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体验新版 GitCode,发现更多精彩内容 >>
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9b560740
编写于
11月 17, 2017
作者:
T
Tao Luo
提交者:
GitHub
11月 17, 2017
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差异文件
Merge pull request #5705 from tensor-tang/mkldnn_concat
enable mkldnn_concat layer
上级
ba868854
88feb517
变更
6
隐藏空白更改
内联
并排
Showing
6 changed file
with
393 addition
and
4 deletion
+393
-4
paddle/gserver/layers/MKLDNNConcatLayer.cpp
paddle/gserver/layers/MKLDNNConcatLayer.cpp
+202
-0
paddle/gserver/layers/MKLDNNConcatLayer.h
paddle/gserver/layers/MKLDNNConcatLayer.h
+129
-0
paddle/gserver/layers/MKLDNNLayer.cpp
paddle/gserver/layers/MKLDNNLayer.cpp
+5
-2
paddle/gserver/layers/MKLDNNLayer.h
paddle/gserver/layers/MKLDNNLayer.h
+4
-1
paddle/gserver/tests/test_MKLDNN.cpp
paddle/gserver/tests/test_MKLDNN.cpp
+41
-0
python/paddle/trainer/config_parser.py
python/paddle/trainer/config_parser.py
+12
-1
未找到文件。
paddle/gserver/layers/MKLDNNConcatLayer.cpp
0 → 100644
浏览文件 @
9b560740
/* 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
;
// need change the output channel, so use oc_ instead
// TODO(TJ): change API, use &oc
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 will use ic_ so temporary change as current input's channel
// TODO(TJ): change ic_ as vector then can remove channels_
ic_
=
channels_
[
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
;
}
}
// change back, ic_ always save the input 0 size
ic_
=
channels_
[
0
];
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 will use inVal_
// TODO(TJ): change move inVals_ to MKLDNNLayer ans remove inVal_
inVal_
=
inVals_
[
i
];
resetInGrad
(
inputs
[
i
],
inVals_
[
i
]
->
getPrimitiveDesc
(),
i
);
CHECK_PRIMITIVE_DESC_EQ
(
inputs
[
i
],
inVals_
[
i
]
->
getPrimitiveDesc
());
}
// change back, inVal_ always save the input 0
inVal_
=
inVals_
[
0
];
}
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 @
9b560740
/* 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
paddle/gserver/layers/MKLDNNLayer.cpp
浏览文件 @
9b560740
...
...
@@ -138,8 +138,11 @@ void MKLDNNLayer::backward(const UpdateCallback& callback) {
}
}
void
MKLDNNLayer
::
reshapeInput
(
int
&
batchsize
,
int
&
height
,
int
&
width
)
{
const
Argument
&
input
=
inputLayers_
[
0
]
->
getOutput
();
void
MKLDNNLayer
::
reshapeInput
(
int
&
batchsize
,
int
&
height
,
int
&
width
,
size_t
inputIdx
)
{
const
Argument
&
input
=
inputLayers_
[
inputIdx
]
->
getOutput
();
batchsize
=
input
.
getBatchSize
();
int
h
=
input
.
getFrameHeight
();
int
w
=
input
.
getFrameWidth
();
...
...
paddle/gserver/layers/MKLDNNLayer.h
浏览文件 @
9b560740
...
...
@@ -178,7 +178,10 @@ protected:
/**
* reshape the input image sizes and input batchsize
*/
void
reshapeInput
(
int
&
batchsize
,
int
&
height
,
int
&
width
);
void
reshapeInput
(
int
&
batchsize
,
int
&
height
,
int
&
width
,
size_t
inputIdx
=
0
);
/**
* reshape output image sizes
...
...
paddle/gserver/tests/test_MKLDNN.cpp
浏览文件 @
9b560740
...
...
@@ -313,6 +313,47 @@ TEST(MKLDNNLayer, AddtoLayer) {
testAddtoLayer
({
4
,
12
,
1
,
1
},
3
);
}
static
void
getMKLDNNConcatConfig
(
TestConfig
&
cfg
,
const
std
::
vector
<
testImageDesc
>&
inputs
)
{
CHECK_GE
(
inputs
.
size
(),
2
)
<<
"at least two inputs"
;
int
oc
=
inputs
[
0
].
ic
;
for
(
size_t
i
=
1
;
i
<
inputs
.
size
();
++
i
)
{
CHECK_EQ
(
inputs
[
i
].
bs
,
inputs
[
0
].
bs
);
CHECK_EQ
(
inputs
[
i
].
ih
,
inputs
[
0
].
ih
);
CHECK_EQ
(
inputs
[
i
].
iw
,
inputs
[
0
].
iw
);
oc
+=
inputs
[
i
].
ic
;
}
cfg
.
biasSize
=
0
;
cfg
.
layerConfig
.
set_type
(
"mkldnn_concat"
);
cfg
.
layerConfig
.
set_size
(
oc
*
inputs
[
0
].
ih
*
inputs
[
0
].
iw
);
cfg
.
layerConfig
.
set_active_type
(
"relu"
);
for
(
size_t
i
=
0
;
i
<
inputs
.
size
();
++
i
)
{
std
::
stringstream
ss
;
ss
<<
"layer_"
<<
i
;
cfg
.
inputDefs
.
push_back
(
{
INPUT_DATA
,
ss
.
str
(),
(
size_t
)(
inputs
[
i
].
ic
)
*
inputs
[
i
].
ih
*
inputs
[
i
].
iw
,
0
});
LayerInputConfig
*
input
=
cfg
.
layerConfig
.
add_inputs
();
ImageConfig
*
img_conf
=
input
->
mutable_image_conf
();
img_conf
->
set_channels
(
inputs
[
i
].
ic
);
img_conf
->
set_img_size_y
(
inputs
[
i
].
ih
);
img_conf
->
set_img_size
(
inputs
[
i
].
iw
);
}
}
void
testConcatLayer
(
const
std
::
vector
<
testImageDesc
>&
inputs
)
{
TestConfig
dnnConfig
;
getMKLDNNConcatConfig
(
dnnConfig
,
inputs
);
RUN_MKLDNN_TEST_LAYER
(
dnnConfig
,
"concat"
,
inputs
[
0
])
}
TEST
(
MKLDNNLayer
,
ConcatLayer
)
{
testConcatLayer
({{
64
,
128
,
1
,
1
},
{
64
,
32
,
1
,
1
},
{
64
,
64
,
1
,
1
}});
testConcatLayer
({{
32
,
100
,
8
,
8
},
{
32
,
10
,
8
,
8
}});
}
void
testActivation
(
std
::
string
actType
,
const
testImageDesc
&
pm
)
{
// TODO(TJ): remove me when paddle support elu activation
if
(
actType
==
"mkldnn_elu"
)
{
...
...
python/paddle/trainer/config_parser.py
浏览文件 @
9b560740
...
...
@@ -3506,11 +3506,17 @@ def ExpressionLayer(name, inputs, **xargs):
@
config_layer
(
'concat'
)
class
ConcatenateLayer
(
LayerBase
):
layer_type
=
'concat'
def
__init__
(
self
,
name
,
inputs
,
bias
=
False
,
**
xargs
):
config_assert
(
inputs
,
'inputs cannot be empty'
)
config_assert
(
not
bias
,
'ConcatenateLayer cannot support bias.'
)
use_mkldnn
=
bool
(
int
(
g_command_config_args
.
get
(
"use_mkldnn"
,
0
)))
if
self
.
layer_type
==
"mkldnn_concat"
:
config_assert
(
use_mkldnn
,
"mkldnn_concat only support MKLDNN"
)
self
.
layer_type
=
'mkldnn_concat'
if
use_mkldnn
else
'concat'
super
(
ConcatenateLayer
,
self
).
__init__
(
name
,
'concat'
,
0
,
inputs
=
inputs
,
**
xargs
)
name
,
self
.
layer_type
,
0
,
inputs
=
inputs
,
**
xargs
)
size
=
0
for
input_index
in
xrange
(
len
(
self
.
inputs
)):
assert
self
.
get_input_layer
(
0
).
height
==
self
.
get_input_layer
(
...
...
@@ -3530,6 +3536,11 @@ class ConcatenateLayer(LayerBase):
self
.
set_layer_size
(
size
)
@
config_layer
(
'mkldnn_concat'
)
class
MKLDNNConcatLayer
(
ConcatenateLayer
):
layer_type
=
'mkldnn_concat'
# like concat layer, but each input layer was processed by a Projection.
@
config_layer
(
'concat2'
)
class
ConcatenateLayer2
(
LayerBase
):
...
...
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