code: def test_distributed_tuple_loss_and_miner_efficient(self):
      for use_ref in [False, True]:
          for pass_labels_to_loss_fn in [False, True]:
              self.loss_and_miner_tester(
                  ContrastiveLoss,
                  PairMarginMiner,
                  True,
                  False,
                  use_ref,
                  miner_kwargs={"pos_margin": 0.5, "neg_margin": 0.5},
                  pass_labels_to_loss_fn=pass_labels_to_loss_fn,
              )
  
imports: import logging
  import os
  import unittest
  import torch
  import torch.distributed
  import torch.multiprocessing
  import torch.optim
  from torch.nn.parallel import DistributedDataParallel
  from pytorch_metric_learning.losses import ContrastiveLoss, CrossBatchMemory
  from pytorch_metric_learning.miners import PairMarginMiner
  from pytorch_metric_learning.utils import distributed
  from ..None import TEST_DEVICE, TEST_DTYPES
label_desc: Use image node_id 5 for calling the TestDistributedLossWrapper obj's underlying member method code with example usage: obj.test_distributed_tuple_loss_and_miner_efficient() without return types