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fix for DDIM live previews in txt2img

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AUTOMATIC 2022-09-08 19:20:41 +03:00
parent 701f76b29a
commit ca3861e05f
1 changed files with 6 additions and 0 deletions
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6
modules/sd_samplers.py
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@ -113,6 +113,11 @@ class VanillaStableDiffusionSampler:
return samples return samples
def sample(self, p, x, conditioning, unconditional_conditioning): def sample(self, p, x, conditioning, unconditional_conditioning):
self.sampler.p_sample_ddim = lambda x_dec, cond, ts, *args, **kwargs: p_sample_ddim_hook(self, x_dec, cond, ts, *args, **kwargs)
self.mask = None
self.nmask = None
self.init_latent = None
samples_ddim, _ = self.sampler.sample(S=p.steps, conditioning=conditioning, batch_size=int(x.shape[0]), shape=x[0].shape, verbose=False, unconditional_guidance_scale=p.cfg_scale, unconditional_conditioning=unconditional_conditioning, x_T=x) samples_ddim, _ = self.sampler.sample(S=p.steps, conditioning=conditioning, batch_size=int(x.shape[0]), shape=x[0].shape, verbose=False, unconditional_guidance_scale=p.cfg_scale, unconditional_conditioning=unconditional_conditioning, x_T=x)
return samples_ddim return samples_ddim
@ -170,6 +175,7 @@ class KDiffusionSampler:
def sample_img2img(self, p, x, noise, conditioning, unconditional_conditioning): def sample_img2img(self, p, x, noise, conditioning, unconditional_conditioning):
t_enc = int(min(p.denoising_strength, 0.999) * p.steps) t_enc = int(min(p.denoising_strength, 0.999) * p.steps)
sigmas = self.model_wrap.get_sigmas(p.steps) sigmas = self.model_wrap.get_sigmas(p.steps)
noise = noise * sigmas[p.steps - t_enc - 1] noise = noise * sigmas[p.steps - t_enc - 1]
xi = x + noise xi = x + noise