我试图运行一个服务,使用简单的变压器罗伯塔模型进行分类。在测试时,推断脚本/函数本身正在按预期工作。当我用快速api包含它时,它会关闭服务器。
uvicorn==0.11.8
fastapi==0.61.1
simpletransformers==0.51.6
cmd : uvicorn --host 0.0.0.0 --port 5000 src.main:app
@app.get("/article_classify")
def classification(text:str):
"""function to classify article using a deep learning model.
Returns:
[type]: [description]
"""
_,_,result = inference(text)
return result
错误:
INFO: Started server process [8262]
INFO: Waiting for application startup.
INFO: Application startup complete.
INFO: Uvicorn running on http://0.0.0.0:5000 (Press CTRL+C to quit)
INFO: 127.0.0.1:36454 - "GET / HTTP/1.1" 200 OK
INFO: 127.0.0.1:36454 - "GET /favicon.ico HTTP/1.1" 404 Not Found
INFO: 127.0.0.1:36454 - "GET /docs HTTP/1.1" 200 OK
INFO: 127.0.0.1:36454 - "GET /openapi.json HTTP/1.1" 200 OK
before
100%|████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 17.85it/s]
INFO: Shutting down
INFO: Finished server process [8262]
推理脚本:
model_name = "checkpoint-3380-epoch-20"
model = MultiLabelClassificationModel("roberta","src/outputs/"+model_name)
def inference(input_text,model_name="checkpoint-3380-epoch-20"):
"""Function to run inverence on one sample text"""
#model = MultiLabelClassificationModel("roberta","src/outputs/"+model_name)
all_tags =[]
if isinstance(input_text,str):
print("before")
result ,output = model.predict([input_text])
print(result)
tags=[]
for idx,each in enumerate(result[0]):
if each==1:
tags.append(classes[idx])
all_tags.append(tags)
elif isinstance(input_text,list):
result ,output = model.predict(input_text)
tags=[]
for res in result :
for idx,each in enumerate(res):
if each==1:
tags.append(classes[idx])
all_tags.append(tags)
return result,output,all_tags
更新:尝试与烧瓶和服务是有效的,但当添加uvicorn之上的烧瓶,它会陷入一个重新启动的循环。
发布于 2021-01-11 05:48:01
我已经通过显式使用多处理启动一个进程池来解决这个问题。
from multiprocessing import set_start_method
from multiprocessing import Process, Manager
try:
set_start_method('spawn')
except RuntimeError:
pass
@app.get("/article_classify")
def classification(text:str):
"""function to classify article using a deep learning model.
Returns:
[type]: [description]
"""
manager = Manager()
return_result = manager.dict()
# as the inference is failing
p = Process(target = inference,args=(text,return_result,))
p.start()
p.join()
# print(return_result)
result = return_result['all_tags']
return result
发布于 2022-04-03 20:40:22
虽然接受的解决方案有效,但我想建议一种不那么麻烦的解决方案,使用uvicron
工作人员。
您可能想尝试将--workers 4
添加到您的CMD
中,这样它就可以读到:
uvicorn --host 0.0.0.0 --port 5000 --workers 4 src.main:app
发布于 2021-11-25 17:42:44
根据https://github.com/ThilinaRajapakse/simpletransformers/issues/761的说法,这与多处理有关。
我设置了args={'use_multiprocessing':False},并且web服务器不再关闭。
https://stackoverflow.com/questions/65505710
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