code: def gen_gt_boxes(self, gt_boxes, gt_classes, num_gt):
      # gt_boxes is (max_gt_boxes, batch_size)
      # gt_classes is (max_gt_boxes, batch_size)
      # num_gt is (1, batch_size)  number of GT box counts
      bboxes = [np.zeros((ngt, 5)) for ngt in num_gt[0]]
  
      gt_boxes = gt_boxes.reshape((-1, 4, self.be.bsz))
      for batch in range(self.be.bsz):
          ngt = num_gt[0][batch]
          bboxes[batch][:, :4] = gt_boxes[:ngt, :, batch]
          bboxes[batch][:, 4] = gt_classes[:ngt, batch]
  
      return bboxes
  
imports: from neon import NervanaObject
  import numpy
  from util import util
  from neon.transforms import Softmax
label_desc: Use image node_id 16 for calling the MBoxLoss obj's underlying member method code with example usage: obj.gen_gt_boxes(gt_boxes, gt_classes, num_gt) and returns: bboxes