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Dual cfg node optimizations when cfg is 1.0 (#8747)

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comfyanonymous 2025-06-30 11:18:25 -07:00 committed by GitHub
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commit cf49a2c5b5
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1 changed files with 7 additions and 1 deletions
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comfy_extras/nodes_custom_sampler.py
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@ -609,8 +609,14 @@ class Guider_DualCFG(comfy.samplers.CFGGuider):
def predict_noise(self, x, timestep, model_options={}, seed=None): def predict_noise(self, x, timestep, model_options={}, seed=None):
negative_cond = self.conds.get("negative", None) negative_cond = self.conds.get("negative", None)
middle_cond = self.conds.get("middle", None) middle_cond = self.conds.get("middle", None)
positive_cond = self.conds.get("positive", None)
if model_options.get("disable_cfg1_optimization", False) == False:
if math.isclose(self.cfg2, 1.0):
negative_cond = None
if math.isclose(self.cfg1, 1.0):
middle_cond = None
out = comfy.samplers.calc_cond_batch(self.inner_model, [negative_cond, middle_cond, self.conds.get("positive", None)], x, timestep, model_options) out = comfy.samplers.calc_cond_batch(self.inner_model, [negative_cond, middle_cond, positive_cond], x, timestep, model_options)
return comfy.samplers.cfg_function(self.inner_model, out[1], out[0], self.cfg2, x, timestep, model_options=model_options, cond=middle_cond, uncond=negative_cond) + (out[2] - out[1]) * self.cfg1 return comfy.samplers.cfg_function(self.inner_model, out[1], out[0], self.cfg2, x, timestep, model_options=model_options, cond=middle_cond, uncond=negative_cond) + (out[2] - out[1]) * self.cfg1
class DualCFGGuider: class DualCFGGuider: