Apply torch.compile to fused_moe/grouped_topk

[mgoin]

Inspired by sgl-project/sglang@1ebe1d6. This improves the generation latency for deepseek models due to the large number of experts. For DeepSeek-Coder-V2-Lite-Instruct we see an increase of 154 -> 163 tokens/s or 5% improvement at bs=1 on H100

script:

VLLM_MLA_DISABLE=1 python benchmarks/benchmark_latency.py --model deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct --max-model-len 2048 --trust-remote-code --batch-size 1 --input-len 128 --output-len 512

main:

Avg prompt throughput: 51.1 tokens/s, Avg generation throughput: 154.8 tokens/s, Running: 1 reqs, Swapped: 0 reqs, Pending: 0 reqs, GPU KV cache usage: 0.1%, CPU KV cache usage: 0.0%.

this pr:

Avg prompt throughput: 51.2 tokens/s, Avg generation throughput: 163.8 tokens/s, Running: 1 reqs, Swapped: 0 reqs, Pending: 0 reqs, GPU KV cache usage: 0.3%, CPU KV cache usage: 0.0%.

[github-actions]

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[mergify]

This pull request has merge conflicts that must be resolved before it can be
merged. Please rebase the PR, @mgoin.

https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/syncing-a-fork