code: def build_train_batch(
      records: Sequence[RecordType],
  ) -> Tuple[dict, List[Dict[str, torch.Tensor]]]:
      images, labels, bboxes, img_metas = [], [], [], []
      for record in records:
          images.append(_img_tensor(record))
          img_metas.append(_img_meta(record))
          labels.append(_labels(record))
          bboxes.append(_bboxes(record))
  
      data = {
          "img": torch.stack(images),
          "img_metas": img_metas,
          "gt_labels": labels,
          "gt_bboxes": bboxes,
      }
  
      return data, records
  
file_path: icevision/icevision/models/mmdet/common/bbox/dataloaders.py
imports: from icevision.models.mmdet.common.utils import convert_background_from_zero_to_last
  from icevision.core import *
  from icevision.imports import *
  from icevision.models.utils import *
label_desc: Use image node_id 4 for calling a global function with example usage: build_train_batch(records) and returns: data,  records