Enable cfg1 optimization for DualModelGuider

This commit is contained in:
kijai 2026-06-05 01:56:02 +03:00
parent 4d360f9c9d
commit f4f350fcda

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@ -933,9 +933,10 @@ class Guider_DualModel(comfy.samplers.CFGGuider):
def predict_noise(self, x, timestep, model_options={}, seed=None):
positive = self.conds.get("positive", None)
if self.uncond_inner is None: # cfg == 1 or no negative -> single model, cond only
return comfy.samplers.calc_cond_batch(self.inner_model, [positive], x, timestep, model_options)[0]
cond = comfy.samplers.calc_cond_batch(self.inner_model, [positive], x, timestep, model_options)[0]
# uncond model not loaded (base cfg==1/no negative), or cfg driven to 1.0 this step -> single model, cond only
if self.uncond_inner is None or (math.isclose(self.cfg, 1.0) and not model_options.get("disable_cfg1_optimization", False)):
return cond
uncond_model_options = model_options
if "multigpu_clones" in model_options: # TODO: support multigpu instead of just running uncond on a single GPU