Turning bsa on produced a bare AssertionError out of the first denoising step:

    File ".../block_sparse_attention/bsa_interface.py", line 639
      assert Tq % tq == 0 and Hq % hq == 0 and Wq % wq == 0

flash_attn_bsa_3d tiles the latent into 3D chunks and needs it to divide evenly on
every axis. With the checkpoint's shipped chunk of (4, 4, 4) that means sides
divisible by 64 — the VAE's 16-pixel latent cell times 4 — and a latent depth
divisible by 4, which puts num_frames at 13, 29, 45, 61, 77, 93 … and NOT at the
step*k+1 the 4n+1 generation rule would suggest.

Upstream's own default 480x832 fails it (480/16 = 30), which is presumably why
the flag ships off: nothing in that AssertionError mentions geometry.

bsa_problems() now says which axis is wrong and what to try instead, with the
chunk read from the checkpoint's bsa_params rather than assumed. The service
checks it per pass and, when the shape cannot be tiled, runs dense attention for
that pass and logs why: turning the flag on in a config must not break requests
that already work, and a silent fallback would leave someone wondering why
nothing got faster. The flag is restored afterwards, so the next request with a
tileable shape still gets it.

The suggestion arithmetic was wrong first time round — it offered 33, which is
exactly the frame count that fails — and the test that checks every suggestion is
itself tileable is what caught it.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0185zEBiy3KWB37xNGSrxL7w