How to configure the parameters of the main thread in the case of multiple workers? about sanic-guide

[ahopkins]

I am not entirely sure what you are trying to achieve. Maybe main_process_start?

https://sanicframework.org/en/guide/basics/listeners.html

[gclm]

no way. This seems to be configured every time the worker is created. At present, an error is still reported.
config code：

@app.listener("main_process_start")
async def init_processor(app, loop):
    mp.set_start_method('spawn')
    app.processor = Processor(MODEL_WEIGHTS, MODEL_LABELS)

error message：

[2021-12-02 16:36:56 +0800] [64614] [ERROR] Exception occurred while handling uri: 'http://localhost:8000/predict/file'
Traceback (most recent call last):
  File "handle_request", line 83, in handle_request
    class Sanic(BaseSanic, metaclass=TouchUpMeta):
  File "/opt/projects/ai-server/server.py", line 29, in predict_file
    result = app.processor.process(img)
  File "/opt/projects/ai-server/models/Detect.py", line 82, in process
    img = self.pre_processor(image)
  File "/opt/projects/ai-server/models/Detect.py", line 74, in pre_processor
    img = torch.from_numpy(img).to(self.device)
  File "/home/breakfox/anaconda3/envs/ai-server/lib/python3.9/site-packages/torch/cuda/__init__.py", line 204, in _lazy_init
    raise RuntimeError(
RuntimeError: Cannot re-initialize CUDA in forked subprocess. To use CUDA with multiprocessing, you must use the 'spawn' start method
Exception occurred while handling uri: 'http://localhost:8000/predict/file'
Traceback (most recent call last):
  File "handle_request", line 83, in handle_request
    class Sanic(BaseSanic, metaclass=TouchUpMeta):
  File "/opt/projects/ai-server/server.py", line 29, in predict_file
    result = app.processor.process(img)
  File "/opt/projects/ai-server/models/Detect.py", line 82, in process
    img = self.pre_processor(image)
  File "/opt/projects/ai-server/models/Detect.py", line 74, in pre_processor
    img = torch.from_numpy(img).to(self.device)
  File "/home/breakfox/anaconda3/envs/ai-server/lib/python3.9/site-packages/torch/cuda/__init__.py", line 204, in _lazy_init
    raise RuntimeError(
RuntimeError: Cannot re-initialize CUDA in forked subprocess. To use CUDA with multiprocessing, you must use the 'spawn' start method

error message docs: https://discuss.pytorch.org/t/not-using-multiprocessing-but-getting-cuda-error-re-forked-subprocess/54610
How to configure it in this case?