[Misc]add coding benchmark for speculative decoding

[CXIAAAAA]

add likaixin/InstructCoder for speculative decoding benchmark throughput

to run instruct coder benchmark:

VLLM_WORKER_MULTIPROC_METHOD=spawn VLLM_USE_V1=1  python3 benchmarks/benchmark_throughput.py --dataset-name=instructcoder --model <you hf model> --input-len 1000 --output-len 100 --num-prompts 2048 --async-engine

to run random benchmark:

VLLM_WORKER_MULTIPROC_METHOD=spawn VLLM_USE_V1=1  python3 benchmarks/benchmark_throughput.py --dataset-name=random --model <you hf model> --input-len 1000 --output-len 100 --num-prompts 2048 --async-engine

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[youran-qi]

Thank you and LGTM!

For your references, here are the statistics about the input / output lengths (number of tokens) in this dataset. Not sure whether you want to change DEFAULT_OUTPUT_LEN accordingly

	avg	min	max
instruction + input	151	15	837
output	179	9	1317

[LiuXiaoxuanPKU]

LGTM, @ywang96 please also take a look in case I miss anything!

Also, I'm just wondering if it's possible to share some simple benchmark results on the instructcoder dataset, really appreciate it!

[LiuXiaoxuanPKU]

Could you add simple description about the dataset, such as 'it includes code-editing tasks such as comment insertion, code optimization, and code refactoring.'