save latents_out earlier
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@ -262,9 +262,6 @@ class DiffusersHolder():
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for i, t in enumerate(timesteps):
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# Set the right starting latents
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if i < idx_start:
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list_latents_out.append(None)
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continue
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elif i == idx_start:
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latents = latents_start.clone()
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# Mix latents
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@ -272,6 +269,9 @@ class DiffusersHolder():
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latents_mixtarget = list_latents_mixing[i - 1].clone()
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latents = interpolate_spherical(latents, latents_mixtarget, list_mixing_coeffs[i])
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if i < idx_start:
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list_latents_out.append(latents)
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# expand the latents if we are doing classifier free guidance
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latent_model_input = torch.cat([latents] * 2) if do_classifier_free_guidance else latents
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latent_model_input = self.pipe.scheduler.scale_model_input(latent_model_input, t)
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