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体验新版 GitCode,发现更多精彩内容 >>
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d78f545c
编写于
5月 07, 2020
作者:
M
MRXLT
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
add ce script
上级
54597c48
变更
5
隐藏空白更改
内联
并排
Showing
5 changed file
with
72 addition
and
13 deletion
+72
-13
python/examples/bert/benchmark.py
python/examples/bert/benchmark.py
+21
-4
python/examples/bert/benchmark.sh
python/examples/bert/benchmark.sh
+9
-5
python/examples/bert/prepare_model.py
python/examples/bert/prepare_model.py
+5
-4
python/paddle_serving_client/utils/__init__.py
python/paddle_serving_client/utils/__init__.py
+12
-0
tools/serving_ce.sh
tools/serving_ce.sh
+25
-0
未找到文件。
python/examples/bert/benchmark.py
浏览文件 @
d78f545c
...
...
@@ -21,7 +21,7 @@ import sys
import
time
from
paddle_serving_client
import
Client
from
paddle_serving_client.utils
import
MultiThreadRunner
from
paddle_serving_client.utils
import
benchmark_args
from
paddle_serving_client.utils
import
benchmark_args
,
show_latency
from
batching
import
pad_batch_data
import
tokenization
import
requests
...
...
@@ -35,11 +35,18 @@ def single_func(idx, resource):
dataset
=
[]
for
line
in
fin
:
dataset
.
append
(
line
.
strip
())
profile_flags
=
False
latency_flags
=
False
if
os
.
getenv
(
"FLAGS_profile_client"
):
profile_flags
=
True
if
os
.
getenv
(
"FLAGS_serving_latency"
):
latency_flags
=
True
latency_list
=
[]
if
args
.
request
==
"rpc"
:
reader
=
BertReader
(
vocab_file
=
"vocab.txt"
,
max_seq_len
=
20
)
fetch
=
[
"pooled_output"
]
client
=
Client
()
client
.
load_client_config
(
args
.
model
)
...
...
@@ -47,11 +54,13 @@ def single_func(idx, resource):
start
=
time
.
time
()
for
i
in
range
(
turns
):
if
args
.
batch_size
>=
1
:
l_start
=
time
.
time
()
feed_batch
=
[]
b_start
=
time
.
time
()
for
bi
in
range
(
args
.
batch_size
):
feed_batch
.
append
(
reader
.
process
(
dataset
[
bi
]))
b_end
=
time
.
time
()
if
profile_flags
:
sys
.
stderr
.
write
(
"PROFILE
\t
pid:{}
\t
bert_pre_0:{} bert_pre_1:{}
\n
"
.
format
(
...
...
@@ -59,13 +68,17 @@ def single_func(idx, resource):
int
(
round
(
b_start
*
1000000
)),
int
(
round
(
b_end
*
1000000
))))
result
=
client
.
predict
(
feed
=
feed_batch
,
fetch
=
fetch
)
l_end
=
time
.
time
()
if
latency_flags
:
latency_list
.
append
(
l_end
*
1000
-
l_start
*
1000
)
else
:
print
(
"unsupport batch size {}"
.
format
(
args
.
batch_size
))
elif
args
.
request
==
"http"
:
raise
(
"not implemented"
)
end
=
time
.
time
()
return
[[
end
-
start
]]
return
[[
end
-
start
]
,
latency_list
]
if
__name__
==
'__main__'
:
...
...
@@ -78,13 +91,17 @@ if __name__ == '__main__':
result
=
multi_thread_runner
.
run
(
single_func
,
args
.
thread
,
{
"endpoint"
:
endpoint_list
,
"turns"
:
turns
})
end
=
time
.
time
()
total_cost
=
end
-
start
avg_cost
=
0
for
i
in
range
(
args
.
thread
):
avg_cost
+=
result
[
0
][
i
]
avg_cost
=
avg_cost
/
args
.
thread
end
=
time
.
time
()
total_cost
=
end
-
start
print
(
"total cost :{} s"
.
format
(
total_cost
))
print
(
"each thread cost :{} s. "
.
format
(
avg_cost
))
print
(
"qps :{} samples/s"
.
format
(
args
.
batch_size
*
args
.
thread
*
turns
/
total_cost
))
if
os
.
getenv
(
"FLAGS_serving_latency"
):
show_latency
(
result
[
1
])
python/examples/bert/benchmark.sh
浏览文件 @
d78f545c
...
...
@@ -2,24 +2,28 @@ rm profile_log
export
CUDA_VISIBLE_DEVICES
=
0,1,2,3
export
FLAGS_profile_server
=
1
export
FLAGS_profile_client
=
1
python
-m
paddle_serving_server_gpu.serve
--model
bert_seq20_model/
--port
9292
--thread
4
--gpu_ids
0,1,2,3 2> elog
>
stdlog &
export
FLAGS_serving_latency
=
1
python
-m
paddle_serving_server_gpu.serve
--model
$1
--port
9292
--thread
4
--gpu_ids
0,1,2,3 2> elog
>
stdlog &
sleep
5
#warm up
$PYTHONROOT
/bin/python benchmark.py
--thread
8
--batch_size
1
--model
./bert_seq20_client
/serving_client_conf.prototxt
--request
rpc
>
profile 2>&1
$PYTHONROOT
/bin/python benchmark.py
--thread
8
--batch_size
1
--model
$2
/serving_client_conf.prototxt
--request
rpc
>
profile 2>&1
for
thread_num
in
8 16 32
for
thread_num
in
4 8 16
do
for
batch_size
in
1 4 16 64 256
do
$PYTHONROOT
/bin/python benchmark.py
--thread
$thread_num
--batch_size
$batch_size
--model
./bert_seq20_client/serving_client_conf.prototxt
--request
rpc
>
profile 2>&1
$PYTHONROOT
/bin/python benchmark.py
--thread
$thread_num
--batch_size
$batch_size
--model
$2
/serving_client_conf.prototxt
--request
rpc
>
profile 2>&1
echo
"model name :"
$1
echo
"thread num :"
$thread_num
echo
"batch size :"
$batch_size
echo
"=================Done===================="
echo
"model name :
$1
"
>>
profile_log
echo
"batch size :
$batch_size
"
>>
profile_log
$PYTHONROOT
/bin/python ../util/show_profile.py profile
$thread_num
>>
profile_log
tail
-n
3 profile
>>
profile_log
tail
-n
8 profile
>>
profile_log
echo
""
>>
profile_log
done
done
...
...
python/examples/bert/prepare_model.py
浏览文件 @
d78f545c
...
...
@@ -17,10 +17,11 @@ import paddle.fluid as fluid
import
sys
import
paddle_serving_client.io
as
serving_io
model_name
=
"bert_chinese_L-12_H-768_A-12"
#model_name = "bert_chinese_L-12_H-768_A-12"
model_name
=
sys
.
argv
[
1
]
module
=
hub
.
Module
(
model_name
)
inputs
,
outputs
,
program
=
module
.
context
(
trainable
=
True
,
max_seq_len
=
int
(
sys
.
argv
[
1
]))
trainable
=
True
,
max_seq_len
=
int
(
sys
.
argv
[
2
]))
place
=
fluid
.
core_avx
.
CPUPlace
()
exe
=
fluid
.
Executor
(
place
)
input_ids
=
inputs
[
"input_ids"
]
...
...
@@ -37,8 +38,8 @@ feed_var_names = [
target_vars
=
[
pooled_output
,
sequence_output
]
serving_io
.
save_model
(
"
bert_seq{}_model"
.
format
(
sys
.
argv
[
1
]),
"
bert_seq{}_client"
.
format
(
sys
.
argv
[
1
]),
{
"
{}_seq{}_model"
.
format
(
sys
.
argv
[
1
],
sys
.
argv
[
2
]),
"
{}_seq{}_client"
.
format
(
sys
.
argv
[
1
],
sys
.
argv
[
2
]),
{
"input_ids"
:
input_ids
,
"position_ids"
:
position_ids
,
"segment_ids"
:
segment_ids
,
...
...
python/paddle_serving_client/utils/__init__.py
浏览文件 @
d78f545c
...
...
@@ -17,6 +17,7 @@ import sys
import
subprocess
import
argparse
from
multiprocessing
import
Pool
import
numpy
as
np
def
benchmark_args
():
...
...
@@ -35,6 +36,17 @@ def benchmark_args():
return
parser
.
parse_args
()
def
show_latency
(
latency_list
):
latency_array
=
np
.
array
(
latency_list
)
info
=
""
info
+=
"mean :{} ms
\n
"
.
format
(
np
.
mean
(
latency_array
))
info
+=
"median :{} ms
\n
"
.
format
(
np
.
median
(
latency_array
))
info
+=
"80 percent :{} ms
\n
"
.
format
(
np
.
percentile
(
latency_array
,
80
))
info
+=
"90 percent :{} ms
\n
"
.
format
(
np
.
percentile
(
latency_array
,
90
))
info
+=
"99 percent :{} ms
\n
"
.
format
(
np
.
percentile
(
latency_array
,
99
))
sys
.
stderr
.
write
(
info
)
class
MultiThreadRunner
(
object
):
def
__init__
(
self
):
pass
...
...
tools/serving_ce.sh
0 → 100644
浏览文件 @
d78f545c
set
-x
set
-v
function
get_model
(){
if
[
!
-d
"bert_cased_L-12_H-768_A-12_model"
]
;
then
python
-c
"from paddle_serving_app.models import ServingModels; models = ServingModels();
\
models.download(
\"
$1
\"
)"
tar
-xzf
$1
.tar.gz
fi
}
function
bert_demo
(){
cd
../python/examples/bert
python prepare_model.py bert_chinese_L-12_H-768_A-12 20
sh benchmark.sh bert_chinese_L-12_H-768_A-12_seq20_model bert_chinese_L-12_H-768_A-12_seq20_client
python prepare_model.py ernie_tiny 20
sh benchmark.sh ernie_tiny_seq20_model ernie_tiny_seq20_client
cd
-
}
function
imagenet_demo
(){
cd
../python/examples/imagenet
sh get_model.sh
}
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