code: def _accumulate_loss(self, report: "Report"):
      for key, value in report.losses.items():
          if key not in self.losses.keys():
              warnings.warn(
                  f"{key} not found in report. Loss calculation "
                  + "might not work as expected."
              )
              self.losses[key] = value
          if isinstance(self.losses[key], torch.Tensor):
              self.losses[key] += value
  
imports: import collections
  import collections.abc
  import copy
  import warnings
  from collections import OrderedDict
  from typing import Any, Callable, Dict, List, Optional, Union
  import torch
  from mmf.common.sample import detach_tensor, SampleList
label_desc: Use image node_id 13 for calling the Report obj's underlying member method code with example usage: obj._accumulate_loss(report) without return types