Part A — BCO Trainer (Binary Classifier Optimization): new task='bco',
training.bco_beta, bco.yaml template, train+sweep routing. Internal
_split_dpo_rows_to_bco adapts paired DPO input to TRL's BCO unpaired
schema; skipped rows logged at DEBUG (mirrors v0.33.0 #47 policy).
Part B — Unified preference dispatcher: additive task='preference' +
training.preference_loss Literal {dpo,simpo,orpo,ipo,bco}. Legacy
task='dpo' / 'simpo' / 'orpo' / 'ipo' / 'bco' remain first-class —
the new surface is purely additive, not a breaking collapse.
_make_inner_cfg uses model_copy so re-validation never sees an
intermediate inconsistent state and the caller's cfg is never mutated.
Part C — KL-controlled DPO variants: dpo_beta_schedule (linear /
cosine / exponential) + dpo_beta_end + dpo_ref_regen_epochs [1, 1000].
BetaScheduleCallback resolves total_steps lazily in on_train_begin
(closes a first-cut bug where total_steps=0 silently emitted beta_end
for every step). RefModelRegenCallback uses load_state_dict(strict=True)
with WARNING-on-mismatch (closes a first-cut silent partial-copy
hazard). Gated to DPO-family tasks only; rejected on mlx backend with
distinct error message.
Part D — Multi-objective preference_loss_weights (2-5 entries, key
allowlist + null-byte rejection, sum-to-1 ±1e-6). Schema-level surface
only; live runtime weighted-loss combination deferred to v0.40.1 with
NotImplementedError stub-then-live (mirrors v0.27.0 MII / v0.37.0
multipack / v0.38.0 quant menu / v0.39.0 ReLoRA pattern).
Net +118 tests (4538 → 4656). All four review-agent waves clean
(Python / Code / Security / TDD).
Known limitation: BCOTrainerWrapper still hardcodes
trust_remote_code=True (carry-over of the v0.36.0 #63 family across
non-SFT trainers).
Also: add docs/ to .gitignore (internal-only docs going forward;
existing docs/QUANTIZATION.md from v0.38.0 stays tracked).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Alpamys