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auto-set upcast if first decode fails, fix flux

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Vladimir Mandic
2024-09-21 13:32:58 -04:00
parent ae221f883e
commit f059313333
6 changed files with 105 additions and 84 deletions
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modules/processing_helpers.py
+10 -4
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@@ -339,6 +339,7 @@ def img2img_image_conditioning(p, source_image, latent_image, image_mask=None):
def validate_sample(tensor):
if not isinstance(tensor, np.ndarray) and not isinstance(tensor, torch.Tensor):
return tensor
dtype = tensor.dtype
if tensor.dtype == torch.bfloat16: # numpy does not support bf16
tensor = tensor.to(torch.float16)
if isinstance(tensor, torch.Tensor) and hasattr(tensor, 'detach'):
@@ -346,16 +347,21 @@ def validate_sample(tensor):
elif isinstance(tensor, np.ndarray):
sample = tensor
else:
shared.log.warning(f'Unknown sample type: {type(tensor)}')
shared.log.warning(f'Decode: type={type(tensor)} unknown sample')
sample = 255.0 * np.moveaxis(sample, 0, 2) if not shared.native else 255.0 * sample
with warnings.catch_warnings(record=True) as w:
cast = sample.astype(np.uint8)
if len(w) > 0:
minimum, maximum, mean = np.min(cast), np.max(cast), np.mean(cast)
if len(w) > 0 or minimum == maximum:
nans = np.isnan(sample).sum()
cast = np.nan_to_num(sample)
minimum, maximum, mean = np.min(cast), np.max(cast), np.mean(cast)
cast = cast.astype(np.uint8)
shared.log.error(f'Failed to validate samples: sample={sample.shape} min={minimum:.2f} max={maximum:.2f} mean={mean:.2f} invalid={nans}')
vae = shared.sd_model.vae.dtype if hasattr(shared.sd_model, 'vae') else None
upcast = getattr(shared.sd_model.vae.config, 'force_upcast', None) if hasattr(shared.sd_model, 'vae') and hasattr(shared.sd_model.vae, 'config') else None
shared.log.error(f'Decode: sample={sample.shape} invalid={nans} mean={mean} dtype={dtype} vae={vae} upcast={upcast} failed to validate')
if upcast is not None and not upcast:
setattr(shared.sd_model.vae.config, 'force_upcast', True) # noqa: B010
shared.log.warning('Decode: upcast=True set, retry operation')
return cast