bandaid for broken ddim sampling #389
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@ -97,7 +97,7 @@ class VanillaStableDiffusionSampler:
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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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# existing code fails with cetin step counts, like 9
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# existing code fails with cetain 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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@ -122,7 +122,12 @@ class VanillaStableDiffusionSampler:
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self.nmask = None
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self.init_latent = None
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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)
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# existing code fails with cetin step counts, like 9
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try:
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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)
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except Exception:
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samples_ddim, _ = self.sampler.sample(S=p.steps+1, 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)
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return samples_ddim
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