def METHOD_NAME(
    cls_prob,
    bbox_pred,
    im_info,
    scales,
    ratios,
    feature_stride,
    threshold,
    rpn_pre_nms_top_n,
    rpn_post_nms_top_n,
    rpn_min_size,
    iou_loss,
):
    """Proposal operator.
    Parameters
    ----------
    cls_prob : relay.Expr
        4-D tensor with shape [batch, 2 * num_anchors, height, width].
    bbox_pred : relay.Expr
        4-D tensor with shape [batch, 4 * num_anchors, height, width].
    im_info : relay.Expr
        2-D tensor with shape [batch, 3]. The last dimension should be in format of
        [im_height, im_width, im_scale]
    scales : list/tuple of float
        Scales of anchor windows.
    ratios : list/tuple of float
        Ratios of anchor windows.
    feature_stride : int
        The size of the receptive field each unit in the convolution layer of the rpn, for example
        the product of all stride's prior to this layer.
    threshold : float
        Non-maximum suppression threshold.
    rpn_pre_nms_top_n : int
        Number of top scoring boxes to apply NMS. -1 to use all boxes.
    rpn_post_nms_top_n : int
        Number of top scoring boxes to keep after applying NMS to RPN proposals.
    rpn_min_size : int
        Minimum height or width in proposal.
    iou_loss : bool
        Usage of IoU loss.
    Returns
    -------
    output : relay.Expr
        2-D tensor with shape [batch * rpn_post_nms_top_n, 5]. The last dimension is in format of
        [batch_index, w_start, h_start, w_end, h_end].
    """
    return _make.METHOD_NAME(
        cls_prob,
        bbox_pred,
        im_info,
        scales,
        ratios,
        feature_stride,
        threshold,
        rpn_pre_nms_top_n,
        rpn_post_nms_top_n,
        rpn_min_size,
        iou_loss,
    )