examples/altered_minds_channel_ladder/README.md

B4 — end-to-end proof that the 3-channel loop trains

Two proofs that the Composer 3-channel loss (grpo + α·sdpo_kl + β·trace_replay_dpo) runs end-to-end, closing the gap left by examples/composer_grpo_sdpo_smoke (which proved init but never fired the SDPO channel — its toy rollouts carry no error sites).

1. CPU proof — SDPO channel FIRES nonzero through the real collator

run.py — builds a REAL ComposerDataCollator batch from a trace with an error turn, so the shipped collator emits ctx_teacher_input_ids + student/teacher_response_idx (the ADR-011 alignment indices). Perturbs the student tokens at the aligned positions (mimicking the hint changing the recovery tokens) so the gathered student/teacher logits differ and the JSD is provably nonzero, then verifies a gradient flows.

$ python run.py
  proof path:            TinyLM-stub-with-differing-tokens
  SDPO JSD (sdpo_kl):    0.056547
  requires_grad:         True
  grad norm into model:  0.001593
  RESULT: PASS ✅ (SDPO channel FIRED nonzero via real collator indices)

Honest scope: the model is a deterministic CPU stub (no download); the collator alignment path is the real shipped code. Real-model path: ALTERED_MINDS_REAL_MODEL=1.

2. GPU proof — real Qwen2.5-0.5B trains, bf16, loss converges

modal_b4_gpu_smoke.py — runs the real 3-channel composition on Qwen/Qwen2.5-0.5B-Instruct on a Modal A10G in bf16: GRPO-proxy LM loss + α·SDPO (hint-conditioned teacher = same model, no-grad) + β·replay-margin, 30 AdamW steps.

$ modal run modal_b4_gpu_smoke.py --n-steps 30
  status              : PASS
  dtype               : torch.bfloat16
  sdpo_fired_nonzero  : True   (max sdpo_kl 0.1855)
  loss_trend_down     : True
  all_finite          : True
  loss first → last   : 4.7262 → 0.0050   (monotone decrease)

bf16 numerics finite throughout, SDPO channel nonzero, loss converges. Cost: ~$1-3 on A10G. Run date 2026-05-29; full curve in gpu_smoke_result.json.

The proxies (GRPO→LM-loss, replay→margin) stand in for the full PG / DPO accounting so the smoke runs without a rollout buffer or teacher set; the SDPO channel is the real generalized_jsd_loss path. A full GRPO run with a real reward and rollouts is the LMA-budget-gated next step (ADR-013).