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489e06d1
编写于
9月 19, 2018
作者:
xiebaiyuan
浏览文件
操作
浏览文件
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差异文件
Merge remote-tracking branch 'upstream/develop' into develop
上级
ed5a5afd
f100efc9
变更
8
显示空白变更内容
内联
并排
Showing
8 changed file
with
39 addition
and
25 deletion
+39
-25
src/fpga/api.cpp
src/fpga/api.cpp
+21
-5
src/fpga/api.h
src/fpga/api.h
+0
-6
src/framework/tensor.h
src/framework/tensor.h
+1
-5
src/io/executor.cpp
src/io/executor.cpp
+6
-4
src/io/executor.h
src/io/executor.h
+1
-1
src/io/paddle_mobile.cpp
src/io/paddle_mobile.cpp
+2
-2
src/io/paddle_mobile.h
src/io/paddle_mobile.h
+1
-1
test/net/test_resnet.cpp
test/net/test_resnet.cpp
+7
-1
未找到文件。
src/fpga/api.cpp
浏览文件 @
489e06d1
...
...
@@ -17,17 +17,21 @@ limitations under the License. */
#include <sys/ioctl.h>
#include <sys/mman.h>
#include <algorithm>
#include <map>
#include "bias_scale.h"
#include "filter.h"
#include "image.h"
#define FPGA_TEST_MODE
//
#define PADDLE_MOBILE_OS_LINUX
#define PADDLE_MOBILE_OS_LINUX
namespace
paddle_mobile
{
namespace
fpga
{
static
int
fd
=
-
1
;
static
const
char
*
device_path
=
"/dev/fpgadrv0"
;
#ifdef PADDLE_MOBILE_OS_LINUX
static
std
::
map
<
void
*
,
size_t
>
memory_map
;
#endif
static
inline
int
do_ioctl
(
int
req
,
const
void
*
arg
)
{
#ifdef PADDLE_MOBILE_OS_LINUX
...
...
@@ -48,10 +52,13 @@ int open_device() {
// memory management;
void
*
fpga_malloc
(
size_t
size
)
{
DLOG
<<
size
<<
" bytes allocated"
;
static
uint64_t
counter
=
0
;
counter
+=
size
;
DLOG
<<
size
<<
" bytes allocated. Total "
<<
counter
<<
" bytes"
;
#ifdef PADDLE_MOBILE_OS_LINUX
return
reinterpret_cast
<
void
*>
(
mmap64
(
NULL
,
size
,
PROT_READ
|
PROT_WRITE
,
MAP_SHARED
,
fd
,
0
));
auto
ptr
=
mmap64
(
nullptr
,
size
,
PROT_READ
|
PROT_WRITE
,
MAP_SHARED
,
fd
,
0
);
memory_map
.
insert
(
std
::
make_pair
(
ptr
,
size
));
return
ptr
;
#else
return
malloc
(
size
);
#endif
...
...
@@ -59,7 +66,16 @@ void *fpga_malloc(size_t size) {
void
fpga_free
(
void
*
ptr
)
{
#ifdef PADDLE_MOBILE_OS_LINUX
munmap
(
ptr
,
0
);
static
uint64_t
counter
=
0
;
size_t
size
=
0
;
auto
iter
=
memory_map
.
find
(
ptr
);
// std::map<void *, size_t>::iterator
if
(
iter
!=
memory_map
.
end
())
{
size
=
iter
->
second
;
munmap
(
ptr
,
size
);
memory_map
.
erase
(
iter
);
}
counter
+=
size
;
DLOG
<<
size
<<
" bytes freed. Total "
<<
counter
<<
" bytes"
;
#else
free
(
ptr
);
#endif
...
...
src/fpga/api.h
浏览文件 @
489e06d1
...
...
@@ -20,8 +20,6 @@ limitations under the License. */
#include <limits>
#include "framework/tensor.h"
// memory management;
namespace
paddle_mobile
{
namespace
fpga
{
...
...
@@ -45,9 +43,6 @@ struct MemoryCopyArgs {
size_t
size
;
};
/**
Conv and Pooling kernel
*/
struct
KernelArgs
{
uint32_t
width
;
uint32_t
height
;
...
...
@@ -109,7 +104,6 @@ struct PoolingArgs {
struct
ImageOutputArgs
output
;
};
// elementwise add arguments
struct
EWAddArgs
{
bool
relu_enabled
;
...
...
src/framework/tensor.h
浏览文件 @
489e06d1
...
...
@@ -289,12 +289,8 @@ class Tensor {
virtual
std
::
type_index
type
()
const
{
return
type_
;
}
virtual
void
set_type
(
std
::
type_index
type
)
{
type_
=
type
;
}
#ifndef PADDLE_MOBILE_FPGA
/*! the pointer of memory block. */
std
::
unique_ptr
<
uint8_t
,
memory
::
PODDeleter
<
uint8_t
>>
ptr_
;
#else
std
::
shared_ptr
<
uint8_t
>
ptr_
;
#endif
/*! the size of memory block. */
size_t
size_
;
...
...
src/io/executor.cpp
浏览文件 @
489e06d1
...
...
@@ -662,13 +662,15 @@ void Executor<Dtype, P>::FeedData(const framework::Tensor &t) {
};
template
<
typename
Dtype
,
Precision
P
>
std
::
shared_ptr
<
framework
::
Tensor
>
Executor
<
Dtype
,
P
>::
FetchResult
()
{
std
::
shared_ptr
<
framework
::
Tensor
>
Executor
<
Dtype
,
P
>::
FetchResult
(
int
id
)
{
std
::
shared_ptr
<
framework
::
BlockDesc
>
to_predict_block
=
to_predict_program_
->
Block
(
0
);
auto
&
ops
=
ops_of_block_
[
*
to_predict_block
.
get
()];
auto
last_op
=
ops
.
rbegin
();
auto
output_map
=
(
*
last_op
)
->
Outputs
();
std
::
vector
<
std
::
string
>
out_keys
=
(
*
last_op
)
->
GetOutKeys
();
PADDLE_MOBILE_ENFORCE
(
id
<
ops
.
size
(),
"Index out of range"
);
auto
last_op
=
id
<
0
?
ops
[
ops
.
size
()
-
1
]
:
ops
[
id
];
auto
output_map
=
last_op
->
Outputs
();
std
::
vector
<
std
::
string
>
out_keys
=
last_op
->
GetOutKeys
();
PADDLE_MOBILE_ENFORCE
(
!
out_keys
.
empty
(),
"the last op contains no output"
);
auto
*
output_tensor
=
framework
::
GetVarValue
<
framework
::
LoDTensor
>
(
out_keys
[
0
],
output_map
,
*
(
program_
.
scope
));
...
...
src/io/executor.h
浏览文件 @
489e06d1
...
...
@@ -99,7 +99,7 @@ class Executor {
public:
void
InjectVariable
(
const
framework
::
Tensor
&
t
,
string
var_name
);
void
FeedData
(
const
framework
::
Tensor
&
t
);
std
::
shared_ptr
<
framework
::
Tensor
>
FetchResult
();
std
::
shared_ptr
<
framework
::
Tensor
>
FetchResult
(
int
id
=
-
1
);
void
Predict_From_To
(
int
start
=
0
,
int
end
=
-
1
);
void
Predict_From
(
int
start
);
void
Predict_To
(
int
end
);
...
...
src/io/paddle_mobile.cpp
浏览文件 @
489e06d1
...
...
@@ -138,8 +138,8 @@ void PaddleMobile<Dtype, P>::FeedData(const framework::Tensor &t) {
};
template
<
typename
Dtype
,
Precision
P
>
std
::
shared_ptr
<
framework
::
Tensor
>
PaddleMobile
<
Dtype
,
P
>::
FetchResult
()
{
return
executor_
->
FetchResult
();
std
::
shared_ptr
<
framework
::
Tensor
>
PaddleMobile
<
Dtype
,
P
>::
FetchResult
(
int
id
)
{
return
executor_
->
FetchResult
(
id
);
};
template
<
typename
Dtype
,
Precision
P
>
...
...
src/io/paddle_mobile.h
浏览文件 @
489e06d1
...
...
@@ -97,7 +97,7 @@ class PaddleMobile {
public:
void
InjectVariable
(
const
framework
::
Tensor
&
t
,
string
var_name
);
void
FeedData
(
const
framework
::
Tensor
&
t
);
std
::
shared_ptr
<
framework
::
Tensor
>
FetchResult
();
std
::
shared_ptr
<
framework
::
Tensor
>
FetchResult
(
int
id
=
-
1
);
void
Predict_From_To
(
int
start
=
0
,
int
end
=
-
1
);
void
Predict_From
(
int
start
);
void
Predict_To
(
int
end
);
...
...
test/net/test_resnet.cpp
浏览文件 @
489e06d1
...
...
@@ -54,7 +54,13 @@ int main() {
paddle_mobile
.
FeedData
(
input_tensor
);
paddle_mobile
.
Predict_To
(
10
);
paddle_mobile
.
Predict_From
(
10
);
paddle_mobile
.
FetchResult
();
auto
tensor_ptr
=
paddle_mobile
.
FetchResult
(
9
);
std
::
cout
<<
"Tensor element number for op[9]: "
<<
tensor_ptr
->
numel
()
<<
std
::
endl
;
auto
result_ptr
=
paddle_mobile
.
FetchResult
();
std
::
cout
<<
"Result tensor element number: "
<<
result_ptr
->
numel
()
<<
std
::
endl
;
auto
time4
=
time
();
std
::
cout
<<
"predict cost :"
<<
time_diff
(
time3
,
time4
)
<<
"ms"
<<
std
::
endl
;
...
...
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