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35bab4f2
编写于
1月 16, 2020
作者:
A
Adam
提交者:
Tao Luo
1月 16, 2020
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电子邮件补丁
差异文件
Add caching mechanizm to requantize_mkldnn_op (#22267)
上级
fe88aeb2
变更
1
显示空白变更内容
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Showing
1 changed file
with
56 addition
and
36 deletion
+56
-36
paddle/fluid/operators/mkldnn/requantize_mkldnn_op.cc
paddle/fluid/operators/mkldnn/requantize_mkldnn_op.cc
+56
-36
未找到文件。
paddle/fluid/operators/mkldnn/requantize_mkldnn_op.cc
浏览文件 @
35bab4f2
...
@@ -21,14 +21,10 @@ limitations under the License. */
...
@@ -21,14 +21,10 @@ limitations under the License. */
namespace
paddle
{
namespace
paddle
{
namespace
operators
{
namespace
operators
{
using
mkldnn
::
memory
;
using
dnnl
::
memory
;
using
mkldnn
::
primitive
;
using
dnnl
::
reorder
;
using
mkldnn
::
reorder
;
using
platform
::
to_void_cast
;
using
platform
::
to_void_cast
;
using
Tensor
=
framework
::
Tensor
;
using
Tensor
=
framework
::
Tensor
;
using
framework
::
DataLayout
;
using
mkldnn
::
stream
;
using
platform
::
GetMKLDNNFormat
;
template
<
typename
T
>
template
<
typename
T
>
class
ReQuantOpKernel
:
public
framework
::
OpKernel
<
T
>
{
class
ReQuantOpKernel
:
public
framework
::
OpKernel
<
T
>
{
...
@@ -42,42 +38,66 @@ class ReQuantOpKernel : public framework::OpKernel<T> {
...
@@ -42,42 +38,66 @@ class ReQuantOpKernel : public framework::OpKernel<T> {
ctx
.
template
device_context
<
platform
::
MKLDNNDeviceContext
>();
ctx
.
template
device_context
<
platform
::
MKLDNNDeviceContext
>();
const
auto
&
engine
=
dev_ctx
.
GetEngine
();
const
auto
&
engine
=
dev_ctx
.
GetEngine
();
std
::
vector
<
primitive
>
pipeline
;
auto
src_tz
=
paddle
::
framework
::
vectorize
(
input
->
dims
());
auto
src_tz
=
paddle
::
framework
::
vectorize
<
int64_t
>
(
input
->
dims
());
auto
dst_tz
=
paddle
::
framework
::
vectorize
<
int64_t
>
(
output
->
dims
());
std
::
string
key
=
platform
::
CreateKey
(
src_tz
,
scale_in
,
scale_out
,
mkldnn
::
memory
::
data_type
src_dt
=
ctx
.
OutputName
(
"Output"
));
paddle
::
framework
::
ToMKLDNNDataType
(
input
->
type
());
const
std
::
string
key_prim
=
key
+
"@reorder_p"
;
mkldnn
::
memory
::
data_type
dst_dt
=
src_dt
;
const
std
::
string
key_src_mem
=
key
+
"@src_mem"
;
MKLDNNMemoryFormat
src_fmt
=
MKLDNNMemoryFormat
::
nhwc
;
const
std
::
string
key_dst_mem
=
key
+
"@dst_mem"
;
MKLDNNMemoryFormat
dst_fmt
=
MKLDNNMemoryFormat
::
nhwc
;
std
::
shared_ptr
<
dnnl
::
memory
>
src_memory
;
std
::
shared_ptr
<
dnnl
::
memory
>
dst_memory
;
std
::
shared_ptr
<
reorder
>
reorder_p
;
reorder_p
=
std
::
static_pointer_cast
<
reorder
>
(
dev_ctx
.
GetBlob
(
key_prim
));
const
T
*
input_data
=
input
->
data
<
T
>
();
const
T
*
input_data
=
input
->
data
<
T
>
();
T
*
output_data
=
output
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
T
*
output_data
=
output
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
float
scale_shift
=
scale_out
/
scale_in
;
mkldnn
::
primitive_attr
attri
;
if
(
reorder_p
==
nullptr
)
{
dnnl
::
primitive_attr
attri
;
int
mask
=
0
;
int
mask
=
0
;
float
scale_shift
=
scale_out
/
scale_in
;
attri
.
set_output_scales
(
mask
,
{
scale_shift
});
attri
.
set_output_scales
(
mask
,
{
scale_shift
});
auto
src_md
=
platform
::
MKLDNNMemDesc
({
src_tz
},
src_dt
,
src_fmt
);
auto
dst_tz
=
paddle
::
framework
::
vectorize
(
output
->
dims
());
auto
src_memory
=
std
::
make_shared
<
mkldnn
::
memory
>
(
dnnl
::
memory
::
data_type
src_dt
=
src_md
,
engine
,
to_void_cast
<
T
>
(
input_data
));
paddle
::
framework
::
ToMKLDNNDataType
(
input
->
type
());
dnnl
::
memory
::
data_type
dst_dt
=
src_dt
;
auto
dst_md
=
platform
::
MKLDNNMemDesc
({
dst_tz
},
dst_dt
,
dst_fmt
);
auto
dst_memory
=
auto
src_md
=
mkldnn
::
memory
(
dst_md
,
engine
,
to_void_cast
<
T
>
(
output_data
));
platform
::
MKLDNNMemDesc
({
src_tz
},
src_dt
,
MKLDNNMemoryFormat
::
nhwc
);
src_memory
=
std
::
make_shared
<
dnnl
::
memory
>
(
src_md
,
engine
,
auto
reorder_pd
=
std
::
shared_ptr
<
reorder
::
primitive_desc
>
(
to_void_cast
<
T
>
(
input_data
));
new
reorder
::
primitive_desc
(
*
src_memory
,
dst_memory
,
attri
));
auto
dst_md
=
auto
reorder_p
=
std
::
shared_ptr
<
reorder
>
(
new
reorder
(
*
reorder_pd
));
platform
::
MKLDNNMemDesc
({
dst_tz
},
dst_dt
,
MKLDNNMemoryFormat
::
nhwc
);
dst_memory
=
std
::
make_shared
<
dnnl
::
memory
>
(
dst_md
,
engine
,
to_void_cast
<
T
>
(
output_data
));
auto
reorder_pd
=
reorder
::
primitive_desc
(
*
src_memory
,
*
dst_memory
,
attri
);
reorder_p
=
std
::
make_shared
<
reorder
>
(
reorder_pd
);
dev_ctx
.
SetBlob
(
key_prim
,
reorder_p
);
dev_ctx
.
SetBlob
(
key_src_mem
,
src_memory
);
dev_ctx
.
SetBlob
(
key_dst_mem
,
dst_memory
);
}
else
{
src_memory
=
std
::
static_pointer_cast
<
dnnl
::
memory
>
(
dev_ctx
.
GetBlob
(
key_src_mem
));
src_memory
->
set_data_handle
(
to_void_cast
<
T
>
(
input_data
));
dst_memory
=
std
::
static_pointer_cast
<
dnnl
::
memory
>
(
dev_ctx
.
GetBlob
(
key_dst_mem
));
dst_memory
->
set_data_handle
(
output_data
);
}
mkldnn
::
stream
astream
(
engine
);
dnnl
::
stream
astream
(
engine
);
reorder_p
->
execute
(
astream
,
*
src_memory
,
dst_memory
);
reorder_p
->
execute
(
astream
,
*
src_memory
,
*
dst_memory
);
astream
.
wait
();
astream
.
wait
();
output
->
set_layout
(
DataLayout
::
kMKLDNN
);
output
->
set_layout
(
framework
::
DataLayout
::
kMKLDNN
);
output
->
set_format
(
GetMKLDNNFormat
(
dst_memory
));
output
->
set_format
(
platform
::
GetMKLDNNFormat
(
*
dst_memory
));
}
}
};
};
...
...
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