code: def _get_num_gts(self, targets, dtype="float32"):
      num_gts = sum(len(a) for a in targets)
      num_gts = paddle.to_tensor([num_gts], dtype=dtype)
      if paddle.distributed.get_world_size() > 1:
          paddle.distributed.all_reduce(num_gts)
          num_gts /= paddle.distributed.get_world_size()
      num_gts = paddle.clip(num_gts, min=1.0)
      return num_gts
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from ppdet.core.workspace import register
  from .iou_loss import GIoULoss
  from ..transformers import bbox_cxcywh_to_xyxy, sigmoid_focal_loss, varifocal_loss_with_logits
  from ..bbox_utils import bbox_iou
label_desc: Use image node_id 9 for calling the DETRLoss obj's underlying member method code with example usage: obj._get_num_gts(targets, dtype) and returns: num_gts