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体验新版 GitCode,发现更多精彩内容 >>
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提交
1ba592d6
编写于
10月 20, 2022
作者:
H
HongyuJia
提交者:
GitHub
10月 20, 2022
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电子邮件补丁
差异文件
opt mkldnn selection judgement (#47217)
上级
ac666538
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
18 addition
and
26 deletion
+18
-26
paddle/fluid/framework/operator.cc
paddle/fluid/framework/operator.cc
+14
-20
paddle/fluid/imperative/prepared_operator.cc
paddle/fluid/imperative/prepared_operator.cc
+4
-6
未找到文件。
paddle/fluid/framework/operator.cc
浏览文件 @
1ba592d6
...
...
@@ -1388,14 +1388,12 @@ bool OperatorWithKernel::SupportsKernelType(
#endif
// NOTE(jiahongyu): If MKLDNN can be used, the function SupportsKernelType needs
// to check whether current op supports MKLDNN kernel. There are three
// statements in if condition: The first statement checks whether library_type_
// are changed by other high priority backends; the second checks whether this
// op has specific implementation; the third checks whether mkldnn kernel can be
// used.
// to check whether current op supports MKLDNN kernel. There are two statements
// in if condition:
// 1. Whether this op has specific implementation;
// 2. Whether mkldnn kernel can be used.
#ifdef PADDLE_WITH_MKLDNN
if
(
kernel_type
.
library_type_
==
framework
::
LibraryType
::
kPlain
&&
!
paddle
::
platform
::
in_mkldnn_white_list
(
type_
)
&&
if
(
!
paddle
::
platform
::
in_mkldnn_white_list
(
type_
)
&&
this
->
CanMKLDNNBeUsed
(
exe_ctx
,
kernel_type
.
data_type_
))
{
auto
tmp_kernel_type
=
kernel_type
;
tmp_kernel_type
.
library_type_
=
framework
::
LibraryType
::
kMKLDNN
;
...
...
@@ -1571,13 +1569,11 @@ void OperatorWithKernel::RunImpl(const Scope& scope,
// NOTE(jiahongyu): The registered MKLDNN kernel have library_type =
// LibraryType::kMKLDNN and data_layout_ = DataLayout::kMKLDNN. But the default
// values are kPlain, so we need to modify the library_type and data_layout_
// here. There are three statements in if condition: The first statement checks
// whether library_type_ are changed by other high priority backends; the second
// checks whether this op has specific implementation; the third checks whether
// mkldnn kernel can be used.
// here. There are two statements in if condition:
// 1. Whether this op has specific implementation;
// 2. Whether mkldnn kernel can be used.
#ifdef PADDLE_WITH_MKLDNN
if
(
kernel_type_
->
library_type_
==
framework
::
LibraryType
::
kPlain
&&
!
paddle
::
platform
::
in_mkldnn_white_list
(
type_
)
&&
if
(
!
paddle
::
platform
::
in_mkldnn_white_list
(
type_
)
&&
this
->
CanMKLDNNBeUsed
(
exe_ctx
,
kernel_type_
->
data_type_
))
{
kernel_type_
->
library_type_
=
framework
::
LibraryType
::
kMKLDNN
;
kernel_type_
->
data_layout_
=
framework
::
DataLayout
::
kMKLDNN
;
...
...
@@ -1814,14 +1810,12 @@ OpKernelType OperatorWithKernel::InnerGetExpectedKernelType(
// NOTE(jiahongyu): PADDLE_WITH_MKLDNN codes are moved outside function
// GetExpectedKernelType, so that if MKLDNN can be used, the library_type_ and
// data_layout_ of expected_kernel_key need to be adjusted. There are three
// statements in if condition: The first statement checks whether library_type_
// are changed by other high priority backends; the second checks whether this
// op has specific implementation; the third checks whether mkldnn kernel can be
// used.
// data_layout_ of expected_kernel_key need to be adjusted. There are two
// statements in if condition:
// 1. Whether this op has specific implementation;
// 2. Whether mkldnn kernel can be used.
#ifdef PADDLE_WITH_MKLDNN
if
(
expected_kernel_key
.
library_type_
==
framework
::
LibraryType
::
kPlain
&&
!
paddle
::
platform
::
in_mkldnn_white_list
(
type_
)
&&
if
(
!
paddle
::
platform
::
in_mkldnn_white_list
(
type_
)
&&
this
->
CanMKLDNNBeUsed
(
ctx
,
expected_kernel_key
.
data_type_
))
{
expected_kernel_key
.
library_type_
=
framework
::
LibraryType
::
kMKLDNN
;
expected_kernel_key
.
data_layout_
=
framework
::
DataLayout
::
kMKLDNN
;
...
...
paddle/fluid/imperative/prepared_operator.cc
浏览文件 @
1ba592d6
...
...
@@ -192,13 +192,11 @@ PreparedOp PrepareImpl(
// NOTE(jiahongyu): The registered MKLDNN kernel have library_type =
// LibraryType::kMKLDNN and data_layout_ = DataLayout::kMKLDNN. But the default
// values are kPlain, so we need to modify the library_type and data_layout_
// here. There are three statements in if condition: The first statement checks
// whether library_type_ are changed by other high priority backends; the second
// checks whether this op has specific implementation; the third checks whether
// mkldnn kernel can be used.
// here. There are two statements in if condition:
// 1. Whether this op has specific implementation;
// 2. Whether mkldnn kernel can be used.
#ifdef PADDLE_WITH_MKLDNN
if
(
expected_kernel_key
.
library_type_
==
framework
::
LibraryType
::
kPlain
&&
!
paddle
::
platform
::
in_mkldnn_white_list
(
op
.
Type
())
&&
if
(
!
paddle
::
platform
::
in_mkldnn_white_list
(
op
.
Type
())
&&
op
.
CanMKLDNNBeUsed
(
dygraph_exe_ctx
,
expected_kernel_key
.
data_type_
))
{
expected_kernel_key
.
library_type_
=
framework
::
LibraryType
::
kMKLDNN
;
expected_kernel_key
.
data_layout_
=
framework
::
DataLayout
::
kMKLDNN
;
...
...
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