def convert_segmentation_to_rle(segmentation):
    """
    Converts given segmentation map of shape `(height, width)` to the run-length encoding (RLE) format.

    Args:
        segmentation (`torch.Tensor` or `numpy.array`):
            A segmentation map of shape `(height, width)` where each value denotes a segment or class id.
    Returns:
        `List[List]`: A list of lists, where each list is the run-length encoding of a segment / class id.
    """
    segment_ids = torch.unique(segmentation)

    run_length_encodings = []
    for idx in segment_ids:
        mask = torch.where(segmentation == idx, 1, 0)
        rle = binary_mask_to_rle(mask)
        run_length_encodings.append(rle)

    return run_length_encodings

    Converts given segmentation map of shape `(height, width)` to the run-length encoding (RLE) format.

    Args:
        segmentation (`torch.Tensor` or `numpy.array`):
            A segmentation map of shape `(height, width)` where each value denotes a segment or class id.
    Returns:
        `List[List]`: A list of lists, where each list is the run-length encoding of a segment / class id.
    
dpkd/transformers/src/transformers/models/deformable_detr/image_processing_deformable_detr.py