def step_pred(self, score, x, t, generator=None):
        """
        Predict the sample from the previous timestep by reversing the SDE. This function propagates the diffusion
        process from the learned model outputs (most often the predicted noise).

        Args:
            score ():
            x ():
            t ():
            generator (`torch.Generator`, *optional*):
                A random number generator.
        """
        if self.timesteps is None:
            raise ValueError(
                "`self.timesteps` is not set, you need to run 'set_timesteps' after creating the scheduler"
            )

        # TODO(Patrick) better comments + non-PyTorch
        # postprocess model score
        log_mean_coeff = -0.25 * t**2 * (self.config.beta_max - self.config.beta_min) - 0.5 * t * self.config.beta_min
        std = torch.sqrt(1.0 - torch.exp(2.0 * log_mean_coeff))
        std = std.flatten()
        while len(std.shape) < len(score.shape):
            std = std.unsqueeze(-1)
        score = -score / std

        # compute
        dt = -1.0 / len(self.timesteps)

        beta_t = self.config.beta_min + t * (self.config.beta_max - self.config.beta_min)
        beta_t = beta_t.flatten()
        while len(beta_t.shape) < len(x.shape):
            beta_t = beta_t.unsqueeze(-1)
        drift = -0.5 * beta_t * x

        diffusion = torch.sqrt(beta_t)
        drift = drift - diffusion**2 * score
        x_mean = x + drift * dt

        # add noise
        noise = randn_tensor(x.shape, layout=x.layout, generator=generator, device=x.device, dtype=x.dtype)
        x = x_mean + diffusion * math.sqrt(-dt) * noise

        return x, x_mean

        Predict the sample from the previous timestep by reversing the SDE. This function propagates the diffusion
        process from the learned model outputs (most often the predicted noise).

        Args:
            score ():
            x ():
            t ():
            generator (`torch.Generator`, *optional*):
                A random number generator.
        
src/diffusers/schedulers/deprecated/scheduling_sde_vp.py