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# https://github.com/mcmonkeyprojects/sd-dynamic-thresholding
from lib_dynamic_thresholding.dynthres_core import DynThresh
class DynamicThresholdingNode:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"model": ("MODEL",),
"mimic_scale": ("FLOAT", {"default": 7.0, "min": 0.0, "max": 100.0, "step": 0.5}),
"threshold_percentile": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}),
"mimic_mode": (DynThresh.Modes, ),
"mimic_scale_min": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 100.0, "step": 0.5}),
"cfg_mode": (DynThresh.Modes, ),
"cfg_scale_min": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 100.0, "step": 0.5}),
"sched_val": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 100.0, "step": 0.01}),
"separate_feature_channels": (["enable", "disable"], ),
"scaling_startpoint": (DynThresh.Startpoints, ),
"variability_measure": (DynThresh.Variabilities, ),
"interpolate_phi": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}),
}
}
RETURN_TYPES = ("MODEL",)
FUNCTION = "patch"
CATEGORY = "advanced/mcmonkey"
def patch(self, model, mimic_scale, threshold_percentile, mimic_mode, mimic_scale_min, cfg_mode, cfg_scale_min, sched_val, separate_feature_channels, scaling_startpoint, variability_measure, interpolate_phi):
dynamic_thresh = DynThresh(mimic_scale, threshold_percentile, mimic_mode, mimic_scale_min, cfg_mode, cfg_scale_min, sched_val, 0, 999, separate_feature_channels == "enable", scaling_startpoint, variability_measure, interpolate_phi)
def sampler_dyn_thresh(args):
input = args["input"]
cond = input - args["cond"]
uncond = input - args["uncond"]
cond_scale = args["cond_scale"]
time_step = model.model.model_sampling.timestep(args["sigma"])
time_step = time_step[0].item()
dynamic_thresh.step = 999 - time_step
return input - dynamic_thresh.dynthresh(cond, uncond, cond_scale, None)
m = model.clone()
m.set_model_sampler_cfg_function(sampler_dyn_thresh)
return (m, )
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