[Core] Change multiproc method default to spawn

[russellb]

The default of fork is known to be problematic. Python itself is changing the default to spawn. The new default is expected to be in place for Python 3.14.

Python references for the change to the default:

• multiprocessing's default posix start method of 'fork' is broken: change to `'forkserver' || 'spawn' python/cpython#84559
• GH-84559: Deprecate fork being the multiprocessing default. python/cpython#100618

We also have several places where this option had to be set to spawn to make tests work. The AMD code even checks and overrides the value if it's not set to spawn.

Simplify things for everyone and just default to spawn, but leave the option in place just in case, at least for now.

[github-actions]

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[russellb]

for reference since i was just looking around ... some other places I've seen advise against fork breaking things (multithreaded things in particular)

• https://docs.habana.ai/en/latest/PyTorch/Getting_Started_with_PyTorch_and_Gaudi/Getting_Started_with_PyTorch.html?highlight=multiprocessing#to[…]ers -- "If training scripts use multiprocessing with multiple workers for PyTorch dataloader, change the start method to spawn or forkserver ..."
• Use 'spawn' multiprocessing method instead of fork instructlab/instructlab#957 -- "The fork method is not safe in multi-threaded environments. It is also incompatible with some hardware accelerators."
• https://pytorch.org/docs/stable/multiprocessing.html#sharing-cuda-tensors -- "Sharing CUDA tensors between processes is supported only in Python 3, using a spawn or forkserver start methods."
• https://pytorch.org/docs/stable/notes/multiprocessing.html -- "The CUDA runtime does not support the fork start method; either the spawn or forkserver start method are required to use CUDA in subprocesses."

[russellb]

In some private chat, it was pointed out that this will break user code using the LLM class if their code is not protected by if name == “main” so this isn’t a good idea for now at least