Fix error when batch count > 1
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@ -269,14 +269,15 @@ class KDiffusionSampler:
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return sigmas
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def create_noise_sampler(self, x, sigmas, seeds):
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def create_noise_sampler(self, x, sigmas, p):
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"""For DPM++ SDE: manually create noise sampler to enable deterministic results across different batch sizes"""
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if shared.opts.no_dpmpp_sde_batch_determinism:
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return None
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from k_diffusion.sampling import BrownianTreeNoiseSampler
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sigma_min, sigma_max = sigmas[sigmas > 0].min(), sigmas.max()
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return BrownianTreeNoiseSampler(x, sigma_min, sigma_max, seed=seeds)
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current_iter_seeds = p.all_seeds[p.iteration * p.batch_size:(p.iteration + 1) * p.batch_size]
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return BrownianTreeNoiseSampler(x, sigma_min, sigma_max, seed=current_iter_seeds)
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def sample_img2img(self, p, x, noise, conditioning, unconditional_conditioning, steps=None, image_conditioning=None):
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steps, t_enc = sd_samplers_common.setup_img2img_steps(p, steps)
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@ -302,7 +303,7 @@ class KDiffusionSampler:
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extra_params_kwargs['sigmas'] = sigma_sched
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if self.funcname == 'sample_dpmpp_sde':
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noise_sampler = self.create_noise_sampler(x, sigmas, p.all_seeds)
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noise_sampler = self.create_noise_sampler(x, sigmas, p)
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extra_params_kwargs['noise_sampler'] = noise_sampler
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self.model_wrap_cfg.init_latent = x
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@ -337,7 +338,7 @@ class KDiffusionSampler:
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extra_params_kwargs['sigmas'] = sigmas
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if self.funcname == 'sample_dpmpp_sde':
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noise_sampler = self.create_noise_sampler(x, sigmas, p.all_seeds)
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noise_sampler = self.create_noise_sampler(x, sigmas, p)
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extra_params_kwargs['noise_sampler'] = noise_sampler
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self.last_latent = x
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