Make contrastive guidance loss do constant instead of sigma loss schedule by default
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@@ -594,7 +594,7 @@ class TrainConfig:
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# toward 1.0 as sigma falls (effective = 1 + (target - 1) * sigma) so the
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# extrapolation never amplifies the unpredictable fresh-noise term at low
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# sigma. Needed for guidance-distilled models with no guidance embedding.
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self.guidance_loss_schedule: str = kwargs.get('guidance_loss_schedule', 'sigma')
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self.guidance_loss_schedule: str = kwargs.get('guidance_loss_schedule', 'constant')
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self.unconditional_prompt: str = kwargs.get('unconditional_prompt', '')
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if isinstance(self.guidance_loss_target, tuple):
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self.guidance_loss_target = list(self.guidance_loss_target)
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