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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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