Merge pull request #12542 from AUTOMATIC1111/res-sampler
Add RES sampler and reorder the sampler list
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f37cc5f5e1
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@ -22,6 +22,9 @@ samplers_k_diffusion = [
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('DPM++ 2M', 'sample_dpmpp_2m', ['k_dpmpp_2m'], {}),
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('DPM++ SDE', 'sample_dpmpp_sde', ['k_dpmpp_sde'], {"second_order": True, "brownian_noise": True}),
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('DPM++ 2M SDE', 'sample_dpmpp_2m_sde', ['k_dpmpp_2m_sde_ka'], {"brownian_noise": True}),
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('DPM++ 2M SDE Heun', 'sample_dpmpp_2m_sde', ['k_dpmpp_2m_sde_heun'], {"brownian_noise": True, "solver_type": "heun"}),
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('DPM++ 2M SDE Heun Karras', 'sample_dpmpp_2m_sde', ['k_dpmpp_2m_sde_heun_ka'], {'scheduler': 'karras', "brownian_noise": True, "solver_type": "heun"}),
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('DPM++ 2M SDE Heun Exponential', 'sample_dpmpp_2m_sde', ['k_dpmpp_2m_sde_heun_exp'], {'scheduler': 'exponential', "brownian_noise": True, "solver_type": "heun"}),
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('DPM++ 3M SDE', 'sample_dpmpp_3m_sde', ['k_dpmpp_3m_sde'], {'discard_next_to_last_sigma': True, "brownian_noise": True}),
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('DPM++ 3M SDE Karras', 'sample_dpmpp_3m_sde', ['k_dpmpp_3m_sde_ka'], {'scheduler': 'karras', 'discard_next_to_last_sigma': True, "brownian_noise": True}),
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('DPM++ 3M SDE Exponential', 'sample_dpmpp_3m_sde', ['k_dpmpp_3m_sde_exp'], {'scheduler': 'exponential', 'discard_next_to_last_sigma': True, "brownian_noise": True}),
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@ -161,6 +164,9 @@ class KDiffusionSampler(sd_samplers_common.Sampler):
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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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if self.config.options.get('solver_type', None) == 'heun':
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extra_params_kwargs['solver_type'] = 'heun'
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self.model_wrap_cfg.init_latent = x
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self.last_latent = x
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self.sampler_extra_args = {
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@ -202,6 +208,9 @@ class KDiffusionSampler(sd_samplers_common.Sampler):
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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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if self.config.options.get('solver_type', None) == 'heun':
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extra_params_kwargs['solver_type'] = 'heun'
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self.last_latent = x
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self.sampler_extra_args = {
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'cond': conditioning,
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@ -210,6 +219,7 @@ class KDiffusionSampler(sd_samplers_common.Sampler):
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'cond_scale': p.cfg_scale,
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's_min_uncond': self.s_min_uncond
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}
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samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
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if self.model_wrap_cfg.padded_cond_uncond:
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