CUDA error, related to multiprocessing

I'm tried to run LightMHC with Cuda 11.8.0

Command:

```bash
python LightMHC/lightmhc/inference.py data.input_csv_path=xray.lightmhc.csv data.output_dir=lighmhc-xray model.n_cpus=32 model.use_gpu=true model.batch_size=64
```

I got an error message:

```python
multiprocessing.pool.RemoteTraceback:
"""
Traceback (most recent call last):
File "/home/baakmanc/miniconda3/envs/lightmhc/lib/python3.8/multiprocessing/pool.py", line 125, in worker
result = (True, func(*args, **kwds))
File "/home/baakmanc/miniconda3/envs/lightmhc/lib/python3.8/multiprocessing/pool.py", line 51, in starmapstar
return list(itertools.starmap(args[0], args[1]))
File "/home/baakmanc/LightMHC/lightmhc/inference.py", line 77, in workflow
model = model.to(device)
File "/home/baakmanc/miniconda3/envs/lightmhc/lib/python3.8/site-packages/torch/nn/modules/module.py", line 673, in to
return self._apply(convert)
File "/home/baakmanc/miniconda3/envs/lightmhc/lib/python3.8/site-packages/torch/nn/modules/module.py", line 387, in _apply
module._apply(fn)
File "/home/baakmanc/miniconda3/envs/lightmhc/lib/python3.8/site-packages/torch/nn/modules/module.py", line 387, in _apply
module._apply(fn)
File "/home/baakmanc/miniconda3/envs/lightmhc/lib/python3.8/site-packages/torch/nn/modules/module.py", line 387, in _apply
module._apply(fn)
File "/home/baakmanc/miniconda3/envs/lightmhc/lib/python3.8/site-packages/torch/nn/modules/module.py", line 409, in _apply
param_applied = fn(param)
File "/home/baakmanc/miniconda3/envs/lightmhc/lib/python3.8/site-packages/torch/nn/modules/module.py", line 671, in convert
return t.to(device, dtype if t.is_floating_point() or t.is_complex() else None, non_blocking)
File "/home/baakmanc/miniconda3/envs/lightmhc/lib/python3.8/site-packages/torch/cuda/__init__.py", line 160, 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
"""
```

I found that the start method can be set to 'spawn' by following the instructions here:
https://pytorch.org/docs/stable/notes/multiprocessing.html

That fixed the issue for me. Just letting you know.