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Add a denoise parameter to the SDTurboScheduler.

This commit is contained in:
comfyanonymous 2023-12-20 02:51:18 -05:00
parent ba3f3aa1ca
commit e82942cc29
1 changed files with 4 additions and 2 deletions
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6
comfy_extras/nodes_custom_sampler.py
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@ -87,6 +87,7 @@ class SDTurboScheduler:
return {"required": return {"required":
{"model": ("MODEL",), {"model": ("MODEL",),
"steps": ("INT", {"default": 1, "min": 1, "max": 10}), "steps": ("INT", {"default": 1, "min": 1, "max": 10}),
"denoise": ("FLOAT", {"default": 1.0, "min": 0, "max": 1.0, "step": 0.01}),
} }
} }
RETURN_TYPES = ("SIGMAS",) RETURN_TYPES = ("SIGMAS",)
@ -94,8 +95,9 @@ class SDTurboScheduler:
FUNCTION = "get_sigmas" FUNCTION = "get_sigmas"
def get_sigmas(self, model, steps): def get_sigmas(self, model, steps, denoise):
timesteps = torch.flip(torch.arange(1, 11) * 100 - 1, (0,))[:steps] start_step = 10 - int(10 * denoise)
timesteps = torch.flip(torch.arange(1, 11) * 100 - 1, (0,))[start_step:start_step + steps]
sigmas = model.model.model_sampling.sigma(timesteps) sigmas = model.model.model_sampling.sigma(timesteps)
sigmas = torch.cat([sigmas, sigmas.new_zeros([1])]) sigmas = torch.cat([sigmas, sigmas.new_zeros([1])])
return (sigmas, ) return (sigmas, )