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c4cf0c74
编写于
5月 30, 2018
作者:
E
eclipsycn
提交者:
GitHub
5月 30, 2018
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差异文件
Merge pull request #321 from smilejames/develop
submit depthwise_conv_op and test
上级
ddf97f91
8d3c8d67
变更
10
显示空白变更内容
内联
并排
Showing
10 changed file
with
342 addition
and
22 deletion
+342
-22
src/operators/conv_op.cpp
src/operators/conv_op.cpp
+0
-7
src/operators/conv_op.h
src/operators/conv_op.h
+7
-0
src/operators/depthwise_conv_op.cpp
src/operators/depthwise_conv_op.cpp
+57
-0
src/operators/depthwise_conv_op.h
src/operators/depthwise_conv_op.h
+49
-0
src/operators/kernel/arm/conv_kernel.cpp
src/operators/kernel/arm/conv_kernel.cpp
+0
-13
src/operators/kernel/arm/depthwise_conv_kernel.cpp
src/operators/kernel/arm/depthwise_conv_kernel.cpp
+126
-0
src/operators/kernel/conv_kernel.h
src/operators/kernel/conv_kernel.h
+19
-2
src/operators/kernel/depthwise_conv_kernel.h
src/operators/kernel/depthwise_conv_kernel.h
+34
-0
test/CMakeLists.txt
test/CMakeLists.txt
+4
-0
test/operators/test_depthwise_conv_op.cpp
test/operators/test_depthwise_conv_op.cpp
+46
-0
未找到文件。
src/operators/conv_op.cpp
浏览文件 @
c4cf0c74
...
@@ -21,13 +21,6 @@ limitations under the License. */
...
@@ -21,13 +21,6 @@ limitations under the License. */
namespace
paddle_mobile
{
namespace
paddle_mobile
{
namespace
operators
{
namespace
operators
{
int
ConvOutputSize
(
int
input_size
,
int
filter_size
,
int
dilation
,
int
padding
,
int
stride
)
{
const
int
dkernel
=
dilation
*
(
filter_size
-
1
)
+
1
;
int
output_size
=
(
input_size
+
2
*
padding
-
dkernel
)
/
stride
+
1
;
return
output_size
;
}
template
<
typename
Dtype
,
typename
T
>
template
<
typename
Dtype
,
typename
T
>
void
ConvOp
<
Dtype
,
T
>::
InferShape
()
const
{
void
ConvOp
<
Dtype
,
T
>::
InferShape
()
const
{
// std::cout << " begin get dims: " << std::endl;
// std::cout << " begin get dims: " << std::endl;
...
...
src/operators/conv_op.h
浏览文件 @
c4cf0c74
...
@@ -44,5 +44,12 @@ class ConvOp : public framework::OperatorWithKernel<DeviceType> {
...
@@ -44,5 +44,12 @@ class ConvOp : public framework::OperatorWithKernel<DeviceType> {
ConvParam
param_
;
ConvParam
param_
;
};
};
inline
int
ConvOutputSize
(
int
input_size
,
int
filter_size
,
int
dilation
,
int
padding
,
int
stride
)
{
const
int
dkernel
=
dilation
*
(
filter_size
-
1
)
+
1
;
int
output_size
=
(
input_size
+
2
*
padding
-
dkernel
)
/
stride
+
1
;
return
output_size
;
}
}
// namespace operators
}
// namespace operators
}
// namespace paddle_mobile
}
// namespace paddle_mobile
src/operators/depthwise_conv_op.cpp
0 → 100644
浏览文件 @
c4cf0c74
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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 "operators/depthwise_conv_op.h"
#include <vector>
#include "framework/data_type.h"
#include "framework/op_proto_maker.h"
#include "framework/op_registry.h"
#include "operators/conv_op.h"
namespace
paddle_mobile
{
namespace
operators
{
template
<
typename
Dtype
,
typename
T
>
void
DepthwiseConvOp
<
Dtype
,
T
>::
InferShape
()
const
{
auto
in_dims
=
param_
.
Input
()
->
dims
();
auto
filter_dims
=
param_
.
Filter
()
->
dims
();
const
std
::
vector
<
int
>
&
strides
=
param_
.
Strides
();
std
::
vector
<
int
>
paddings
=
param_
.
Paddings
();
int
groups
=
param_
.
Groups
();
std
::
vector
<
int
>
dilations
=
param_
.
Dilations
();
PADDLE_MOBILE_ENFORCE
((
in_dims
.
size
()
==
filter_dims
.
size
()
&&
dilations
.
size
()
==
paddings
.
size
()
&&
paddings
.
size
()
==
strides
.
size
()),
"ConvParam is not suitable"
);
std
::
vector
<
int64_t
>
output_shape
({
in_dims
[
0
],
filter_dims
[
0
]});
for
(
size_t
i
=
0
;
i
<
strides
.
size
();
++
i
)
{
output_shape
.
push_back
(
ConvOutputSize
(
in_dims
[
i
+
2
],
filter_dims
[
i
+
2
],
dilations
[
i
],
paddings
[
i
],
strides
[
i
]));
}
framework
::
DDim
ddim
=
framework
::
make_ddim
(
output_shape
);
param_
.
Output
()
->
Resize
(
ddim
);
}
template
class
DepthwiseConvOp
<
CPU
,
float
>;
}
// namespace operators
}
// namespace paddle_mobile
namespace
ops
=
paddle_mobile
::
operators
;
USE_OP
(
depthwise_conv2d
);
REGISTER_OPERATOR
(
depthwise_conv2d
,
ops
::
DepthwiseConvOp
);
src/operators/depthwise_conv_op.h
0 → 100644
浏览文件 @
c4cf0c74
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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. */
#pragma once
#include <string>
#include "framework/operator.h"
#include "operators/kernel/depthwise_conv_kernel.h"
namespace
paddle_mobile
{
namespace
operators
{
template
<
typename
DeviceType
,
typename
T
>
class
DepthwiseConvOp
:
public
framework
::
OperatorWithKernel
<
DeviceType
>
{
public:
DepthwiseConvOp
(
const
std
::
string
&
type
,
const
VariableNameMap
&
inputs
,
const
VariableNameMap
&
outputs
,
const
framework
::
AttributeMap
&
attrs
,
std
::
shared_ptr
<
framework
::
Scope
>
scope
)
:
framework
::
OperatorWithKernel
<
DeviceType
>
(
type
,
inputs
,
outputs
,
attrs
,
scope
),
param_
(
inputs
,
outputs
,
attrs
,
*
scope
)
{}
using
framework
::
OperatorWithKernel
<
DeviceType
>::
OperatorWithKernel
;
void
InferShape
()
const
override
;
void
RunImpl
()
const
{
operators
::
DepthwiseConvKernel
<
DeviceType
,
T
>
kernel
;
kernel
.
Compute
(
param_
);
this
->
ClearVariables
({
"Filter"
,
"Input"
});
}
private:
ConvParam
param_
;
};
}
// namespace operators
}
// namespace paddle_mobile
src/operators/kernel/arm/conv_kernel.cpp
浏览文件 @
c4cf0c74
...
@@ -17,19 +17,6 @@ limitations under the License. */
...
@@ -17,19 +17,6 @@ limitations under the License. */
namespace
paddle_mobile
{
namespace
paddle_mobile
{
namespace
operators
{
namespace
operators
{
bool
IsExpand
(
const
std
::
vector
<
int64_t
>
&
filter_dim
,
const
std
::
vector
<
int
>
&
strides
,
const
std
::
vector
<
int
>
&
paddings
,
const
std
::
vector
<
int
>
&
dilations
)
{
bool
filter_1
=
true
,
strides_1
=
true
,
padding_0
=
true
,
dilation_1
=
true
;
for
(
size_t
j
=
0
;
j
<
strides
.
size
();
++
j
)
{
filter_1
=
filter_1
&&
(
static_cast
<
int
>
(
filter_dim
[
j
+
2
])
==
1
);
strides_1
=
strides_1
&&
(
strides
[
j
]
==
1
);
padding_0
=
padding_0
&&
(
paddings
[
j
]
==
0
);
dilation_1
=
dilation_1
&&
(
dilations
[
j
]
==
1
);
}
return
!
(
filter_1
&&
strides_1
&&
padding_0
&&
dilation_1
);
}
template
<
>
template
<
>
void
ConvKernel
<
CPU
,
float
>::
Compute
(
const
ConvParam
&
param
)
const
{
void
ConvKernel
<
CPU
,
float
>::
Compute
(
const
ConvParam
&
param
)
const
{
LOG
(
kLOG_DEBUG
)
<<
param
;
LOG
(
kLOG_DEBUG
)
<<
param
;
...
...
src/operators/kernel/arm/depthwise_conv_kernel.cpp
0 → 100644
浏览文件 @
c4cf0c74
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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 "operators/kernel/depthwise_conv_kernel.h"
#include "operators/kernel/conv_kernel.h"
namespace
paddle_mobile
{
namespace
operators
{
template
<
>
void
DepthwiseConvKernel
<
CPU
,
float
>::
Compute
(
const
ConvParam
&
param
)
const
{
LOG
(
kLOG_DEBUG
)
<<
param
;
const
Tensor
*
input
=
param
.
Input
();
Tensor
filter
=
*
param
.
Filter
();
Tensor
*
output
=
param
.
Output
();
output
->
mutable_data
<
float
>
();
int
groups
=
param
.
Groups
();
std
::
vector
<
int
>
strides
=
param
.
Strides
();
std
::
vector
<
int
>
paddings
=
param
.
Paddings
();
std
::
vector
<
int
>
dilations
=
param
.
Dilations
();
DLOG
<<
" compute end get Attrs "
<<
strides
[
0
];
const
int
batch_size
=
static_cast
<
int
>
(
input
->
dims
()[
0
]);
std
::
vector
<
int64_t
>
filter_shape_vec
(
framework
::
vectorize
(
filter
.
dims
()));
std
::
vector
<
int64_t
>
output_shape_vec
(
framework
::
vectorize
(
output
->
dims
()));
size_t
data_dim
=
filter_shape_vec
.
size
()
-
2
;
std
::
vector
<
int64_t
>
col_shape_vec
(
1
+
2
*
data_dim
);
col_shape_vec
[
0
]
=
input
->
dims
()[
1
]
/
groups
;
for
(
size_t
j
=
0
;
j
<
data_dim
;
++
j
)
{
col_shape_vec
[
j
+
1
]
=
filter_shape_vec
[
j
+
2
];
col_shape_vec
[
j
+
1
+
data_dim
]
=
output_shape_vec
[
j
+
2
];
}
framework
::
DDim
col_shape
(
framework
::
make_ddim
(
col_shape_vec
));
framework
::
DDim
col_matrix_shape
=
framework
::
flatten_to_2d
(
col_shape
,
data_dim
+
1
);
bool
is_expand
=
IsExpand
(
filter_shape_vec
,
strides
,
paddings
,
dilations
);
Tensor
col
;
Tensor
col_matrix
;
if
(
is_expand
)
{
col
.
mutable_data
<
float
>
(
col_shape
);
col_matrix
.
ShareDataWith
(
col
);
col_matrix
.
Resize
(
col_matrix_shape
);
}
DLOG
<<
" col_shape = "
<<
col_shape
;
DLOG
<<
" col_matrix_shape = "
<<
col_matrix_shape
;
framework
::
DDim
input_shape
=
framework
::
slice_ddim
(
input
->
dims
(),
1
,
static_cast
<
int
>
(
input
->
dims
().
size
()));
DLOG
<<
" input_shape = "
<<
input_shape
;
framework
::
DDim
filter_matrix_shape
=
{
filter
.
dims
()[
0
],
filter
.
numel
()
/
filter
.
dims
()[
0
]};
filter
.
Resize
(
filter_matrix_shape
);
DLOG
<<
" filter.dims() = "
<<
filter
.
dims
();
framework
::
DDim
output_matrix_shape
=
{
output
->
dims
()[
1
],
output
->
numel
()
/
(
output
->
dims
()[
0
]
*
output
->
dims
()[
1
])};
// convolution operator: im2col(or vol2col) + gemm
int
in_step
=
static_cast
<
int
>
(
input
->
dims
()[
1
])
/
groups
;
int
out_step
=
static_cast
<
int
>
(
output
->
dims
()[
1
])
/
groups
;
math
::
Vol2ColFunctor
<
CPU
,
float
>
vol2col
;
math
::
Im2ColFunctor
<
math
::
ColFormat
::
kCFO
,
CPU
,
float
>
im2col
;
for
(
int
i
=
0
;
i
<
batch_size
;
i
++
)
{
Tensor
in_batch
=
input
->
Slice
(
i
,
i
+
1
).
Resize
(
input_shape
);
Tensor
out_batch
=
output
->
Slice
(
i
,
i
+
1
).
Resize
(
output_matrix_shape
);
DLOG
<<
" in_batch.dims() = "
<<
in_batch
.
dims
();
DLOG
<<
" out_batch.dims() = "
<<
out_batch
.
dims
();
for
(
int
g
=
0
;
g
<
groups
;
g
++
)
{
Tensor
in_slice
=
in_batch
.
Slice
(
g
*
in_step
,
(
g
+
1
)
*
in_step
);
if
(
!
is_expand
)
{
col
.
ShareDataWith
(
in_slice
);
col_matrix
.
ShareDataWith
(
col
);
col_matrix
.
Resize
(
col_matrix_shape
);
}
else
if
(
data_dim
==
2U
)
{
// im2col
im2col
(
in_slice
,
dilations
,
strides
,
std
::
vector
<
int
>
{
paddings
[
0
],
paddings
[
1
],
paddings
[
0
],
paddings
[
1
]},
&
col
);
}
else
if
(
data_dim
==
3U
)
{
// vol2col
vol2col
(
in_slice
,
dilations
,
strides
,
paddings
,
&
col
);
}
// gemm
Tensor
out_slice
=
out_batch
.
Slice
(
g
*
out_step
,
(
g
+
1
)
*
out_step
);
Tensor
filter_slice
=
filter
.
Slice
(
g
*
out_step
,
(
g
+
1
)
*
out_step
);
DLOG
<<
" out_slice "
<<
out_slice
.
dims
();
DLOG
<<
" filter_slice "
<<
filter_slice
.
dims
();
DLOG
<<
" col_matrix "
<<
col_matrix
.
dims
();
math
::
matmul
<
float
>
(
filter_slice
,
false
,
col_matrix
,
false
,
static_cast
<
float
>
(
1
),
&
out_slice
,
static_cast
<
float
>
(
0
));
auto
filter_ptr
=
filter_slice
.
data
<
float
>
();
}
}
}
template
class
DepthwiseConvKernel
<
CPU
,
float
>;
}
// namespace operators
}
// namespace paddle_mobile
src/operators/kernel/conv_kernel.h
浏览文件 @
c4cf0c74
...
@@ -12,6 +12,7 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
...
@@ -12,6 +12,7 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
See the License for the specific language governing permissions and
limitations under the License. */
limitations under the License. */
#include <vector>
#include "framework/operator.h"
#include "framework/operator.h"
#include "operators/math/im2col.h"
#include "operators/math/im2col.h"
#include "operators/math/math_function.h"
#include "operators/math/math_function.h"
...
@@ -23,12 +24,28 @@ limitations under the License. */
...
@@ -23,12 +24,28 @@ limitations under the License. */
namespace
paddle_mobile
{
namespace
paddle_mobile
{
namespace
operators
{
namespace
operators
{
using
namespace
framework
;
using
framework
::
OpKernelBase
;
template
<
typename
DeviceType
,
typename
T
>
template
<
typename
DeviceType
,
typename
T
>
class
ConvKernel
:
public
framework
::
OpKernelBase
<
DeviceType
,
ConvParam
>
{
class
ConvKernel
:
public
OpKernelBase
<
DeviceType
,
ConvParam
>
{
public:
public:
void
Compute
(
const
ConvParam
&
param
)
const
;
void
Compute
(
const
ConvParam
&
param
)
const
;
};
};
inline
bool
IsExpand
(
const
std
::
vector
<
int64_t
>
&
filter_dim
,
const
std
::
vector
<
int
>
&
strides
,
const
std
::
vector
<
int
>
&
paddings
,
const
std
::
vector
<
int
>
&
dilations
)
{
bool
filter_1
=
true
,
strides_1
=
true
,
padding_0
=
true
,
dilation_1
=
true
;
for
(
size_t
j
=
0
;
j
<
strides
.
size
();
++
j
)
{
filter_1
=
filter_1
&&
(
static_cast
<
int
>
(
filter_dim
[
j
+
2
])
==
1
);
strides_1
=
strides_1
&&
(
strides
[
j
]
==
1
);
padding_0
=
padding_0
&&
(
paddings
[
j
]
==
0
);
dilation_1
=
dilation_1
&&
(
dilations
[
j
]
==
1
);
}
return
!
(
filter_1
&&
strides_1
&&
padding_0
&&
dilation_1
);
}
}
// namespace operators
}
// namespace operators
}
// namespace paddle_mobile
}
// namespace paddle_mobile
src/operators/kernel/depthwise_conv_kernel.h
0 → 100644
浏览文件 @
c4cf0c74
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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 "framework/operator.h"
#include "operators/math/im2col.h"
#include "operators/math/math_function.h"
#include "operators/math/vol2col.h"
#include "operators/op_param.h"
#pragma once;
namespace
paddle_mobile
{
namespace
operators
{
using
framework
::
OpKernelBase
;
template
<
typename
DeviceType
,
typename
T
>
class
DepthwiseConvKernel
:
public
OpKernelBase
<
DeviceType
,
ConvParam
>
{
public:
void
Compute
(
const
ConvParam
&
param
)
const
;
};
}
// namespace operators
}
// namespace paddle_mobile
test/CMakeLists.txt
浏览文件 @
c4cf0c74
...
@@ -91,3 +91,7 @@ target_link_libraries(test-googlenet paddle-mobile)
...
@@ -91,3 +91,7 @@ target_link_libraries(test-googlenet paddle-mobile)
# gen test
# gen test
ADD_EXECUTABLE
(
test-sigmoid operators/test_sigmoid_op.cpp test_include.h
)
ADD_EXECUTABLE
(
test-sigmoid operators/test_sigmoid_op.cpp test_include.h
)
target_link_libraries
(
test-sigmoid paddle-mobile
)
target_link_libraries
(
test-sigmoid paddle-mobile
)
# gen test
ADD_EXECUTABLE
(
test-depthwise-conv-op operators/test_depthwise_conv_op.cpp test_helper.h test_include.h executor_for_test.h
)
target_link_libraries
(
test-depthwise-conv-op paddle-mobile
)
test/operators/test_depthwise_conv_op.cpp
0 → 100644
浏览文件 @
c4cf0c74
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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 "../executor_for_test.h"
#include "../test_include.h"
#include "operators/depthwise_conv_op.h"
int
main
()
{
paddle_mobile
::
Loader
<
paddle_mobile
::
CPU
>
loader
;
// ../models/image_classification_resnet.inference.model
auto
program
=
loader
.
Load
(
g_mobilenet_ssd
);
PADDLE_MOBILE_ENFORCE
(
program
.
originProgram
!=
nullptr
,
"program file read fail"
);
Executor4Test
<
paddle_mobile
::
CPU
,
paddle_mobile
::
operators
::
DepthwiseConvOp
<
paddle_mobile
::
CPU
,
float
>>
executor
(
program
,
"depthwise_conv2d"
);
paddle_mobile
::
framework
::
LoDTensor
input
;
// GetInput<float>(g_test_image_1x3x224x224, &input, {1, 3, 224, 224});
// use SetupTensor if not has local input image .
SetupTensor
<
float
>
(
&
input
,
{
1
,
32
,
150
,
150
},
static_cast
<
float
>
(
0
),
static_cast
<
float
>
(
1
));
auto
input_ptr
=
input
.
data
<
float
>
();
auto
out_ddim
=
paddle_mobile
::
framework
::
make_ddim
({
1
,
32
,
150
,
150
});
auto
output
=
executor
.
Predict
(
input
,
"batch_norm_0.tmp_3"
,
"depthwise_conv2d_0.tmp_0"
,
out_ddim
);
auto
output_ptr
=
output
->
data
<
float
>
();
for
(
int
j
=
0
;
j
<
output
->
numel
();
++
j
)
{
DLOG
<<
" value of output: "
<<
output_ptr
[
j
];
}
return
0
;
}
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