The causal adapter never passed a kv_cache, so CausalWanTransformer3DModel.forward routed to
_forward_train (no cross-chunk KV) on every chunk instead of _forward_inference (the CausVid
Alg-2 KV-cache path). Each chunk denoised blind to the previous ones; the loop's cross-chunk
"context" was a toy mean(prior_latents) the adapter ignored. Result: hard discontinuities at
every chunk boundary (frame-to-frame absdiff spikes 43-55 every ~12 frames).
Fix (cuda path only; toy/CPU path and the 237-test suite untouched):
- WanDiT.alloc_causal_caches(): allocate the persistent per-block KV + cross-attn caches sized
from the model config (mirrors CausalDenoisingStage._initialize_kv_cache).
- WanDiT.__call__: thread kv_cache/crossattn_cache/current_start/cache_start/start_frame/
frame_seqlen so the model runs _forward_inference.
- wan_causal/loop.py: own the caches in LoopState (per-request -> interleave-safe); pass
current_start = chunk_idx*chunk_size*frame_seqlen per chunk; do the clean-KV write
(timestep ~0) after each chunk so the next attends to it.
Verified on H100: frame-to-frame absdiff mean 12.8->4.4, max 55.4->8.3; chunk-boundary spikes
eliminated; coherent across all 7 chunks. CPU causal toy tests unchanged (24 passed).
SolitaryThinker
f90e8f3e76