def infer_with_flip_aug(self, x, pad_input: bool=True, **kwargs) -> torch.Tensor:
        """
        Inference interface for the model with horizontal flip augmentation
        Horizontal flip augmentation improves the accuracy of the model by averaging the output of the model with and without horizontal flip.
        Args:
            x (torch.Tensor): input tensor of shape (b, c, h, w)
            pad_input (bool, optional): whether to use padding augmentation. Defaults to True.
        Returns:
            torch.Tensor: output tensor of shape (b, 1, h, w)
        """
        # infer with horizontal flip and average
        out = self._infer_with_pad_aug(x, pad_input=pad_input, **kwargs)
        out_flip = self._infer_with_pad_aug(torch.flip(x, dims=[3]), pad_input=pad_input, **kwargs)
        out = (out + torch.flip(out_flip, dims=[3])) / 2
        return out

        Inference interface for the model with horizontal flip augmentation
        Horizontal flip augmentation improves the accuracy of the model by averaging the output of the model with and without horizontal flip.
        Args:
            x (torch.Tensor): input tensor of shape (b, c, h, w)
            pad_input (bool, optional): whether to use padding augmentation. Defaults to True.
        Returns:
            torch.Tensor: output tensor of shape (b, 1, h, w)
        
ControlNet-v1-1-nightly/annotator/zoe/zoedepth/models/depth_model.py