class_docstr: Implementation of `TridentNet <https://arxiv.org/abs/1901.01892>`_
docstr: make copies of img and gts to fit multi-branch.
docstr_tok: ["make","copies","of","img","and","gts","to","fit","multi-branch","."]
code: def forward_train(
      self, img, img_metas, gt_bboxes, gt_labels, **kwargs
  ):
      """make copies of img and gts to fit multi-branch."""
      trident_gt_bboxes = tuple(gt_bboxes * self.num_branch)
      trident_gt_labels = tuple(gt_labels * self.num_branch)
      trident_img_metas = tuple(img_metas * self.num_branch)
  
      return super(TridentFasterRCNN, self).forward_train(
          img, trident_img_metas, trident_gt_bboxes, trident_gt_labels
      )
  
file_path: insightface/detection/scrfd/mmdet/models/detectors/trident_faster_rcnn.py
imports: from ..builder import DETECTORS
  from .faster_rcnn import FasterRCNN
label_desc: Use image node_id 4 for calling the TridentFasterRCNN obj's underlying member method code with example usage: obj.forward_train(img, img_metas, gt_bboxes, gt_labels) and returns: super