Skip to content
体验新版
项目
组织
正在加载...
登录
切换导航
打开侧边栏
PaddlePaddle
PaddleDetection
提交
37a272e6
P
PaddleDetection
项目概览
PaddlePaddle
/
PaddleDetection
大约 1 年 前同步成功
通知
695
Star
11112
Fork
2696
代码
文件
提交
分支
Tags
贡献者
分支图
Diff
Issue
184
列表
看板
标记
里程碑
合并请求
40
Wiki
0
Wiki
分析
仓库
DevOps
项目成员
Pages
P
PaddleDetection
项目概览
项目概览
详情
发布
仓库
仓库
文件
提交
分支
标签
贡献者
分支图
比较
Issue
184
Issue
184
列表
看板
标记
里程碑
合并请求
40
合并请求
40
Pages
分析
分析
仓库分析
DevOps
Wiki
0
Wiki
成员
成员
收起侧边栏
关闭侧边栏
动态
分支图
创建新Issue
提交
Issue看板
未验证
提交
37a272e6
编写于
3月 20, 2018
作者:
Q
Qiao Longfei
提交者:
GitHub
3月 20, 2018
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
add executor.prepare (#9022)
optimize executor.run
上级
30b70323
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
116 addition
and
93 deletion
+116
-93
paddle/fluid/framework/executor.cc
paddle/fluid/framework/executor.cc
+11
-17
paddle/fluid/framework/executor.h
paddle/fluid/framework/executor.h
+12
-3
python/paddle/fluid/executor.py
python/paddle/fluid/executor.py
+93
-72
python/paddle/fluid/tests/unittests/test_executor_and_mul.py
python/paddle/fluid/tests/unittests/test_executor_and_mul.py
+0
-1
未找到文件。
paddle/fluid/framework/executor.cc
浏览文件 @
37a272e6
...
...
@@ -14,12 +14,8 @@ limitations under the License. */
#include "paddle/fluid/framework/executor.h"
#include <set>
#include "gflags/gflags.h"
#include "paddle/fluid/framework/channel.h"
#include "paddle/fluid/framework/feed_fetch_method.h"
#include "paddle/fluid/framework/feed_fetch_type.h"
#include "paddle/fluid/framework/lod_rank_table.h"
#include "paddle/fluid/framework/lod_tensor_array.h"
#include "paddle/fluid/framework/op_registry.h"
...
...
@@ -40,14 +36,13 @@ namespace {
int
kProgramId
=
-
1
;
}
// namespace
struct
ExecutorPrepareContext
{
ExecutorPrepareContext
(
const
framework
::
ProgramDesc
&
prog
,
size_t
block_id
)
:
prog_
(
prog
),
block_id_
(
block_id
)
{}
ExecutorPrepareContext
::
ExecutorPrepareContext
(
const
framework
::
ProgramDesc
&
prog
,
size_t
block_id
)
:
prog_
(
prog
),
block_id_
(
block_id
)
{}
const
framework
::
ProgramDesc
&
prog_
;
size_t
block_id_
;
std
::
vector
<
std
::
unique_ptr
<
OperatorBase
>>
ops_
;
};
ExecutorPrepareContext
::~
ExecutorPrepareContext
()
{
VLOG
(
5
)
<<
"destroy ExecutorPrepareContext"
;
}
Executor
::
Executor
(
const
platform
::
Place
&
place
)
:
place_
(
place
)
{}
...
...
@@ -101,9 +96,8 @@ static void CheckTensorNANOrInf(const std::string& name,
void
Executor
::
Run
(
const
ProgramDesc
&
pdesc
,
Scope
*
scope
,
int
block_id
,
bool
create_local_scope
,
bool
create_vars
)
{
platform
::
RecordBlock
b
(
block_id
);
auto
*
ctx
=
Prepare
(
pdesc
,
block_id
);
RunPreparedContext
(
ctx
,
scope
,
create_local_scope
,
create_vars
);
delete
ctx
;
auto
ctx
=
Prepare
(
pdesc
,
block_id
);
RunPreparedContext
(
ctx
.
get
(),
scope
,
create_local_scope
,
create_vars
);
}
// Check whether the block already has feed operators and feed_holder.
...
...
@@ -274,15 +268,15 @@ void Executor::Run(const ProgramDesc& program, Scope* scope,
}
}
ExecutorPrepareContext
*
Executor
::
Prepare
(
const
ProgramDesc
&
program
,
int
block_id
)
{
std
::
unique_ptr
<
ExecutorPrepareContext
>
Executor
::
Prepare
(
const
ProgramDesc
&
program
,
int
block_id
)
{
auto
*
ctx
=
new
ExecutorPrepareContext
(
program
,
block_id
);
PADDLE_ENFORCE_LT
(
static_cast
<
size_t
>
(
block_id
),
program
.
Size
());
auto
&
block
=
program
.
Block
(
block_id
);
for
(
auto
&
op_desc
:
block
.
AllOps
())
{
ctx
->
ops_
.
push_back
(
OpRegistry
::
CreateOp
(
*
op_desc
));
}
return
ctx
;
return
std
::
unique_ptr
<
ExecutorPrepareContext
>
(
ctx
)
;
}
void
Executor
::
RunPreparedContext
(
ExecutorPrepareContext
*
ctx
,
Scope
*
scope
,
...
...
paddle/fluid/framework/executor.h
浏览文件 @
37a272e6
...
...
@@ -22,7 +22,16 @@ limitations under the License. */
namespace
paddle
{
namespace
framework
{
struct
ExecutorPrepareContext
;
struct
ExecutorPrepareContext
{
ExecutorPrepareContext
(
const
framework
::
ProgramDesc
&
prog
,
size_t
block_id
);
~
ExecutorPrepareContext
();
const
framework
::
ProgramDesc
&
prog_
;
size_t
block_id_
;
std
::
vector
<
std
::
unique_ptr
<
OperatorBase
>>
ops_
;
};
class
Executor
{
public:
// TODO(dzhwinter) : Do not rely on this function, it will be removed
...
...
@@ -47,8 +56,8 @@ class Executor {
const
std
::
string
&
feed_holder_name
=
"feed"
,
const
std
::
string
&
fetch_holder_name
=
"fetch"
);
static
ExecutorPrepareContext
*
Prepare
(
const
ProgramDesc
&
program
,
int
block_id
);
static
std
::
unique_ptr
<
ExecutorPrepareContext
>
Prepare
(
const
ProgramDesc
&
program
,
int
block_id
);
void
RunPreparedContext
(
ExecutorPrepareContext
*
ctx
,
Scope
*
scope
,
bool
create_local_scope
=
true
,
...
...
python/paddle/fluid/executor.py
浏览文件 @
37a272e6
...
...
@@ -235,6 +235,77 @@ class Executor(object):
tensor
.
set_lod
(
lod
)
return
tensor
def
_get_program_cache
(
self
,
program_cache_key
):
return
self
.
program_caches
.
get
(
program_cache_key
,
None
)
def
_add_program_cache
(
self
,
program_cache_key
,
program
):
self
.
program_caches
[
program_cache_key
]
=
program
def
_add_feed_fetch_ops
(
self
,
program
,
feed
,
fetch_list
,
feed_var_name
,
fetch_var_name
):
tmp_program
=
program
.
clone
()
global_block
=
tmp_program
.
global_block
()
if
feed_var_name
in
global_block
.
vars
:
feed_var
=
global_block
.
var
(
feed_var_name
)
else
:
feed_var
=
global_block
.
create_var
(
name
=
feed_var_name
,
type
=
core
.
VarDesc
.
VarType
.
FEED_MINIBATCH
,
persistable
=
True
)
if
fetch_var_name
in
global_block
.
vars
:
fetch_var
=
global_block
.
var
(
fetch_var_name
)
else
:
fetch_var
=
global_block
.
create_var
(
name
=
fetch_var_name
,
type
=
core
.
VarDesc
.
VarType
.
FETCH_LIST
,
persistable
=
True
)
# prepend feed operators
if
not
has_feed_operators
(
global_block
,
feed
,
feed_var_name
):
for
i
,
name
in
enumerate
(
feed
):
out
=
global_block
.
var
(
name
)
global_block
.
prepend_op
(
type
=
'feed'
,
inputs
=
{
'X'
:
[
feed_var
]},
outputs
=
{
'Out'
:
[
out
]},
attrs
=
{
'col'
:
i
})
# append fetch_operators
if
not
has_fetch_operators
(
global_block
,
fetch_list
,
fetch_var_name
):
for
i
,
var
in
enumerate
(
fetch_list
):
assert
isinstance
(
var
,
Variable
)
or
isinstance
(
var
,
str
),
(
"Wrong type for fetch_list[%s]: %s"
%
(
i
,
type
(
var
)))
global_block
.
append_op
(
type
=
'fetch'
,
inputs
=
{
'X'
:
[
var
]},
outputs
=
{
'Out'
:
[
fetch_var
]},
attrs
=
{
'col'
:
i
})
return
tmp_program
def
_feed_data
(
self
,
program
,
feed
,
feed_var_name
,
scope
):
# feed var to framework
for
op
in
program
.
global_block
().
ops
:
if
op
.
desc
.
type
()
==
'feed'
:
feed_target_name
=
op
.
desc
.
output
(
'Out'
)[
0
]
cur_feed
=
feed
[
feed_target_name
]
if
not
isinstance
(
cur_feed
,
core
.
LoDTensor
):
cur_feed
=
self
.
aslodtensor
(
cur_feed
)
idx
=
op
.
desc
.
attr
(
'col'
)
core
.
set_feed_variable
(
scope
,
cur_feed
,
feed_var_name
,
idx
)
else
:
break
def
_fetch_data
(
self
,
fetch_list
,
fetch_var_name
,
scope
):
outs
=
[
core
.
get_fetch_variable
(
scope
,
fetch_var_name
,
i
)
for
i
in
xrange
(
len
(
fetch_list
))
]
return
outs
def
run
(
self
,
program
=
None
,
feed
=
None
,
...
...
@@ -268,7 +339,6 @@ class Executor(object):
raise
TypeError
(
"feed should be a map"
)
if
fetch_list
is
None
:
fetch_list
=
[]
if
program
is
None
:
program
=
default_main_program
()
...
...
@@ -278,79 +348,30 @@ class Executor(object):
if
scope
is
None
:
scope
=
global_scope
()
program_cache
=
None
program_cache_key
=
get_program_cache_key
(
feed
,
fetch_list
)
cache_key
=
get_program_cache_key
(
feed
,
fetch_list
)
if
use_program_cache
:
# find program cache by cache_key
program_cache
=
self
.
program_caches
.
get
(
program_cache_key
,
None
)
# TODO(qiao): Should check program_cache and program are exactly the same.
cached_program
=
self
.
_get_program_cache
(
cache_key
)
if
cached_program
is
None
:
cached_program
=
self
.
_add_feed_fetch_ops
(
program
=
program
,
feed
=
feed
,
fetch_list
=
fetch_list
,
feed_var_name
=
feed_var_name
,
fetch_var_name
=
fetch_var_name
)
self
.
_add_program_cache
(
cache_key
,
cached_program
)
program
=
cached_program
else
:
self
.
program_caches
.
pop
(
program_cache_key
,
None
)
if
program_cache
is
None
:
program_cache
=
program
.
clone
()
if
use_program_cache
:
self
.
program_caches
[
program_cache_key
]
=
program_cache
global_block
=
program_cache
.
global_block
()
if
feed_var_name
in
global_block
.
vars
:
feed_var
=
global_block
.
var
(
feed_var_name
)
else
:
feed_var
=
global_block
.
create_var
(
name
=
feed_var_name
,
type
=
core
.
VarDesc
.
VarType
.
FEED_MINIBATCH
,
persistable
=
True
)
if
fetch_var_name
in
global_block
.
vars
:
fetch_var
=
global_block
.
var
(
fetch_var_name
)
else
:
fetch_var
=
global_block
.
create_var
(
name
=
fetch_var_name
,
type
=
core
.
VarDesc
.
VarType
.
FETCH_LIST
,
persistable
=
True
)
# prepend feed operators
if
not
has_feed_operators
(
global_block
,
feed
,
feed_var_name
):
for
i
,
name
in
enumerate
(
feed
):
out
=
global_block
.
var
(
name
)
global_block
.
prepend_op
(
type
=
'feed'
,
inputs
=
{
'X'
:
[
feed_var
]},
outputs
=
{
'Out'
:
[
out
]},
attrs
=
{
'col'
:
i
})
# append fetch_operators
if
not
has_fetch_operators
(
global_block
,
fetch_list
,
fetch_var_name
):
for
i
,
var
in
enumerate
(
fetch_list
):
assert
isinstance
(
var
,
Variable
)
or
isinstance
(
var
,
str
),
(
"Wrong type for fetch_list[%s]: %s"
%
(
i
,
type
(
var
)))
global_block
.
append_op
(
type
=
'fetch'
,
inputs
=
{
'X'
:
[
var
]},
outputs
=
{
'Out'
:
[
fetch_var
]},
attrs
=
{
'col'
:
i
})
# feed var to framework
for
op
in
program_cache
.
global_block
().
ops
:
if
op
.
desc
.
type
()
==
'feed'
:
feed_target_name
=
op
.
desc
.
output
(
'Out'
)[
0
]
cur_feed
=
feed
[
feed_target_name
]
if
not
isinstance
(
cur_feed
,
core
.
LoDTensor
):
cur_feed
=
self
.
aslodtensor
(
cur_feed
)
idx
=
op
.
desc
.
attr
(
'col'
)
core
.
set_feed_variable
(
scope
,
cur_feed
,
feed_var_name
,
idx
)
else
:
break
self
.
executor
.
run
(
program_cache
.
desc
,
scope
,
0
,
True
,
True
)
outs
=
[
core
.
get_fetch_variable
(
scope
,
fetch_var_name
,
i
)
for
i
in
xrange
(
len
(
fetch_list
))
]
self
.
program_caches
.
pop
(
cache_key
,
None
)
program
=
self
.
_add_feed_fetch_ops
(
program
=
program
,
feed
=
feed
,
fetch_list
=
fetch_list
,
feed_var_name
=
feed_var_name
,
fetch_var_name
=
fetch_var_name
)
self
.
_feed_data
(
program
,
feed
,
feed_var_name
,
scope
)
self
.
executor
.
run
(
program
.
desc
,
scope
,
0
,
True
,
True
)
outs
=
self
.
_fetch_data
(
fetch_list
,
fetch_var_name
,
scope
)
if
return_numpy
:
outs
=
as_numpy
(
outs
)
return
outs
python/paddle/fluid/tests/unittests/test_executor_and_mul.py
浏览文件 @
37a272e6
...
...
@@ -16,7 +16,6 @@ import unittest
import
numpy
import
paddle.fluid.core
as
core
from
paddle.fluid.executor
import
Executor
from
paddle.fluid.layers
import
mul
,
data
...
...
编辑
预览
Markdown
is supported
0%
请重试
或
添加新附件
.
添加附件
取消
You are about to add
0
people
to the discussion. Proceed with caution.
先完成此消息的编辑!
取消
想要评论请
注册
或
登录