Within the bounded Wan+LTX-2 scope:
- Wan2.2-A14B MoE now GENERATES on a single 80GB GPU via CPU offload (TorchWanDiT offload_group):
the two 14B experts live on CPU and only the active one is swapped onto the GPU at the boundary-
timestep transition (a single swap, not per-step). GPU-verified: 60GB peak (vs 79GB OOM), produced
wan22_a14b_lion.mp4 (17x480x832, std 54.7, motion 8.36). Single-expert Wan stays resident.
- LTX-2 base (single-stage) port: build_ltx2_base_card + build_ltx2_base_program reuse the LTX-2
adapters at FULL latent res with a request-driven many-step flow-match (LTX2DenoiseLoop full_res/
request_steps/base_flow_sigmas; distilled base/refine path preserved via False defaults). The SAME
single-stage card serves LTX-2.3-Distilled (also single-stage: no spatial_upsampler) — dispatched by
the new has_spatial_upsampler discriminator in _select_builders. v2_basic_ltx2.py added; VideoGenerator
gains shutdown() for API parity.
- Fixes: from_config 'os' scoping (shadowed module import); LTX-2 upsampler per_channel_statistics
source (the AE's .decoder, not the top-level module).
Verification status: A14B offload, the upsampler, and the arch-dispatch refactor were GPU-verified
earlier this session. LTX-2 base/2.3 are CPU-verified (cards/programs build, dispatch routes, schedule
correct); their GPU smoke tests were pending when the box was rescheduled aarch64->x86 mid-session,
which broke the aarch64 venv (numpy/torch unrunnable on x86) — GPU re-verify blocked on the env.
