def METHOD_NAME(self,
             inputs: torch.Tensor,
             data_samples: Optional[Sequence[TextDetDataSample]] = None,
             **kwargs) -> torch.Tensor:
    """Network forward process. Usually includes backbone, neck and head
    forward without any post-processing.
     Args:
        inputs (Tensor): Inputs with shape (N, C, H, W).
        data_samples (list[TextDetDataSample]): A list of N
            datasamples, containing meta information and gold annotations
            for each of the images.
    Returns:
        Tensor or tuple[Tensor]: A tuple of features from ``det_head``
        forward.
    """
    x = self.extract_feat(inputs)
    return self.det_head(x, data_samples)