fix(cute_dsl): avoid MoE wrapper runner reference cycle (#3340)

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## 📌 Description

`CuteDslMoEWrapper` currently passes `self._forward_with_tactic` as a
bound method into `CuteDslFusedMoENvfp4Runner`, creating a strong
reference cycle: `wrapper -> runner -> bound method -> wrapper`. When
the wrapper is used with `use_cuda_graph=True`, this can keep
wrapper-owned CUDA graph resources alive after user code has dropped the
wrapper, until Python cyclic GC eventually runs.

This PR replaces that bound-method callback with a weakref trampoline.
The runner can still call into a live wrapper, but it no longer owns the
wrapper lifetime. This prevents stale wrapper CUDA resources from
surviving across same-process tests or later autotune runs.

## 🔍 Related Issues

https://github.com/flashinfer-ai/flashinfer/pull/3286
https://github.com/flashinfer-ai/flashinfer/pull/3301
https://github.com/flashinfer-ai/flashinfer/pull/3252

## 🚀 Pull Request Checklist

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request, please make sure the following items are complete.

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- [x] I have installed `pre-commit` by running `pip install pre-commit`
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and fixed any reported issues.

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## 🧪 Tests

Adds a focused regression test that warms a CUDA-graph wrapper, verifies
it is finalized before cyclic GC, and then runs a subsequent autotuned
wrapper call to ensure the output remains NaN-free.

- [x] Tests have been added or updated as needed.
- [x] All tests are passing (`unittest`, etc.).

## Reviewer Notes

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## Summary by CodeRabbit

* **Bug Fixes**
* Improved handling and cleanup of CUDA-graph wrappers to prevent
resource leaks and provide a clear error when a wrapper is no longer
available.

* **Tests**
* Added lifetime tests covering CUDA-graph wrappers before and after
autotune; verify stable, non-NaN outputs during autotune.

* **Documentation**
* Updated comment about cold-L2 cache behavior and noted follow-up to
re-enable it once a related issue is addressed.

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Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>