Wan 2.2 A14B ships a per-model boundary_ratio (0.9 I2V, 0.875 T2V) that selects the high- or low-noise expert per step. The video and base-model image loaders both load the shipped value; the slider override is applied at generation time in set_pipeline_args, the one point both paths pass through before invoking the pipeline.
The denoising loop reads config.boundary_ratio each call, so tuning takes effect with no reload for video and base-model images alike. The slider defaults to -1, meaning use the model's value; 0 to 1 set the boundary explicitly. Single-expert stages stay load-time because they drop a transformer to free VRAM.
A single handler bound to the AR dropdown, width and height (in the
shared create_resolution_inputs and the resize section) wrote both
sliders on every change. With a ratio selected it locked one axis and
snapped it back on each edit, the two sliders looped, and the math ran
server-side one round-trip per keystroke, echoing a value back into the
field being typed in and yanking it.
Move aspect-ratio linking to the browser (ui/resolutionLock.ts): a
debounced edit writes only the partner axis, never the field being
edited, and commits immediately on blur, enter, or slider release. Keep
the kanvas notify on notifyKanvasResize wired to the resize sliders'
gradio .change, so it still fires on programmatic size updates (detect,
paste, swap) that client-side listeners miss. Drop the per-change AR
wiring, res_apply, and the resolutionChange* helpers.
Gradio renders radio and checkboxgroup titles as a bare block-info span
outside any label, so the hint scan missed them and those titles never
received a tooltip or localization. Add the block-info selector to the
element scan, deduplicating against the nodes already collected.
Rebuild the core bundle.
Document the space or comma separated model-type list that quantization
skips, with the family codes shown in the load log and an example.
Mark it as requiring a model reload, matching the other quantization
settings, since the value is read only during model load.
Surface YoloRestorer.restore() as a standalone operation: a Detailer
postprocessing script in the Process tab and a thin /sdapi/v1/detail
endpoint, neither requiring a base generation pass.
- modules/postprocess/yolo.py: YoloRestorer.make_processing() builds the
synthetic Img2Img processing object both entry points feed to restore(),
resolving the seed so the inpaint passes are reproducible
- modules/api/process.py: post_detail handler exposes the full detailer
parameter set and returns the detailed image plus optional annotations
as base64
- scripts/postprocessing_detailer.py: reuses shared.yolo.ui('extras') and
runs through make_processing()
- modules/postprocessing.py: run_extras takes a per-script script_args
dict, also letting the extras API drive other scripts such as Remove
background; omitting it leaves existing callers unchanged
- modules/api/models.py: ReqDetail / ResDetail
- modules/processing_info.py: guard create_infotext's Image/Hires CFG
reporting against an unset (None) cfg_image, matching the is-not-None
checks the other cfg_image readers use; the detailer inpaint pass runs
with it unset
- test/test-detailer-api.py: covers both paths; effect tests measure the
diff inside the detected region with extreme isolated parameter values,
and the suite disables model quantization for the run and restores the
original settings afterward
modules/ui_extra_networks.py emits onclick="cardClicked(...)" on
every network card, but cardClicked was module-private in
ui/extraNetworks.ts and got tree-shaken out of the bundle. Attach
it to window like showCardDetails so card clicks resolve and the
<lora:...> insertion path works.
Vladimir Mandic
CalamitousFelicitousness
Pablo Hellmann
QualiaRain