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9385e500
编写于
11月 08, 2019
作者:
J
juncaipeng
提交者:
GitHub
11月 08, 2019
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delete useless detection_model_test.cc, test=develop (#2393)
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// Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#include <gflags/gflags.h>
#include <gtest/gtest.h>
#include <fstream>
#include <vector>
#include "lite/api/paddle_api.h"
#include "lite/api/paddle_use_kernels.h"
#include "lite/api/paddle_use_ops.h"
#include "lite/api/paddle_use_passes.h"
#include "lite/api/test_helper.h"
#include "lite/core/op_registry.h"
DEFINE_bool
(
is_run_model_optimize
,
false
,
"apply model_optimize_tool to model, use optimized model to test"
);
namespace
paddle
{
namespace
lite_api
{
void
OutputOptModel
(
const
std
::
string
&
load_model_dir
,
const
std
::
string
&
save_optimized_model_dir
)
{
lite_api
::
CxxConfig
config
;
config
.
set_model_dir
(
load_model_dir
);
config
.
set_valid_places
({
Place
{
TARGET
(
kX86
),
PRECISION
(
kFloat
)},
Place
{
TARGET
(
kARM
),
PRECISION
(
kFloat
)},
});
auto
predictor
=
lite_api
::
CreatePaddlePredictor
(
config
);
int
ret
=
system
(
paddle
::
lite
::
string_format
(
"rm -rf %s"
,
save_optimized_model_dir
.
c_str
())
.
c_str
());
if
(
ret
==
0
)
{
LOG
(
INFO
)
<<
"delete old optimized model "
<<
save_optimized_model_dir
;
}
predictor
->
SaveOptimizedModel
(
save_optimized_model_dir
,
LiteModelType
::
kNaiveBuffer
);
LOG
(
INFO
)
<<
"Load model from "
<<
load_model_dir
;
LOG
(
INFO
)
<<
"Save optimized model to "
<<
save_optimized_model_dir
;
}
#ifdef LITE_WITH_LIGHT_WEIGHT_FRAMEWORK
void
Run
(
const
std
::
string
&
model_dir
,
const
int
repeat
,
const
int
warmup_times
,
const
int
thread_num
)
{
// set config and create predictor
lite_api
::
MobileConfig
config
;
config
.
set_model_dir
(
model_dir
);
config
.
set_threads
(
thread_num
);
if
(
thread_num
==
1
)
{
config
.
set_power_mode
(
LITE_POWER_HIGH
);
}
else
{
config
.
set_power_mode
(
LITE_POWER_NO_BIND
);
}
auto
predictor
=
lite_api
::
CreatePaddlePredictor
(
config
);
// set input
auto
input_image
=
predictor
->
GetInput
(
0
);
input_image
->
Resize
({
1
,
3
,
300
,
300
});
auto
input_image_data
=
input_image
->
mutable_data
<
float
>
();
std
::
ifstream
read_file
(
"/data/local/tmp/pjc/ssd_img.txt"
);
if
(
!
read_file
.
is_open
())
{
LOG
(
INFO
)
<<
"read image file fail"
;
return
;
}
auto
input_shape
=
input_image
->
shape
();
int64_t
input_image_size
=
1
;
for
(
auto
t
:
input_shape
)
{
input_image_size
*=
t
;
}
for
(
int
i
=
0
;
i
<
input_image_size
;
i
++
)
{
read_file
>>
input_image_data
[
i
];
}
// warmup and run
for
(
int
i
=
0
;
i
<
warmup_times
;
++
i
)
{
predictor
->
Run
();
}
auto
start
=
lite
::
GetCurrentUS
();
for
(
int
i
=
0
;
i
<
repeat
;
++
i
)
{
predictor
->
Run
();
}
// show result
auto
end
=
lite
::
GetCurrentUS
();
LOG
(
INFO
)
<<
"================== Speed Report ==================="
;
LOG
(
INFO
)
<<
"Model: "
<<
FLAGS_model_dir
<<
", threads num "
<<
FLAGS_threads
<<
", warmup: "
<<
FLAGS_warmup
<<
", repeats: "
<<
FLAGS_repeats
<<
", spend "
<<
(
end
-
start
)
/
FLAGS_repeats
/
1000.0
<<
" ms in average."
;
auto
out
=
predictor
->
GetOutput
(
0
);
auto
out_data
=
out
->
data
<
float
>
();
LOG
(
INFO
)
<<
"output shape:"
;
auto
out_shape
=
out
->
shape
();
for
(
auto
t
:
out_shape
)
{
LOG
(
INFO
)
<<
t
;
}
LOG
(
INFO
)
<<
"output data:"
;
int
output_len
=
20
;
for
(
int
i
=
0
;
i
<
output_len
;
i
++
)
{
LOG
(
INFO
)
<<
out_data
[
i
];
}
}
#endif
}
// namespace lite_api
}
// namespace paddle
TEST
(
Faster_RCNN
,
test_arm
)
{
std
::
string
save_optimized_model_dir
;
if
(
FLAGS_is_run_model_optimize
)
{
save_optimized_model_dir
=
FLAGS_model_dir
+
"opt"
;
paddle
::
lite_api
::
OutputOptModel
(
FLAGS_model_dir
,
save_optimized_model_dir
);
}
std
::
string
run_model_dir
=
FLAGS_is_run_model_optimize
?
save_optimized_model_dir
:
FLAGS_model_dir
;
paddle
::
lite_api
::
Run
(
run_model_dir
,
FLAGS_repeats
,
FLAGS_threads
,
FLAGS_warmup
);
}
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