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workaround for a weird bug in DDIM's make_schedule

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AUTOMATIC 2022-08-31 15:29:01 +03:00
parent 53e7616b51
commit 51c65457c4
1 changed files with 7 additions and 2 deletions
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9
webui.py
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@ -847,7 +847,6 @@ class VanillaStableDiffusionSampler:
def __init__(self, constructor): def __init__(self, constructor):
self.sampler = constructor(sd_model) self.sampler = constructor(sd_model)
self.orig_p_sample_ddim = self.sampler.p_sample_ddim self.orig_p_sample_ddim = self.sampler.p_sample_ddim
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.mask = None
self.nmask = None self.nmask = None
self.init_latent = None self.init_latent = None
@ -855,9 +854,15 @@ class VanillaStableDiffusionSampler:
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)
self.sampler.make_schedule(ddim_num_steps=p.steps, ddim_eta=0.0, verbose=False) # existing code fail with cetin step counts, like 9
try:
self.sampler.make_schedule(ddim_num_steps=p.steps, verbose=False)
except Exception:
self.sampler.make_schedule(ddim_num_steps=p.steps+1, verbose=False)
x1 = self.sampler.stochastic_encode(x, torch.tensor([t_enc] * int(x.shape[0])).to(device), noise=noise) x1 = self.sampler.stochastic_encode(x, torch.tensor([t_enc] * int(x.shape[0])).to(device), noise=noise)
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 = p.mask self.mask = p.mask
self.nmask = p.nmask self.nmask = p.nmask
self.init_latent = p.init_latent self.init_latent = p.init_latent