Add haic0 patch for AMD kimi k2.5 MTP support

[haic0]

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[claude]

Claude Code Review

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[chunfangamd]

@haic0 could you please branch against the InferenceX repo directly and create the PR?

[chunfangamd]

It's better to leave the unrelated lines unmodified

[functionstackx]

thanks for the PR @haic0

We haven't thought much about the guidelines for MTP for models that dont natively ship with it as we didn't think we would include it for inferencexv3 & have previously rejected submissions for it #1026 (review) do you think we should include it for inferencex v3 i.e. the questions that need some thought is:

1. what speculator weight & speculator # of layers/arch should be used?
2. Can different vendors submit different speculator weights?
3. Can different vendors submit different speculator? If so, how you are maintain similar acceptance rate between vendors. i.e. [Model Runner V2] Enable forcing a specific acceptance rate during rejection sampling vllm-project/vllm#38045 --speculative-config '{"method": "eagle", "model": <eagle_model>, "num_speculative_tokens": 3, "rejection_sample_method": "synthetic", "synthetic_acceptance_rate": <test-value>}' if you are doing this, how do we ensure that the specific AR distribution implementation is similar across different frameworks?
4. should we be using lightseekorg/kimi-k2.6-eagle3 https://github.com/vllm-project/recipes/pull/347/changes ?

We already have 3 different models that natively ship with MTP (deepseek, glm5, qwen3.5), is it worth it to spend time thinking about MTP for models that don't come natively with MTP?

[chunfangamd]

The corresponding file benchmarks/single_node/kimik2.5_int4_mi325x_mtp.sh is missing

[chunfangamd]

The corresponding file benchmarks/single_node/kimik2.5_int4_mi300x_mtp.sh is missing