code: def forward(self, loss_dict, embeddings, labels):
      self.reset_stats()
      assert len(loss_dict) == 1
      loss_name = list(loss_dict.keys())[0]
      loss_info = loss_dict[loss_name]
      (
          losses,
          loss_indices,
          reduction_type,
          kwargs,
      ) = self.unpack_loss_info(loss_info)
      loss_val = self.reduce_the_loss(
          losses,
          loss_indices,
          reduction_type,
          kwargs,
          embeddings,
          labels,
      )
      return loss_val
  
imports: import torch
  from ..utils import common_functions
  from ..utils.module_with_records import ModuleWithRecords
label_desc: Use image node_id 2 for calling the BaseReducer obj's underlying member method code with example usage: obj.forward(loss_dict, embeddings, labels) and returns: loss_val