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olivv-cs-ComfyUI-FunPack/web
digital-garbageandClaude Opus 4.8 d423d313fe Batch Training: sampler consumes Studio variant-packed conditioning (Phase 4 contract)
Per the Studio/sampler boundary law (Studio owns conditioning; sampler only samples), the
sampler no longer encodes anything. It now auto-detects when Studio has packed N shortcut
VARIANTS into positive — each scene entry tagged with 'funpack_batch_variant' = variant
index — via _split_batch_variants: if present, it samples one chain per variant (variant
count wins); otherwise it falls back to seed-only repeats of batch_iterations. Decisions:
'sampler loops, Studio varies' + 'pack into positive + markers'.

Each entry now saves its OWN conditioning (<id>.cond.pt) — identical across a seed-only
batch, distinct per variant — and the manifest records variant index + prompt per item.
Submit (batch_training.py) trains the VF per entry from its own cond, so variant batches
teach the model which prompt variant rated better (not just seed-quality variance). Studio
panel shows the variant tag + prompt per row.

Studio-side variant PRODUCTION (resolve shortcuts N times, encode, pack markers) is the
remaining half — a Studio/refiner feature, tracked next. Sampler side is ready for it.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-02 17:49:52 +03:00
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