87 lines
3.7 KiB
Python
87 lines
3.7 KiB
Python
from .dynthres_core import DynThresh
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class DynamicThresholdingComfyNode:
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"model": ("MODEL",),
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"mimic_scale": ("FLOAT", {"default": 7.0, "min": 0.0, "max": 100.0, "step": 0.5}),
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"threshold_percentile": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}),
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"mimic_mode": (DynThresh.Modes, ),
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"mimic_scale_min": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 100.0, "step": 0.5}),
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"cfg_mode": (DynThresh.Modes, ),
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"cfg_scale_min": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 100.0, "step": 0.5}),
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"sched_val": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 100.0, "step": 0.01}),
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"separate_feature_channels": (["enable", "disable"], ),
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"scaling_startpoint": (DynThresh.Startpoints, ),
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"variability_measure": (DynThresh.Variabilities, ),
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"interpolate_phi": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}),
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}
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}
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RETURN_TYPES = ("MODEL",)
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FUNCTION = "patch"
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CATEGORY = "advanced/mcmonkey"
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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):
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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)
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def sampler_dyn_thresh(args):
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input = args["input"]
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cond = input - args["cond"]
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uncond = input - args["uncond"]
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cond_scale = args["cond_scale"]
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time_step = model.model.model_sampling.timestep(args["sigma"])
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time_step = time_step[0].item()
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dynamic_thresh.step = 999 - time_step
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if cond_scale == mimic_scale:
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return input - (uncond + (cond - uncond) * cond_scale)
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else:
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return input - dynamic_thresh.dynthresh(cond, uncond, cond_scale, None)
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m = model.clone()
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m.set_model_sampler_cfg_function(sampler_dyn_thresh)
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return (m, )
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class DynamicThresholdingSimpleComfyNode:
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"model": ("MODEL",),
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"mimic_scale": ("FLOAT", {"default": 7.0, "min": 0.0, "max": 100.0, "step": 0.5}),
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"threshold_percentile": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}),
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}
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}
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RETURN_TYPES = ("MODEL",)
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FUNCTION = "patch"
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CATEGORY = "advanced/mcmonkey"
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def patch(self, model, mimic_scale, threshold_percentile):
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dynamic_thresh = DynThresh(mimic_scale, threshold_percentile, "CONSTANT", 0, "CONSTANT", 0, 0, 0, 999, False, "MEAN", "AD", 1)
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def sampler_dyn_thresh(args):
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input = args["input"]
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cond = input - args["cond"]
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uncond = input - args["uncond"]
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cond_scale = args["cond_scale"]
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time_step = model.model.model_sampling.timestep(args["sigma"])
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time_step = time_step[0].item()
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dynamic_thresh.step = 999 - time_step
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if cond_scale == mimic_scale:
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return input - (uncond + (cond - uncond) * cond_scale)
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else:
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return input - dynamic_thresh.dynthresh(cond, uncond, cond_scale, None)
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m = model.clone()
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m.set_model_sampler_cfg_function(sampler_dyn_thresh)
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return (m, )
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