048d0422c7
Check cancellation immediately after a ControlNet from_pretrained and before any device placement, so an unload/eviction that raced the download does not allocate several GB onto the GPU after the load was already cleared. Require a loadable weight or shard index (not just config.json) before a local ControlNet folder is advertised, so an interrupted copy is hidden instead of failing deep in from_pretrained as a generic 500. Do not record a strength-0 ControlNet in the gallery recipe: it is treated as disabled and skipped, so the image is unconditioned and the metadata must not claim a ControlNet was applied. Build the control-type picker from the selected ControlNet's advertised control_types instead of a hardcoded passthrough/canny pair, so a union model with a precomputed depth or pose map sends the correct control_mode. |
||
|---|---|---|
| .. | ||
| data_recipe | ||
| export | ||
| inference | ||
| rag | ||
| training | ||
| __init__.py | ||
| _torchao_stub.py | ||
| import_guards.py | ||
| tool_healing.py | ||