GRPOTrainer: Parallelism for updating named params

### Feature request

Running GRPOTrainer with an MOE like Qwen3/Qwen-30BA3B is incredibly slow because of move_model_to_vllm which loops through all the named params and sequentially updates the vLLM server for each of the named params. Since the MOE (128 experts) has a large number of named params, this step is slow.

Curious if we can do this updated step parallely?

https://github.com/huggingface/trl/blob/main/trl/trainer/grpo_trainer.py#L917-L920

### Motivation

Better support for MOE GRPO training

### Your contribution

Can submit PR if this is a viable approach