code: def unpack_loss_info(self, loss_info):
      (
          losses,
          loss_indices,
          reduction_type,
          kwargs,
      ) = super().unpack_loss_info(loss_info)
      if reduction_type != "already_reduced":
          kwargs = {"divisor": loss_info["divisor"]}
          self.divisor = kwargs["divisor"]
      return losses, loss_indices, reduction_type, kwargs
  
file_path: pytorch-metric-learning/src/pytorch_metric_learning/reducers/divisor_reducer.py
imports: import torch
  from ..utils import common_functions
  from .base_reducer import BaseReducer
label_desc: Use image node_id 2 for calling the DivisorReducer obj's underlying member method code with example usage: obj.unpack_loss_info(loss_info) and returns: losses,  loss_indices,  reduction_type,  kwargs