The texture flow is imgshape2tex - it denoises 32 PBR channels while SEEING the shape
latent, so in_channels is 64 against out_channels 32. Upstream feeds the shape latent
as concat_cond and the model does sparse_cat([x, concat_cond], dim=-1); both share
coords, so it reduces to a channel concat. Added to slat_flow and carried on the
sampler (it is fixed for the whole trajectory and must reach BOTH CFG branches).
Verified running on the real checkpoints: 3,988,052 PBR voxels x 6 channels in 65.8s
(base_color 0:3, metallic 3:4, roughness 4:5, alpha 5:6).
Two things here fail SILENTLY rather than loudly, so both are asserted in comments:
1. shape_slat arrives DENORMALISED - the shape stage un-standardises it for the
decoder - but the texture flow was trained against the standardised form. It is
re-normalised before use as concat_cond. Skipping that gives a plausible mesh with
wrong colours, not an error.
2. tex_dec has pred_subdiv=False: it cannot invent subdivisions and must be handed the
shape decoder's subs as guides, so texture voxels land on the geometry that was
actually built.
The decoder's output is mapped * 0.5 + 0.5 into [0,1], the range o_voxel expects.
BAKE ORDER. Handing o_voxel the raw ~8M-face mesh hangs - the same wall the standalone
remesh test hit (killed at 20min), and the trellis2 lane's own operator note says the
uncapped bake peaks at 75GB. So the mesh is welded, stripped of floaters and decimated
BEFORE baking; the baker samples the attribute VOLUME at mesh positions, so a
decimated mesh still gets correct colours. Measured on the way through:
welded 3,988,052 -> 3,983,672 verts
floaters 12 components -> 1 kept, 6,332 faces dropped
decimated 7,996,876 -> 214,322 faces
pre-bake 34.6s
That floater count is worth noting: 12 components, not the 52,855 the first health
pass reported. Welding first is what makes the difference.
remesh now defaults OFF in to_glb, unlike upstream. Upstream runs on CUDA; this is the
CPU/Metal build and its remesher took >20 minutes on a 214k-face mesh. It is also
handed an already-clean mesh, so there is far less for it to fix.
Operator gains texture + texture_size params; geometry-only stays the default because
it is ~3min against the textured path's extra flow and bake.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
slat_flow joins ss_flow: max abs diff 9.3e-6, 700/700 params, against upstream running
on CPU torch. All three SLAT checkpoints load clean and run (img2shape 512/1024 and
imgshape2tex, the last taking 64 in-channels since shape is concatenated).
The SLAT flows differ from ss_flow in two ways, both handled in the shared core:
tokens are a SparseTensor's voxels so attention runs per batch item, and RoPE phases
are NOT shipped - positions are the input's own coordinates, so they are derived at
call time by rope_phases_from_coords.
tests/oracle_slat.py keeps the CPU-torch oracle harness: it patches both the dense and
sparse flash-attn kernels with SDPA equivalents. Use it rather than reasoning about
correctness - it has already caught three bugs a perfect 700/700 key match did not.
