Learned tile-sparse attention (Veda, arXiv 2605.30325): tiles, tile plans, predictor
scoring and selection in plain torch (tested on CPU, including a real tiny H3 with a
stand-in kernel), an INT8 Triton kernel derived from SageAttention (untested on a GPU),
installed through the same override and per-step wrapper as SLA. Runs at the predictor's
trained budget; LoRA, MXFP8, Two stages, dense steps and the attention backend compose.
Settings > Models offers the official Hugging Face download of the predictor on a click,
with its licence beside it; taggers and this share one downloader (core/fetch.py).
The port plan calls for every module under modules/ to declare a
CATEGORY so Settings/Engine panels can group by it. Only alg, sharpen,
appearance, and full_control had one; the other 12 (loaders, empty
latent, media load, minimax_h3, output decode, sampling modifiers/
sampler, system pipeline) are plain infrastructure with no user-facing
settings dial, so they land in "system" except output_decode (post,
matching its STAGE) and the two sampling modules (sampling). Verified
against core/tests (548 passed) -- category validation and the
registry's field-mapping catch a typo here, per the earlier fixture-gap
fix.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Ported from v4, minus two mechanisms that are no longer needed. The LoRA
loader takes one LoRA and chains, so the FlexibleOptionalInputType dict
subclass that lied to ComfyUI's validator has nothing left to do. The CLIP
loader uses numbered slots like core's DualCLIPLoader instead of a JSON
array in a string widget.
Autogrow looked like the right answer for the encoder list and is not: it
sets force_input on any widget input, so a list of combos renders as sockets
and the file picker stops being a picker. Every core use of it is a
connection type.
GGUF and SLA are deliberately not here. Both are capabilities rather than
loader options, and both belong in modules of their own.
The tests follow what the loaders PRODUCE rather than stopping at the call:
the attention override is carried into comfy's real dispatch and checked
against every backend this machine registers, because an override that only
fails at the first attention call fails at sampling, not at load.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
digital-garbage