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c66b5ce2
编写于
11月 16, 2017
作者:
T
tensor-tang
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add mkldnn concat layer
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2 changed file
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paddle/gserver/layers/MKLDNNConcatLayer.cpp
paddle/gserver/layers/MKLDNNConcatLayer.cpp
+190
-0
paddle/gserver/layers/MKLDNNConcatLayer.h
paddle/gserver/layers/MKLDNNConcatLayer.h
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paddle/gserver/layers/MKLDNNConcatLayer.cpp
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c66b5ce2
/* Copyright (c) 2017 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 "MKLDNNConcatLayer.h"
using
namespace
mkldnn
;
// NOLINT
typedef
memory
::
format
format
;
namespace
paddle
{
REGISTER_LAYER
(
mkldnn_concat
,
MKLDNNConcatLayer
);
bool
MKLDNNConcatLayer
::
init
(
const
LayerMap
&
layerMap
,
const
ParameterMap
&
parameterMap
)
{
if
(
!
MKLDNNLayer
::
init
(
layerMap
,
parameterMap
))
{
return
false
;
}
CHECK_GT
(
inputLayers_
.
size
(),
1UL
);
CHECK
(
!
biasParameter_
);
return
true
;
}
void
MKLDNNConcatLayer
::
reshape
(
int
&
bs
,
int
&
ic
,
int
&
ih
,
int
&
iw
,
int
oc
,
int
&
oh
,
int
&
ow
)
{
reshapeInput
(
bs
,
ih
,
iw
);
ic
=
inputLayers_
[
0
]
->
getSize
()
/
ih
/
iw
;
CHECK_EQ
((
size_t
)
ic
*
ih
*
iw
,
inputLayers_
[
0
]
->
getSize
());
CHECK_EQ
(
inputElemenCnt_
,
(
size_t
)
bs
*
ic
*
ih
*
iw
);
CHECK_GT
(
inputLayers_
.
size
(),
1UL
);
channels_
.
resize
(
inputLayers_
.
size
());
channels_
[
0
]
=
ic
;
oc
=
ic
;
for
(
size_t
i
=
1
;
i
<
inputLayers_
.
size
();
i
++
)
{
int
batchsize
,
height
,
witdh
;
reshapeInput
(
batchsize
,
height
,
witdh
,
i
);
CHECK_EQ
(
bs
,
batchsize
);
CHECK_EQ
(
ih
,
height
);
CHECK_EQ
(
iw
,
witdh
);
channels_
[
i
]
=
inputLayers_
[
i
]
->
getSize
()
/
height
/
witdh
;
CHECK_EQ
((
size_t
)
channels_
[
i
]
*
height
*
witdh
,
inputLayers_
[
i
]
->
getSize
());
oc
+=
channels_
[
i
];
}
oh
=
ih
;
ow
=
iw
;
reshapeOutput
(
oh
,
ow
);
resizeOutput
(
bs
,
oc
*
oh
*
ow
);
}
void
MKLDNNConcatLayer
::
resetFwd
(
std
::
vector
<
primitive
>&
pipeline
,
MKLDNNMatrixPtr
&
in
,
MKLDNNMatrixPtr
&
wgt
,
MKLDNNMatrixPtr
&
bias
,
MKLDNNMatrixPtr
&
out
)
{
resetFwdBuffers
(
inVals_
,
out
);
in
=
inVals_
[
0
];
std
::
shared_ptr
<
concat
::
primitive_desc
>
fwdPD
;
resetFwdPD
(
fwdPD
,
inVals_
,
out
);
resetFwdPipeline
(
pipeline
,
fwdPD
,
inVals_
,
out
);
}
void
MKLDNNConcatLayer
::
resetBwd
(
std
::
vector
<
primitive
>&
pipeline
,
MKLDNNMatrixPtr
&
in
,
MKLDNNMatrixPtr
&
wgt
,
MKLDNNMatrixPtr
&
bias
,
MKLDNNMatrixPtr
&
out
)
{
resetBwdBuffers
(
inGrads_
,
out
);
in
=
inGrads_
[
0
];
resetBwdPipeline
(
pipeline
,
bwds_
,
inGrads_
,
out
);
}
void
MKLDNNConcatLayer
::
resetFwdBuffers
(
std
::
vector
<
MKLDNNMatrixPtr
>&
inputs
,
MKLDNNMatrixPtr
&
out
)
{
inputs
.
resize
(
inputLayers_
.
size
());
bool
has8c
=
false
,
has16c
=
false
,
hasnc
=
false
;
for
(
size_t
i
=
0
;
i
<
inputs
.
size
();
i
++
)
{
resetInValue
(
inputs
[
i
],
nullptr
,
i
);
CHECK
(
inputs
[
i
]);
auto
dm
=
inputs
[
i
]
->
getDims
();
// inputs format can be different, but ndims must equal
CHECK
(
i
==
0
||
dm
.
size
()
==
inputs
[
0
]
->
getDims
().
size
());
CHECK_EQ
(
bs_
,
dm
[
0
]);
CHECK_EQ
(
channels_
[
i
],
dm
[
1
]);
if
(
dm
.
size
()
>
2
)
{
CHECK_EQ
(
ih_
,
dm
[
2
]);
CHECK_EQ
(
iw_
,
dm
[
3
]);
}
if
(
inputs
[
i
]
->
getFormat
()
==
format
::
nc
)
{
hasnc
=
true
;
}
if
(
inputs
[
i
]
->
getFormat
()
==
format
::
nChw8c
)
{
has8c
=
true
;
}
if
(
inputs
[
i
]
->
getFormat
()
==
format
::
nChw16c
)
{
has16c
=
true
;
}
}
format
outFmt
;
if
(
has16c
&&
oc_
%
16
==
0
)
{
outFmt
=
format
::
nChw16c
;
}
else
if
(
has8c
&&
oc_
%
8
==
0
)
{
outFmt
=
format
::
nChw8c
;
}
else
if
(
hasnc
)
{
CHECK
(
oh_
==
1
&&
ow_
==
1
);
outFmt
=
format
::
nc
;
}
else
{
outFmt
=
format
::
nchw
;
}
memory
::
dims
outDims
=
hasnc
?
memory
::
dims
{
bs_
,
oc_
}
:
memory
::
dims
{
bs_
,
oc_
,
oh_
,
ow_
};
auto
outPD
=
MKLDNNMatrix
::
createPrimitiveDesc
(
outDims
,
outFmt
,
engine_
);
resetOutValue
(
out
,
outPD
);
}
void
MKLDNNConcatLayer
::
resetFwdPD
(
std
::
shared_ptr
<
concat
::
primitive_desc
>&
pd
,
std
::
vector
<
MKLDNNMatrixPtr
>&
inputs
,
MKLDNNMatrixPtr
out
)
{
std
::
vector
<
memory
::
primitive_desc
>
srcPDs
;
for
(
size_t
i
=
0
;
i
<
inputs
.
size
();
i
++
)
{
srcPDs
.
push_back
(
inputs
[
i
]
->
getPrimitiveDesc
());
}
CHECK
(
out
);
pd
.
reset
(
new
concat
::
primitive_desc
(
out
->
getMemoryDesc
(),
axis_
,
srcPDs
));
CHECK_PRIMITIVE_DESC_EQ
(
out
,
pd
->
dst_primitive_desc
());
}
void
MKLDNNConcatLayer
::
resetFwdPipeline
(
std
::
vector
<
primitive
>&
pipeline
,
std
::
shared_ptr
<
concat
::
primitive_desc
>&
pd
,
std
::
vector
<
MKLDNNMatrixPtr
>&
inputs
,
MKLDNNMatrixPtr
&
out
)
{
std
::
vector
<
primitive
::
at
>
srcs
;
for
(
size_t
i
=
0
;
i
<
inputs
.
size
();
i
++
)
{
srcs
.
push_back
(
*
(
inputs
[
i
]));
}
fwd_
.
reset
(
new
concat
(
*
pd
,
srcs
,
*
out
));
pipeline
.
push_back
(
*
fwd_
);
}
void
MKLDNNConcatLayer
::
resetBwdBuffers
(
std
::
vector
<
MKLDNNMatrixPtr
>&
inputs
,
MKLDNNMatrixPtr
&
out
)
{
CHECK
(
outVal_
);
resetOutGrad
(
out
,
outVal_
->
getPrimitiveDesc
());
CHECK
(
out
);
inputs
.
resize
(
inputLayers_
.
size
());
for
(
size_t
i
=
0
;
i
<
inputs
.
size
();
i
++
)
{
CHECK
(
inVals_
[
i
]);
resetInGrad
(
inputs
[
i
],
inVals_
[
i
]
->
getPrimitiveDesc
(),
i
);
CHECK_PRIMITIVE_DESC_EQ
(
inputs
[
i
],
inVals_
[
i
]
->
getPrimitiveDesc
());
}
}
void
MKLDNNConcatLayer
::
resetBwdPipeline
(
std
::
vector
<
mkldnn
::
primitive
>&
pipeline
,
std
::
vector
<
std
::
shared_ptr
<
mkldnn
::
primitive
>>&
prims
,
std
::
vector
<
MKLDNNMatrixPtr
>&
inputs
,
MKLDNNMatrixPtr
&
out
)
{
// reset the backward primitives
memory
::
dims
offsets
=
{
0
,
0
,
0
,
0
};
prims
.
resize
(
inputs
.
size
());
CHECK_EQ
(
inputs
.
size
(),
channels_
.
size
());
for
(
size_t
i
=
0
;
i
<
inputs
.
size
();
i
++
)
{
auto
viewPD
=
view
::
primitive_desc
(
out
->
getPrimitiveDesc
(),
inputs
[
i
]
->
getDims
(),
offsets
);
auto
bwdPD
=
reorder
::
primitive_desc
(
viewPD
.
dst_primitive_desc
(),
inputs
[
i
]
->
getPrimitiveDesc
());
prims
[
i
].
reset
(
new
reorder
(
bwdPD
,
*
out
,
*
(
inputs
[
i
])));
offsets
[
axis_
]
+=
channels_
[
i
];
// push to pipeline
pipeline
.
push_back
(
*
prims
[
i
]);
}
}
}
// namespace paddle
paddle/gserver/layers/MKLDNNConcatLayer.h
0 → 100644
浏览文件 @
c66b5ce2
/* Copyright (c) 2017 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. */
#pragma once
#include "MKLDNNLayer.h"
#include "mkldnn.hpp"
namespace
paddle
{
/**
* @brief A subclass of MKLDNNLayer Concatenate layer.
*
* The config file api is mkldnn_concat
*/
class
MKLDNNConcatLayer
:
public
MKLDNNLayer
{
protected:
std
::
vector
<
MKLDNNMatrixPtr
>
inVals_
;
std
::
vector
<
MKLDNNMatrixPtr
>
inGrads_
;
std
::
vector
<
std
::
shared_ptr
<
mkldnn
::
primitive
>>
bwds_
;
// input channel numbers
std
::
vector
<
int
>
channels_
;
// concat_dimension in MKLDNN
// if axis_ == 0, concat batchsize
// if axis_ == 1, concat channel (default)
int
axis_
;
public:
explicit
MKLDNNConcatLayer
(
const
LayerConfig
&
config
)
:
MKLDNNLayer
(
config
),
axis_
(
1
)
{}
~
MKLDNNConcatLayer
()
{}
bool
init
(
const
LayerMap
&
layerMap
,
const
ParameterMap
&
parameterMap
)
override
;
void
reshape
(
int
&
bs
,
int
&
ic
,
int
&
ih
,
int
&
iw
,
int
oc
,
int
&
oh
,
int
&
ow
)
override
;
void
resetFwd
(
std
::
vector
<
mkldnn
::
primitive
>&
pipeline
,
MKLDNNMatrixPtr
&
in
,
MKLDNNMatrixPtr
&
wgt
,
MKLDNNMatrixPtr
&
bias
,
MKLDNNMatrixPtr
&
out
)
override
;
void
resetBwd
(
std
::
vector
<
mkldnn
::
primitive
>&
pipeline
,
MKLDNNMatrixPtr
&
in
,
MKLDNNMatrixPtr
&
wgt
,
MKLDNNMatrixPtr
&
bias
,
MKLDNNMatrixPtr
&
out
)
override
;
void
printSizeInfo
()
override
{
CHECK_EQ
(
channels_
.
size
(),
inputLayers_
.
size
());
for
(
size_t
i
=
0
;
i
<
channels_
.
size
();
++
i
)
{
VLOG
(
MKLDNN_SIZES
)
<<
"Input "
<<
i
<<
", "
<<
inputLayers_
[
i
]
->
getName
()
<<
": "
<<
bs_
<<
", "
<<
channels_
[
i
]
<<
", "
<<
ih_
<<
", "
<<
iw_
;
}
VLOG
(
MKLDNN_SIZES
)
<<
"Output: "
<<
bs_
<<
", "
<<
oc_
<<
", "
<<
oh_
<<
", "
<<
ow_
;
}
void
printValueFormat
()
override
{
for
(
size_t
i
=
0
;
i
<
inVals_
.
size
();
++
i
)
{
VLOG
(
MKLDNN_FMTS
)
<<
"Input "
<<
i
<<
inputLayers_
[
i
]
->
getName
()
<<
": "
<<
inVals_
[
i
]
->
getFormat
()
<<
" >>>"
;
}
if
(
outVal_
)
{
VLOG
(
MKLDNN_FMTS
)
<<
outVal_
->
getFormat
()
<<
" >>> "
;
}
if
(
extOutVal_
)
{
VLOG
(
MKLDNN_FMTS
)
<<
extOutVal_
->
getFormat
();
}
}
void
printGradFormat
()
override
{
if
(
extOutGrad_
)
{
VLOG
(
MKLDNN_FMTS
)
<<
extOutGrad_
->
getFormat
();
}
if
(
outGrad_
)
{
VLOG
(
MKLDNN_FMTS
)
<<
outGrad_
->
getFormat
()
<<
" <<< "
;
}
for
(
size_t
i
=
0
;
i
<
inGrads_
.
size
();
++
i
)
{
VLOG
(
MKLDNN_FMTS
)
<<
"Input "
<<
i
<<
inputLayers_
[
i
]
->
getName
()
<<
": "
<<
inGrads_
[
i
]
->
getFormat
()
<<
"<<<"
;
}
}
protected:
/**
* Forward functions: reset buffers(inputs, output, bias),
* reset primitive descriptor,
* reset pipeline.
*/
void
resetFwdBuffers
(
std
::
vector
<
MKLDNNMatrixPtr
>&
inputs
,
MKLDNNMatrixPtr
&
out
);
void
resetFwdPD
(
std
::
shared_ptr
<
mkldnn
::
concat
::
primitive_desc
>&
pd
,
std
::
vector
<
MKLDNNMatrixPtr
>&
inputs
,
MKLDNNMatrixPtr
out
);
void
resetFwdPipeline
(
std
::
vector
<
mkldnn
::
primitive
>&
pipeline
,
std
::
shared_ptr
<
mkldnn
::
concat
::
primitive_desc
>&
pd
,
std
::
vector
<
MKLDNNMatrixPtr
>&
inputs
,
MKLDNNMatrixPtr
&
out
);
/**
* Backward functions: reset buffers(inputs, output, bias)
* reset primitives and pipeline
*/
void
resetBwdBuffers
(
std
::
vector
<
MKLDNNMatrixPtr
>&
inputs
,
MKLDNNMatrixPtr
&
out
);
void
resetBwdPipeline
(
std
::
vector
<
mkldnn
::
primitive
>&
pipeline
,
std
::
vector
<
std
::
shared_ptr
<
mkldnn
::
primitive
>>&
prims
,
std
::
vector
<
MKLDNNMatrixPtr
>&
inputs
,
MKLDNNMatrixPtr
&
out
);
};
}
// namespace paddle
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