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586775a9
编写于
6月 28, 2021
作者:
L
LDOUBLEV
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-239
tools/infer/benchmark_utils.py
tools/infer/benchmark_utils.py
+0
-232
tools/infer/predict_rec.py
tools/infer/predict_rec.py
+0
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tools/infer/predict_system.py
tools/infer/predict_system.py
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tools/infer/benchmark_utils.py
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fa2d08f2
# Copyright (c) 2021 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.
import
argparse
import
os
import
time
import
logging
import
paddle
import
paddle.inference
as
paddle_infer
from
pathlib
import
Path
CUR_DIR
=
os
.
path
.
dirname
(
os
.
path
.
abspath
(
__file__
))
class
PaddleInferBenchmark
(
object
):
def
__init__
(
self
,
config
,
model_info
:
dict
=
{},
data_info
:
dict
=
{},
perf_info
:
dict
=
{},
resource_info
:
dict
=
{},
save_log_path
:
str
=
""
,
**
kwargs
):
"""
Construct PaddleInferBenchmark Class to format logs.
args:
config(paddle.inference.Config): paddle inference config
model_info(dict): basic model info
{'model_name': 'resnet50'
'precision': 'fp32'}
data_info(dict): input data info
{'batch_size': 1
'shape': '3,224,224'
'data_num': 1000}
perf_info(dict): performance result
{'preprocess_time_s': 1.0
'inference_time_s': 2.0
'postprocess_time_s': 1.0
'total_time_s': 4.0}
resource_info(dict):
cpu and gpu resources
{'cpu_rss': 100
'gpu_rss': 100
'gpu_util': 60}
"""
# PaddleInferBenchmark Log Version
self
.
log_version
=
1.0
# Paddle Version
self
.
paddle_version
=
paddle
.
__version__
self
.
paddle_commit
=
paddle
.
__git_commit__
paddle_infer_info
=
paddle_infer
.
get_version
()
self
.
paddle_branch
=
paddle_infer_info
.
strip
().
split
(
': '
)[
-
1
]
# model info
self
.
model_info
=
model_info
# data info
self
.
data_info
=
data_info
# perf info
self
.
perf_info
=
perf_info
try
:
self
.
model_name
=
model_info
[
'model_name'
]
self
.
precision
=
model_info
[
'precision'
]
self
.
batch_size
=
data_info
[
'batch_size'
]
self
.
shape
=
data_info
[
'shape'
]
self
.
data_num
=
data_info
[
'data_num'
]
self
.
preprocess_time_s
=
round
(
perf_info
[
'preprocess_time_s'
],
4
)
self
.
inference_time_s
=
round
(
perf_info
[
'inference_time_s'
],
4
)
self
.
postprocess_time_s
=
round
(
perf_info
[
'postprocess_time_s'
],
4
)
self
.
total_time_s
=
round
(
perf_info
[
'total_time_s'
],
4
)
except
:
self
.
print_help
()
raise
ValueError
(
"Set argument wrong, please check input argument and its type"
)
# conf info
self
.
config_status
=
self
.
parse_config
(
config
)
self
.
save_log_path
=
save_log_path
# mem info
if
isinstance
(
resource_info
,
dict
):
self
.
cpu_rss_mb
=
int
(
resource_info
.
get
(
'cpu_rss_mb'
,
0
))
self
.
gpu_rss_mb
=
int
(
resource_info
.
get
(
'gpu_rss_mb'
,
0
))
self
.
gpu_util
=
round
(
resource_info
.
get
(
'gpu_util'
,
0
),
2
)
else
:
self
.
cpu_rss_mb
=
0
self
.
gpu_rss_mb
=
0
self
.
gpu_util
=
0
# init benchmark logger
self
.
benchmark_logger
()
def
benchmark_logger
(
self
):
"""
benchmark logger
"""
# Init logger
FORMAT
=
'%(asctime)s - %(name)s - %(levelname)s - %(message)s'
log_output
=
f
"
{
self
.
save_log_path
}
/
{
self
.
model_name
}
.log"
Path
(
f
"
{
self
.
save_log_path
}
"
).
mkdir
(
parents
=
True
,
exist_ok
=
True
)
logging
.
basicConfig
(
level
=
logging
.
INFO
,
format
=
FORMAT
,
handlers
=
[
logging
.
FileHandler
(
filename
=
log_output
,
mode
=
'w'
),
logging
.
StreamHandler
(),
])
self
.
logger
=
logging
.
getLogger
(
__name__
)
self
.
logger
.
info
(
f
"Paddle Inference benchmark log will be saved to
{
log_output
}
"
)
def
parse_config
(
self
,
config
)
->
dict
:
"""
parse paddle predictor config
args:
config(paddle.inference.Config): paddle inference config
return:
config_status(dict): dict style config info
"""
config_status
=
{}
config_status
[
'runtime_device'
]
=
"gpu"
if
config
.
use_gpu
()
else
"cpu"
config_status
[
'ir_optim'
]
=
config
.
ir_optim
()
config_status
[
'enable_tensorrt'
]
=
config
.
tensorrt_engine_enabled
()
config_status
[
'precision'
]
=
self
.
precision
config_status
[
'enable_mkldnn'
]
=
config
.
mkldnn_enabled
()
config_status
[
'cpu_math_library_num_threads'
]
=
config
.
cpu_math_library_num_threads
(
)
return
config_status
def
report
(
self
,
identifier
=
None
):
"""
print log report
args:
identifier(string): identify log
"""
if
identifier
:
identifier
=
f
"[
{
identifier
}
]"
else
:
identifier
=
""
self
.
logger
.
info
(
"
\n
"
)
self
.
logger
.
info
(
"---------------------- Paddle info ----------------------"
)
self
.
logger
.
info
(
f
"
{
identifier
}
paddle_version:
{
self
.
paddle_version
}
"
)
self
.
logger
.
info
(
f
"
{
identifier
}
paddle_commit:
{
self
.
paddle_commit
}
"
)
self
.
logger
.
info
(
f
"
{
identifier
}
paddle_branch:
{
self
.
paddle_branch
}
"
)
self
.
logger
.
info
(
f
"
{
identifier
}
log_api_version:
{
self
.
log_version
}
"
)
self
.
logger
.
info
(
"----------------------- Conf info -----------------------"
)
self
.
logger
.
info
(
f
"
{
identifier
}
runtime_device:
{
self
.
config_status
[
'runtime_device'
]
}
"
)
self
.
logger
.
info
(
f
"
{
identifier
}
ir_optim:
{
self
.
config_status
[
'ir_optim'
]
}
"
)
self
.
logger
.
info
(
f
"
{
identifier
}
enable_memory_optim:
{
True
}
"
)
self
.
logger
.
info
(
f
"
{
identifier
}
enable_tensorrt:
{
self
.
config_status
[
'enable_tensorrt'
]
}
"
)
self
.
logger
.
info
(
f
"
{
identifier
}
enable_mkldnn:
{
self
.
config_status
[
'enable_mkldnn'
]
}
"
)
self
.
logger
.
info
(
f
"
{
identifier
}
cpu_math_library_num_threads:
{
self
.
config_status
[
'cpu_math_library_num_threads'
]
}
"
)
self
.
logger
.
info
(
"----------------------- Model info ----------------------"
)
self
.
logger
.
info
(
f
"
{
identifier
}
model_name:
{
self
.
model_name
}
"
)
self
.
logger
.
info
(
f
"
{
identifier
}
precision:
{
self
.
precision
}
"
)
self
.
logger
.
info
(
"----------------------- Data info -----------------------"
)
self
.
logger
.
info
(
f
"
{
identifier
}
batch_size:
{
self
.
batch_size
}
"
)
self
.
logger
.
info
(
f
"
{
identifier
}
input_shape:
{
self
.
shape
}
"
)
self
.
logger
.
info
(
f
"
{
identifier
}
data_num:
{
self
.
data_num
}
"
)
self
.
logger
.
info
(
"----------------------- Perf info -----------------------"
)
self
.
logger
.
info
(
f
"
{
identifier
}
cpu_rss(MB):
{
self
.
cpu_rss_mb
}
, gpu_rss(MB):
{
self
.
gpu_rss_mb
}
, gpu_util:
{
self
.
gpu_util
}
%"
)
self
.
logger
.
info
(
f
"
{
identifier
}
total time spent(s):
{
self
.
total_time_s
}
"
)
self
.
logger
.
info
(
f
"
{
identifier
}
preprocess_time(ms):
{
round
(
self
.
preprocess_time_s
*
1000
,
1
)
}
, inference_time(ms):
{
round
(
self
.
inference_time_s
*
1000
,
1
)
}
, postprocess_time(ms):
{
round
(
self
.
postprocess_time_s
*
1000
,
1
)
}
"
)
def
print_help
(
self
):
"""
print function help
"""
print
(
"""Usage:
==== Print inference benchmark logs. ====
config = paddle.inference.Config()
model_info = {'model_name': 'resnet50'
'precision': 'fp32'}
data_info = {'batch_size': 1
'shape': '3,224,224'
'data_num': 1000}
perf_info = {'preprocess_time_s': 1.0
'inference_time_s': 2.0
'postprocess_time_s': 1.0
'total_time_s': 4.0}
resource_info = {'cpu_rss_mb': 100
'gpu_rss_mb': 100
'gpu_util': 60}
log = PaddleInferBenchmark(config, model_info, data_info, perf_info, resource_info)
log('Test')
"""
)
def
__call__
(
self
,
identifier
=
None
):
"""
__call__
args:
identifier(string): identify log
"""
self
.
report
(
identifier
)
tools/infer/predict_rec.py
浏览文件 @
586775a9
...
...
@@ -219,15 +219,12 @@ class TextRecognizer(object):
i
])
input_tensor
.
copy_from_cpu
(
inputs
[
i
])
self
.
predictor
.
run
()
self
.
rec_times
.
inference_time
.
end
()
outputs
=
[]
for
output_tensor
in
self
.
output_tensors
:
output
=
output_tensor
.
copy_to_cpu
()
outputs
.
append
(
output
)
preds
=
{
"predict"
:
outputs
[
2
]}
else
:
self
.
rec_times
.
preprocess_time
.
end
()
self
.
rec_times
.
inference_time
.
start
()
self
.
input_tensor
.
copy_from_cpu
(
norm_img_batch
)
self
.
predictor
.
run
()
...
...
@@ -239,8 +236,6 @@ class TextRecognizer(object):
rec_result
=
self
.
postprocess_op
(
preds
)
for
rno
in
range
(
len
(
rec_result
)):
rec_res
[
indices
[
beg_img_no
+
rno
]]
=
rec_result
[
rno
]
self
.
rec_times
.
postprocess_time
.
end
()
self
.
rec_times
.
img_num
+=
int
(
norm_img_batch
.
shape
[
0
])
return
rec_res
,
time
.
time
()
-
st
...
...
tools/infer/predict_system.py
浏览文件 @
586775a9
...
...
@@ -33,8 +33,7 @@ import tools.infer.predict_det as predict_det
import
tools.infer.predict_cls
as
predict_cls
from
ppocr.utils.utility
import
get_image_file_list
,
check_and_read_gif
from
ppocr.utils.logging
import
get_logger
from
tools.infer.utility
import
draw_ocr_box_txt
,
get_current_memory_mb
import
tools.infer.benchmark_utils
as
benchmark_utils
from
tools.infer.utility
import
draw_ocr_box_txt
logger
=
get_logger
()
...
...
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