[Spec Decode] Clean up spec decode example

[WoosukKwon]

This PR cleans up the spec decoding example, removing outdated parameters and print more metrics.

[github-actions]

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[gemini-code-assist]

Summary of Changes

Hello @WoosukKwon, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request focuses on refining the spec_decode.py example script. My aim was to clean up the command-line interface by removing obsolete parameters and to enhance the output by providing more comprehensive and accurate performance metrics for speculative decoding, making the example more relevant and informative.

Highlights

• Argument Cleanup: I've removed several outdated or unused command-line arguments (--dataset, --max-num-seqs, --draft-tp, --max-num-batched-tokens, --max-model-len) from the parse_args function in spec_decode.py to streamline the script's interface.
• Configuration Simplification: I've removed the draft_tensor_parallel_size and max_model_len parameters from the speculative_config dictionaries for both eagle and ngram methods, and also removed max_model_len from the LLM constructor call, aligning with the argument cleanup.
• Enhanced Metric Reporting: I've updated the script to print more detailed metrics, including total_num_output_tokens, num_draft_tokens, and num_accepted_tokens. The mean acceptance length calculation has also been updated to use these new metrics for more accurate reporting. Additionally, mtp has been added as a new choice for the --method argument.

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[gemini-code-assist]

Code Review

This PR cleans up the spec decoding example by removing outdated parameters and printing more metrics. There are a couple of issues that need to be addressed. The first is that the removed command-line arguments are still being used, which will cause the script to crash. The second is a potential division-by-zero error when calculating metrics.

[gemini-code-assist]

To prevent a potential ZeroDivisionError, add a condition to check if num_drafts is zero before performing the division.

Suggested change

	print(f"mean acceptance length: {1 + (num_accepted_tokens / num_drafts):.2f}")
	print(f"mean acceptance length: {1 + (num_accepted_tokens / num_drafts):.2f}")

[houseroad]

seems legit, maybe a condition to use 0 or num_accepted_tokens / num_drafts.

[draftbk]

I found there is a duplicated example and was wondering if we want to clean that up:

• https://github.com/vllm-project/vllm/blob/main/examples/offline_inference/eagle.py

[houseroad]

seems legit, maybe a condition to use 0 or num_accepted_tokens / num_drafts.

[WoosukKwon]

@draftbk Good catch. Let's remove it in this PR. IIRC, @ekagra-ranjan also found the redundancy.