[Do Not Merge] - LoRA V1 Reference PR

[varun-sundar-rabindranath]

LoRA works end-to-end with this PR. However, this PR introduces a lot of changes that (some unnecessary) need to split up into smaller PRs. Putting up this PR as a reference for sub PRs.

Benchmarks:
Machine - 1xA100

Command:

VLLM_USE_V1="1" python3 benchmarks/benchmark_throughput.py --model  meta-llama/Llama-2-7b-hf --backend vllm   --dataset ./ShareGPT_V3_unfiltered_cleaned_split.json --num-prompts 1000  --max-loras 4  --max-lora-rank 8 --enable-lora --lora-path "yard1/llama-2-7b-sql-lora-test" -O 3

Throughput: 9.27 requests/s, 4462.35 total tokens/s, 2181.49 output tokens/s

python3 benchmarks/benchmark_throughput.py --model  meta-llama/Llama-2-7b-hf --backend vllm   --dataset ./ShareGPT_V3_unfiltered_cleaned_split.json --num-prompts 1000  --max-loras 4  --max-lora-rank 8 --enable-lora --lora-path "yard1/llama-2-7b-sql-lora-test" --num-scheduler-steps 8

Throughput: 9.60 requests/s, 4617.92 total tokens/s, 2257.54 output tokens/s

Plan for PR split:

• Base PR (changes to gpu_model_runner.py, v1 scheduler, and prefix caching) - [V1] LoRA Support #10957
• Changes to support torch.compile for LoRA
• Add LoRA kernels for V1
• Add and Test add/remove/pin LoRA functions for runtime Load/Unload of LoRAs.

[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, @varun-sundar-rabindranath.

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