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d541ab39
编写于
9月 04, 2018
作者:
Y
yangfei
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电子邮件补丁
差异文件
imp fusion_bn_add_relu op in resnet
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5
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5 changed file
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src/operators/fusion_conv_bn_add_relu_op.cpp
src/operators/fusion_conv_bn_add_relu_op.cpp
+61
-0
src/operators/fusion_conv_bn_add_relu_op.h
src/operators/fusion_conv_bn_add_relu_op.h
+125
-0
src/operators/kernel/arm/conv_bn_add_relu_kernel.cpp
src/operators/kernel/arm/conv_bn_add_relu_kernel.cpp
+66
-0
src/operators/kernel/central-arm-func/conv_bn_add_relu_arm_func.h
...ators/kernel/central-arm-func/conv_bn_add_relu_arm_func.h
+146
-0
src/operators/kernel/conv_bn_add_relu_kernel.h
src/operators/kernel/conv_bn_add_relu_kernel.h
+45
-0
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src/operators/fusion_conv_bn_add_relu_op.cpp
0 → 100644
浏览文件 @
d541ab39
/* 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. */
#ifdef FUSION_CONVBNADDRELU_OP
#include "operators/fusion_conv_bn_add_relu_op.h"
#include "operators/math/conv_func.h"
namespace
paddle_mobile
{
namespace
operators
{
template
<
typename
Dtype
,
typename
T
>
void
FusionConvBNAddReluOp
<
Dtype
,
T
>::
InferShape
()
const
{
auto
in_dims
=
this
->
param_
.
Input
()
->
dims
();
auto
filter_dims
=
this
->
param_
.
Filter
()
->
dims
();
const
std
::
vector
<
int
>
&
strides
=
this
->
param_
.
Strides
();
std
::
vector
<
int
>
paddings
=
this
->
param_
.
Paddings
();
int
groups
=
this
->
param_
.
Groups
();
std
::
vector
<
int
>
dilations
=
this
->
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
(
math
::
ConvOutputSize
(
in_dims
[
i
+
2
],
filter_dims
[
i
+
2
],
dilations
[
i
],
paddings
[
i
],
strides
[
i
]));
}
framework
::
DDim
ddim
=
framework
::
make_ddim
(
output_shape
);
this
->
param_
.
Output
()
->
Resize
(
ddim
);
}
}
// namespace operators
}
// namespace paddle_mobile
namespace
ops
=
paddle_mobile
::
operators
;
#ifdef PADDLE_MOBILE_CPU
REGISTER_OPERATOR_CPU
(
fusion_conv_bn_add_relu
,
ops
::
FusionConvBNAddReluOp
);
#endif
#ifdef PADDLE_MOBILE_MALI_GPU
#endif
#ifdef PADDLE_MOBILE_FPGA
REGISTER_OPERATOR_FPGA
(
fusion_conv_bn_add_relu
,
ops
::
FusionConvBNAddReluOp
);
#endif
#endif
src/operators/fusion_conv_bn_add_relu_op.h
0 → 100644
浏览文件 @
d541ab39
/* 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. */
#ifdef FUSION_CONVBNADDRELU_OP
#pragma once
#include <string>
#include <vector>
#include "framework/operator.h"
#include "framework/program/program-optimize/fusion_op_register.h"
#include "op_param.h"
#include "operators/kernel/conv_bn_add_relu_kernel.h"
namespace
paddle_mobile
{
namespace
operators
{
using
std
::
string
;
using
std
::
vector
;
class
FusionConvBNAddReluMatcher
:
public
framework
::
FusionOpMatcher
{
public:
FusionConvBNAddReluMatcher
()
{
node_
=
framework
::
Node
(
G_OP_TYPE_CONV
);
node_
>
std
::
make_shared
<
framework
::
Node
>
(
G_OP_TYPE_BATCHNORM
)
>
std
::
make_shared
<
framework
::
Node
>
(
G_OP_TYPE_ELEMENTWISE_ADD
)
>
std
::
make_shared
<
framework
::
Node
>
(
G_OP_TYPE_RELU
);
}
void
FolderNodes
(
framework
::
Node
*
node
,
std
::
vector
<
std
::
shared_ptr
<
framework
::
Node
>>
*
removed_nodes
)
{
node
->
Folder
(
node_
.
Depth
(),
Type
(),
{{
G_OP_TYPE_ELEMENTWISE_ADD
,
{{
"Y"
,
"Y"
},{
"X"
,
"X"
}}},
{
G_OP_TYPE_BATCHNORM
,
{{
"Scale"
,
"Scale"
},
{
"Mean"
,
"Mean"
},
{
"Bias"
,
"Bias"
},
{
"Variance"
,
"Variance"
},
{
"Y"
,
"BNY"
}}}},
removed_nodes
);
}
std
::
string
Type
()
{
return
G_OP_TYPE_FUSION_CONV_BN_ADD_RELU
;
}
std
::
vector
<
std
::
pair
<
int
,
std
::
string
>>
NeedCheck
()
{
DLOG
<<
" conv bn add relu check add X "
;
return
{{
2
,
"Y"
},
{
2
,
"X"
}};
}
};
template
<
typename
DeviceType
,
typename
T
>
class
FusionConvBNAddReluOp
:
public
framework
::
OperatorWithKernel
<
DeviceType
,
FusionConvBNAddReluParam
<
DeviceType
>
,
operators
::
ConvBNAddReluKernel
<
DeviceType
,
T
>>
{
public:
FusionConvBNAddReluOp
(
const
string
&
type
,
const
VariableNameMap
&
inputs
,
const
VariableNameMap
&
outputs
,
const
framework
::
AttributeMap
&
attrs
,
std
::
shared_ptr
<
framework
::
Scope
>
scope
)
:
framework
::
OperatorWithKernel
<
DeviceType
,
FusionConvBNAddReluParam
<
DeviceType
>
,
operators
::
ConvBNAddReluKernel
<
DeviceType
,
T
>>
(
type
,
inputs
,
outputs
,
attrs
,
scope
)
{}
using
framework
::
OperatorWithKernel
<
DeviceType
,
FusionConvBNAddReluParam
<
DeviceType
>
,
operators
::
ConvBNAddReluKernel
<
DeviceType
,
T
>>::
OperatorWithKernel
;
void
InferShape
()
const
override
;
protected:
};
#ifdef PADDLE_MOBILE_CPU
#ifndef FUSION_CONV_BN_ADD_RELU_REGISTER
static
framework
::
FusionOpRegistrar
fusion_conv_bn_add_relu_registrar
(
new
FusionConvBNAddReluMatcher
());
#define FUSION_CONV_BN_ADD_RELU_REGISTER
#endif
#endif
#ifdef PADDLE_MOBILE_MALI_GPU
#ifndef FUSION_CONV_BN_ADD_RELU_REGISTER
static
framework
::
FusionOpRegistrar
fusion_conv_bn_add_relu_registrar
(
new
FusionConvBNAddReluMatcher
());
#define FUSION_CONV_BN_ADD_RELU_REGISTER
#endif
#endif
#ifdef PADDLE_MOBILE_FPGA
#ifndef FUSION_CONV_BN_ADD_RELU_REGISTER
static
framework
::
FusionOpRegistrar
fusion_conv_bn_add_relu_registrar
(
new
FusionConvBNAddReluMatcher
());
#define FUSION_CONV_BN_ADD_RELU_REGISTER
#endif
#endif
}
// namespace operators
}
// namespace paddle_mobile
#ifdef PADDLE_MOBILE_CPU
USE_OP_CPU
(
fusion_conv_bn_add_relu
);
#endif
#ifdef PADDLE_MOBILE_MALI_GPU
#endif
#ifdef PADDLE_MOBILE_FPGA
USE_OP_FPGA
(
fusion_conv_bn_add_relu
);
#endif
#endif
src/operators/kernel/arm/conv_bn_add_relu_kernel.cpp
0 → 100644
浏览文件 @
d541ab39
/* 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. */
#ifdef FUSION_CONVBNADDRELU_OP
#include "operators/kernel/conv_bn_add_relu_kernel.h"
#include "operators/kernel/central-arm-func/conv_bn_add_relu_arm_func.h"
namespace
paddle_mobile
{
namespace
operators
{
template
<
>
bool
ConvBNAddReluKernel
<
CPU
,
float
>::
Init
(
FusionConvBNAddReluParam
<
CPU
>
*
param
)
{
const
Tensor
*
mean
=
param
->
InputMean
();
const
Tensor
*
variance
=
param
->
InputVariance
();
const
Tensor
*
scale
=
param
->
InputScale
();
const
Tensor
*
bias
=
param
->
InputBias
();
const
float
epsilon
=
param
->
Epsilon
();
auto
mean_ptr
=
mean
->
data
<
float
>
();
auto
variance_ptr
=
variance
->
data
<
float
>
();
auto
scale_ptr
=
scale
->
data
<
float
>
();
auto
bias_ptr
=
bias
->
data
<
float
>
();
const
int
C
=
mean
->
numel
();
float
inv_std_ptr
[
C
];
for
(
int
i
=
0
;
i
<
C
;
i
++
)
{
inv_std_ptr
[
i
]
=
1
/
static_cast
<
float
>
(
pow
((
variance_ptr
[
i
]
+
epsilon
),
0.5
));
}
Tensor
*
new_scale
=
new
Tensor
();
Tensor
*
new_bias
=
new
Tensor
();
auto
new_scale_ptr
=
new_scale
->
mutable_data
<
float
>
({
C
});
auto
new_bias_ptr
=
new_bias
->
mutable_data
<
float
>
({
C
});
for
(
int
i
=
0
;
i
<
C
;
i
++
)
{
new_scale_ptr
[
i
]
=
inv_std_ptr
[
i
]
*
scale_ptr
[
i
];
new_bias_ptr
[
i
]
=
bias_ptr
[
i
]
-
mean_ptr
[
i
]
*
inv_std_ptr
[
i
]
*
scale_ptr
[
i
];
}
param
->
SetNewScale
(
new_scale
);
param
->
SetNewBias
(
new_bias
);
return
true
;
}
template
<
>
void
ConvBNAddReluKernel
<
CPU
,
float
>::
Compute
(
const
FusionConvBNAddReluParam
<
CPU
>
&
param
)
const
{
ConvBNAddReluCompute
<
float
>
(
param
);
}
template
class
ConvBNAddReluKernel
<
CPU
,
float
>;
}
// namespace operators
}
// namespace paddle_mobile
#endif
src/operators/kernel/central-arm-func/conv_bn_add_relu_arm_func.h
0 → 100644
浏览文件 @
d541ab39
/* 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. */
#ifdef FUSION_CONVBNADDRELU_OP
#pragma once
#include <vector>
#include "operators/math/depthwise_conv_3x3.h"
#include "operators/math/im2col.h"
#include "operators/math/math_function.h"
#include "operators/math/vol2col.h"
#include "operators/op_param.h"
namespace
paddle_mobile
{
namespace
operators
{
void
ConvBNAddReluBasic
(
const
FusionConvBNAddReluParam
<
CPU
>
&
param
)
{
const
Tensor
*
input
=
param
.
Input
();
Tensor
filter
=
*
param
.
Filter
();
Tensor
new_bias
=
*
param
.
NewBias
();
Tensor
new_scale
=
*
param
.
NewScale
();
Tensor
*
output
=
param
.
Output
();
Tensor
*
bias1
=
param
.
Bias
();
int
groups
=
param
.
Groups
();
DLOG
<<
"yangfei2"
;
DLOG
<<
bias1
->
dims
();
std
::
vector
<
int
>
strides
=
param
.
Strides
();
std
::
vector
<
int
>
paddings
=
param
.
Paddings
();
std
::
vector
<
int
>
dilations
=
param
.
Dilations
();
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
=
math
::
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
);
}
framework
::
DDim
input_shape
=
framework
::
slice_ddim
(
input
->
dims
(),
1
,
static_cast
<
int
>
(
input
->
dims
().
size
()));
framework
::
DDim
filter_matrix_shape
=
{
filter
.
dims
()[
0
],
filter
.
numel
()
/
filter
.
dims
()[
0
]};
filter
.
Resize
(
filter_matrix_shape
);
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
);
Tensor
bias_batch
=
bias1
->
Slice
(
i
,
i
+
1
).
Resize
(
output_matrix_shape
);
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
);
Tensor
bias_data
=
bias_batch
.
Slice
(
g
*
out_step
,
(
g
+
1
)
*
out_step
);
math
::
matmulWithBnAdd
<
float
>
(
filter_slice
,
false
,
col_matrix
,
false
,
static_cast
<
float
>
(
1
),
&
out_slice
,
static_cast
<
float
>
(
1
),
true
,
&
new_scale
,
&
new_bias
,
g
,
bias_data
.
data
<
float
>
());
}
}
}
template
<
typename
P
>
void
ConvBNAddReluCompute
(
const
FusionConvBNAddReluParam
<
CPU
>
&
param
)
{
Tensor
Bias
;
Bias
.
mutable_data
<
float
>
({
param
.
Groups
()});
if
(
param
.
Groups
()
==
param
.
Input
()
->
dims
()[
1
]
&&
param
.
Input
()
->
dims
()[
1
]
==
param
.
Output
()
->
dims
()[
1
]
&&
param
.
Filter
()
->
dims
()[
2
]
==
param
.
Filter
()
->
dims
()[
3
]
&&
param
.
Filter
()
->
dims
()[
2
]
==
3
&&
param
.
Strides
()[
0
]
==
1
)
{
math
::
DepthwiseConvAddBNRelu3x3s1p1
(
param
.
Input
(),
param
.
Filter
(),
param
.
Output
(),
param
.
NewScale
(),
param
.
NewBias
(),
true
);
}
else
if
(
param
.
Groups
()
==
param
.
Input
()
->
dims
()[
1
]
&&
param
.
Input
()
->
dims
()[
1
]
==
param
.
Output
()
->
dims
()[
1
]
&&
param
.
Filter
()
->
dims
()[
2
]
==
param
.
Filter
()
->
dims
()[
3
]
&&
param
.
Filter
()
->
dims
()[
2
]
==
3
&&
param
.
Strides
()[
0
]
==
2
)
{
// math::DepthwiseConvAddBNRelu3x3s2p1(param.Input(), param.Filter(),
// param.Output(), param.NewScale(),
// param.NewBias(), 1);
math
::
DepthwiseConvAddBNRelu3x3s2p1v2
(
param
.
Input
(),
param
.
Filter
(),
param
.
Output
(),
param
.
NewScale
(),
param
.
NewBias
(),
true
);
}
else
{
ConvBNAddReluBasic
(
param
);
}
}
}
// namespace operators
}
// namespace paddle_mobile
#endif
src/operators/kernel/conv_bn_add_relu_kernel.h
0 → 100644
浏览文件 @
d541ab39
/* 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
#ifdef FUSION_CONVBNADDRELU_OP
#include <vector>
#include "framework/ddim.h"
#include "framework/operator.h"
#include "operators/math/conv_func.h"
#include "operators/math/im2col.h"
#include "operators/math/math_function.h"
#include "operators/math/vol2col.h"
#include "operators/op_param.h"
namespace
paddle_mobile
{
namespace
operators
{
using
framework
::
DDim
;
using
framework
::
OpKernelBase
;
template
<
typename
DeviceType
,
typename
T
>
class
ConvBNAddReluKernel
:
public
OpKernelBase
<
DeviceType
,
FusionConvBNAddReluParam
<
DeviceType
>>
{
public:
void
Compute
(
const
FusionConvBNAddReluParam
<
DeviceType
>
&
param
)
const
;
bool
Init
(
FusionConvBNAddReluParam
<
DeviceType
>
*
param
);
};
}
// namespace operators
}
// namespace paddle_mobile
#endif
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