docstr: Decode the bbox and do NMS for JDE model. 
  
  Args:
      head_out (list): Bbox_pred and cls_prob of bbox_head output.
      anchors (list): Anchors of JDE model.
  
  Returns:
      boxes_idx (Tensor): The index of kept bboxes after decode 'JDEBox'. 
      bbox_pred (Tensor): The output is the prediction with shape [N, 6]
          including labels, scores and bboxes.
      bbox_num (Tensor): The number of prediction of each batch with shape [N].
      nms_keep_idx (Tensor): The index of kept bboxes after NMS. 
code: def forward(self, head_out, anchors):
      """
      Decode the bbox and do NMS for JDE model.
  
      Args:
          head_out (list): Bbox_pred and cls_prob of bbox_head output.
          anchors (list): Anchors of JDE model.
  
      Returns:
          boxes_idx (Tensor): The index of kept bboxes after decode 'JDEBox'.
          bbox_pred (Tensor): The output is the prediction with shape [N, 6]
              including labels, scores and bboxes.
          bbox_num (Tensor): The number of prediction of each batch with shape [N].
          nms_keep_idx (Tensor): The index of kept bboxes after NMS.
      """
      boxes_idx, yolo_boxes_scores = self.decode(head_out, anchors)
  
      if len(boxes_idx) == 0:
          boxes_idx = self.fake_boxes_idx
          yolo_boxes_out = self.fake_yolo_boxes_out
          yolo_scores_out = self.fake_yolo_scores_out
      else:
          yolo_boxes = paddle.gather_nd(yolo_boxes_scores, boxes_idx)
          # TODO: only support bs=1 now
          yolo_boxes_out = paddle.reshape(
              yolo_boxes[:, :4], shape=[1, len(boxes_idx), 4]
          )
          yolo_scores_out = paddle.reshape(
              yolo_boxes[:, 4:5], shape=[1, 1, len(boxes_idx)]
          )
          boxes_idx = boxes_idx[:, 1:]
  
      if self.return_idx:
          bbox_pred, bbox_num, nms_keep_idx = self.nms(
              yolo_boxes_out, yolo_scores_out, self.num_classes
          )
          if bbox_pred.shape[0] == 0:
              bbox_pred = self.fake_bbox_pred
              bbox_num = self.fake_bbox_num
              nms_keep_idx = self.fake_nms_keep_idx
          return boxes_idx, bbox_pred, bbox_num, nms_keep_idx
      else:
          bbox_pred, bbox_num, _ = self.nms(
              yolo_boxes_out, yolo_scores_out, self.num_classes
          )
          if bbox_pred.shape[0] == 0:
              bbox_pred = self.fake_bbox_pred
              bbox_num = self.fake_bbox_num
          return _, bbox_pred, bbox_num, _
  
imports: import numpy
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from ppdet.core.workspace import register
  from ppdet.modeling.bbox_utils import nonempty_bbox
  from .transformers import bbox_cxcywh_to_xyxy
label_desc: Use image node_id 2 for calling the JDEBBoxPostProcess obj's underlying member method code with example usage: obj.forward(head_out, anchors) and returns: boxes_idx,  bbox_pred,  bbox_num,  nms_keep_idx, _,  bbox_pred,  bbox_num,  _