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@@ -274,8 +274,6 @@ class DDPMScheduler(SchedulerMixin, ConfigMixin):
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new_config["predict_epsilon"] = predict_epsilon
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self._internal_dict = FrozenDict(new_config)
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t = timestep
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if model_output.shape[1] == sample.shape[1] * 2 and self.variance_type in ["learned", "learned_range"]:
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model_output, predicted_variance = torch.split(model_output, sample.shape[1], dim=1)
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else:
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