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体验新版 GitCode,发现更多精彩内容 >>
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db2b6b65
编写于
5月 14, 2020
作者:
P
pawelpiotrowicz
提交者:
GitHub
5月 14, 2020
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
Hide globals & redesign restore PR (#24279)
test=develop
上级
4a105f80
变更
10
隐藏空白更改
内联
并排
Showing
10 changed file
with
136 addition
and
90 deletion
+136
-90
paddle/fluid/framework/data_layout_transform.cc
paddle/fluid/framework/data_layout_transform.cc
+4
-3
paddle/fluid/framework/data_transform.cc
paddle/fluid/framework/data_transform.cc
+2
-1
paddle/fluid/framework/executor.cc
paddle/fluid/framework/executor.cc
+2
-1
paddle/fluid/framework/operator.cc
paddle/fluid/framework/operator.cc
+2
-2
paddle/fluid/inference/api/analysis_predictor.cc
paddle/fluid/inference/api/analysis_predictor.cc
+10
-9
paddle/fluid/operators/controlflow/fetch_op.cc
paddle/fluid/operators/controlflow/fetch_op.cc
+4
-4
paddle/fluid/operators/mkldnn/conv_mkldnn_op.cc
paddle/fluid/operators/mkldnn/conv_mkldnn_op.cc
+2
-2
paddle/fluid/platform/device_context.cc
paddle/fluid/platform/device_context.cc
+45
-43
paddle/fluid/platform/device_context.h
paddle/fluid/platform/device_context.h
+61
-21
paddle/fluid/platform/mkldnn_reuse.h
paddle/fluid/platform/mkldnn_reuse.h
+4
-4
未找到文件。
paddle/fluid/framework/data_layout_transform.cc
浏览文件 @
db2b6b65
...
...
@@ -124,9 +124,10 @@ void TransDataLayoutFromMKLDNN(const OpKernelType& kernel_type_for_var,
"TransDataLayoutFromMKLDNN only supports transform from MKLDNN to "
"non-MKLDNN"
);
innerTransDataLayoutFromMKLDNN
(
in_layout
,
paddle
::
platform
::
get_cur_paddle_data_layout
(),
in
,
out
,
place
);
innerTransDataLayoutFromMKLDNN
(
in_layout
,
paddle
::
platform
::
MKLDNNDeviceContext
::
tls
().
get_cur_paddle_data_layout
(),
in
,
out
,
place
);
}
void
innerTransDataLayoutFromMKLDNN
(
DataLayout
in_layout
,
DataLayout
out_layout
,
...
...
paddle/fluid/framework/data_transform.cc
浏览文件 @
db2b6b65
...
...
@@ -59,7 +59,8 @@ void TransformData(const OpKernelType &expected_kernel_type,
// For NHWC data we need reshape of tensors as MKL-DNN
// is expecting NHWC dims description order
platform
::
MatchShapeToLayout
(
&
out
,
lin
,
lout
);
paddle
::
platform
::
set_cur_paddle_data_layout
(
lin
);
paddle
::
platform
::
MKLDNNDeviceContext
::
tls
().
set_cur_paddle_data_layout
(
lin
);
out
.
set_layout
(
DataLayout
::
kMKLDNN
);
out
.
set_format
(
out_format
);
}
else
{
...
...
paddle/fluid/framework/executor.cc
浏览文件 @
db2b6b65
...
...
@@ -89,7 +89,8 @@ Executor::~Executor() {
platform
::
MKLDNNDeviceContext
*
dev_ctx
=
(
platform
::
MKLDNNDeviceContext
*
)
pool
.
Get
(
place_
);
dev_ctx
->
ResetBlobMap
();
platform
::
set_cur_paddle_data_layout
(
paddle
::
framework
::
DataLayout
::
kNCHW
);
platform
::
MKLDNNDeviceContext
::
tls
().
set_cur_paddle_data_layout
(
paddle
::
framework
::
DataLayout
::
kNCHW
);
}
#endif
}
...
...
paddle/fluid/framework/operator.cc
浏览文件 @
db2b6b65
...
...
@@ -1155,8 +1155,8 @@ Scope* OperatorWithKernel::PrepareData(
if
((
tensor_in
->
layout
()
==
DataLayout
::
kMKLDNN
)
&&
(
var
->
IsType
<
LoDTensor
>
()
==
true
)
&&
(
expected_kernel_key
.
data_layout_
!=
DataLayout
::
kMKLDNN
)
&&
(
paddle
::
platform
::
get_cur_paddle_data_layout
()
==
DataLayout
::
kNHWC
))
{
(
paddle
::
platform
::
MKLDNNDeviceContext
::
tls
()
.
get_cur_paddle_data_layout
()
==
DataLayout
::
kNHWC
))
{
// Mixed execution : MKL-DNN and GPU is not supported!
if
(
!
new_scope
)
{
new_scope
=
&
scope
.
NewScope
();
...
...
paddle/fluid/inference/api/analysis_predictor.cc
浏览文件 @
db2b6b65
...
...
@@ -244,13 +244,14 @@ bool AnalysisPredictor::PrepareExecutor() {
void
AnalysisPredictor
::
MkldnnPreSet
(
const
std
::
vector
<
PaddleTensor
>
&
inputs
)
{
#ifdef PADDLE_WITH_MKLDNN
VLOG
(
2
)
<<
"AnalysisPredictor::Run get_cur_mkldnn_session_id="
<<
platform
::
get_cur_mkldnn_session_id
();
<<
platform
::
MKLDNNDeviceContext
::
tls
().
get_cur_mkldnn_session_id
();
// In cache clearing mode.
if
(
config_
.
mkldnn_cache_capacity_
>
0
)
{
VLOG
(
2
)
<<
"In mkldnn cache clear mode."
;
platform
::
set_cur_mkldnn_session_id
(
platform
::
kMKLDNNSessionID_CacheClearing
);
platform
::
set_cur_input_shape_cache_capacity
(
platform
::
MKLDNNDeviceContext
::
tls
().
set_cur_mkldnn_session_id
(
platform
::
MKLDNNDeviceContextThreadLocals
::
kMKLDNNSessionID_CacheClearing
);
platform
::
MKLDNNDeviceContext
::
tls
().
set_cur_input_shape_cache_capacity
(
config_
.
mkldnn_cache_capacity_
);
// Set current_input_shape for caching dynamic shape.
std
::
stringstream
ss
;
...
...
@@ -260,7 +261,7 @@ void AnalysisPredictor::MkldnnPreSet(const std::vector<PaddleTensor> &inputs) {
}
}
VLOG
(
2
)
<<
"Set input shape="
<<
ss
.
str
();
platform
::
set_cur_input_shape_str
(
ss
.
str
());
platform
::
MKLDNNDeviceContext
::
tls
().
set_cur_input_shape_str
(
ss
.
str
());
}
#endif
}
...
...
@@ -277,10 +278,10 @@ void AnalysisPredictor::MkldnnPostReset() {
CHECK_LE
(
shape_blob_size
,
static_cast
<
size_t
>
(
config_
.
mkldnn_cache_capacity_
));
}
paddle
::
platform
::
set_cur_mkldnn_session_id
(
platform
::
kMKLDNNSessionID_Default
);
platform
::
set_cur_input_shape_cache_capacity
(
0
);
platform
::
set_cur_input_shape_str
(
""
);
paddle
::
platform
::
MKLDNNDeviceContext
::
tls
().
set_cur_mkldnn_session_id
(
platform
::
MKLDNNDeviceContextThreadLocals
::
kMKLDNNSessionID_Default
);
platform
::
MKLDNNDeviceContext
::
tls
().
set_cur_input_shape_cache_capacity
(
0
);
platform
::
MKLDNNDeviceContext
::
tls
().
set_cur_input_shape_str
(
""
);
}
#endif
}
...
...
paddle/fluid/operators/controlflow/fetch_op.cc
浏览文件 @
db2b6b65
...
...
@@ -34,10 +34,10 @@ static void DataCopy(const framework::LoDTensor &src_item,
// Convert to desired Paddle layout, apart from grads of filter
// as params are not a subject to paddle's data_format
framework
::
innerTransDataLayoutFromMKLDNN
(
src_item
.
layout
(),
fetch_var_name
==
framework
::
GradVarName
(
"Filter"
)
?
framework
::
DataLayout
::
kNCHW
:
paddle
::
platform
::
get_cur_paddle_data_layout
(),
src_item
.
layout
(),
fetch_var_name
==
framework
::
GradVarName
(
"Filter"
)
?
framework
::
DataLayout
::
kNCHW
:
paddle
::
platform
::
MKLDNNDeviceContext
::
tls
()
.
get_cur_paddle_data_layout
(),
src_item
,
&
out
,
platform
::
CPUPlace
());
TensorCopySync
(
out
,
platform
::
CPUPlace
(),
dst_item
);
}
else
{
...
...
paddle/fluid/operators/mkldnn/conv_mkldnn_op.cc
浏览文件 @
db2b6b65
...
...
@@ -446,8 +446,8 @@ class ConvMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
// of conv int8 mkl-dnn. Once conv fp32 and conv int8
// are merged/unified, this will disappear
std
::
string
key_tid
=
""
;
if
(
platform
::
get_cur_mkldnn_session_id
()
==
platform
::
kMKLDNNSessionID_Default
)
{
if
(
platform
::
MKLDNNDeviceContext
::
tls
().
get_cur_mkldnn_session_id
()
==
platform
::
MKLDNNDeviceContextThreadLocals
::
kMKLDNNSessionID_Default
)
{
key_tid
=
"-t:"
+
platform
::
ThreadIDasStr
();
}
...
...
paddle/fluid/platform/device_context.cc
浏览文件 @
db2b6b65
...
...
@@ -375,36 +375,37 @@ MKLDNNDeviceContext::MKLDNNDeviceContext(CPUPlace place)
p_mutex_
.
reset
(
new
std
::
mutex
());
}
namespace
{
// Current mkldnn session id.
thread_local
size_t
cur_mkldnn_session_id
=
kMKLDNNSessionID_Default
;
// Current data input shape string.
// - For fixed-shape, it's a null string in default.
// - For dynamic-shape, it's user specific.
thread_local
std
::
string
cur_input_shape_str
=
""
;
// the cache capacity of different input shapes for MKLDNN.
// Default 1 means fixed input shape, not dynamic shape.
thread_local
int
cur_input_shape_cache_capacity
=
1
;
// Recently registered data_format. This is needed to
// know for converting MKL-DNN Tensor to non MKL-DNN
thread_local
paddle
::
framework
::
DataLayout
cur_paddle_data_layout
=
paddle
::
framework
::
DataLayout
::
kNCHW
;
}
// namespace
void
set_cur_mkldnn_session_id
(
size_t
sid
)
{
cur_mkldnn_session_id
=
sid
;
}
size_t
get_cur_mkldnn_session_id
(
void
)
{
return
cur_mkldnn_session_id
;
}
void
set_cur_input_shape_str
(
std
::
string
input_shape_str
)
{
MKLDNNDeviceContextThreadLocals
::
Body
::
Body
()
{
cur_mkldnn_session_id
=
kMKLDNNSessionID_Default
;
cur_input_shape_str
=
""
;
cur_input_shape_cache_capacity
=
1
;
cur_paddle_data_layout
=
paddle
::
framework
::
DataLayout
::
kNCHW
;
}
void
MKLDNNDeviceContextThreadLocals
::
Body
::
set_cur_mkldnn_session_id
(
size_t
sid
)
{
cur_mkldnn_session_id
=
sid
;
}
size_t
MKLDNNDeviceContextThreadLocals
::
Body
::
get_cur_mkldnn_session_id
(
void
)
{
return
cur_mkldnn_session_id
;
}
void
MKLDNNDeviceContextThreadLocals
::
Body
::
set_cur_input_shape_str
(
std
::
string
input_shape_str
)
{
cur_input_shape_str
=
input_shape_str
;
}
void
set_cur_input_shape_cache_capacity
(
int
input_shape_cache_capacity
)
{
void
MKLDNNDeviceContextThreadLocals
::
Body
::
set_cur_input_shape_cache_capacity
(
int
input_shape_cache_capacity
)
{
cur_input_shape_cache_capacity
=
input_shape_cache_capacity
;
}
void
set_cur_paddle_data_layout
(
framework
::
DataLayout
dl
)
{
void
MKLDNNDeviceContextThreadLocals
::
Body
::
set_cur_paddle_data_layout
(
framework
::
DataLayout
dl
)
{
cur_paddle_data_layout
=
dl
;
}
framework
::
DataLayout
get_cur_paddle_data_layout
(
void
)
{
framework
::
DataLayout
MKLDNNDeviceContextThreadLocals
::
Body
::
get_cur_paddle_data_layout
(
void
)
{
return
cur_paddle_data_layout
;
}
...
...
@@ -414,32 +415,32 @@ void MKLDNNDeviceContext::ResetBlobMap() const {
}
size_t
MKLDNNDeviceContext
::
GetShapeBlobSize
()
const
{
std
::
lock_guard
<
std
::
mutex
>
lock
(
*
p_mutex_
);
std
::
lock_guard
<
decltype
(
*
p_mutex_
)
>
lock
(
*
p_mutex_
);
BlobMap
*
pMap
=
p_blobmap_
.
get
();
auto
map_it
=
pMap
->
find
(
cur_mkldnn_session_id
);
auto
map_it
=
pMap
->
find
(
tls
().
cur_mkldnn_session_id
);
if
(
map_it
==
pMap
->
end
())
{
LOG
(
FATAL
)
<<
"MKLDNNDeviceContext don't find cur_mkldnn_session_id : "
<<
cur_mkldnn_session_id
;
<<
tls
().
cur_mkldnn_session_id
;
}
return
map_it
->
second
->
size
();
}
void
MKLDNNDeviceContext
::
SetBlob
(
const
std
::
string
&
name
,
std
::
shared_ptr
<
void
>
data
)
const
{
BlobPtr_t
<
void
>
data
)
const
{
BlobMap
*
pMap
=
p_blobmap_
.
get
();
std
::
shared_ptr
<
ShapeBlob
>
sBlob
=
nullptr
;
std
::
shared_ptr
<
KeyBlob
>
pBlob
=
nullptr
;
BlobPtr_t
<
ShapeBlob
>
sBlob
=
nullptr
;
BlobPtr_t
<
KeyBlob
>
pBlob
=
nullptr
;
int
sid
=
platform
::
get_cur_mkldnn_session_id
();
int
sid
=
tls
().
get_cur_mkldnn_session_id
();
std
::
lock_guard
<
std
::
mutex
>
lock
(
*
p_mutex_
);
std
::
lock_guard
<
decltype
(
*
p_mutex_
)
>
lock
(
*
p_mutex_
);
// Find ShapeBlob for current mkldnn session id.
auto
map_it
=
pMap
->
find
(
sid
);
if
(
map_it
==
pMap
->
end
())
{
// 1st time to set blob in current thread
sBlob
=
std
::
shared_ptr
<
ShapeBlob
>
(
new
ShapeBlob
()
);
sBlob
=
std
::
make_shared
<
ShapeBlob
>
(
);
(
*
pMap
)[
sid
]
=
sBlob
;
VLOG
(
2
)
<<
"SetBlob: sid="
<<
sid
<<
", add new sid
\n
"
;
}
else
{
...
...
@@ -447,21 +448,22 @@ void MKLDNNDeviceContext::SetBlob(const std::string& name,
}
// Find KeyBlob for current input shape
auto
key_it
=
sBlob
->
find
(
cur_input_shape_str
);
auto
key_it
=
sBlob
->
find
(
tls
().
cur_input_shape_str
);
if
(
key_it
==
sBlob
->
end
())
{
// In cache clearing mode, cur_input_shape_cache_capacity defines
// max pblob capacity
if
((
static_cast
<
size_t
>
(
sid
)
==
kMKLDNNSessionID_CacheClearing
)
&&
if
((
static_cast
<
size_t
>
(
sid
)
==
MKLDNNDeviceContextThreadLocals
::
kMKLDNNSessionID_CacheClearing
)
&&
sBlob
->
size
()
&&
(
sBlob
->
size
()
>=
static_cast
<
size_t
>
(
cur_input_shape_cache_capacity
)))
{
static_cast
<
size_t
>
(
tls
().
cur_input_shape_cache_capacity
)))
{
VLOG
(
2
)
<<
"sid="
<<
sid
<<
", remove all blobs of shape: "
<<
sBlob
->
begin
()
->
first
;
sBlob
->
erase
(
sBlob
->
begin
()
->
first
);
}
pBlob
=
std
::
shared_ptr
<
KeyBlob
>
(
new
KeyBlob
()
);
(
*
sBlob
)[
cur_input_shape_str
]
=
pBlob
;
pBlob
=
std
::
make_shared
<
KeyBlob
>
(
);
(
*
sBlob
)[
tls
().
cur_input_shape_str
]
=
pBlob
;
}
else
{
pBlob
=
key_it
->
second
;
}
...
...
@@ -478,15 +480,15 @@ void MKLDNNDeviceContext::SetBlob(const std::string& name,
return
;
}
std
::
shared_ptr
<
void
>
MKLDNNDeviceContext
::
GetBlob
(
MKLDNNDeviceContext
::
BlobPtr_t
<
void
>
MKLDNNDeviceContext
::
GetBlob
(
const
std
::
string
&
name
)
const
{
BlobMap
*
pMap
=
p_blobmap_
.
get
();
std
::
shared_ptr
<
ShapeBlob
>
sBlob
=
nullptr
;
std
::
shared_ptr
<
KeyBlob
>
pBlob
=
nullptr
;
BlobPtr_t
<
ShapeBlob
>
sBlob
=
nullptr
;
BlobPtr_t
<
KeyBlob
>
pBlob
=
nullptr
;
int
sid
=
platform
::
get_cur_mkldnn_session_id
();
int
sid
=
tls
().
get_cur_mkldnn_session_id
();
std
::
lock_guard
<
std
::
mutex
>
lock
(
*
p_mutex_
);
std
::
lock_guard
<
decltype
(
*
p_mutex_
)
>
lock
(
*
p_mutex_
);
// Find ShapeBlob for current mkldnn session id firstly
auto
map_it
=
pMap
->
find
(
sid
);
...
...
@@ -497,9 +499,9 @@ std::shared_ptr<void> MKLDNNDeviceContext::GetBlob(
sBlob
=
map_it
->
second
;
// Find KeyBlob for current input shape secondly
auto
sBlob_it
=
sBlob
->
find
(
cur_input_shape_str
);
auto
sBlob_it
=
sBlob
->
find
(
tls
().
cur_input_shape_str
);
if
(
sBlob_it
==
sBlob
->
end
())
{
VLOG
(
2
)
<<
"GetBlob: sid="
<<
cur_input_shape_str
VLOG
(
2
)
<<
"GetBlob: sid="
<<
tls
().
cur_input_shape_str
<<
", miss input_shape_str
\n
"
;
return
nullptr
;
}
...
...
paddle/fluid/platform/device_context.h
浏览文件 @
db2b6b65
...
...
@@ -421,30 +421,66 @@ struct DefaultDeviceContextType<platform::CUDAPinnedPlace> {
#endif
#ifdef PADDLE_WITH_MKLDNN
// Following three maps are used to cache MKLDNN primitives.
// There relations are:
// - BlobMap = Map<cur_thread_id, ShapeBlob>
// - ShapeBlob = Map<cur_input_shape_str, KeyBlob>
// - KeyBlob = Map<blob_name, blob>
// Where:
using
KeyBlob
=
std
::
unordered_map
<
std
::
string
,
std
::
shared_ptr
<
void
>>
;
using
ShapeBlob
=
std
::
unordered_map
<
std
::
string
,
std
::
shared_ptr
<
KeyBlob
>>
;
using
BlobMap
=
std
::
unordered_map
<
int
,
std
::
shared_ptr
<
ShapeBlob
>>
;
// default mkldnn session id
constexpr
size_t
kMKLDNNSessionID_Default
=
0
;
// mkldnn session id for cache clearing mode
constexpr
size_t
kMKLDNNSessionID_CacheClearing
=
-
1
;
void
set_cur_mkldnn_session_id
(
size_t
);
size_t
get_cur_mkldnn_session_id
(
void
);
void
set_cur_input_shape_str
(
std
::
string
input_shape_str
);
void
set_cur_input_shape_cache_capacity
(
int
input_shape_cache_capacity
);
void
set_cur_paddle_data_layout
(
framework
::
DataLayout
);
framework
::
DataLayout
get_cur_paddle_data_layout
(
void
);
class
MKLDNNDeviceContextThreadLocals
{
// default mkldnn session id
typedef
MKLDNNDeviceContextThreadLocals
self
;
struct
Body
{
size_t
cur_mkldnn_session_id
;
// Current data input shape string.
// - For fixed-shape, it's a null string in default.
// - For dynamic-shape, it's user specific.
std
::
string
cur_input_shape_str
;
// the cache capacity of different input shapes for MKLDNN.
// Default 1 means fixed input shape, not dynamic shape.
int
cur_input_shape_cache_capacity
;
// Recently registered data_format. This is needed to
// know for converting MKL-DNN Tensor to non MKL-DNN
paddle
::
framework
::
DataLayout
cur_paddle_data_layout
;
Body
();
void
set_cur_mkldnn_session_id
(
size_t
sid
);
size_t
get_cur_mkldnn_session_id
(
void
);
void
set_cur_input_shape_str
(
std
::
string
input_shape_str
);
void
set_cur_input_shape_cache_capacity
(
int
input_shape_cache_capacity
);
void
set_cur_paddle_data_layout
(
framework
::
DataLayout
dl
);
framework
::
DataLayout
get_cur_paddle_data_layout
(
void
);
};
MKLDNNDeviceContextThreadLocals
()
=
default
;
MKLDNNDeviceContextThreadLocals
(
const
MKLDNNDeviceContextThreadLocals
&
c
)
=
delete
;
public:
// default mkldnn session id
static
constexpr
size_t
kMKLDNNSessionID_Default
=
0
;
// mkldnn session id for cache clearing mode
static
constexpr
size_t
kMKLDNNSessionID_CacheClearing
=
-
1
;
static
Body
&
fetch
()
{
thread_local
Body
b
;
return
b
;
}
};
class
MKLDNNDeviceContext
:
public
CPUDeviceContext
{
public:
template
<
class
T
>
using
BlobPtr_t
=
std
::
shared_ptr
<
T
>
;
template
<
class
P1
,
class
P2
>
using
umap_value_smart_t
=
std
::
unordered_map
<
P1
,
BlobPtr_t
<
P2
>>
;
template
<
class
T
>
using
umap_key_string_t
=
umap_value_smart_t
<
std
::
string
,
T
>
;
// Following three maps are used to cache MKLDNN primitives.
// There relations are:
// - BlobMap = Map<cur_thread_id, ShapeBlob>
// - ShapeBlob = Map<cur_input_shape_str, KeyBlob>
// - KeyBlob = Map<blob_name, blob>
using
KeyBlob
=
umap_key_string_t
<
void
>
;
using
ShapeBlob
=
umap_key_string_t
<
KeyBlob
>
;
using
BlobMap
=
umap_value_smart_t
<
int
,
ShapeBlob
>
;
explicit
MKLDNNDeviceContext
(
CPUPlace
place
);
/* \brief Get the active engine */
...
...
@@ -462,6 +498,10 @@ class MKLDNNDeviceContext : public CPUDeviceContext {
// Find a saved blob. Return nullptr if not found
std
::
shared_ptr
<
void
>
GetBlob
(
const
std
::
string
&
name
)
const
;
static
auto
tls
()
->
decltype
(
MKLDNNDeviceContextThreadLocals
::
fetch
())
{
return
MKLDNNDeviceContextThreadLocals
::
fetch
();
}
private:
mkldnn
::
engine
engine_
;
std
::
shared_ptr
<
BlobMap
>
p_blobmap_
;
...
...
paddle/fluid/platform/mkldnn_reuse.h
浏览文件 @
db2b6b65
...
...
@@ -42,8 +42,8 @@ class MKLDNNHandlerT {
key_common_
(
base_key
),
fwd_pd_
(
nullptr
),
bwd_pd_
(
nullptr
)
{
if
(
platform
::
get_cur_mkldnn_session_id
()
!=
platform
::
kMKLDNNSessionID_Default
)
{
if
(
platform
::
MKLDNNDeviceContext
::
tls
().
get_cur_mkldnn_session_id
()
!=
platform
::
MKLDNNDeviceContextThreadLocals
::
kMKLDNNSessionID_Default
)
{
key_
=
key_common_
;
}
else
{
key_
=
key_common_
+
"-t:"
+
ThreadIDasStr
();
...
...
@@ -177,8 +177,8 @@ class MKLDNNHandler {
MKLDNNHandler
(
const
MKLDNNDeviceContext
&
dev_ctx
,
mkldnn
::
engine
engine
,
const
std
::
string
&
base_key
)
:
dev_ctx_
(
dev_ctx
),
engine_
(
engine
),
key_common_
(
base_key
)
{
if
(
platform
::
get_cur_mkldnn_session_id
()
!=
platform
::
kMKLDNNSessionID_Default
)
{
if
(
platform
::
MKLDNNDeviceContext
::
tls
().
get_cur_mkldnn_session_id
()
!=
platform
::
MKLDNNDeviceContextThreadLocals
::
kMKLDNNSessionID_Default
)
{
key_
=
key_common_
;
}
else
{
key_
=
key_common_
+
"-t:"
+
ThreadIDasStr
();
...
...
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