Add ltx_enhancements.py with four automatic generation improvements
driven by the refiner rating system:
Technique 2 - Per-block attention temperature: sharper (colder) attention
on semantic anchor blocks 14/19 when quality/concept is missing; softer
on early blocks when details are missing. Capped at 0.72-1.22x range.
Technique 3 - Temporal RoPE style: frame_rate manipulation via
model_function_wrapper. Selector exposed in FunPackVideoRefinerV2 node
(optional input) and in Studio popup Refiner tab.
natural=no change, accelerate=+35% fps, decelerate=-28% fps,
loop/freeze=experimental coordinate tricks.
Technique 4 - Denoise creativity mask: spatial noise weighting derived
from latent variance; high-variance regions get more denoising freedom
scaled by reward. Built but applied by downstream latent consumers.
Technique 5 - Attention anchor transfer: hidden states at anchor blocks
14 and 19 are captured via patches_replace["dit"] on every run and saved
to refinements/attn_maps/temp_{key}.pt. When the user rates a run
Perfect, bless_attention_maps() promotes the temp file to a blessed file.
Subsequent runs inject the blessed maps at 5-28% strength scaled by
reward, transferring semantic structure from good outputs onto new runs.
All enhancements are composable with existing attn2 direction patches
and STG/PAG blocks via patches_replace composition.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
