- Admission fails fast with AdmissionInfeasible on infeasible/deadlocked reservations instead of a
10M-iteration busy-spin: no-progress detection in run_to_completion/run_interleaved via a real
progress token, plus feasibility pre-checks (need > pool capacity).
- Compute budget is now a refundable concurrency gate (release() refunds spent), not a
never-refunded lifetime cap that silently deadlocks.
- §7.1: the text-encoder feature CacheKey carries adapter_versions + precision (no stale serve across
te-LoRA stacks); per-component weight versions mean a transformer-only RL weight sync no longer
flushes the frozen text-encoder cache (component-scoped invalidation, not wholesale).
- Interleave gate flags symmetric-empty output instead of passing it vacuously.
- skipped_steps counted only when the override is actually consumed; BatchScheduler wired for round
batch-accounting (metric renamed stepped_units); ResidualCache.get cleanup; stream chunks carry a
latent preview payload; dead progress-vars removed.
- 5 regression tests added for the previously-untested paths. 54 tests pass (pytest + zero-dep runner).
A scoped, CPU-testable realization of design_v3.md — the architecture where the atomic unit
is a typed (recipe, runtime) ModelCard, the model owns loop semantics while the runtime owns
loop lifecycle, one resident instance runs many loops, and training records behavior on the
same loops it serves.
Implements:
- card/ loop/ runtime/ cache/ memory/ parallel/ parity/ extend/ program/ request/ training/
spanning design_v3 §4-§13: ModelCard + validate(); driven loops (init/next/advance/finalize);
step-interleaving Engine with reservation-before-admission + per-class caches keyed by CacheKey;
the C0-C4 consistency ladder + the non-negotiable batch-of-N interleave parity gate.
- Inference: Wan2.1-1.3B (T2V), LTX2.3 (two-stage distilled, shared transformer), Wan-causal
(chunk rollout + slab-KV streaming).
- Training (Wan2.1-1.3B), each driving the SAME loops the engine serves: finetune (flow-match),
DMD2 (teacher/critic distribution matching), DiffusionNFT (likelihood-free C2, samples from the
decay-blended old policy, group-relative advantages, shared-prompt cache reuse), self-forcing
(causal chunk loop). The engine never imports training (the §10 dependency rule, grep-verified).
numpy-only core (no torch/GPU here); heavy Wan/LTX forwards are deterministic toy stand-ins with
lazy torch-adapter seams (ComponentSpec.load_id/factory) for a GPU box. 49 tests pass via pytest
and a zero-dependency runner; interleave parity verified (and a buggy module-global interceptor
provably breaks it). Omni-ready spine (ar_decode/chunk_step loop kinds, multi-loop instances,
LoopState.extension) for the phase-2 Cosmos3 + vllm-omni omni ports.
Run: python3 -m pytest mini_fastvideo/tests/ -q ; python3 -m mini_fastvideo.examples
SolitaryThinker