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体验新版 GitCode,发现更多精彩内容 >>
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1c81301e
编写于
5月 11, 2018
作者:
K
Krzysztof Binias
浏览文件
操作
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差异文件
Update activations for MKL-DNN
上级
35e55636
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
41 addition
and
19 deletion
+41
-19
paddle/fluid/operators/activation_mkldnn_op.cc
paddle/fluid/operators/activation_mkldnn_op.cc
+12
-9
paddle/fluid/operators/activation_op.cc
paddle/fluid/operators/activation_op.cc
+21
-4
paddle/fluid/operators/mkldnn_activation_op.h
paddle/fluid/operators/mkldnn_activation_op.h
+8
-6
未找到文件。
paddle/fluid/operators/activation_mkldnn_op.cc
浏览文件 @
1c81301e
...
...
@@ -52,9 +52,11 @@ void eltwise_forward(const ExecContext &ctx, mkldnn::algorithm algorithm,
mkldnn
::
memory
::
format
::
nchw
);
// create memory primitives
auto
src_memory
=
auto
src_memory
=
std
::
make_shared
<
mkldnn
::
memory
>
(
mkldnn
::
memory
({
data_md
,
mkldnn_engine
},
static_cast
<
void
*>
(
const_cast
<
float
*>
(
src_data
)));
static_cast
<
void
*>
(
const_cast
<
float
*>
(
src_data
))));
// save source memory to device context to be referred in backward path
dev_ctx
.
SetBlob
(
"InputX@eltwise_pd"
,
src_memory
);
auto
dst_memory
=
mkldnn
::
memory
({
data_md
,
mkldnn_engine
},
static_cast
<
void
*>
(
const_cast
<
float
*>
(
dst_data
)));
...
...
@@ -69,7 +71,7 @@ void eltwise_forward(const ExecContext &ctx, mkldnn::algorithm algorithm,
forward_desc
,
mkldnn_engine
);
dev_ctx
.
SetBlob
(
key_eltwise_pd
,
forward_pd
);
auto
eltwise
=
mkldnn
::
eltwise_forward
(
*
forward_pd
,
src_memory
,
dst_memory
);
auto
eltwise
=
mkldnn
::
eltwise_forward
(
*
forward_pd
,
*
src_memory
,
dst_memory
);
// push primitive to stream and wait until it's executed
std
::
vector
<
mkldnn
::
primitive
>
pipeline
=
{
eltwise
};
...
...
@@ -83,8 +85,7 @@ void eltwise_grad(const ExecContext &ctx, mkldnn::algorithm algorithm,
const
auto
&
mkldnn_engine
=
dev_ctx
.
GetEngine
();
// get buffers
const
auto
*
x
=
ctx
.
template
Input
<
Tensor
>(
"X"
);
const
auto
*
src
=
x
->
template
data
<
T
>();
const
auto
*
x
=
ctx
.
template
Input
<
Tensor
>(
"Out"
);
auto
*
dout
=
ctx
.
template
Input
<
Tensor
>(
framework
::
GradVarName
(
"Out"
));
const
auto
*
diff_dst
=
dout
->
template
data
<
T
>();
...
...
@@ -103,9 +104,11 @@ void eltwise_grad(const ExecContext &ctx, mkldnn::algorithm algorithm,
:
platform
::
MKLDNNMemDesc
(
src_tz
,
mkldnn
::
memory
::
f32
,
mkldnn
::
memory
::
format
::
nchw
);
// retrieve source memory from device context
const
std
::
shared_ptr
<
void
>
src_memory
=
dev_ctx
.
GetBlob
(
"InputX@eltwise_pd"
);
auto
*
p_src_memory
=
static_cast
<
mkldnn
::
memory
*>
(
src_memory
.
get
());
// create memory primitives
auto
src_memory
=
mkldnn
::
memory
(
{
data_md
,
mkldnn_engine
},
static_cast
<
void
*>
(
const_cast
<
float
*>
(
src
)));
auto
diff_src_memory
=
mkldnn
::
memory
({
data_md
,
mkldnn_engine
},
static_cast
<
void
*>
(
const_cast
<
float
*>
(
diff_src
)));
...
...
@@ -128,8 +131,8 @@ void eltwise_grad(const ExecContext &ctx, mkldnn::algorithm algorithm,
auto
eltwise_bwd_prim_desc
=
mkldnn
::
eltwise_backward
::
primitive_desc
(
backward_desc
,
mkldnn_engine
,
*
p_forward_pd
);
auto
eltwise_bwd
=
mkldnn
::
eltwise_backward
(
eltwise_bwd_prim_desc
,
src_memory
,
diff_dst_memory
,
diff_src_memory
);
auto
eltwise_bwd
=
mkldnn
::
eltwise_backward
(
eltwise_bwd_prim_desc
,
*
p_src_memory
,
diff_dst_memory
,
diff_src_memory
);
// push primitive to stream and wait until it's executed
std
::
vector
<
mkldnn
::
primitive
>
pipeline
=
{
eltwise_bwd
};
...
...
paddle/fluid/operators/activation_op.cc
浏览文件 @
1c81301e
...
...
@@ -458,21 +458,22 @@ namespace ops = paddle::operators;
#define FOR_EACH_INPLACE_OP_FUNCTOR(__macro) \
__macro(Sigmoid, sigmoid); \
__macro(Relu, relu); \
__macro(Exp, exp); \
__macro(Tanh, tanh); \
__macro(Ceil, ceil); \
__macro(Floor, floor); \
__macro(Sqrt, sqrt); \
__macro(SoftRelu, soft_relu); \
__macro(Relu6, relu6); \
__macro(Reciprocal, reciprocal); \
__macro(HardSigmoid, hard_sigmoid);
#define FOR_EACH_MKLDNN_INPLACE_OP_FUNCTOR(__macro) \
__macro(Relu, relu); \
__macro(Tanh, tanh); \
__macro(Sqrt, sqrt);
#define FOR_EACH_OP_FUNCTOR(__macro) \
__macro(LogSigmoid, logsigmoid); \
__macro(SoftShrink, softshrink); \
__macro(Abs, abs); \
__macro(Cos, cos); \
__macro(Sin, sin); \
__macro(Round, round); \
...
...
@@ -490,18 +491,32 @@ namespace ops = paddle::operators;
__macro(Swish, swish); \
__macro(ThresholdedRelu, thresholded_relu);
#define FOR_EACH_MKLDNN_OP_FUNCTOR(__macro) __macro(Abs, abs);
#define REGISTER_INPLACE_ACTIVATION_OP(OP_NAME, KERNEL_TYPE) \
REGISTER_OPERATOR(KERNEL_TYPE, ::paddle::operators::ActivationOp, \
::paddle::operators::OP_NAME##OpMaker, \
::paddle::operators::OP_NAME##GradMaker); \
REGISTER_OPERATOR(KERNEL_TYPE##_grad, ::paddle::operators::ActivationOpGrad)
#define REGISTER_INPLACE_ACTIVATION_MKLDNN_OP(OP_NAME, KERNEL_TYPE) \
REGISTER_OPERATOR(KERNEL_TYPE, ops::ActivationWithMKLDNNOp, \
::paddle::operators::OP_NAME##OpMaker, \
::paddle::operators::OP_NAME##GradMaker); \
REGISTER_OPERATOR(KERNEL_TYPE##_grad, ops::ActivationWithMKLDNNOpGrad)
#define REGISTER_ACTIVATION_OP(OP_NAME, KERNEL_TYPE) \
REGISTER_OPERATOR(KERNEL_TYPE, ::paddle::operators::ActivationOp, \
::paddle::operators::OP_NAME##OpMaker, \
::paddle::framework::DefaultGradOpDescMaker<true>); \
REGISTER_OPERATOR(KERNEL_TYPE##_grad, ::paddle::operators::ActivationOpGrad)
#define REGISTER_ACTIVATION_MKLDNN_OP(OP_NAME, KERNEL_TYPE) \
REGISTER_OPERATOR(KERNEL_TYPE, ops::ActivationWithMKLDNNOp, \
::paddle::operators::OP_NAME##OpMaker, \
::paddle::framework::DefaultGradOpDescMaker<true>); \
REGISTER_OPERATOR(KERNEL_TYPE##_grad, ops::ActivationWithMKLDNNOpGrad)
#define REGISTER_ACTIVATION_CPU_KERNEL(act_type, functor, grad_functor) \
REGISTER_OP_CPU_KERNEL( \
act_type, ops::ActivationKernel<paddle::platform::CPUDeviceContext, \
...
...
@@ -516,5 +531,7 @@ namespace ops = paddle::operators;
ops::grad_functor<double>>);
FOR_EACH_OP_FUNCTOR
(
REGISTER_ACTIVATION_OP
);
FOR_EACH_MKLDNN_OP_FUNCTOR
(
REGISTER_ACTIVATION_MKLDNN_OP
);
FOR_EACH_INPLACE_OP_FUNCTOR
(
REGISTER_INPLACE_ACTIVATION_OP
);
FOR_EACH_MKLDNN_INPLACE_OP_FUNCTOR
(
REGISTER_INPLACE_ACTIVATION_MKLDNN_OP
);
FOR_EACH_KERNEL_FUNCTOR
(
REGISTER_ACTIVATION_CPU_KERNEL
);
paddle/fluid/operators/mkldnn_activation_op.h
浏览文件 @
1c81301e
...
...
@@ -13,6 +13,8 @@ See the License for the specific language governing permissions and
limitations under the License. */
#pragma once
#include <string>
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
...
...
@@ -61,9 +63,9 @@ class MKLDNNActivationGradKernel
};
namespace
{
// NOLINT
framework
::
OpKernelType
GetKernelType
(
const
framework
::
ExecutionContext
&
ctx
,
const
framework
::
OperatorWithKernel
&
oper
)
{
framework
::
OpKernelType
GetKernelType
(
const
framework
::
ExecutionContext
&
ctx
,
const
framework
::
OperatorWithKernel
&
oper
,
const
std
::
string
&
name
)
{
framework
::
LibraryType
library
{
framework
::
LibraryType
::
kPlain
};
#ifdef PADDLE_WITH_MKLDNN
if
(
library
==
framework
::
LibraryType
::
kPlain
&&
...
...
@@ -73,7 +75,7 @@ framework::OpKernelType GetKernelType(
#endif
framework
::
DataLayout
layout
=
framework
::
DataLayout
::
kAnyLayout
;
return
framework
::
OpKernelType
(
framework
::
ToDataType
(
ctx
.
Input
<
framework
::
Tensor
>
(
"X"
)
->
type
()),
framework
::
ToDataType
(
ctx
.
Input
<
framework
::
Tensor
>
(
name
)
->
type
()),
ctx
.
GetPlace
(),
layout
,
library
);
}
}
// anonymous namespace
...
...
@@ -89,7 +91,7 @@ class ActivationWithMKLDNNOp : public framework::OperatorWithKernel {
framework
::
OpKernelType
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
return
GetKernelType
(
ctx
,
*
this
);
return
GetKernelType
(
ctx
,
*
this
,
"X"
);
}
};
...
...
@@ -103,7 +105,7 @@ class ActivationWithMKLDNNOpGrad : public framework::OperatorWithKernel {
framework
::
OpKernelType
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
return
GetKernelType
(
ctx
,
*
this
);
return
GetKernelType
(
ctx
,
*
this
,
"Out"
);
}
};
...
...
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