why is my fastapi or uvicorn getting shutdown?

Question

I am trying to run a service that uses simple transformers Roberta model to do classification. the inferencing script/function itself is working as expected when tested. when i include that with fast api its shutting down the server.

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

error :

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]

inferencing script :

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

update: tried with flask and the service is working but when adding uvicorn on top of flask its getting stuck in a loop of restart.

Answer 1

I have solved this issue by starting a process pool using multiprocessing explicitly.

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