youngkingdom/ComfyUI-WanMoeKSampler
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simplify sigmas computation

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Stéphane du Hamel
2025-08-12 13:18:28 +02:00
parent ccc0adf360
commit 12cfa70738
1 changed files with 3 additions and 4 deletions
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7
nodes.py
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@ -31,17 +31,16 @@ def wan_ksampler(model_high_noise, model_low_noise, seed, steps, cfgs, sampler_n
last_step=9999
# first, we get all sigmas
sampler = comfy.samplers.KSampler(model_high_noise, steps=steps, device=model_high_noise.load_device, sampler=sampler_name, scheduler=scheduler, denoise=denoise, model_options=model_high_noise.model_options)
sigmas = sampler.sigmas
# why are timesteps 0-1000?
sampling = model_high_noise.get_model_object("model_sampling")
sigmas = comfy.samplers.calculate_sigmas(sampling,scheduler,steps)
# why are timesteps 0-1000?
timesteps = [sampling.timestep(sigma)/1000 for sigma in sigmas.tolist()]
switching_step = steps
for (i,t) in enumerate(timesteps[1:]):
if t < boundary:
switching_step = i
break
print(f"switching model at step {i}")
print(f"switching model at step {switching_step}")
start_with_high = start_step<switching_step
end_wth_low = last_step>=switching_step