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fix(samplers): report validation failures without backtrace

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Sampler capability gates raised plain ValueError when schedulers_fallback is
disabled, so the API middleware and the gradio call wrapper printed a full
backtrace for an expected outcome. Add errors.ValidationError, raise it from
the gates, and report it message-only in errors.display; the UI error box and
the API error response already carry the message.
This commit is contained in:
CalamitousFelicitousness
2026-06-10 01:27:38 +01:00
parent e783981f3d
commit 47aa9a2c93
3 changed files with 16 additions and 9 deletions
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modules/sd_samplers_diffusers.py
+5 -5
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@@ -450,7 +450,7 @@ class DiffusionSampler:
sigma_applied = True
if not sigma_applied:
if debug or not shared.opts.schedulers_fallback:
raise ValueError(f'Sampler: name="{name}" does not support sigma="{sched_sigma}"')
raise errors.ValidationError(f'Sampler: name="{name}" does not support sigma="{sched_sigma}"')
else:
log.warning(f'Sampler: name="{name}" does not support sigma="{sched_sigma}", using default schedule')
else:
@@ -520,7 +520,7 @@ class DiffusionSampler:
if debug:
errors.display(e, 'Samplers')
if debug or not shared.opts.schedulers_fallback:
raise
raise errors.ValidationError(f'Sampler: name="{name}" {e}') from e
self.sampler = None
return
@@ -529,7 +529,7 @@ class DiffusionSampler:
cls_source = inspect.getsource(constructor)
if '"flow_prediction"' not in cls_source and "'flow_prediction'" not in cls_source:
if debug or not shared.opts.schedulers_fallback:
raise ValueError(f'Sampler: name="{name}" does not appear to support flow_prediction')
raise errors.ValidationError(f'Sampler: name="{name}" does not appear to support flow_prediction')
else:
log.warning(f'Sampler: name="{name}" does not support flow_prediction')
self.sampler = None
@@ -549,7 +549,7 @@ class DiffusionSampler:
default_accept_sigmas = (model is not None) and hasattr(model.default_scheduler, 'set_timesteps') and "sigmas" in set(inspect.signature(model.default_scheduler.set_timesteps).parameters.keys())
if default_accept_sigmas and not accept_sigmas:
if debug or not shared.opts.schedulers_fallback:
raise ValueError(f'Sampler: name="{name}" does not accept sigmas')
raise errors.ValidationError(f'Sampler: name="{name}" does not accept sigmas')
else:
log.warning(f'Sampler: name="{name}" does not accept sigmas')
self.sampler = None
@@ -559,7 +559,7 @@ class DiffusionSampler:
if default_accept_scale_noise and not accept_scale_noise:
log.warning(f'Sampler: name="{name}" does not implement scale noise')
if debug or not shared.opts.schedulers_fallback:
raise ValueError(f'Sampler: name="{name}" does not implement scale noise')
raise errors.ValidationError(f'Sampler: name="{name}" does not implement scale noise')
else:
log.warning(f'Sampler: name="{name}" does not implement scale noise')
self.sampler = None