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体验新版 GitCode,发现更多精彩内容 >>
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698071cc
编写于
10月 13, 2017
作者:
T
tensor-tang
浏览文件
操作
浏览文件
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电子邮件补丁
差异文件
share mkldnn output value data if next layer is cpu device
上级
6715beaa
变更
5
隐藏空白更改
内联
并排
Showing
5 changed file
with
19 addition
and
16 deletion
+19
-16
paddle/gserver/layers/MKLDNNConvLayer.cpp
paddle/gserver/layers/MKLDNNConvLayer.cpp
+10
-5
paddle/gserver/layers/MKLDNNFcLayer.cpp
paddle/gserver/layers/MKLDNNFcLayer.cpp
+2
-2
paddle/gserver/layers/MKLDNNLayer.h
paddle/gserver/layers/MKLDNNLayer.h
+1
-5
paddle/gserver/layers/MKLDNNPoolLayer.cpp
paddle/gserver/layers/MKLDNNPoolLayer.cpp
+4
-2
paddle/gserver/tests/MKLDNNTester.cpp
paddle/gserver/tests/MKLDNNTester.cpp
+2
-2
未找到文件。
paddle/gserver/layers/MKLDNNConvLayer.cpp
浏览文件 @
698071cc
...
...
@@ -243,7 +243,7 @@ void MKLDNNConvLayer::resetFwdPipeline(
void
MKLDNNConvLayer
::
resetInValue
(
std
::
shared_ptr
<
conv_fwd
::
primitive_desc
>&
pd
,
MKLDNNMatrixPtr
&
in
)
{
const
MatrixPtr
&
inMat
=
inputLayers_
[
0
]
->
getOutput
().
value
;
const
MatrixPtr
&
inMat
=
inputLayers_
[
0
]
->
getOutput
Value
()
;
in
=
MKLDNNMatrix
::
create
(
inMat
,
pd
->
src_primitive_desc
());
// create buffer and reorder if input value do not match
...
...
@@ -308,15 +308,20 @@ void MKLDNNConvLayer::resetOutValue(
const
MatrixPtr
&
cpuOut
=
getOutput
(
CPU_DEVICE
).
value
;
memory
::
dims
outDims
=
memory
::
dims
{
bs_
,
oc_
,
oh_
,
ow_
};
cpuOutVal_
=
MKLDNNMatrix
::
create
(
cpuOut
,
outDims
,
format
::
nchw
,
engine_
);
if
(
cpuOutVal_
->
getPrimitiveDesc
()
!=
out
->
getPrimitiveDesc
())
{
if
(
cpuOutVal_
->
getPrimitiveDesc
()
!=
pd
->
dst_primitive_desc
())
{
out
=
MKLDNNMatrix
::
create
(
nullptr
,
pd
->
dst_primitive_desc
());
cvtOutVal_
=
MKLDNNMatrix
::
createReorder
(
out
,
cpuOutVal_
);
CHECK
(
cvtOutVal_
)
<<
"should not be empt
r
y"
;
CHECK
(
cvtOutVal_
)
<<
"should not be empty"
;
}
else
{
// CPU output share the same data of MKLDNN output
cpuOut
->
setData
(
out
->
getData
());
cpuOutVal_
=
out
;
}
// when output is cpu device, change the mkldnn output value and make they
// share the same data. Then if next layer use inputlayer->getOuputValue()
// to achieve the input value, it will get the right data.
output_
.
value
=
std
::
dynamic_pointer_cast
<
Matrix
>
(
cpuOutVal_
);
return
;
}
output_
.
value
=
std
::
dynamic_pointer_cast
<
Matrix
>
(
out
);
}
void
MKLDNNConvLayer
::
resetBwdWgtPD
(
...
...
paddle/gserver/layers/MKLDNNFcLayer.cpp
浏览文件 @
698071cc
...
...
@@ -180,10 +180,10 @@ void MKLDNNFcLayer::resetWgtBiasValue(MKLDNNMatrixPtr& wgt,
void
MKLDNNFcLayer
::
resetOutValue
(
MKLDNNMatrixPtr
&
out
)
{
out
=
MKLDNNMatrix
::
create
(
output_
.
value
,
{
bs_
,
oc_
},
format
::
nc
,
engine_
);
if
(
!
outputIsOnlyMKLDNN
())
{
// fc cpu output value do not need create convert
// just share point
// fc cpu output value do not need create convert, just share data
getOutput
(
CPU_DEVICE
).
value
->
setData
(
out
->
getData
());
}
output_
.
value
=
std
::
dynamic_pointer_cast
<
Matrix
>
(
out
);
}
void
MKLDNNFcLayer
::
resetFwdPD
(
std
::
shared_ptr
<
fc_fwd
::
primitive_desc
>&
pd
,
...
...
paddle/gserver/layers/MKLDNNLayer.h
浏览文件 @
698071cc
...
...
@@ -127,10 +127,6 @@ public:
pipelineFwd_
.
clear
();
reshape
(
bs_
,
ic_
,
ih_
,
iw_
,
oc_
,
oh_
,
ow_
);
resetFwd
(
pipelineFwd_
,
inVal_
,
wgtVal_
,
biasVal_
,
outVal_
);
if
(
outVal_
)
{
// change original output value to mkldnn output value
output_
.
value
=
std
::
dynamic_pointer_cast
<
Matrix
>
(
outVal_
);
}
convertWeightsFromPaddle
();
needResetBwd_
=
true
;
}
...
...
@@ -264,7 +260,7 @@ protected:
*/
virtual
void
resetOutGrad
(
MKLDNNMatrixPtr
&
out
,
mkldnn
::
memory
::
primitive_desc
pd
)
{
CHECK
(
outputIsOnlyMKLDNN
())
<<
"
only
support mixed with other device yet"
;
CHECK
(
outputIsOnlyMKLDNN
())
<<
"
do not
support mixed with other device yet"
;
mergeGrad_
=
nullptr
;
out
=
MKLDNNMatrix
::
create
(
output_
.
grad
,
pd
);
if
(
outputMap_
.
size
()
<=
1
)
{
...
...
paddle/gserver/layers/MKLDNNPoolLayer.cpp
浏览文件 @
698071cc
...
...
@@ -142,14 +142,16 @@ void MKLDNNPoolLayer::resetOutValue(MKLDNNMatrixPtr& out) {
const
MatrixPtr
&
cpuOut
=
getOutput
(
CPU_DEVICE
).
value
;
cpuOutVal_
=
MKLDNNMatrix
::
create
(
cpuOut
,
outDims
,
format
::
nchw
,
engine_
);
if
(
cpuOutVal_
->
getPrimitiveDesc
()
!=
out
->
getPrimitiveDesc
())
{
out
=
MKLDNNMatrix
::
create
(
nullptr
,
out
->
getPrimitiveDesc
());
cvtOutVal_
=
MKLDNNMatrix
::
createReorder
(
out
,
cpuOutVal_
);
CHECK
(
cvtOutVal_
)
<<
"should not be emptry"
;
}
else
{
// CPU output share the same data of MKLDNN output
cpuOut
->
setData
(
out
->
getData
());
cpuOutVal_
=
out
;
}
output_
.
value
=
std
::
dynamic_pointer_cast
<
Matrix
>
(
cpuOutVal_
);
return
;
}
output_
.
value
=
std
::
dynamic_pointer_cast
<
Matrix
>
(
outVal_
);
}
void
MKLDNNPoolLayer
::
resetFwdPD
(
std
::
shared_ptr
<
pool_fwd
::
primitive_desc
>&
pd
,
...
...
paddle/gserver/tests/MKLDNNTester.cpp
浏览文件 @
698071cc
...
...
@@ -124,8 +124,8 @@ void MKLDNNTester::randomTopDiffs() {
void
MKLDNNTester
::
checkForward
()
{
VLOG
(
MKLDNN_ALL
)
<<
"Check Forward"
;
printTopDatas
();
double
delta
=
compareMatrix
(
dnnLayer_
->
getOutput
(
CPU_DEVICE
).
value
,
refLayer_
->
getOutputValue
());
double
delta
=
compareMatrix
(
dnnLayer_
->
getOutputValue
(),
refLayer_
->
getOutputValue
());
EXPECT_LE
(
fabs
(
delta
),
eps_
);
}
...
...
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