fix(monkey_patch): patch Q/K norms on existing Qwen models

[luca-888]

Summary

Patch self_attn.q_norm and k_norm when applying Liger to existing Qwen3, Qwen3 MoE, Qwen3 Next, Qwen3.5 and Qwen3.5 MoE instances.

Reuse each model's RMSNorm helper and respect rms_norm. Extend the existing instance tests following the Qwen3 VL/VL MoE and Gemma3 pattern: construct native HF instances first, then check Q/K norm forward bindings before and after patching. Also verify preserved weights and epsilon, casting settings, and unchanged Linear Attention norms.

Testing Done

• Hardware Type: H100 80GB
• Instance tests: 21 passed. All 13 new Q/K regression assertions fail before the fix and pass after it.
• RMSNorm numerical tests: 64 passed.
• Convergence: 16 passed, 1 known baseline failure, 5 existing skips.

The BF16 Qwen3 MoE with-logits failure also occurs on the base commit.

These results are from prior validation; tests were not rerun after switching to explicit model classes.

PyTorch 2.9.1 / CUDA 12.8, Triton 3.5.1, Transformers 5.15.1. Hybrid convergence uses FLA 0.5.2 and TileLang 0.1.14.

Before uses the existing Liger instance patch with native Q/K norms; After adds this fix. Both use matched random weights and inputs, BF16, SDPA, identical other kernel settings, and no torch.compile. Each runs in a separate process with warmup and five measurement rounds. Speedup is Before / After.

For these configurations, the patch covers all attention layers in Qwen3-8B (36/36) and Qwen3-30B-A3B (48/48). In Qwen3.5-9B and Qwen3.5-35B-A3B, it covers only the Full Attention layers (8/32 and 10/40); Linear Attention norms are unchanged.

Q/K norms and a single Full Attention module on one H100 80GB, forward + backward median time in ms:

Model	Batch × seq	Q+K Before → After	Speedup	Attention Before → After	Speedup
Qwen3-8B	4 × 2048	2.439 → 0.562	4.34×	8.883 → 6.705	1.32×
Qwen3-8B	1 × 8192	2.435 → 0.542	4.50×	13.552 → 11.269	1.20×
Qwen3.5-9B	4 × 2048	2.560 → 0.739	3.46×	10.763 → 8.802	1.22×
Qwen3.5-9B	1 × 8192	2.564 → 0.729	3.52×	16.063 → 14.108	1.14×
Qwen3-30B-A3B	4 × 2048	2.219 → 0.643	3.45×	7.071 → 5.280	1.34×
Qwen3-30B-A3B	1 × 8192	2.212 → 0.659	3.36×	11.597 → 9.858	1.18×
Qwen3.5-35B-A3B	4 × 2048	2.292 → 0.740	3.10×	8.248 → 6.324	1.30×
Qwen3.5-35B-A3B	1 × 8192	2.288 → 0.691	3.31×	13.475 → 11.539	1.17×

• run make test (targeted tests above; full suite not run)
• run make checkstyle (prior validation)
• run make test-convergence (targeted tests above; full suite not run)