我该如何解决这个YoloV8问题

Question

有人能告诉我为什么我会遇到这个错误吗？

Traceback (most recent call last):
  File "<string>", line 1, in <module>
  File "D:\Programming\Pythoncode\Resources\lib\multiprocessing\spawn.py", line 116, in spawn_main
    exitcode = _main(fd, parent_sentinel)
  File "D:\Programming\Pythoncode\Resources\lib\multiprocessing\spawn.py", line 125, in _main
    prepare(preparation_data)
  File "D:\Programming\Pythoncode\Resources\lib\multiprocessing\spawn.py", line 236, in prepare
    _fixup_main_from_path(data['init_main_from_path'])
  File "D:\Programming\Pythoncode\Resources\lib\multiprocessing\spawn.py", line 287, in _fixup_main_from_path
    main_content = runpy.run_path(main_path,
  File "D:\Programming\Pythoncode\Resources\lib\runpy.py", line 288, in run_path        
    return _run_module_code(code, init_globals, run_name,
  File "D:\Programming\Pythoncode\Resources\lib\runpy.py", line 97, in _run_module_code 
    _run_code(code, mod_globals, init_globals,
  File "D:\Programming\Pythoncode\Resources\lib\runpy.py", line 87, in _run_code        
    exec(code, run_globals)
  File "d:\Programming\Pythoncode\Computer_Vision\test.py", line 7, in <module>
    results = model.train(data="D:\Programming\Pythoncode\Computer_Vision\data.yaml", epochs=1, imgsz=640)
  File "D:\Programming\Pythoncode\Resources\lib\site-packages\ultralytics\engine\model.py", line 644, in train
    self.trainer.train()
  File "D:\Programming\Pythoncode\Resources\lib\site-packages\ultralytics\engine\trainer.py", line 208, in train
    self._do_train(world_size)
  File "D:\Programming\Pythoncode\Resources\lib\site-packages\ultralytics\engine\trainer.py", line 322, in _do_train
    self._setup_train(world_size)
  File "D:\Programming\Pythoncode\Resources\lib\site-packages\ultralytics\engine\trainer.py", line 286, in _setup_train
    self.train_loader = self.get_dataloader(self.trainset, batch_size=batch_size, rank=RANK, mode="train")
  File "D:\Programming\Pythoncode\Resources\lib\site-packages\ultralytics\models\yolo\detect\train.py", line 55, in get_dataloader
    return build_dataloader(dataset, batch_size, workers, shuffle, rank)  # return dataloader
  File "D:\Programming\Pythoncode\Resources\lib\site-packages\ultralytics\data\build.py", line 114, in build_dataloader
    return InfiniteDataLoader(
  File "D:\Programming\Pythoncode\Resources\lib\site-packages\ultralytics\data\build.py", line 40, in __init__
    self.iterator = super().__iter__()
  File "D:\Programming\Pythoncode\Resources\lib\site-packages\torch\utils\data\dataloader.py", line 439, in __iter__
    return self._get_iterator()
  File "D:\Programming\Pythoncode\Resources\lib\site-packages\torch\utils\data\dataloader.py", line 387, in _get_iterator
    return _MultiProcessingDataLoaderIter(self)
  File "D:\Programming\Pythoncode\Resources\lib\site-packages\torch\utils\data\dataloader.py", line 1040, in __init__
    w.start()
  File "D:\Programming\Pythoncode\Resources\lib\multiprocessing\process.py", line 121, in start
    self._popen = self._Popen(self)
  File "D:\Programming\Pythoncode\Resources\lib\multiprocessing\context.py", line 224, in _Popen
    return _default_context.get_context().Process._Popen(process_obj)
  File "D:\Programming\Pythoncode\Resources\lib\multiprocessing\context.py", line 327, in _Popen
    return Popen(process_obj)
  File "D:\Programming\Pythoncode\Resources\lib\multiprocessing\popen_spawn_win32.py", line 45, in __init__
    prep_data = spawn.get_preparation_data(process_obj._name)
  File "D:\Programming\Pythoncode\Resources\lib\multiprocessing\spawn.py", line 154, in get_preparation_data
    _check_not_importing_main()
  File "D:\Programming\Pythoncode\Resources\lib\multiprocessing\spawn.py", line 134, in _check_not_importing_main
    raise RuntimeError('''
RuntimeError:
        An attempt has been made to start a new process before the
        current process has finished its bootstrapping phase.

This probably means that you are not using fork to start your
child processes and you have forgotten to use the proper idiom
in the main module:

    if __name__ == '__main__':
        freeze_support()
        ...

The "freeze_support()" line can be omitted if the program
is not going to be frozen to produce an executable.

这是主要的代码：

from ultralytics import YOLO



model = YOLO('yolov8n.pt')

results = model.train(data="D:\Programming\Pythoncode\Computer_Vision\data.yaml", epochs=1, imgsz=640)

而data.yaml文件里有这些内容：

train: 
    D:\Programming\Pythoncode\Computer_Vision\train\images val:
    D:\Programming\Pythoncode\Computer_Vision\valid\images test:
    D:\Programming\Pythoncode\Computer_Vision\test\images

nc: 1
names: ['fire']

计算机视觉错误调试深度学习 yolov8 数据集配置

我该如何解决这个YoloV8问题

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