docstr: head_out_list(List[Tensor]): scores, deltas, rois
docstr_tok: ["head_out_list","(","List","[","Tensor","]",")",":","scores",",","deltas",",","rois"]
code: def get_prediction(self, head_out_list):
      """
      head_out_list(List[Tensor]): scores, deltas, rois
      """
      pred_list = []
      scores_list = [F.softmax(head[0]) for head in head_out_list]
      scores = paddle.add_n(scores_list) / self.num_cascade_stages
      # Get deltas and rois from the last stage
      _, deltas, rois = head_out_list[-1]
      return scores, deltas, rois
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddle.nn.initializer import Normal
  from ppdet.core.workspace import register
  from .bbox_head import BBoxHead, TwoFCHead, XConvNormHead
  from .roi_extractor import RoIAlign
  from ..shape_spec import ShapeSpec
  from ..bbox_utils import delta2bbox, clip_bbox, nonempty_bbox
  from ..cls_utils import _get_class_default_kwargs
label_desc: Use image node_id 5 for calling the CascadeHead obj's underlying member method code with example usage: obj.get_prediction(head_out_list) and returns: scores,  deltas,  rois