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add new samplers

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C43H66N12O12S2 2022-09-29 10:15:38 +03:00 committed by AUTOMATIC1111
parent be5555fce4
commit b05355770c
1 changed files with 10 additions and 1 deletions
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11
modules/sd_samplers.py
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@ -23,6 +23,8 @@ samplers_k_diffusion = [
('Heun', 'sample_heun', ['k_heun']),
('DPM2', 'sample_dpm_2', ['k_dpm_2']),
('DPM2 a', 'sample_dpm_2_ancestral', ['k_dpm_2_a']),
('DPM fast', 'sample_dpm_fast', ['k_dpm_fast']),
('DPM adaptive', 'sample_dpm_adaptive', ['k_dpm_ad']),
]
samplers_data_k_diffusion = [
@ -37,6 +39,8 @@ samplers = [
SamplerData('PLMS', lambda model: VanillaStableDiffusionSampler(ldm.models.diffusion.plms.PLMSSampler, model), []),
]
samplers_for_img2img = [x for x in samplers if x.name != 'PLMS']
samplers_for_img2img.remove(samplers_for_img2img[6])
samplers_for_img2img.remove(samplers_for_img2img[6])
sampler_extra_params = {
'sample_euler': ['s_churn', 's_tmin', 's_tmax', 's_noise'],
@ -309,7 +313,12 @@ class KDiffusionSampler:
x = x * sigmas[0]
extra_params_kwargs = self.initialize(p)
if 'sigma_min' in inspect.signature(self.func).parameters:
if 'n' in inspect.signature(self.func).parameters:
samples = self.func(self.model_wrap_cfg, x, sigma_min=self.model_wrap.sigmas[0].item(), sigma_max=self.model_wrap.sigmas[-1].item(), n=steps, extra_args={'cond': conditioning, 'uncond': unconditional_conditioning, 'cond_scale': p.cfg_scale}, disable=False, callback=self.callback_state, **extra_params_kwargs)
return samples
samples = self.func(self.model_wrap_cfg, x, sigma_min=self.model_wrap.sigmas[0].item(), sigma_max=self.model_wrap.sigmas[-1].item(), extra_args={'cond': conditioning, 'uncond': unconditional_conditioning, 'cond_scale': p.cfg_scale}, disable=False, callback=self.callback_state, **extra_params_kwargs)
return samples
samples = self.func(self.model_wrap_cfg, x, sigmas, extra_args={'cond': conditioning, 'uncond': unconditional_conditioning, 'cond_scale': p.cfg_scale}, disable=False, callback=self.callback_state, **extra_params_kwargs)
return samples