[Refactor] refactor humming linear and moe backends to use explicit layer configs

[jinzhen-lin]

This PR refactor the Humming linear and MoE backends to use explicit layer configs and tensors instead of passing vLLM layers into the backend.

Also update Humming CI coverage and pin the dependency to the latest upstream commit.

AI assistance (OpenAI Codex) was used.

[claude]

Claude Code Review

This pull request is from a fork — automated review is disabled. A repository maintainer can comment @claude review to run a one-time review.

[mergify]

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

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

[bnellnm]

Is it safe to delete all the parameters in the layer? I'm not very familiar with all the parameters used by linear layers but I'd be worried that there are other required parameters that might not be transformed that need to be preserved?

[jinzhen-lin]

Currently, all parameters in layer are tensors related to humming. A similar processing step has already been performed earlier in the same function (deleting all parameters and then recreating them). However, the logic in these two places can indeed be merged, and I have already combined them into one.

[bnellnm]

What is this method used for?

[jinzhen-lin]

vllm/vllm/model_executor/layers/fused_moe/modular_kernel.py

Lines 663 to 670 in 38a267c

	@staticmethod
	def _supports_batch_invariance() -> bool:
	"""
	Whether the kernel supports batch invariance, i.e. the output does not
	depend on the order of the tokens in the input batch. This is useful
	for determining if the kernel can used with VLLM_BATCH_INVARIANT=1.
	"""
	return False

Humming supports batch invariant, we need to override this method to make it work properly.

[bnellnm]

I didn't see it referenced anywhere else. Is it for future work?

[jinzhen-lin]

vllm/vllm/model_executor/layers/fused_moe/modular_kernel.py

Lines 577 to 578 in d0ce3da

	elif envs.VLLM_BATCH_INVARIANT and not cls._supports_batch_invariance():
	return False, _make_reason("batch invariance")

It is used for kernel filitering here.

[bnellnm]

Are you planning on eventually removing the layer argument here as well? Why not pass layer.humming_configs?

[jinzhen-lin]

This part cannot be removed for now, as it is responsible for reading various weight tensors. The weight preprocessing results of Humming may produce a few extra tensors compared to the original, for example, in the case of mxfp4 × fp8, Humming splits the e8m0 scale into a group scale plus a tensor scale / channel scale form. However, the mxfp4 MoE oracle does not reserve space for the tensor scale / channel scale.

I plan to address this in future work.

[bnellnm]

Ditto

[bnellnm]

Ditto

[mergify]

Hi @jinzhen-lin, the pre-commit checks have failed. Please run:

uv pip install pre-commit>=4.5.1
pre-commit install
pre-commit run --all-files

Then, commit the changes and push to your branch.

For future commits, pre-commit will run automatically on changed files before each commit.

[github-actions]

✅ Triggered Buildkite CI #82649 for commit e75e020ca591.

[mergify]

Hi @jinzhen-lin, the pre-commit checks have failed. Please run:

uv pip install pre-commit>=4.5.1
pre-commit install
pre-commit run --all-files

Then, commit the changes and push to your branch.

For future commits, pre-commit will run automatically on changed files before each commit.

[jinzhen-lin]

/ci run

[github-actions]

✅ Triggered Buildkite CI #82687 for commit 6c678f0d99f7.

[jinzhen-lin]

/ci run

[jinzhen-lin]

/ci run

[jinzhen-lin]

/ci run

[github-actions]

✅ Triggered Buildkite CI #82765 for commit 83f648991370.

[jinzhen-lin]

@mgoin The failed tests seem unreleated.

[mgoin]

Very nice work, appreciate it!!