workaround for a weird bug in DDIM's make_schedule
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parent
53e7616b51
commit
51c65457c4
9
webui.py
9
webui.py
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@ -847,7 +847,6 @@ class VanillaStableDiffusionSampler:
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def __init__(self, constructor):
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def __init__(self, constructor):
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self.sampler = constructor(sd_model)
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self.sampler = constructor(sd_model)
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self.orig_p_sample_ddim = self.sampler.p_sample_ddim
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self.orig_p_sample_ddim = self.sampler.p_sample_ddim
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self.sampler.p_sample_ddim = lambda x_dec, cond, ts, *args, **kwargs: p_sample_ddim_hook(self, x_dec, cond, ts, *args, **kwargs)
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self.mask = None
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self.mask = None
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self.nmask = None
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self.nmask = None
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self.init_latent = None
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self.init_latent = None
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@ -855,9 +854,15 @@ class VanillaStableDiffusionSampler:
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def sample_img2img(self, p, x, noise, conditioning, unconditional_conditioning):
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def sample_img2img(self, p, x, noise, conditioning, unconditional_conditioning):
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t_enc = int(min(p.denoising_strength, 0.999) * p.steps)
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t_enc = int(min(p.denoising_strength, 0.999) * p.steps)
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self.sampler.make_schedule(ddim_num_steps=p.steps, ddim_eta=0.0, verbose=False)
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# existing code fail with cetin step counts, like 9
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try:
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self.sampler.make_schedule(ddim_num_steps=p.steps, verbose=False)
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except Exception:
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self.sampler.make_schedule(ddim_num_steps=p.steps+1, verbose=False)
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x1 = self.sampler.stochastic_encode(x, torch.tensor([t_enc] * int(x.shape[0])).to(device), noise=noise)
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x1 = self.sampler.stochastic_encode(x, torch.tensor([t_enc] * int(x.shape[0])).to(device), noise=noise)
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self.sampler.p_sample_ddim = lambda x_dec, cond, ts, *args, **kwargs: p_sample_ddim_hook(self, x_dec, cond, ts, *args, **kwargs)
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self.mask = p.mask
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self.mask = p.mask
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self.nmask = p.nmask
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self.nmask = p.nmask
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self.init_latent = p.init_latent
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self.init_latent = p.init_latent
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