[train_rlhf_llama] When using vllm，Time-consuming optimization is not obvious as expectation.

When running the train_rlhf_llama.sh script for LLaMA2-7B, the performance gain from using vLLM as the inference backend is not significant compared to Megatron (approximately a 20% improvement). According to some other reports, the expected improvement should be around 200%. How can it be promoted?

Start with train_rlhf_llama.sh and reproduce the LLaMA2-7B comparison between vLLM and Megatron, recording the reported roughly 20% gain. Trace the timing from that entry point to identify the relevant performance bottleneck; done means a measured explanation and improvement toward the expected result, with reproduction details documented.

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