code: def __init__(self, miner, efficient=False):
      super().__init__()
      if not isinstance(miner, BaseMiner):
          raise TypeError("The input miner must extend BaseMiner")
      self.miner = miner
      self.efficient = efficient
  
imports: import torch
  from ..losses import BaseMetricLossFunction, CrossBatchMemory
  from ..miners import BaseMiner
  from ..utils import common_functions
  from ..utils import loss_and_miner_utils
label_desc: Use image node_id 1 to create a new DistributedMinerWrapper object from inherited base classes: torch.nn with example: obj = DistributedMinerWrapper(miner, efficient)