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should be here instead lol

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yoinked 2024-09-19 17:50:17 -07:00 committed by GitHub
parent 72009e7696
commit ed42dfe45c
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2 changed files with 23 additions and 3 deletions
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4
comfy/samplers.py
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@ -729,7 +729,7 @@ def sample(model, noise, positive, negative, cfg, device, sampler, sigmas, model
return cfg_guider.sample(noise, latent_image, sampler, sigmas, denoise_mask, callback, disable_pbar, seed) return cfg_guider.sample(noise, latent_image, sampler, sigmas, denoise_mask, callback, disable_pbar, seed)
SCHEDULER_NAMES = ["normal", "karras", "exponential", "sgm_uniform", "simple", "ddim_uniform", "beta", "laplace"] SCHEDULER_NAMES = ["normal", "karras", "exponential", "sgm_uniform", "simple", "ddim_uniform", "beta"]
SAMPLER_NAMES = KSAMPLER_NAMES + ["ddim", "uni_pc", "uni_pc_bh2"] SAMPLER_NAMES = KSAMPLER_NAMES + ["ddim", "uni_pc", "uni_pc_bh2"]
def calculate_sigmas(model_sampling, scheduler_name, steps): def calculate_sigmas(model_sampling, scheduler_name, steps):
@ -747,8 +747,6 @@ def calculate_sigmas(model_sampling, scheduler_name, steps):
sigmas = normal_scheduler(model_sampling, steps, sgm=True) sigmas = normal_scheduler(model_sampling, steps, sgm=True)
elif scheduler_name == "beta": elif scheduler_name == "beta":
sigmas = beta_scheduler(model_sampling, steps) sigmas = beta_scheduler(model_sampling, steps)
elif scheduler_name == "laplace":
sigmas = k_diffusion_sampling.get_sigmas_laplace(n=steps, sigma_min=float(model_sampling.sigma_min), sigma_max=float(model_sampling.sigma_max))
else: else:
logging.error("error invalid scheduler {}".format(scheduler_name)) logging.error("error invalid scheduler {}".format(scheduler_name))
return sigmas return sigmas

22
comfy_extras/nodes_custom_sampler.py
View File

@ -90,6 +90,27 @@ class PolyexponentialScheduler:
sigmas = k_diffusion_sampling.get_sigmas_polyexponential(n=steps, sigma_min=sigma_min, sigma_max=sigma_max, rho=rho) sigmas = k_diffusion_sampling.get_sigmas_polyexponential(n=steps, sigma_min=sigma_min, sigma_max=sigma_max, rho=rho)
return (sigmas, ) return (sigmas, )
class LaplaceScheduler:
@classmethod
def INPUT_TYPES(s):
return {"required":
{"steps": ("INT", {"default": 20, "min": 1, "max": 10000}),
"sigma_max": ("FLOAT", {"default": 14.614642, "min": 0.0, "max": 5000.0, "step":0.01, "round": False}),
"sigma_min": ("FLOAT", {"default": 0.0291675, "min": 0.0, "max": 5000.0, "step":0.01, "round": False}),
"mu": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 100.0, "step":0.01, "round": False}),
"beta": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 100.0, "step":0.01, "round": False}),
}
}
RETURN_TYPES = ("SIGMAS",)
CATEGORY = "sampling/custom_sampling/schedulers"
FUNCTION = "get_sigmas"
def get_sigmas(self, steps, sigma_max, sigma_min, mu, beta):
sigmas = k_diffusion_sampling.get_sigmas_laplace(n=steps, sigma_min=sigma_min, sigma_max=sigma_max, mu=mu, beta=beta)
return (sigmas, )
class SDTurboScheduler: class SDTurboScheduler:
@classmethod @classmethod
def INPUT_TYPES(s): def INPUT_TYPES(s):
@ -673,6 +694,7 @@ NODE_CLASS_MAPPINGS = {
"KarrasScheduler": KarrasScheduler, "KarrasScheduler": KarrasScheduler,
"ExponentialScheduler": ExponentialScheduler, "ExponentialScheduler": ExponentialScheduler,
"PolyexponentialScheduler": PolyexponentialScheduler, "PolyexponentialScheduler": PolyexponentialScheduler,
"LaplaceScheduler": LaplaceScheduler,
"VPScheduler": VPScheduler, "VPScheduler": VPScheduler,
"BetaSamplingScheduler": BetaSamplingScheduler, "BetaSamplingScheduler": BetaSamplingScheduler,
"SDTurboScheduler": SDTurboScheduler, "SDTurboScheduler": SDTurboScheduler,