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- config/arch/srm_v1.yaml: arch config for pretrain.py integration
- scripts/train_srm.py: standalone from-scratch trainer based on step4
(HRM training infra adapted for SRM joint operator)
The arch.yaml exposes κ, η, α, n_iters, n_aol_layers as Hydra params.
train_srm.py adds joint Lyapunov diagnostic via JVP on srm_block to verify
λ_1 ≤ log((1-α)+α·κ) per micro-step. Smoke tested with hidden=128, n_iters=4
on Sudoku 1k: empirical Lip 0.28 << bound 0.90.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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