fix metax & update ppu

[helloyongyang]

No description provided.

[gemini-code-assist]

Code Review

This pull request updates the parallel environment initialization in lightx2v_platform/base/metax_cuda.py to use torch.cuda.set_device instead of torch.npu.set_device. Feedback points out that using the global rank (dist.get_rank()) to set the CUDA device will cause failures in multi-node distributed training, and suggests using the local rank from the LOCAL_RANK environment variable instead.

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[gemini-code-assist]

Using dist.get_rank() to set the CUDA device will cause failures in multi-node distributed training. dist.get_rank() returns the global rank, which can exceed the number of GPUs available on a single node (e.g., rank 8 on a second 8-GPU node). Instead, you should use the local rank (typically retrieved from the LOCAL_RANK environment variable) to set the device.

Suggested change

	torch.cuda.set_device(dist.get_rank())
	import os
	torch.cuda.set_device(int(os.environ.get("LOCAL_RANK", 0)))