Four correctness fixes on the training side:
- The labeling grid read caption sidecars under except OSError, but a
non-UTF-8 sidecar raises UnicodeDecodeError (a ValueError), so one bad
file 500d /diffusion/dataset/{name}/images and the grid could not be
opened to repair it. Read it as no caption, matching the info summary.
- An image past Pillow's own hard limit raises DecompressionBombError,
which derives straight from Exception and so escaped the upload guard's
(OSError, UnidentifiedImageError, ValueError) and returned 500 instead
of the intended 400.
- lora_dropout accepted 1.0, which makes PEFT build nn.Dropout(p=1.0):
lora_A and lora_B receive no gradient and the run saves an untrained
adapter while reporting normal progress. Bound it below 1.0, matching
the LLM request schema.
- The train panel re-seeded the base repo on every dataset refresh
because the family object identity changes on each info fetch, so an
upload or caption save silently replaced the user's chosen base and the
run started on a different model. Track the pick and only re-seed on a
real family change.
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