fix: print every step + first-step timing to diagnose slow forward

fix: OOM at batch=256 — cap batch by logits memory, enable grad ckpt

perf: tune train_hyper_loop for 300-step convergence

Fix loss rebound: lower Muon LR (0.02→0.008), clamp ternary latents, steeper cosine decay

Upload chimera/training/loops.py

Fix NaN loss reporting: show nan instead of 0.0 when all steps in window are NaN

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feat: loops.py v11 — aligned with GENESIS engine, no distiller overhead"

feat: loops.py — integrate Muon + MTP + EMA distillation in training loop"

feat: train_hyper_loop with progressive looping, evolution loss feedback, no progressive_unfreeze default\n\nActivates dormant ch1mera paradigms:\n1. Progressive looping: 1→2→3 Parcae loops during training\n2. Evolution receives prev_loss for surprise-based memory writes\n3. progressive_unfreeze disabled by default (all layers train from start)\n4. Logs loop count and NaN-safe averaging"

fix: loops.py — use chimera_turbo v8 defaults (wd=0.01, warmup=750, β2=0.98) instead of hardcoded values"

fix: re-enable torch.compile in train_hyper_loop (STE graph breaks fixed)"

fix: train_hyper_loop grad_accum=1 (DataLoader already batches), better tok/s logging

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