[Bugfix][Quantization] Reuse online NVFP4 MoE kernel across reloads

[S1ro1]

Purpose

Online NVFP4 MoE models re-run process_weights_after_loading whenever fresh BF16 weights are loaded and quantized in place. _setup_kernel currently also replaces the MoE kernel and quantization-config objects on every reload. Compiled and captured execution paths still reference the original kernel object, so replacing it can leave reloads executing against stale state and eventually produce non-finite outputs.

This change keeps the online NVFP4 MoE kernel and its quantization config stable for the lifetime of the layer. Weight conversion and process_weights_after_loading remain outside the guard and still run on every reload, so each fresh set of BF16 weights is quantized and installed as before.

Related to #41670 and #48902, but not a duplicate: this covers online NVFP4 and deliberately preserves per-reload weight processing.

AI assistance (OpenAI Codex) was used for investigation, implementation, and test drafting. I reviewed and understand the change.

Test Plan

• Add a focused lifecycle test that calls _setup_kernel twice and verifies:
  • weight conversion runs twice;
  • processed weights are installed twice;
  • the MoE kernel is constructed once;
  • the quantization config is constructed once.
• Run formatting and lint checks on the changed files.
• Run paired five-step Prime-RL jobs with online NVFP4, piecewise CUDA graphs, two ETP=4 inference replicas, and a BF16 trainer. The jobs differ only by this fix.

Test Result

• uvx ruff check tests/quantization/test_online.py vllm/model_executor/layers/quantization/online/nvfp4.py: passed.
• uvx ruff format --check tests/quantization/test_online.py vllm/model_executor/layers/quantization/online/nvfp4.py: passed.
• Focused lifecycle check in the deployment environment: two conversions, two weight-processing calls, one kernel construction, and one quantization-config construction.

Paired end-to-end result:

Run	Steps completed	Non-finite rollout errors
With fix	5	0
Without fix	5	16 at step 5 (11.1% of that rollout batch)

The fixed run completed all five reloads without an invalid response. The control first returned non-finite values after repeated reloads and recorded 16 provider errors in its fifth persisted batch.

No documentation change is needed because this restores the existing online-reload contract.

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Essential Elements of an Effective PR Description Checklist

• The purpose of the PR is described.
• The test plan is provided.
• Test and paired end-to-end results are provided.
• No documentation update is required.

[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, @S1ro1.

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

[aoshen02]

@S1ro1 Could you please resolve the conflict?