOAT
,
shape2
));
test
.
run
();
}
}
}
}
}
}
}
}
};
TEST
(
Convolution
,
NNPACK
)
{
// NNPACK only supports stride = 1
ConvolutionTest
test
(
"GemmConv-CPU"
,
"NNPACKConv-CPU"
,
FLAGS_algo
);
}
}
// namespace paddle
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