fix incorrect sigmas of DPMSolverMultistepInverseScheduler for flow_prediction #12262
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yiyixuxu
reviewed
Sep 10, 2025
| @@ -299,7 +299,9 @@ def set_timesteps(self, num_inference_steps: int = None, device: Union[str, torc | |||
| elif self.config.use_flow_sigmas: | |||
| alphas = np.linspace(1, 1 / self.config.num_train_timesteps, num_inference_steps + 1) | |||
| sigmas = 1.0 - alphas | |||
| sigmas = np.flip(self.config.flow_shift * sigmas / (1 + (self.config.flow_shift - 1) * sigmas))[:-1].copy() | |||
| sigmas = np.flip(self.config.flow_shift * sigmas / (1 + (self.config.flow_shift - 1) * sigmas))[:-1][ | |||
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is it same as this?
sigmas = (self.config.flow_shift * sigmas / (1 + (self.config.flow_shift - 1) * sigmas))[1:].copy()
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What does this PR do?
This PR fixes a bug in DPMSolverMultistepInverseScheduler where the sigmas used in flow_prediction were not properly inverted.
Previously, the scheduler directly used forward sigmas, which led to inconsistencies during inverse diffusion steps.
This PR ensures that the sigmas are correctly inverted before being applied in flow_prediction, aligning the behavior with the intended inverse process.
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