fix: LMIC base class multi_bit support in build() and compile()

Section 45.8: Single-run enforcement fix (no retries), trainer.py max(1,max_retries) patch

feat: comprehensive W&B logging + retry=0 hardening

fix(dtp): support multi_bit mode - look for binary_accuracy keys

feat: multi-bit labeling (Wu et al. TCHES 2024)

feat: wire sigmoid gates through training pipeline (trainer, CLI, agent)

feat: add DTP EMA smoothing to prevent weight oscillations from cosine annealing warm restarts

feat: implement DB-MTL gradient balancing callback (Lin et al., Neural Networks 2023)

feat: add XLA jit_compile support for LMIC/LMIC-TSBN

feat: add gradient clipping (clipnorm) to LMIC/LMIC-TSBN — Phase 1 stability fix

feat: add per-layer gradient norm logging to W&B — logs shared conv, per-task BN, head, gate norms every epoch

feat: add Focal Loss + Cosine Annealing for LMIC v6

feat: LMIC-TSBN model + persistence fixes across restarts

feat: LMIC architecture - Localized Multi-Input CNN for 16-byte key recovery

feat: training speed optimizations — mixed precision, vectorized augmentation, cached eval predictions

v3: Add DTP + Spectral Decoupling, fix GradNorm OOM, fix _fail_job cancel