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@@ -157,7 +157,7 @@ class CFGDenoiser(torch.nn.Module):
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cond = self.sampler.sampler_extra_args['cond']
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uncond = self.sampler.sampler_extra_args['uncond']
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cond = prompt_parser.reconstruct_multicond_batch(cond, self.step)
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cond_composition, cond = prompt_parser.reconstruct_multicond_batch(cond, self.step)
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uncond = prompt_parser.reconstruct_cond_batch(uncond, self.step)
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# If we use masks, blending between the denoised and original latent images occurs here.
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@@ -179,7 +179,8 @@ class CFGDenoiser(torch.nn.Module):
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denoiser_params = CFGDenoiserParams(x, image_cond, sigma, state.sampling_step, state.sampling_steps, cond, uncond, self)
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cfg_denoiser_callback(denoiser_params)
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denoised = forge_sampler.forge_sample(self, denoiser_params=denoiser_params, cond_scale=cond_scale)
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denoised = forge_sampler.forge_sample(self, denoiser_params=denoiser_params,
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cond_scale=cond_scale, cond_composition=cond_composition)
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preview = self.sampler.last_latent = denoised
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sd_samplers_common.store_latent(preview)
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