docs: TRELLIS.2 Apple Silicon recon — trellis-mac is already TRELLIS.2, MLX ladder, PR #175 watch

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
This commit is contained in:
m3ultra 2026-07-18 23:44:30 +10:00
parent 4bc2f56d34
commit 2734ef9107

View File

@ -0,0 +1,84 @@
# TRELLIS.2 on Apple Silicon — recon (2026-07-18)
**Verdict up front:** we already run TRELLIS.2 locally — `vendor/trellis-mac`
(torch-MPS + Metal kernels) IS TRELLIS.2-4B and is wired as the
`trellis_mac` operator. There is no "MLX interface" shortcut for CUDA code
(CUDA kernels must be *rewritten*, not wrapped), but ~90% of TRELLIS.2 is
standard tensor math that MPS/MLX already runs; only four custom CUDA
pieces matter, and the community has replaced all four. The open work is
**speed** (unfused sparse ops ≈ 10× slower than CUDA) and **quality gaps**
(hole-filling disabled, forced pre-simplification) — not feasibility.
## What we run today (`vendor/trellis-mac`, shivampkumar fork)
- torch-MPS + `PYTORCH_ENABLE_MPS_FALLBACK`, Metal kernels by @pedronaugusto
(mtlgemm / mtldiffrast / mtlbvh / mtlmesh), SDPA attention.
- Full inference: sparse structure → shape SLat → tex SLat → decode →
dual-grid mesh extract → simplify → Metal PBR bake → GLB.
- Our benchmark: **318 s/gen on m3ultra**, ~18 GB peak (M4 Pro 24GB: 5m13s
cold at 512). H100 does 317 s — the gap is almost entirely the unfused
sparse conv + padded attention.
- Known gaps vs fal's trellis-2: CuMesh skipped → **no hole filling**,
meshes pre-simplified ~858K→200K faces before baking, Metal BVH
instability, macOS GPU-watchdog can kill long kernels (detected +
workarounds printed by generate.py). macOS 26 needed for the metallib
(fleet is on 26.5 ✓).
- Licensing: DINOv3 is Meta-gated; **RMBG-2.0 preprocessing is CC BY-NC**.
## What TRELLIS.2 actually needs (upstream: Linux, CUDA 12.4, ≥24 GB)
| CUDA dep | Role | Mac status |
|---|---|---|
| o-voxel ext (hash/convert/rasterize) | the O-Voxel representation | pure-Python reimpl (trellis-mac `backends/`) + CPU fork |
| FlexGEMM (**Triton**) | all sparse conv | **the crux** — Triton ≠ Metal; Metal `mtlgemm` or slow pure-torch gather/scatter |
| flash-attn / xformers | 4B flow transformer attention | SDPA (padded → unfused, big cost) |
| CuMesh | decimate/remesh/**hole-fill**/UV | skipped → `fast_simplification`; hole-fill lost |
| nvdiffrast | texture bake | `mtldiffrast` (Metal) |
| nvdiffrec | preview renders only | not needed |
## The MLX question, answered
- **No shim exists or can exist**: CUDA kernels are NVIDIA-machine code;
"an MLX interface" means rewriting each custom op in MLX/Metal. MLX can
express them (`mx.fast.metal_kernel` JIT-compiles Metal from Python) —
but MLX has **no sparse-tensor type and no sparse-voxel precedent**;
SparseTensor/varlen semantics must be hand-rolled. A TRELLIS.2-MLX would
be a first.
- **Our own playbook (proven 2×) is adopt-then-patch, not from-scratch**:
hunyuan3d-mlx = dgrauet's 8.4k-LOC port + our thin packaging layer;
corridorkey-mlx = cmoyates/Niko's 5.3k-LOC port + our **8-line**
`mx.compile`-in-tiled-mode patch = the 1.47× win. From-scratch dense→MLX
ports of this scale are months of solo work (mflux, mlx-video authors).
- **Starting points already exist**: upstream **PR #175** (Jourloy,
2026-07-17 — MPS + Metal + an *experimental `mlx` backend flag*, 28
tests green on M4 Max) and **pedronaugusto/trellis2-apple** (an
`mlx_backend/` dir, no benchmarks yet).
## Recommended ladder (effort-ordered)
1. **Hours — tune what we have**: benchmark `trellis_mac` 1024_cascade vs
fal trellis-2 on identical inputs (BENCHMARKS.md format); route
MESHGOD's batch/overnight work to the local lane (m3ultra clears 18 GB
~14× over; fal stays for interactive one-offs). $93/mo → mostly $0.
2. **Days — adopt + fleet-patch**: vendor PR #175 / trellis2-apple as
`monster/trellis2-*` Gitea forks (house pattern); run the corridorkey
ablation moves on them: attention head_dim → pad to 64 fast-path,
`mx.compile` on fixed shapes, sdpa gating by GPU generation, tiled-vs-
full sweeps. Prize: **M1 Ultra compatibility** (MLX-native, like
hunyuan3d — today trellis is m3-only in practice) = 2nd free 3D box.
3. **Weeks — the real kernel work** (only if we want fal-class speed):
fused Metal sparse-conv (gather-GEMM-scatter) + varlen attention via
`mx.fast.metal_kernel`; port CuMesh hole-filling. Closes most of the
10× gap; genuinely novel, upstreamable to PR #175.
4. **Quality parity misc**: raise simplification budget on 256 GB boxes,
swap RMBG-2.0 → our licensed bg-remove lane, wire `trellis_mac` into
MESHGOD's `local/` model list next to hunyuan3d-mlx.
## Sources
- github.com/microsoft/TRELLIS.2 (setup.sh = dep manifest) · PR #175 ·
issue #74 · shivampkumar/trellis-mac · pedronaugusto/trellis2-apple
- ml-explore.github.io/mlx custom-metal-kernels docs
- Local: HANDOFF_HY3D_MLX.md, CORRIDORKEY.md, BENCHMARKS.md,
vendor/trellis-mac/README, vendor/corridorkey-mlx/prompts/ (the 6-phase
parity-first port template — the blueprint if we ever do ladder step 3)