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Author SHA1 Message Date
Alpamys 2292e81c3f feat(modality): v0.53.2 — lift Modality II stubs (distill + classifier + EBFT/GDPO + reasoning_effort)
Closes #132, #133, #135, #137. Records #71 ONNX QA (partial — tiny-gpt2
PASS, TinyLlama-1.1B blocked by host RAM during onnx.load post-process).

New trainer wrappers:
- DistillTrainerWrapper (soup_cli/trainer/distill.py) — student + frozen
  teacher, KL/JS divergence kernels scaled by T**2, device-bridge for HF
  Trainer auto-CUDA promotion, DataCollatorForSeq2Seq for variable-length
  loss-masked rows, separate trust_remote_code resolution per model.
- ClassifierTrainerWrapper (soup_cli/trainer/classifier.py) — single/multi
  label sequence classification, 1024-entry multi-label cap, label_names
  string-to-int resolution. Routes classifier / reranker / cross_encoder.

Live loss kernels:
- apply_ebft_loss (structured / strided) + attach_ebft_compute_loss (SFT)
- apply_gdpo_loss (standard / length_normalized / margin) +
  attach_gdpo_compute_loss (DPO). Both attach hooks idempotent.

Prompt-format wiring:
- apply_reasoning_effort_prefix injects gpt-oss
  <|reasoning_effort|>{low,medium,high}<|/reasoning_effort|> header.
- build_assistant_only_labels(train_on_eot=True) keeps EOT/EOS unmasked.

Bugs surfaced + fixed during Wave 3 CPU smoke (regression guards in tests):
- Distill collator did not pad pre-tokenised labels (variable-length crash)
- Distill compute_loss device-mismatch when HF Trainer auto-promoted
  student to CUDA while teacher stayed on CPU.

Tests: 7722 -> 7842 (+120 in test_v0532.py). 5 review agents run; every
CRITICAL/HIGH/MEDIUM/LOW finding fixed.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-13 12:56:50 +05:00