[Feature request] "polyexponential" sampler

[Muskelmagier]

Just a quick feature request for the polyexponential sampler.

It has some use in that it generally produces more varied and detailed outputs but has some amount of error if you use less than 30 steps.

it would simply take a small edit in the comfiUI sampler.py in line 666

SCHEDULER_NAMES = ["normal", "karras", "polyexponential", "exponential", "sgm_uniform", "simple", "ddim_uniform"]
SAMPLER_NAMES = KSAMPLER_NAMES + ["ddim", "uni_pc", "uni_pc_bh2"]

def calculate_sigmas(model_sampling, scheduler_name, steps):
    if scheduler_name == "karras":
        sigmas = k_diffusion_sampling.get_sigmas_karras(n=steps, sigma_min=float(model_sampling.sigma_min), sigma_max=float(model_sampling.sigma_max))
    elif scheduler_name == "polyexponential":