4.6 KiB
LTXVTiledFusionSampler
Per-step tiled latent fusion for IC-LoRA (and other LTX conditioning) at resolutions larger than the model's trained window.
This is not LTXVTiledSampler. That node independently samples a grid of
tiles. This node keeps one latent canvas and one noise field, runs the
model on overlapping crops at every denoise step, and Gaussian-blends the
stepped tiles back onto the canvas. Tiles share a trajectory, so seams do not
form. Peak VRAM tracks spatial tile size and the temporal window
actually stepped (one content window plus one guide block when streaming),
not the full canvas. Cached tile latents/noise/masks follow canvas_device;
processed conds stay on the GPU. Streaming also does one full-res VAE encode
per temporal window.
Graph shape
UNET + IC-LoRA
Gemma CLIP → CLIPTextEncode (pos / neg)
guide frames → LTX Add Video IC-LoRA Guide (positive, negative, latents)
KSamplerSelect (euler / heun / …) → SAMPLER
sigmas (Manual Sigmas or any scheduler, descending, ending at 0)
│
▼
LTXV Tiled Fusion Sampler → LATENT → VAE Decode (tiled)
The latent must come from the IC-LoRA guide node. It carries appended guide
frames and a noise mask. This node crops those extra frames itself, so
LTXVCropGuides is not needed.
Leave use_streaming off on the guide (the default) for a whole-clip encode.
For clips longer than the trained window, turn use_streaming on and set the
same tile_frames (typically 97) on both the guide and this sampler. That
re-encodes each temporal window as its own clip and writes
ltxv_tiled_fusion_temporal_plan onto the conditioning. The sampler disables
windowing if the plan is missing. Do not slice a whole-clip guide: mid-clip
causal latents are not fresh-clip-start latents.
Sampler input
The SAMPLER socket is the same object SamplerCustomAdvanced takes. Fusion
owns the sigma loop and calls sampler.sampler_function once per tile with a
two-sigma slice. Use discrete step methods (euler, heun, dpm_2). History
methods (dpmpp_2m, lms) lose their multi-step memory. Adaptive samplers
cannot fuse. Ancestral methods add independent noise per tile and can seam.
Settings that matter
| Input | Notes |
|---|---|
tile_width / tile_height |
The IC-LoRA's trained spatial window in pixels (multiples of 32). Smaller tiles see content at the wrong scale. |
overlap_frac |
Stay at 0.5 or above. Below that a periodic grid appears on structured content. |
blend_var |
Gaussian overlap variance. Default 0.05. |
grid_cycle |
1 = fixed grid (cheapest), 4 = shift the grid across steps. Spatial only. |
tile_frames |
Temporal window in pixel frames (97 for LTX). 0 = one extent. >0 needs use_streaming on LTXAddVideoICLoRAGuide with the same value. |
vae |
Optional. Supplies temporal/spatial downscale (otherwise read from the diffusion model). |
use_tiled_encode on the guide node |
Must stay false. Spatially tiled guide encodes imprint a grid into the conditioning. |
use_streaming on the guide node |
Off by default. On = per-window fresh encode + plan. |
overlap_frac, blend_var, and grid_cycle are spatial fusion knobs. They do
not replace an untiled composition pass when the LoRA is generating a new look
at a canvas far above the trained window.
Example workflows
Under example_workflows/2.5/:
| Graph | What it shows |
|---|---|
LTX-2.5_V2V_TiledFusion_Upscale.json |
Detail-refine IC-LoRA; output_size FullHD / 4K / 8K, HD tiles |
LTX-2.5_V2V_TiledFusion_Native_4K_8K.json |
Stage-1 FullHD composition, then 4K or 8K refine |
LTX-2.5_V2V_TiledFusion_SDR_to_HDR.json |
Same ladder with the HDR IC-LoRA + LTXVHDRDecodePostprocess |
All of them take SAMPLER from KSamplerSelect (euler) and sigmas from
Manual Sigmas (descending, ending at 0). Size combos live on Preprocess
(Get Tiling Sizes + canvas resize are inside that subgraph). Keep
use_tiled_encode false on every LTXAddVideoICLoRAGuide. Turn
use_streaming on and set the same tile_frames on the guide and the
sampler when the clip is longer than one window.
Prompt for look and style only — lighting, palette, sharpness, grade. Do not name specific objects in the scene; after upscale, named details can appear in every spatial tile. The negative prompt is used as written.