[Performance] Add --enable-ep-weight-filter CLI option

[esmeetu]

Summary

• Add --enable-ep-weight-filter opt-in CLI flag to skip non-local expert weights during model loading when EP is active
• Makes the EP weight filter from [Performance][Model Loader] Skip non-local expert weights during EP model loading #37136 an explicit opt-in feature
• No behavior change without the flag
• Regression mentioned in [Bugfix] Fix EP weight filter breaking EPLB and NVFP4 accuracy #37322

Usage

vllm serve model \
  --enable-expert-parallel \
  --enable-ep-weight-filter

Without --enable-ep-weight-filter, loading behavior is identical to main.

Test plan

• vllm serve without --enable-ep-weight-filter — no behavior change
• vllm serve --enable-expert-parallel --enable-ep-weight-filter on per-expert MoE — correct loading, reduced I/O
• Non-MoE model with flag — no effect
• 3D fused-expert model with flag — no effect (filter returns None)

🤖 Generated with Claude Code

[gemini-code-assist]

Code Review

This pull request introduces an opt-in command-line flag --enable-ep-weight-filter to optimize model loading for Mixture-of-Experts models with expert parallelism. The changes correctly add the new configuration option and integrate it into the model loading logic. My main feedback is to add a validation check to ensure enable_expert_parallel is active when enable_ep_weight_filter is used, to prevent silent failures from misconfiguration and improve user experience.

[gemini-code-assist]

To improve robustness and prevent user confusion from misconfiguration, it's a good practice to validate that enable_expert_parallel is enabled when enable_ep_weight_filter is used. Currently, if a user enables enable_ep_weight_filter without enable_expert_parallel, it will fail silently.

Consider adding a validation check in the _validate_parallel_config method of this class, similar to how enable_eplb is validated. This would raise an error for invalid combinations.

Example:

if self.enable_ep_weight_filter and not self.enable_expert_parallel:
    raise ValueError(
        "enable_expert_parallel must be True to use enable_ep_weight_filter."
    )