def METHOD_NAME(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