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5c39519e
编写于
9月 21, 2020
作者:
H
huzhiqiang
提交者:
GitHub
9月 21, 2020
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电子邮件补丁
差异文件
[Framework] Add method for specifying initial size of `workspace_` (#4378)
上级
cda2e2d9
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
63 addition
and
3 deletion
+63
-3
lite/api/paddle_api.cc
lite/api/paddle_api.cc
+8
-0
lite/api/paddle_api.h
lite/api/paddle_api.h
+13
-0
lite/api/paddle_api_test.cc
lite/api/paddle_api_test.cc
+4
-1
lite/core/device_info.h
lite/core/device_info.h
+38
-2
未找到文件。
lite/api/paddle_api.cc
浏览文件 @
5c39519e
...
@@ -356,5 +356,13 @@ void MobileConfig::set_model_buffer(const char *model_buffer,
...
@@ -356,5 +356,13 @@ void MobileConfig::set_model_buffer(const char *model_buffer,
model_from_memory_
=
true
;
model_from_memory_
=
true
;
}
}
// This is the method for allocating workspace_size according to L3Cache size
void
MobileConfig
::
SetArmL3CacheSize
(
L3CacheSetMethod
method
,
int
absolute_val
)
{
#ifdef LITE_WITH_ARM
lite
::
DeviceInfo
::
Global
().
SetArmL3CacheSize
(
method
,
absolute_val
);
#endif
}
}
// namespace lite_api
}
// namespace lite_api
}
// namespace paddle
}
// namespace paddle
lite/api/paddle_api.h
浏览文件 @
5c39519e
...
@@ -32,6 +32,14 @@ using shape_t = std::vector<int64_t>;
...
@@ -32,6 +32,14 @@ using shape_t = std::vector<int64_t>;
using
lod_t
=
std
::
vector
<
std
::
vector
<
uint64_t
>>
;
using
lod_t
=
std
::
vector
<
std
::
vector
<
uint64_t
>>
;
enum
class
LiteModelType
{
kProtobuf
=
0
,
kNaiveBuffer
,
UNK
};
enum
class
LiteModelType
{
kProtobuf
=
0
,
kNaiveBuffer
,
UNK
};
// Methods for allocating L3Cache on Arm platform
enum
class
L3CacheSetMethod
{
kDeviceL3Cache
=
0
,
// Use the system L3 Cache size, best performance.
kDeviceL2Cache
=
1
,
// Use the system L2 Cache size, trade off performance
// with less memory consumption.
kAbsolute
=
2
,
// Use the external setting.
// kAutoGrow = 3, // Not supported yet, least memory consumption.
};
// return true if current device supports OpenCL model
// return true if current device supports OpenCL model
LITE_API
bool
IsOpenCLBackendValid
();
LITE_API
bool
IsOpenCLBackendValid
();
...
@@ -294,6 +302,11 @@ class LITE_API MobileConfig : public ConfigBase {
...
@@ -294,6 +302,11 @@ class LITE_API MobileConfig : public ConfigBase {
// NOTE: This is a deprecated API and will be removed in latter release.
// NOTE: This is a deprecated API and will be removed in latter release.
const
std
::
string
&
param_buffer
()
const
{
return
param_buffer_
;
}
const
std
::
string
&
param_buffer
()
const
{
return
param_buffer_
;
}
// This is the method for allocating workspace_size according to L3Cache size
void
SetArmL3CacheSize
(
L3CacheSetMethod
method
=
L3CacheSetMethod
::
kDeviceL3Cache
,
int
absolute_val
=
-
1
);
};
};
template
<
typename
ConfigT
>
template
<
typename
ConfigT
>
...
...
lite/api/paddle_api_test.cc
浏览文件 @
5c39519e
...
@@ -107,7 +107,8 @@ TEST(CxxApi, share_external_data) {
...
@@ -107,7 +107,8 @@ TEST(CxxApi, share_external_data) {
TEST
(
LightApi
,
run
)
{
TEST
(
LightApi
,
run
)
{
lite_api
::
MobileConfig
config
;
lite_api
::
MobileConfig
config
;
config
.
set_model_from_file
(
FLAGS_model_dir
+
".opt2.naive.nb"
);
config
.
set_model_from_file
(
FLAGS_model_dir
+
".opt2.naive.nb"
);
// disable L3 cache on workspace_ allocating
config
.
SetArmL3CacheSize
(
L3CacheSetMethod
::
kDeviceL2Cache
);
auto
predictor
=
lite_api
::
CreatePaddlePredictor
(
config
);
auto
predictor
=
lite_api
::
CreatePaddlePredictor
(
config
);
auto
inputs
=
predictor
->
GetInputNames
();
auto
inputs
=
predictor
->
GetInputNames
();
...
@@ -148,6 +149,8 @@ TEST(MobileConfig, LoadfromMemory) {
...
@@ -148,6 +149,8 @@ TEST(MobileConfig, LoadfromMemory) {
// set model buffer and run model
// set model buffer and run model
lite_api
::
MobileConfig
config
;
lite_api
::
MobileConfig
config
;
config
.
set_model_from_buffer
(
model_buffer
);
config
.
set_model_from_buffer
(
model_buffer
);
// allocate 1M initial space for workspace_
config
.
SetArmL3CacheSize
(
L3CacheSetMethod
::
kAbsolute
,
1024
*
1024
);
auto
predictor
=
lite_api
::
CreatePaddlePredictor
(
config
);
auto
predictor
=
lite_api
::
CreatePaddlePredictor
(
config
);
auto
input_tensor
=
predictor
->
GetInput
(
0
);
auto
input_tensor
=
predictor
->
GetInput
(
0
);
...
...
lite/core/device_info.h
浏览文件 @
5c39519e
...
@@ -17,6 +17,7 @@
...
@@ -17,6 +17,7 @@
#include <cstdarg>
#include <cstdarg>
#include <string>
#include <string>
#include <vector>
#include <vector>
#include "lite/api/paddle_api.h"
#include "lite/core/tensor.h"
#include "lite/core/tensor.h"
#include "lite/utils/cp_logging.h"
#include "lite/utils/cp_logging.h"
#ifdef LITE_WITH_MLU
#ifdef LITE_WITH_MLU
...
@@ -27,6 +28,7 @@
...
@@ -27,6 +28,7 @@
namespace
paddle
{
namespace
paddle
{
namespace
lite
{
namespace
lite
{
using
L3CacheSetMethod
=
lite_api
::
L3CacheSetMethod
;
#if ((defined LITE_WITH_ARM) || (defined LITE_WITH_MLU))
#if ((defined LITE_WITH_ARM) || (defined LITE_WITH_MLU))
typedef
enum
{
typedef
enum
{
...
@@ -65,11 +67,41 @@ class DeviceInfo {
...
@@ -65,11 +67,41 @@ class DeviceInfo {
int
l1_cache_size
()
const
{
return
L1_cache_
[
active_ids_
[
0
]];
}
int
l1_cache_size
()
const
{
return
L1_cache_
[
active_ids_
[
0
]];
}
int
l2_cache_size
()
const
{
return
L2_cache_
[
active_ids_
[
0
]];
}
int
l2_cache_size
()
const
{
return
L2_cache_
[
active_ids_
[
0
]];
}
int
l3_cache_size
()
const
{
return
L3_cache_
[
active_ids_
[
0
]];
}
int
l3_cache_size
()
const
{
return
L3_cache_
[
active_ids_
[
0
]];
}
// Methods for allocating L3Cache on Arm platform
// Enum class L3CacheSetMethod is declared in `lite/api/paddle_api.h`
void
SetArmL3CacheSize
(
L3CacheSetMethod
method
=
L3CacheSetMethod
::
kDeviceL3Cache
,
int
absolute_val
=
-
1
)
{
l3_cache_method_
=
method
;
absolute_l3cache_size_
=
absolute_val
;
// Realloc memory for sgemm in this context.
workspace_
.
clear
();
workspace_
.
Resize
({
llc_size
()});
workspace_
.
mutable_data
<
int8_t
>
();
}
int
llc_size
()
const
{
int
llc_size
()
const
{
auto
size
=
L3_cache_
[
active_ids_
[
0
]]
>
0
?
L3_cache_
[
active_ids_
[
0
]]
auto
size
=
absolute_l3cache_size_
;
:
L2_cache_
[
active_ids_
[
0
]];
switch
(
l3_cache_method_
)
{
// kDeviceL3Cache = 0, use the system L3 Cache size, best performance.
case
L3CacheSetMethod
::
kDeviceL3Cache
:
size
=
L3_cache_
[
active_ids_
[
0
]]
>
0
?
L3_cache_
[
active_ids_
[
0
]]
:
L2_cache_
[
active_ids_
[
0
]];
break
;
// kDeviceL2Cache = 1, use the system L2 Cache size, trade off performance
// with less memory consumption.
case
L3CacheSetMethod
::
kDeviceL2Cache
:
size
=
L2_cache_
[
active_ids_
[
0
]];
break
;
// kAbsolute = 2, use the external setting.
case
L3CacheSetMethod
::
kAbsolute
:
break
;
default:
LOG
(
FATAL
)
<<
"Error: unknown l3_cache_method_ !"
;
}
return
size
>
0
?
size
:
512
*
1024
;
return
size
>
0
?
size
:
512
*
1024
;
}
}
bool
has_dot
()
const
{
return
dot_
[
active_ids_
[
0
]];
}
bool
has_dot
()
const
{
return
dot_
[
active_ids_
[
0
]];
}
bool
has_fp16
()
const
{
return
fp16_
[
active_ids_
[
0
]];
}
bool
has_fp16
()
const
{
return
fp16_
[
active_ids_
[
0
]];
}
...
@@ -121,6 +153,10 @@ class DeviceInfo {
...
@@ -121,6 +153,10 @@ class DeviceInfo {
void
RequestPowerRandHighMode
(
int
shift_num
,
int
thread_num
);
void
RequestPowerRandHighMode
(
int
shift_num
,
int
thread_num
);
void
RequestPowerRandLowMode
(
int
shift_num
,
int
thread_num
);
void
RequestPowerRandLowMode
(
int
shift_num
,
int
thread_num
);
// Methods for allocating L3Cache on Arm platform
// Enum class L3CacheSetMethod is declared in `lite/api/paddle_api.h`
L3CacheSetMethod
l3_cache_method_
{
L3CacheSetMethod
::
kDeviceL3Cache
};
int
absolute_l3cache_size_
{
-
1
};
DeviceInfo
()
=
default
;
DeviceInfo
()
=
default
;
};
};
#endif // LITE_WITH_ARM
#endif // LITE_WITH_ARM
...
...
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