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@lstein lstein commented Oct 13, 2022

At step counts greater than ~75, the ksamplers start producing noisy images when using the Karras noise schedule. This PR reverts to using the model's own noise schedule, which eliminates the problem at the cost of slowing convergence at lower step counts.

This PR also introduces a new CLI --save_intermediates <n> argument, which will save every nth intermediate image into a subdirectory named intermediates/<image_prefix>.

Addresses issue #1083.

At step counts greater than ~75, the ksamplers start producing noisy
images when using the Karras noise schedule. This PR reverts to using
the model's own noise schedule, which eliminates the problem at the
cost of slowing convergence at lower step counts.

This PR also introduces a new CLI `--save_intermediates <n>' argument,
which will save every nth intermediate image into a subdirectory
named `intermediates/<image_prefix>'.

Addresses issue #1083.
@Neosettler
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Good catch lstein. This patch seems worthy of a new release.

@lstein
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lstein commented Oct 14, 2022

Good catch lstein. This patch seems worthy of a new release.

It wasn't me who caught it. It was the user who submitted issue #1083.

@lstein lstein merged commit e98fe9c into development Oct 14, 2022
@lstein lstein deleted the fix-noisy-images branch October 14, 2022 04:02
@db3000
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db3000 commented Oct 14, 2022

Thanks for the quick fix!

@Neosettler
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The actual fix for the noisy image is in:
ldm/models/diffusion/ksampler.py just those 2 lines?
- self.sigmas = self.karras_sigmas
+self.sigmas = self.model_sigmas
+#self.sigmas = self.karras_sigmas

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5 participants