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fix noisy images at high step counts

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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.
This commit is contained in:
Lincoln Stein
2022-10-13 12:06:12 -04:00
parent 7f491fd2d2
commit e98fe9c22d
5 changed files with 24 additions and 2 deletions
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ldm/models/diffusion/ksampler.py
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@ -98,7 +98,8 @@ class KSampler(Sampler):
rho=7.,
device=self.device,
)
self.sigmas = self.karras_sigmas
self.sigmas = self.model_sigmas
#self.sigmas = self.karras_sigmas
# ALERT: We are completely overriding the sample() method in the base class, which
# means that inpainting will not work. To get this to work we need to be able to