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0582291c
编写于
11月 14, 2018
作者:
H
hjchen2
浏览文件
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差异文件
Merge branch 'dev-latest' of
https://github.com/hjchen2/paddle-mobile
into dev-latest
上级
39a281b8
c40d0048
变更
3
显示空白变更内容
内联
并排
Showing
3 changed file
with
10 addition
and
28 deletion
+10
-28
CMakeLists.txt
CMakeLists.txt
+3
-5
src/framework/executor.cpp
src/framework/executor.cpp
+7
-22
tools/toolchains/arm-android-neon.cmake
tools/toolchains/arm-android-neon.cmake
+0
-1
未找到文件。
CMakeLists.txt
浏览文件 @
0582291c
cmake_minimum_required
(
VERSION 3.0.0
)
option
(
USE_OPENMP
"openmp support"
ON
)
option
(
DEBUGING
"enable debug mode"
O
FF
)
option
(
USE_EXCEPTION
"use std exception"
O
FF
)
option
(
DEBUGING
"enable debug mode"
O
N
)
option
(
USE_EXCEPTION
"use std exception"
O
N
)
option
(
SYMBOL_HIDDEN
"symbol hidden"
OFF
)
# on when use jni or ios io
option
(
LOG_PROFILE
"log profile"
OFF
)
# select the platform to build
option
(
CPU
"armv7 with neon"
ON
)
option
(
GPU_MALI
"mali gpu"
OFF
)
...
...
@@ -15,7 +16,6 @@ if(FPGA)
option
(
FPGAV2
"fpga v2"
OFF
)
endif
()
project
(
paddle-mobile
)
file
(
GLOB_RECURSE PADDLE_MOBILE_CC src/*.cc src/*.cpp src/*.c src/*.mm
)
...
...
@@ -247,5 +247,3 @@ elseif(FPGA)
add_subdirectory
(
test
)
endif
()
add_subdirectory
(
test
)
src/framework/executor.cpp
浏览文件 @
0582291c
...
...
@@ -95,12 +95,13 @@ Executor<Dtype, P>::Executor(const framework::Program<Dtype> p, int batch_size,
}
template
<
typename
Dtype
>
void
LoadMemInternal
(
void
**
data
,
framework
::
LoDTensor
*
tensor
)
{
static
void
LoadMemInternal
(
void
**
data
,
framework
::
LoDTensor
*
tensor
,
bool
quant_uint8
=
false
)
{
char
**
data_buf
=
reinterpret_cast
<
char
**>
(
data
);
int64_t
size
=
tensor
->
numel
();
Dtype
*
tensor_data
=
tensor
->
mutable_data
<
Dtype
>
();
if
(
0
)
{
//
TODO(hjchen2)
should be moved into operator init function
if
(
quant_uint8
)
{
// should be moved into operator init function
float
min_value
;
float
max_value
;
memory
::
Copy
(
&
min_value
,
data_buf
,
sizeof
(
float
));
...
...
@@ -156,7 +157,8 @@ void Executor<Dtype, P>::LoadMemory(
// parse tensor from stream
switch
(
tensor_desc
.
DataType
())
{
case
framework
::
VARTYPE_TYPE_FP32
:
LoadMemInternal
<
float
>
(
reinterpret_cast
<
void
**>
(
data_buf
),
tensor
);
LoadMemInternal
<
float
>
(
reinterpret_cast
<
void
**>
(
data_buf
),
tensor
,
program_
.
quantification
);
break
;
case
framework
::
VARTYPE_TYPE_INT8
:
LoadMemInternal
<
int8_t
>
(
reinterpret_cast
<
void
**>
(
data_buf
),
tensor
);
...
...
@@ -263,7 +265,6 @@ std::shared_ptr<framework::Tensor> Executor<Dtype, P>::Predict(
framework
::
Variable
*
g_feed_value
=
program_
.
scope
->
Var
(
"feed"
);
framework
::
Tensor
*
feed_tensor
=
g_feed_value
->
GetMutable
<
framework
::
LoDTensor
>
();
DLOG
<<
"feed_tensor dim: "
<<
feed_tensor
->
dims
();
feed_tensor
->
Resize
(
t
.
dims
());
feed_tensor
->
ShareDataWith
(
t
);
std
::
shared_ptr
<
framework
::
BlockDesc
>
to_predict_block
=
...
...
@@ -298,16 +299,8 @@ std::shared_ptr<framework::Tensor> Executor<Dtype, P>::Predict(
for
(
int
i
=
0
;
i
<
profile
.
size
();
i
++
)
{
const
auto
&
pInfo
=
profile
[
i
];
uint64_t
timeCost
=
pInfo
.
runEnd
-
pInfo
.
runBegin
;
if
(
ops
[
i
]
->
Type
()
==
"conv2d"
)
{
auto
inputs
=
ops
[
i
]
->
Inputs
();
auto
*
filter
=
framework
::
GetVarValue
<
framework
::
LoDTensor
>
(
"Filter"
,
inputs
,
*
(
program_
.
scope
));
int
kernel_size
=
filter
->
dims
()[
2
];
_tp
[
ops
[
i
]
->
Type
()
+
"_"
+
std
::
to_string
(
kernel_size
)]
+=
timeCost
;
}
else
{
_tp
[
ops
[
i
]
->
Type
()]
+=
timeCost
;
}
}
printf
(
"====================[ profile ]======================
\n
"
);
using
prof_t
=
std
::
pair
<
std
::
string
,
uint64_t
>
;
std
::
vector
<
prof_t
>
_tv
(
_tp
.
begin
(),
_tp
.
end
());
...
...
@@ -376,14 +369,6 @@ std::shared_ptr<framework::LoDTensor> Executor<Dtype, P>::PredictLod(
for
(
int
i
=
0
;
i
<
profile
.
size
();
i
++
)
{
const
auto
&
pInfo
=
profile
[
i
];
uint64_t
timeCost
=
pInfo
.
runEnd
-
pInfo
.
runBegin
;
if
(
ops
[
i
]
->
Type
()
==
"conv2d"
)
{
auto
inputs
=
ops
[
i
]
->
Inputs
();
auto
input_keys
=
ops
[
i
]
->
GetInputKeys
();
auto
*
filter
=
framework
::
GetVarValue
<
framework
::
LoDTensor
>
(
input_keys
[
1
],
inputs
,
*
(
program_
.
scope
));
int
kernel_size
=
filter
->
dims
()[
2
];
printf
(
"kernel size: %d
\n
"
,
kernel_size
);
}
_tp
[
ops
[
i
]
->
Type
()]
+=
timeCost
;
}
printf
(
"====================[ profile ]======================
\n
"
);
...
...
tools/toolchains/arm-android-neon.cmake
浏览文件 @
0582291c
...
...
@@ -3,4 +3,3 @@ set(ANDROID_PIE TRUE)
set
(
ANDROID_STL
"c++_static"
)
set
(
ANDROID_PLATFORM
"android-22"
)
include
(
"
${
CMAKE_CURRENT_LIST_DIR
}
/../android-cmake/android.toolchain.cmake"
)
#include("/Users/chenhoujiang/Project/android-ndk-r16b/build/cmake/android.toolchain.cmake")
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