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Co-Authored-By: Ryan Dick <14897797+RyanJDick@users.noreply.github.com>
This commit is contained in:
Sergey Borisov 2024-07-26 19:47:28 +03:00
parent bd8890be11
commit 5810cee6c9
2 changed files with 11 additions and 1 deletions
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6
invokeai/app/invocations/denoise_latents.py
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@ -775,6 +775,10 @@ class DenoiseLatentsInvocation(BaseInvocation):
### inpaint
mask, masked_latents, is_gradient_mask = self.prep_inpaint_mask(context, latents)
# NOTE: We used to identify inpainting models by inpecting the shape of the loaded UNet model weights. Now we
# use the ModelVariantType config. During testing, there was a report of a user with models that had an
# incorrect ModelVariantType value. Re-installing the model fixed the issue. If this issue turns out to be
# prevalent, we will have to revisit how we initialize the inpainting extensions.
if unet_config.variant == ModelVariantType.Inpaint:
ext_manager.add_extension(InpaintModelExt(mask, masked_latents, is_gradient_mask))
elif mask is not None:
@ -830,6 +834,8 @@ class DenoiseLatentsInvocation(BaseInvocation):
seed, noise, latents = self.prepare_noise_and_latents(context, self.noise, self.latents)
mask, masked_latents, gradient_mask = self.prep_inpaint_mask(context, latents)
# At this point, the mask ranges from 0 (leave unchanged) to 1 (inpaint).
# We invert the mask here for compatibility with the old backend implementation.
if mask is not None:
mask = 1 - mask

6
invokeai/backend/stable_diffusion/extensions/inpaint.py
View File

@ -75,7 +75,11 @@ class InpaintExt(ExtensionBase):
@callback(ExtensionCallbackType.PRE_DENOISE_LOOP)
def init_tensors(self, ctx: DenoiseContext):
if not self._is_normal_model(ctx.unet):
raise ValueError("InpaintExt should be used only on normal models!")
raise ValueError(
"InpaintExt should be used only on normal (non-inpainting) models. This could be caused by an "
"inpainting model that was incorrectly marked as a non-inpainting model. In some cases, this can be "
"fixed by removing and re-adding the model (so that it gets re-probed)."
)
self._mask = self._mask.to(device=ctx.latents.device, dtype=ctx.latents.dtype)