def infer(self, x, pad_input: bool=True, with_flip_aug: bool=True, **kwargs) -> torch.Tensor:
        """
        Inference interface for the model
        Args:
            x (torch.Tensor): input tensor of shape (b, c, h, w)
            pad_input (bool, optional): whether to use padding augmentation. Defaults to True.
            with_flip_aug (bool, optional): whether to use horizontal flip augmentation. Defaults to True.
        Returns:
            torch.Tensor: output tensor of shape (b, 1, h, w)
        """
        if with_flip_aug:
            return self.infer_with_flip_aug(x, pad_input=pad_input, **kwargs)
        else:
            return self._infer_with_pad_aug(x, pad_input=pad_input, **kwargs)

        Inference interface for the model
        Args:
            x (torch.Tensor): input tensor of shape (b, c, h, w)
            pad_input (bool, optional): whether to use padding augmentation. Defaults to True.
            with_flip_aug (bool, optional): whether to use horizontal flip 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