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
bd79e046
P
PaddleDetection
项目概览
PaddlePaddle
/
PaddleDetection
11 个月 前同步成功
通知
692
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
体验新版 GitCode,发现更多精彩内容 >>
未验证
提交
bd79e046
编写于
9月 18, 2018
作者:
Y
Yu Yang
提交者:
GitHub
9月 18, 2018
浏览文件
操作
浏览文件
下载
差异文件
Merge pull request #13431 from chengduoZH/refine_lod
Speed up lod
上级
6b4d290c
6534f852
变更
9
隐藏空白更改
内联
并排
Showing
9 changed file
with
381 addition
and
326 deletion
+381
-326
paddle/fluid/framework/details/cow_ptr.h
paddle/fluid/framework/details/cow_ptr.h
+23
-61
paddle/fluid/framework/details/cow_ptr_test.cc
paddle/fluid/framework/details/cow_ptr_test.cc
+8
-0
paddle/fluid/framework/mixed_vector.h
paddle/fluid/framework/mixed_vector.h
+326
-241
paddle/fluid/operators/detection_map_op.h
paddle/fluid/operators/detection_map_op.h
+15
-13
paddle/fluid/operators/extract_rows_op.cc
paddle/fluid/operators/extract_rows_op.cc
+1
-1
paddle/fluid/operators/math/selected_rows_functor.cu
paddle/fluid/operators/math/selected_rows_functor.cu
+4
-6
paddle/fluid/operators/sum_op.h
paddle/fluid/operators/sum_op.h
+0
-1
python/paddle/fluid/tests/unittests/op_test.py
python/paddle/fluid/tests/unittests/op_test.py
+1
-1
python/paddle/fluid/tests/unittests/test_detection_map_op.py
python/paddle/fluid/tests/unittests/test_detection_map_op.py
+3
-2
未找到文件。
paddle/fluid/framework/details/cow_ptr.h
浏览文件 @
bd79e046
...
@@ -20,79 +20,41 @@ namespace paddle {
...
@@ -20,79 +20,41 @@ namespace paddle {
namespace
framework
{
namespace
framework
{
namespace
details
{
namespace
details
{
// Change it to thread safe flags if needed.
template
<
class
T
>
class
ThreadUnsafeOwnershipFlags
{
class
COWPtr
{
public:
public:
explicit
ThreadUnsafeOwnershipFlags
(
bool
flag
)
:
flag_
(
flag
)
{}
typedef
std
::
shared_ptr
<
T
>
RefPtr
;
ThreadUnsafeOwnershipFlags
(
const
ThreadUnsafeOwnershipFlags
&
other
)
=
delete
;
ThreadUnsafeOwnershipFlags
&
operator
=
(
const
ThreadUnsafeOwnershipFlags
&
other
)
=
delete
;
ThreadUnsafeOwnershipFlags
(
ThreadUnsafeOwnershipFlags
&&
other
)
=
default
;
void
SetOwnership
(
bool
flag
)
{
flag_
=
flag
;
}
private:
RefPtr
m_sp
;
// Invoke the callback if it is not owned.
void
detach
()
{
template
<
typename
Callback
>
T
*
tmp
=
m_sp
.
get
();
void
AcquireOwnershipOnce
(
Callback
acquire
)
{
if
(
!
(
tmp
==
nullptr
||
m_sp
.
unique
()))
{
if
(
!
flag_
)
{
m_sp
=
RefPtr
(
new
T
(
*
tmp
));
acquire
();
flag_
=
true
;
}
}
}
}
private:
bool
flag_
;
};
// Copy-On-Write pointer.
// It will hold a T* pointer, and only copy once when `MutableData` is invoked.
//
// The template parameter OwnershipFlags should have:
// * a constructor takes a bool. True if own.
// * SetOwnership(bool flag).
// * AcquireOwnershipOnce(Callback). It will invoke the callback if it is not
// owned.
//
// https://en.wikipedia.org/wiki/Copy-on-write
template
<
typename
T
,
typename
OwnershipFlags
=
ThreadUnsafeOwnershipFlags
>
class
COWPtr
{
public:
public:
// Ctor from raw pointer.
COWPtr
()
:
m_sp
(
nullptr
)
{}
explicit
COWPtr
(
T
*
ptr
)
:
payload_
(
ptr
),
ownership_
{
true
}
{}
explicit
COWPtr
(
T
*
t
)
:
m_sp
(
t
)
{}
explicit
COWPtr
(
const
RefPtr
&
refptr
)
:
m_sp
(
refptr
)
{}
// Move methods. Steal ownership from origin
const
T
&
Data
()
const
{
return
operator
*
();
}
COWPtr
(
COWPtr
&&
other
)
:
payload_
(
other
.
payload_
),
ownership_
{
std
::
move
(
other
.
ownership_
)}
{}
COWPtr
&
operator
=
(
COWPtr
&&
origin
)
=
default
;
// Copy methods. Not own payload
T
*
MutableData
()
{
return
operator
->
();
}
COWPtr
(
const
COWPtr
&
other
)
:
payload_
(
other
.
payload_
),
ownership_
{
false
}
{}
COWPtr
&
operator
=
(
const
COWPtr
&
other
)
{
payload_
=
other
.
payload_
;
ownership_
.
SetOwnership
(
false
);
return
*
this
;
}
// Access read only data.
const
T
&
Data
()
const
{
return
*
payload_
;
}
// Access mutable data. If the data is not owned, the data will be copied
const
T
&
operator
*
()
const
{
return
*
m_sp
;
}
// before.
T
&
operator
*
()
{
T
*
MutableData
()
{
detach
();
ownership_
.
AcquireOwnershipOnce
(
return
*
m_sp
;
[
this
]
{
payload_
.
reset
(
new
T
(
*
payload_
));
});
}
return
payload_
.
get
();
const
T
*
operator
->
()
const
{
return
m_sp
.
operator
->
();
}
T
*
operator
->
()
{
detach
();
return
m_sp
.
operator
->
();
}
}
private:
// Actual data pointer.
std
::
shared_ptr
<
T
>
payload_
;
// Ownership flag.
OwnershipFlags
ownership_
;
};
};
}
// namespace details
}
// namespace details
}
// namespace framework
}
// namespace framework
}
// namespace paddle
}
// namespace paddle
paddle/fluid/framework/details/cow_ptr_test.cc
浏览文件 @
bd79e046
...
@@ -30,6 +30,14 @@ TEST(COWPtr, all) {
...
@@ -30,6 +30,14 @@ TEST(COWPtr, all) {
ASSERT_EQ
(
ptr2
.
Data
(),
10
);
ASSERT_EQ
(
ptr2
.
Data
(),
10
);
}
}
TEST
(
COWPtr
,
change_old
)
{
COWPtr
<
int
>
ptr
(
new
int
{
0
});
COWPtr
<
int
>
ptr2
=
ptr
;
*
ptr
.
MutableData
()
=
10
;
ASSERT_EQ
(
ptr2
.
Data
(),
0
);
ASSERT_EQ
(
ptr
.
Data
(),
10
);
}
}
// namespace details
}
// namespace details
}
// namespace framework
}
// namespace framework
}
// namespace paddle
}
// namespace paddle
paddle/fluid/framework/mixed_vector.h
浏览文件 @
bd79e046
...
@@ -17,10 +17,12 @@
...
@@ -17,10 +17,12 @@
#include <algorithm>
#include <algorithm>
#include <initializer_list>
#include <initializer_list>
#include <memory>
#include <memory>
#include <utility>
#include <vector>
#include <vector>
#include "paddle/fluid/framework/details/cow_ptr.h"
#include "paddle/fluid/framework/tensor.h"
#include "paddle/fluid/framework/tensor.h"
#include "paddle/fluid/framework/tensor_util.h"
#include "paddle/fluid/framework/tensor_util.h"
#include "paddle/fluid/memory/memcpy.h"
#include "glog/logging.h"
#include "glog/logging.h"
...
@@ -28,206 +30,401 @@ namespace paddle {
...
@@ -28,206 +30,401 @@ namespace paddle {
namespace
framework
{
namespace
framework
{
#if defined(PADDLE_WITH_CUDA)
#if defined(PADDLE_WITH_CUDA)
namespace
details
{
struct
CUDABuffer
{
void
*
data_
{
nullptr
};
size_t
size_
{
0
};
platform
::
CUDAPlace
place_
;
CUDABuffer
()
{}
CUDABuffer
(
platform
::
Place
place
,
size_t
size
)
:
size_
(
size
),
place_
(
boost
::
get
<
platform
::
CUDAPlace
>
(
place
))
{
data_
=
memory
::
Alloc
(
place_
,
size
);
}
~
CUDABuffer
()
{
ClearMemory
();
}
CUDABuffer
(
const
CUDABuffer
&
o
)
=
delete
;
CUDABuffer
&
operator
=
(
const
CUDABuffer
&
o
)
=
delete
;
void
Resize
(
platform
::
Place
place
,
size_t
size
)
{
ClearMemory
();
place_
=
boost
::
get
<
platform
::
CUDAPlace
>
(
place
);
data_
=
memory
::
Alloc
(
place_
,
size
);
size_
=
size
;
}
void
Swap
(
CUDABuffer
&
o
)
{
std
::
swap
(
data_
,
o
.
data_
);
std
::
swap
(
place_
,
o
.
place_
);
std
::
swap
(
size_
,
o
.
size_
);
}
private:
void
ClearMemory
()
const
{
if
(
data_
)
{
memory
::
Free
(
place_
,
data_
);
}
}
};
}
// namespace details
// Vector<T> implements the std::vector interface, and can get Data or
// Vector<T> implements the std::vector interface, and can get Data or
// MutableData from any place. The data will be synced implicitly inside.
// MutableData from any place. The data will be synced implicitly inside.
template
<
typename
T
>
template
<
typename
T
>
class
Vector
{
class
Vector
{
public:
public:
using
value_type
=
T
;
using
value_type
=
T
;
using
iterator
=
typename
std
::
vector
<
T
>::
iterator
;
using
const_iterator
=
typename
std
::
vector
<
T
>::
const_iterator
;
// Default ctor. Create empty Vector
private:
Vector
()
{
InitEmpty
();
}
// The actual class to implement vector logic
class
VectorData
{
public:
VectorData
()
:
flag_
(
kDataInCPU
)
{}
VectorData
(
size_t
count
,
const
T
&
value
)
:
cpu_
(
count
,
value
),
flag_
(
kDataInCPU
)
{}
VectorData
(
std
::
initializer_list
<
T
>
init
)
:
cpu_
(
init
),
flag_
(
kDataInCPU
)
{}
template
<
typename
U
>
explicit
VectorData
(
const
std
::
vector
<
U
>
&
dat
)
:
cpu_
(
dat
),
flag_
(
kDataInCPU
)
{}
VectorData
(
const
VectorData
&
o
)
{
o
.
ImmutableCPU
();
cpu_
=
o
.
cpu_
;
flag_
=
kDataInCPU
;
}
// Fill vector with value. The vector size is `count`.
VectorData
&
operator
=
(
const
VectorData
&
o
)
{
explicit
Vector
(
size_t
count
,
const
T
&
value
=
T
())
{
o
.
ImmutableCPU
();
InitEmpty
();
cpu_
=
o
.
cpu_
;
if
(
count
!=
0
)
{
flag_
=
kDataInCPU
;
resize
(
count
);
details
::
CUDABuffer
null
;
T
*
ptr
=
begin
();
gpu_
.
Swap
(
null
);
for
(
size_t
i
=
0
;
i
<
count
;
++
i
)
{
return
*
this
;
ptr
[
i
]
=
value
;
}
T
&
operator
[](
size_t
i
)
{
MutableCPU
();
return
cpu_
[
i
];
}
const
T
&
operator
[](
size_t
i
)
const
{
ImmutableCPU
();
return
cpu_
[
i
];
}
size_t
size
()
const
{
return
cpu_
.
size
();
}
iterator
begin
()
{
MutableCPU
();
return
cpu_
.
begin
();
}
iterator
end
()
{
MutableCPU
();
return
cpu_
.
end
();
}
T
&
front
()
{
MutableCPU
();
return
cpu_
.
front
();
}
T
&
back
()
{
MutableCPU
();
return
cpu_
.
back
();
}
const_iterator
begin
()
const
{
ImmutableCPU
();
return
cpu_
.
begin
();
}
const_iterator
end
()
const
{
ImmutableCPU
();
return
cpu_
.
end
();
}
const
T
&
back
()
const
{
ImmutableCPU
();
return
cpu_
.
back
();
}
T
*
data
()
{
return
&
(
*
this
)[
0
];
}
const
T
*
data
()
const
{
return
&
(
*
this
)[
0
];
}
const
T
&
front
()
const
{
ImmutableCPU
();
return
cpu_
.
front
();
}
// assign this from iterator.
// NOTE: the iterator must support `end-begin`
template
<
typename
Iter
>
void
assign
(
Iter
begin
,
Iter
end
)
{
MutableCPU
();
cpu_
.
assign
(
begin
,
end
);
}
// push_back. If the previous capacity is not enough, the memory will
// double.
void
push_back
(
T
elem
)
{
MutableCPU
();
cpu_
.
push_back
(
elem
);
}
// extend a vector by iterator.
// NOTE: the iterator must support end-begin
template
<
typename
It
>
void
Extend
(
It
begin
,
It
end
)
{
MutableCPU
();
auto
out_it
=
std
::
back_inserter
<
std
::
vector
<
T
>>
(
this
->
cpu_
);
std
::
copy
(
begin
,
end
,
out_it
);
}
// resize the vector
void
resize
(
size_t
size
)
{
MutableCPU
();
cpu_
.
resize
(
size
);
}
// get cuda ptr. immutable
const
T
*
CUDAData
(
platform
::
Place
place
)
const
{
PADDLE_ENFORCE
(
platform
::
is_gpu_place
(
place
),
"CUDA Data must on CUDA place"
);
ImmutableCUDA
(
place
);
return
reinterpret_cast
<
T
*>
(
gpu_
.
data_
);
}
// get cuda ptr. mutable
T
*
CUDAMutableData
(
platform
::
Place
place
)
{
const
T
*
ptr
=
CUDAData
(
place
);
flag_
=
kDirty
|
kDataInCUDA
;
return
const_cast
<
T
*>
(
ptr
);
}
// clear
void
clear
()
{
cpu_
.
clear
();
flag_
=
kDirty
|
kDataInCPU
;
}
size_t
capacity
()
const
{
return
cpu_
.
capacity
();
}
// reserve data
void
reserve
(
size_t
size
)
{
cpu_
.
reserve
(
size
);
}
// implicit cast operator. Vector can be cast to std::vector implicitly.
operator
std
::
vector
<
T
>
()
const
{
ImmutableCPU
();
return
cpu_
;
}
bool
operator
==
(
const
VectorData
&
other
)
const
{
ImmutableCPU
();
other
.
ImmutableCPU
();
return
cpu_
==
other
.
cpu_
;
}
private:
enum
DataFlag
{
kDataInCPU
=
0x01
,
kDataInCUDA
=
0x02
,
// kDirty means the data has been changed in one device.
kDirty
=
0x10
};
void
CopyToCPU
()
const
{
// COPY GPU Data To CPU
void
*
src
=
gpu_
.
data_
;
void
*
dst
=
cpu_
.
data
();
memory
::
Copy
(
platform
::
CPUPlace
(),
dst
,
gpu_
.
place_
,
src
,
gpu_
.
size_
,
nullptr
);
}
void
MutableCPU
()
{
if
(
IsInCUDA
()
&&
IsDirty
())
{
CopyToCPU
();
}
}
flag_
=
kDirty
|
kDataInCPU
;
}
}
}
// Ctor with init_list
void
ImmutableCUDA
(
platform
::
Place
place
)
const
{
Vector
(
std
::
initializer_list
<
T
>
init
)
{
if
(
IsDirty
())
{
if
(
init
.
size
()
==
0
)
{
if
(
IsInCPU
())
{
InitEmpty
();
CopyCPUDataToCUDA
(
place
);
}
else
{
UnsetFlag
(
kDirty
);
InitByIter
(
init
.
size
(),
init
.
begin
(),
init
.
end
());
SetFlag
(
kDataInCUDA
);
}
else
if
(
IsInCUDA
()
&&
!
(
boost
::
get
<
platform
::
CUDAPlace
>
(
place
)
==
gpu_
.
place_
))
{
CopyCUDADataToAnotherPlace
(
place
);
// Still dirty
}
else
{
// Dirty && DataInCUDA && Device is same
// Do nothing
}
}
else
{
if
(
!
IsInCUDA
())
{
// Even data is not dirty. However, data is not in CUDA. Copy data.
CopyCPUDataToCUDA
(
place
);
SetFlag
(
kDataInCUDA
);
}
else
if
(
!
(
boost
::
get
<
platform
::
CUDAPlace
>
(
place
)
==
gpu_
.
place_
))
{
CopyCUDADataToAnotherPlace
(
place
);
}
else
{
// Not Dirty && DataInCUDA && Device is same
// Do nothing.
}
}
}
}
}
void
CopyCUDADataToAnotherPlace
(
const
platform
::
Place
&
place
)
const
{
details
::
CUDABuffer
tmp
(
place
,
gpu_
.
size_
);
const
void
*
src
=
gpu_
.
data_
;
void
*
dst
=
tmp
.
data_
;
memory
::
Copy
(
tmp
.
place_
,
dst
,
gpu_
.
place_
,
src
,
gpu_
.
size_
,
nullptr
);
gpu_
.
Swap
(
tmp
);
}
void
CopyCPUDataToCUDA
(
const
platform
::
Place
&
place
)
const
{
void
*
src
=
cpu_
.
data
();
gpu_
.
Resize
(
place
,
cpu_
.
size
()
*
sizeof
(
T
));
void
*
dst
=
gpu_
.
data_
;
auto
stream
=
static_cast
<
platform
::
CUDADeviceContext
*>
(
platform
::
DeviceContextPool
::
Instance
().
Get
(
place
))
->
stream
();
memory
::
Copy
(
gpu_
.
place_
,
dst
,
platform
::
CPUPlace
(),
src
,
gpu_
.
size_
,
stream
);
}
void
ImmutableCPU
()
const
{
if
(
IsDirty
()
&&
!
IsInCPU
())
{
// If data has been changed in CUDA, or
// CPU has no data.
CopyToCPU
();
UnsetFlag
(
kDirty
);
}
SetFlag
(
kDataInCPU
);
}
void
UnsetFlag
(
int
flag
)
const
{
flag_
&=
~
flag
;
}
void
SetFlag
(
int
flag
)
const
{
flag_
|=
flag
;
}
bool
IsDirty
()
const
{
return
flag_
&
kDirty
;
}
bool
IsInCUDA
()
const
{
return
flag_
&
kDataInCUDA
;
}
bool
IsInCPU
()
const
{
return
flag_
&
kDataInCPU
;
}
mutable
std
::
vector
<
T
>
cpu_
;
mutable
details
::
CUDABuffer
gpu_
;
mutable
int
flag_
;
};
public:
// Default ctor. Create empty Vector
Vector
()
:
m_
(
new
VectorData
())
{}
// Fill vector with value. The vector size is `count`.
explicit
Vector
(
size_t
count
,
const
T
&
value
=
T
())
:
m_
(
new
VectorData
(
count
,
value
))
{}
// Ctor with init_list
Vector
(
std
::
initializer_list
<
T
>
init
)
:
m_
(
new
VectorData
(
init
))
{}
// implicit cast from std::vector.
// implicit cast from std::vector.
template
<
typename
U
>
template
<
typename
U
>
Vector
(
const
std
::
vector
<
U
>
&
dat
)
{
// NOLINT
Vector
(
const
std
::
vector
<
U
>
&
dat
)
:
m_
(
new
VectorData
(
dat
))
{
// NOLINT
if
(
dat
.
size
()
==
0
)
{
InitEmpty
();
}
else
{
InitByIter
(
dat
.
size
(),
dat
.
begin
(),
dat
.
end
());
}
}
}
// Copy ctor
// Copy ctor
Vector
(
const
Vector
<
T
>
&
other
)
{
this
->
operator
=
(
other
)
;
}
Vector
(
const
Vector
<
T
>
&
other
)
{
m_
=
other
.
m_
;
}
// Copy operator
// Copy operator
Vector
<
T
>
&
operator
=
(
const
Vector
<
T
>
&
other
)
{
Vector
<
T
>
&
operator
=
(
const
Vector
<
T
>
&
other
)
{
if
(
other
.
size
()
!=
0
)
{
m_
=
other
.
m_
;
this
->
InitByIter
(
other
.
size
(),
other
.
begin
(),
other
.
end
());
}
else
{
InitEmpty
();
}
return
*
this
;
return
*
this
;
}
}
// Move ctor
// Move ctor
Vector
(
Vector
<
T
>
&&
other
)
{
Vector
(
Vector
<
T
>
&&
other
)
{
m_
=
std
::
move
(
other
.
m_
);
}
this
->
size_
=
other
.
size_
;
this
->
flag_
=
other
.
flag_
;
if
(
other
.
cuda_vec_
.
memory_size
())
{
this
->
cuda_vec_
.
ShareDataWith
(
other
.
cuda_vec_
);
}
if
(
other
.
cpu_vec_
.
memory_size
())
{
this
->
cpu_vec_
.
ShareDataWith
(
other
.
cpu_vec_
);
}
}
// CPU data access method. Mutable.
// CPU data access method. Mutable.
T
&
operator
[](
size_t
i
)
{
T
&
operator
[](
size_t
i
)
{
return
(
*
m_
)[
i
];
}
MutableCPU
();
return
const_cast
<
T
*>
(
cpu_vec_
.
data
<
T
>
())[
i
];
}
// CPU data access method. Immutable.
// CPU data access method. Immutable.
const
T
&
operator
[](
size_t
i
)
const
{
const
T
&
operator
[](
size_t
i
)
const
{
return
(
*
m_
)[
i
];
}
ImmutableCPU
();
return
cpu_vec_
.
data
<
T
>
()[
i
];
}
// std::vector iterator methods. Based on CPU data access method
// std::vector iterator methods. Based on CPU data access method
size_t
size
()
const
{
return
size_
;
}
size_t
size
()
const
{
return
m_
->
size
()
;
}
T
*
begin
()
{
return
capacity
()
==
0
?
&
EmptyDummy
()
:
&
this
->
operator
[](
0
);
}
iterator
begin
()
{
return
m_
->
begin
(
);
}
T
*
end
()
{
iterator
end
()
{
return
m_
->
end
();
}
return
capacity
()
==
0
?
&
EmptyDummy
()
:
&
this
->
operator
[](
size
());
}
T
&
front
()
{
return
*
begin
();
}
T
&
front
()
{
return
m_
->
front
();
}
T
&
back
()
{
T
&
back
()
{
return
m_
->
back
();
}
auto
it
=
end
();
--
it
;
return
*
it
;
}
const
T
*
begin
()
const
{
const_iterator
begin
()
const
{
return
m_
->
begin
();
}
return
capacity
()
==
0
?
&
EmptyDummy
()
:
&
this
->
operator
[](
0
);
}
const
T
*
end
()
const
{
const_iterator
end
()
const
{
return
m_
->
end
();
}
return
capacity
()
==
0
?
&
EmptyDummy
()
:
&
this
->
operator
[](
size
());
}
const
T
*
cbegin
()
const
{
return
begin
();
}
const
_iterator
cbegin
()
const
{
return
begin
();
}
const
T
*
cend
()
const
{
return
end
();
}
const
_iterator
cend
()
const
{
return
end
();
}
const
T
&
back
()
const
{
const
T
&
back
()
const
{
return
m_
->
back
();
}
auto
it
=
end
();
--
it
;
return
*
it
;
}
T
*
data
()
{
return
begin
();
}
T
*
data
()
{
return
m_
->
data
();
}
const
T
*
data
()
const
{
return
begin
();
}
const
T
*
data
()
const
{
return
m_
->
data
();
}
const
T
&
front
()
const
{
return
*
begin
();
}
const
T
&
front
()
const
{
return
m_
->
front
();
}
// end of std::vector iterator methods
// end of std::vector iterator methods
// assign this from iterator.
// assign this from iterator.
// NOTE: the iterator must support `end-begin`
// NOTE: the iterator must support `end-begin`
template
<
typename
Iter
>
template
<
typename
Iter
>
void
assign
(
Iter
begin
,
Iter
end
)
{
void
assign
(
Iter
begin
,
Iter
end
)
{
InitByIter
(
end
-
begin
,
begin
,
end
);
m_
->
assign
(
begin
,
end
);
}
}
// push_back. If the previous capacity is not enough, the memory will
// push_back. If the previous capacity is not enough, the memory will
// double.
// double.
void
push_back
(
T
elem
)
{
void
push_back
(
T
elem
)
{
m_
->
push_back
(
elem
);
}
if
(
size_
+
1
>
capacity
())
{
reserve
((
size_
+
1
)
<<
1
);
}
*
end
()
=
elem
;
++
size_
;
}
// extend a vector by iterator.
// extend a vector by iterator.
// NOTE: the iterator must support end-begin
// NOTE: the iterator must support end-begin
template
<
typename
It
>
template
<
typename
It
>
void
Extend
(
It
begin
,
It
end
)
{
void
Extend
(
It
begin
,
It
end
)
{
size_t
pre_size
=
size_
;
m_
->
Extend
(
begin
,
end
);
resize
(
pre_size
+
(
end
-
begin
));
T
*
ptr
=
this
->
begin
()
+
pre_size
;
for
(;
begin
<
end
;
++
begin
,
++
ptr
)
{
*
ptr
=
*
begin
;
}
}
}
// resize the vector
// resize the vector
void
resize
(
size_t
size
)
{
void
resize
(
size_t
size
)
{
if
(
size
+
1
<=
capacity
())
{
if
(
m_
.
Data
().
size
()
!=
size
)
{
size_
=
size
;
m_
->
resize
(
size
);
}
else
{
MutableCPU
();
Tensor
cpu_tensor
;
platform
::
Place
cpu
=
platform
::
CPUPlace
();
T
*
ptr
=
cpu_tensor
.
mutable_data
<
T
>
(
framework
::
make_ddim
({
static_cast
<
int64_t
>
(
size
)}),
cpu
);
const
T
*
old_ptr
=
cpu_vec_
.
memory_size
()
==
0
?
nullptr
:
cpu_vec_
.
data
<
T
>
();
if
(
old_ptr
!=
nullptr
)
{
std
::
copy
(
old_ptr
,
old_ptr
+
size_
,
ptr
);
}
size_
=
size
;
cpu_vec_
.
ShareDataWith
(
cpu_tensor
);
}
}
}
}
// get cuda ptr. immutable
// get cuda ptr. immutable
const
T
*
CUDAData
(
platform
::
Place
place
)
const
{
const
T
*
CUDAData
(
platform
::
Place
place
)
const
{
PADDLE_ENFORCE
(
platform
::
is_gpu_place
(
place
),
return
m_
.
Data
().
CUDAData
(
place
);
"CUDA Data must on CUDA place"
);
ImmutableCUDA
(
place
);
return
cuda_vec_
.
data
<
T
>
();
}
}
// get cuda ptr. mutable
// get cuda ptr. mutable
T
*
CUDAMutableData
(
platform
::
Place
place
)
{
T
*
CUDAMutableData
(
platform
::
Place
place
)
{
const
T
*
ptr
=
CUDAData
(
place
);
return
m_
->
CUDAMutableData
(
place
);
flag_
=
kDirty
|
kDataInCUDA
;
return
const_cast
<
T
*>
(
ptr
);
}
}
// clear
// clear
void
clear
()
{
void
clear
()
{
m_
->
clear
();
}
size_
=
0
;
flag_
=
kDirty
|
kDataInCPU
;
}
size_t
capacity
()
const
{
size_t
capacity
()
const
{
return
m_
->
capacity
();
}
return
cpu_vec_
.
memory_size
()
/
SizeOfType
(
typeid
(
T
));
}
// reserve data
// reserve data
void
reserve
(
size_t
size
)
{
void
reserve
(
size_t
size
)
{
m_
->
reserve
(
size
);
}
size_t
pre_size
=
size_
;
resize
(
size
);
resize
(
pre_size
);
}
// the unify method to access CPU or CUDA data. immutable.
// the unify method to access CPU or CUDA data. immutable.
const
T
*
Data
(
platform
::
Place
place
)
const
{
const
T
*
Data
(
platform
::
Place
place
)
const
{
...
@@ -248,12 +445,7 @@ class Vector {
...
@@ -248,12 +445,7 @@ class Vector {
}
}
// implicit cast operator. Vector can be cast to std::vector implicitly.
// implicit cast operator. Vector can be cast to std::vector implicitly.
operator
std
::
vector
<
T
>
()
const
{
operator
std
::
vector
<
T
>
()
const
{
return
*
m_
;
}
std
::
vector
<
T
>
result
;
result
.
resize
(
size
());
std
::
copy
(
begin
(),
end
(),
result
.
begin
());
return
result
;
}
bool
operator
==
(
const
Vector
<
T
>
&
other
)
const
{
bool
operator
==
(
const
Vector
<
T
>
&
other
)
const
{
if
(
size
()
!=
other
.
size
())
return
false
;
if
(
size
()
!=
other
.
size
())
return
false
;
...
@@ -267,118 +459,11 @@ class Vector {
...
@@ -267,118 +459,11 @@ class Vector {
return
true
;
return
true
;
}
}
private:
const
void
*
Handle
()
const
{
return
&
m_
.
Data
();
}
void
InitEmpty
()
{
size_
=
0
;
flag_
=
kDataInCPU
;
}
template
<
typename
Iter
>
void
InitByIter
(
size_t
size
,
Iter
begin
,
Iter
end
)
{
platform
::
Place
cpu
=
platform
::
CPUPlace
();
T
*
ptr
=
this
->
cpu_vec_
.
template
mutable_data
<
T
>(
framework
::
make_ddim
({
static_cast
<
int64_t
>
(
size
)}),
cpu
);
for
(
size_t
i
=
0
;
i
<
size
;
++
i
)
{
*
ptr
++
=
*
begin
++
;
}
flag_
=
kDataInCPU
|
kDirty
;
size_
=
size
;
}
enum
DataFlag
{
kDataInCPU
=
0x01
,
kDataInCUDA
=
0x02
,
// kDirty means the data has been changed in one device.
kDirty
=
0x10
};
void
CopyToCPU
()
const
{
// COPY GPU Data To CPU
TensorCopy
(
cuda_vec_
,
platform
::
CPUPlace
(),
&
cpu_vec_
);
WaitPlace
(
cuda_vec_
.
place
());
}
void
MutableCPU
()
{
if
(
IsInCUDA
()
&&
IsDirty
())
{
CopyToCPU
();
}
flag_
=
kDirty
|
kDataInCPU
;
}
void
ImmutableCUDA
(
platform
::
Place
place
)
const
{
if
(
IsDirty
())
{
if
(
IsInCPU
())
{
TensorCopy
(
cpu_vec_
,
boost
::
get
<
platform
::
CUDAPlace
>
(
place
),
&
cuda_vec_
);
WaitPlace
(
place
);
UnsetFlag
(
kDirty
);
SetFlag
(
kDataInCUDA
);
}
else
if
(
IsInCUDA
()
&&
!
(
place
==
cuda_vec_
.
place
()))
{
framework
::
Tensor
tmp
;
TensorCopy
(
cuda_vec_
,
boost
::
get
<
platform
::
CUDAPlace
>
(
place
),
&
tmp
);
WaitPlace
(
cuda_vec_
.
place
());
cuda_vec_
.
ShareDataWith
(
tmp
);
// Still dirty
}
else
{
// Dirty && DataInCUDA && Device is same
// Do nothing
}
}
else
{
if
(
!
IsInCUDA
())
{
// Even data is not dirty. However, data is not in CUDA. Copy data.
TensorCopy
(
cpu_vec_
,
boost
::
get
<
platform
::
CUDAPlace
>
(
place
),
&
cuda_vec_
);
WaitPlace
(
place
);
SetFlag
(
kDataInCUDA
);
}
else
if
(
!
(
place
==
cuda_vec_
.
place
()))
{
framework
::
Tensor
tmp
;
WaitPlace
(
cuda_vec_
.
place
());
TensorCopy
(
cuda_vec_
,
boost
::
get
<
platform
::
CUDAPlace
>
(
place
),
&
tmp
);
WaitPlace
(
cuda_vec_
.
place
());
WaitPlace
(
place
);
cuda_vec_
.
ShareDataWith
(
tmp
);
}
else
{
// Not Dirty && DataInCUDA && Device is same
// Do nothing.
}
}
}
void
ImmutableCPU
()
const
{
if
(
IsDirty
()
&&
!
IsInCPU
())
{
// If data has been changed in CUDA, or CPU has no data.
CopyToCPU
();
UnsetFlag
(
kDirty
);
}
SetFlag
(
kDataInCPU
);
}
void
UnsetFlag
(
int
flag
)
const
{
flag_
&=
~
flag
;
}
void
SetFlag
(
int
flag
)
const
{
flag_
|=
flag
;
}
bool
IsDirty
()
const
{
return
flag_
&
kDirty
;
}
private:
// Vector is an COW object.
bool
IsInCUDA
()
const
{
return
flag_
&
kDataInCUDA
;
}
details
::
COWPtr
<
VectorData
>
m_
;
bool
IsInCPU
()
const
{
return
flag_
&
kDataInCPU
;
}
static
void
WaitPlace
(
const
platform
::
Place
place
)
{
if
(
platform
::
is_gpu_place
(
place
))
{
platform
::
DeviceContextPool
::
Instance
()
.
Get
(
boost
::
get
<
platform
::
CUDAPlace
>
(
place
))
->
Wait
();
}
}
static
T
&
EmptyDummy
()
{
static
T
dummy
=
T
();
return
dummy
;
}
mutable
int
flag_
;
mutable
Tensor
cpu_vec_
;
mutable
Tensor
cuda_vec_
;
size_t
size_
;
};
};
#else // PADDLE_WITH_CUDA
#else // PADDLE_WITH_CUDA
...
...
paddle/fluid/operators/detection_map_op.h
浏览文件 @
bd79e046
...
@@ -76,8 +76,8 @@ class DetectionMAPOpKernel : public framework::OpKernel<T> {
...
@@ -76,8 +76,8 @@ class DetectionMAPOpKernel : public framework::OpKernel<T> {
auto
ap_type
=
GetAPType
(
ctx
.
Attr
<
std
::
string
>
(
"ap_type"
));
auto
ap_type
=
GetAPType
(
ctx
.
Attr
<
std
::
string
>
(
"ap_type"
));
int
class_num
=
ctx
.
Attr
<
int
>
(
"class_num"
);
int
class_num
=
ctx
.
Attr
<
int
>
(
"class_num"
);
auto
label_lod
=
in_label
->
lod
();
auto
&
label_lod
=
in_label
->
lod
();
auto
detect_lod
=
in_detect
->
lod
();
auto
&
detect_lod
=
in_detect
->
lod
();
PADDLE_ENFORCE_EQ
(
label_lod
.
size
(),
1UL
,
PADDLE_ENFORCE_EQ
(
label_lod
.
size
(),
1UL
,
"Only support one level sequence now."
);
"Only support one level sequence now."
);
PADDLE_ENFORCE_EQ
(
label_lod
[
0
].
size
(),
detect_lod
[
0
].
size
(),
PADDLE_ENFORCE_EQ
(
label_lod
[
0
].
size
(),
detect_lod
[
0
].
size
(),
...
@@ -166,11 +166,11 @@ class DetectionMAPOpKernel : public framework::OpKernel<T> {
...
@@ -166,11 +166,11 @@ class DetectionMAPOpKernel : public framework::OpKernel<T> {
auto
labels
=
framework
::
EigenTensor
<
T
,
2
>::
From
(
input_label
);
auto
labels
=
framework
::
EigenTensor
<
T
,
2
>::
From
(
input_label
);
auto
detect
=
framework
::
EigenTensor
<
T
,
2
>::
From
(
input_detect
);
auto
detect
=
framework
::
EigenTensor
<
T
,
2
>::
From
(
input_detect
);
auto
label_lod
=
input_label
.
lod
();
auto
&
label_lod
=
input_label
.
lod
();
auto
detect_lod
=
input_detect
.
lod
();
auto
&
detect_lod
=
input_detect
.
lod
();
int
batch_size
=
label_lod
[
0
].
size
()
-
1
;
int
batch_size
=
label_lod
[
0
].
size
()
-
1
;
auto
label_index
=
label_lod
[
0
];
auto
&
label_index
=
label_lod
[
0
];
for
(
int
n
=
0
;
n
<
batch_size
;
++
n
)
{
for
(
int
n
=
0
;
n
<
batch_size
;
++
n
)
{
std
::
map
<
int
,
std
::
vector
<
Box
>>
boxes
;
std
::
map
<
int
,
std
::
vector
<
Box
>>
boxes
;
...
@@ -274,7 +274,6 @@ class DetectionMAPOpKernel : public framework::OpKernel<T> {
...
@@ -274,7 +274,6 @@ class DetectionMAPOpKernel : public framework::OpKernel<T> {
output_true_pos
->
set_lod
(
true_pos_lod
);
output_true_pos
->
set_lod
(
true_pos_lod
);
output_false_pos
->
set_lod
(
false_pos_lod
);
output_false_pos
->
set_lod
(
false_pos_lod
);
return
;
}
}
void
GetInputPos
(
const
framework
::
Tensor
&
input_pos_count
,
void
GetInputPos
(
const
framework
::
Tensor
&
input_pos_count
,
...
@@ -292,7 +291,7 @@ class DetectionMAPOpKernel : public framework::OpKernel<T> {
...
@@ -292,7 +291,7 @@ class DetectionMAPOpKernel : public framework::OpKernel<T> {
auto
SetData
=
[](
const
framework
::
LoDTensor
&
pos_tensor
,
auto
SetData
=
[](
const
framework
::
LoDTensor
&
pos_tensor
,
std
::
map
<
int
,
std
::
vector
<
std
::
pair
<
T
,
int
>>>&
pos
)
{
std
::
map
<
int
,
std
::
vector
<
std
::
pair
<
T
,
int
>>>&
pos
)
{
const
T
*
pos_data
=
pos_tensor
.
data
<
T
>
();
const
T
*
pos_data
=
pos_tensor
.
data
<
T
>
();
auto
pos_data_lod
=
pos_tensor
.
lod
()[
0
];
auto
&
pos_data_lod
=
pos_tensor
.
lod
()[
0
];
for
(
size_t
i
=
0
;
i
<
pos_data_lod
.
size
()
-
1
;
++
i
)
{
for
(
size_t
i
=
0
;
i
<
pos_data_lod
.
size
()
-
1
;
++
i
)
{
for
(
size_t
j
=
pos_data_lod
[
i
];
j
<
pos_data_lod
[
i
+
1
];
++
j
)
{
for
(
size_t
j
=
pos_data_lod
[
i
];
j
<
pos_data_lod
[
i
+
1
];
++
j
)
{
T
score
=
pos_data
[
j
*
2
];
T
score
=
pos_data
[
j
*
2
];
...
@@ -317,20 +316,23 @@ class DetectionMAPOpKernel : public framework::OpKernel<T> {
...
@@ -317,20 +316,23 @@ class DetectionMAPOpKernel : public framework::OpKernel<T> {
std
::
map
<
int
,
std
::
vector
<
std
::
pair
<
T
,
int
>>>*
false_pos
)
const
{
std
::
map
<
int
,
std
::
vector
<
std
::
pair
<
T
,
int
>>>*
false_pos
)
const
{
int
batch_size
=
gt_boxes
.
size
();
int
batch_size
=
gt_boxes
.
size
();
for
(
int
n
=
0
;
n
<
batch_size
;
++
n
)
{
for
(
int
n
=
0
;
n
<
batch_size
;
++
n
)
{
auto
image_gt_boxes
=
gt_boxes
[
n
];
auto
&
image_gt_boxes
=
gt_boxes
[
n
];
for
(
auto
it
=
image_gt_boxes
.
begin
();
it
!=
image_gt_boxes
.
end
();
++
it
)
{
for
(
auto
&
image_gt_box
:
image_gt_boxes
)
{
size_t
count
=
0
;
size_t
count
=
0
;
auto
labeled_bboxes
=
it
->
second
;
auto
&
labeled_bboxes
=
image_gt_box
.
second
;
if
(
evaluate_difficult
)
{
if
(
evaluate_difficult
)
{
count
=
labeled_bboxes
.
size
();
count
=
labeled_bboxes
.
size
();
}
else
{
}
else
{
for
(
size_t
i
=
0
;
i
<
labeled_bboxes
.
size
();
++
i
)
for
(
auto
&
box
:
labeled_bboxes
)
{
if
(
!
(
labeled_bboxes
[
i
].
is_difficult
))
++
count
;
if
(
!
box
.
is_difficult
)
{
++
count
;
}
}
}
}
if
(
count
==
0
)
{
if
(
count
==
0
)
{
continue
;
continue
;
}
}
int
label
=
i
t
->
first
;
int
label
=
i
mage_gt_box
.
first
;
if
(
label_pos_count
->
find
(
label
)
==
label_pos_count
->
end
())
{
if
(
label_pos_count
->
find
(
label
)
==
label_pos_count
->
end
())
{
(
*
label_pos_count
)[
label
]
=
count
;
(
*
label_pos_count
)[
label
]
=
count
;
}
else
{
}
else
{
...
...
paddle/fluid/operators/extract_rows_op.cc
浏览文件 @
bd79e046
...
@@ -50,7 +50,7 @@ class ExtractRowsOp : public framework::OperatorBase {
...
@@ -50,7 +50,7 @@ class ExtractRowsOp : public framework::OperatorBase {
auto
&
in
=
scope
.
FindVar
(
Input
(
"X"
))
->
Get
<
framework
::
SelectedRows
>
();
auto
&
in
=
scope
.
FindVar
(
Input
(
"X"
))
->
Get
<
framework
::
SelectedRows
>
();
auto
out
=
scope
.
FindVar
(
Output
(
"Out"
))
->
GetMutable
<
framework
::
LoDTensor
>
();
auto
out
=
scope
.
FindVar
(
Output
(
"Out"
))
->
GetMutable
<
framework
::
LoDTensor
>
();
auto
in_rows
=
in
.
rows
();
auto
&
in_rows
=
in
.
rows
();
auto
out_dim
=
framework
::
make_ddim
(
auto
out_dim
=
framework
::
make_ddim
(
std
::
vector
<
int64_t
>
{
static_cast
<
int64_t
>
(
in_rows
.
size
()),
1
});
std
::
vector
<
int64_t
>
{
static_cast
<
int64_t
>
(
in_rows
.
size
()),
1
});
auto
dst_ptr
=
out
->
mutable_data
<
int64_t
>
(
out_dim
,
in
.
place
());
auto
dst_ptr
=
out
->
mutable_data
<
int64_t
>
(
out_dim
,
in
.
place
());
...
...
paddle/fluid/operators/math/selected_rows_functor.cu
浏览文件 @
bd79e046
...
@@ -60,11 +60,9 @@ struct SelectedRowsAdd<platform::CUDADeviceContext, T> {
...
@@ -60,11 +60,9 @@ struct SelectedRowsAdd<platform::CUDADeviceContext, T> {
auto
out_place
=
context
.
GetPlace
();
auto
out_place
=
context
.
GetPlace
();
PADDLE_ENFORCE
(
platform
::
is_gpu_place
(
out_place
));
PADDLE_ENFORCE
(
platform
::
is_gpu_place
(
out_place
));
memory
::
Copy
(
memory
::
Copy
(
boost
::
get
<
platform
::
CUDAPlace
>
(
out_place
),
out_data
,
boost
::
get
<
platform
::
CUDAPlace
>
(
out_place
),
out_data
,
boost
::
get
<
platform
::
CUDAPlace
>
(
in1_place
),
in1_data
,
boost
::
get
<
platform
::
CUDAPlace
>
(
in1_place
),
in1_data
,
in1_value
.
numel
()
*
sizeof
(
T
),
context
.
stream
());
in1_value
.
numel
()
*
sizeof
(
T
),
reinterpret_cast
<
const
platform
::
CUDADeviceContext
&>
(
context
).
stream
());
auto
*
in2_data
=
in2_value
.
data
<
T
>
();
auto
*
in2_data
=
in2_value
.
data
<
T
>
();
memory
::
Copy
(
boost
::
get
<
platform
::
CUDAPlace
>
(
out_place
),
memory
::
Copy
(
boost
::
get
<
platform
::
CUDAPlace
>
(
out_place
),
...
@@ -148,7 +146,7 @@ struct SelectedRowsAddTo<platform::CUDADeviceContext, T> {
...
@@ -148,7 +146,7 @@ struct SelectedRowsAddTo<platform::CUDADeviceContext, T> {
auto
in1_height
=
input1
.
height
();
auto
in1_height
=
input1
.
height
();
PADDLE_ENFORCE_EQ
(
in1_height
,
input2
->
height
());
PADDLE_ENFORCE_EQ
(
in1_height
,
input2
->
height
());
framework
::
Vector
<
int64_t
>
in1_rows
(
input1
.
rows
()
);
auto
&
in1_rows
=
input1
.
rows
(
);
auto
&
in2_rows
=
*
(
input2
->
mutable_rows
());
auto
&
in2_rows
=
*
(
input2
->
mutable_rows
());
auto
&
in1_value
=
input1
.
value
();
auto
&
in1_value
=
input1
.
value
();
...
...
paddle/fluid/operators/sum_op.h
浏览文件 @
bd79e046
...
@@ -123,7 +123,6 @@ class SumKernel : public framework::OpKernel<T> {
...
@@ -123,7 +123,6 @@ class SumKernel : public framework::OpKernel<T> {
out_value
->
Resize
(
framework
::
make_ddim
(
in_dim
));
out_value
->
Resize
(
framework
::
make_ddim
(
in_dim
));
out_value
->
mutable_data
<
T
>
(
context
.
GetPlace
());
out_value
->
mutable_data
<
T
>
(
context
.
GetPlace
());
// if all the input sparse vars are empty, no need to
// if all the input sparse vars are empty, no need to
// merge these vars.
// merge these vars.
if
(
first_dim
==
0UL
)
{
if
(
first_dim
==
0UL
)
{
...
...
python/paddle/fluid/tests/unittests/op_test.py
浏览文件 @
bd79e046
...
@@ -348,7 +348,7 @@ class OpTest(unittest.TestCase):
...
@@ -348,7 +348,7 @@ class OpTest(unittest.TestCase):
actual_t
,
expect_t
,
atol
=
atol
,
equal_nan
=
equal_nan
),
actual_t
,
expect_t
,
atol
=
atol
,
equal_nan
=
equal_nan
),
"Output ("
+
out_name
+
") has diff at "
+
str
(
place
)
+
"Output ("
+
out_name
+
") has diff at "
+
str
(
place
)
+
"
\n
Expect "
+
str
(
expect_t
)
+
"
\n
"
+
"But Got"
+
"
\n
Expect "
+
str
(
expect_t
)
+
"
\n
"
+
"But Got"
+
str
(
actual_t
))
str
(
actual_t
)
+
" in class "
+
self
.
__class__
.
__name__
)
if
isinstance
(
expect
,
tuple
):
if
isinstance
(
expect
,
tuple
):
self
.
assertListEqual
(
actual
.
recursive_sequence_lengths
(),
self
.
assertListEqual
(
actual
.
recursive_sequence_lengths
(),
expect
[
1
],
"Output ("
+
out_name
+
expect
[
1
],
"Output ("
+
out_name
+
...
...
python/paddle/fluid/tests/unittests/test_detection_map_op.py
浏览文件 @
bd79e046
...
@@ -20,6 +20,7 @@ import six
...
@@ -20,6 +20,7 @@ import six
import
sys
import
sys
import
collections
import
collections
import
math
import
math
import
paddle.fluid
as
fluid
from
op_test
import
OpTest
from
op_test
import
OpTest
...
@@ -32,7 +33,7 @@ class TestDetectionMAPOp(OpTest):
...
@@ -32,7 +33,7 @@ class TestDetectionMAPOp(OpTest):
self
.
detect
=
np
.
array
(
self
.
detect
).
astype
(
'float32'
)
self
.
detect
=
np
.
array
(
self
.
detect
).
astype
(
'float32'
)
self
.
mAP
=
np
.
array
(
self
.
mAP
).
astype
(
'float32'
)
self
.
mAP
=
np
.
array
(
self
.
mAP
).
astype
(
'float32'
)
if
(
len
(
self
.
class_pos_count
)
>
0
)
:
if
len
(
self
.
class_pos_count
)
>
0
:
self
.
class_pos_count
=
np
.
array
(
self
.
class_pos_count
).
astype
(
self
.
class_pos_count
=
np
.
array
(
self
.
class_pos_count
).
astype
(
'int32'
)
'int32'
)
self
.
true_pos
=
np
.
array
(
self
.
true_pos
).
astype
(
'float32'
)
self
.
true_pos
=
np
.
array
(
self
.
true_pos
).
astype
(
'float32'
)
...
@@ -273,7 +274,7 @@ class TestDetectionMAPOp11Point(TestDetectionMAPOp):
...
@@ -273,7 +274,7 @@ class TestDetectionMAPOp11Point(TestDetectionMAPOp):
class
TestDetectionMAPOpMultiBatch
(
TestDetectionMAPOp
):
class
TestDetectionMAPOpMultiBatch
(
TestDetectionMAPOp
):
def
init_test_case
(
self
):
def
init_test_case
(
self
):
super
(
TestDetectionMAPOpMultiBatch
,
self
).
init_test_case
()
super
(
TestDetectionMAPOpMultiBatch
,
self
).
init_test_case
()
self
.
class_pos_count
=
[
0
,
2
,
1
]
self
.
class_pos_count
=
[
0
,
2
,
1
,
0
]
self
.
true_pos_lod
=
[[
0
,
3
,
2
]]
self
.
true_pos_lod
=
[[
0
,
3
,
2
]]
self
.
true_pos
=
[[
0.7
,
1.
],
[
0.3
,
0.
],
[
0.2
,
1.
],
[
0.8
,
0.
],
[
0.1
,
1.
]]
self
.
true_pos
=
[[
0.7
,
1.
],
[
0.3
,
0.
],
[
0.2
,
1.
],
[
0.8
,
0.
],
[
0.1
,
1.
]]
self
.
false_pos_lod
=
[[
0
,
3
,
2
]]
self
.
false_pos_lod
=
[[
0
,
3
,
2
]]
...
...
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