code: def test_convert_deferred_batch_norm():
      bn = nn.BatchNorm2d(3, track_running_stats=False)
      bn = DeferredBatchNorm.convert_deferred_batch_norm(
          bn, chunks=CHUNKS
      )
      assert (
          type(bn) is nn.BatchNorm2d
      )  # because of track_running_stats=False
  
      dbn = DeferredBatchNorm(3, chunks=CHUNKS)
      dbn_again = DeferredBatchNorm.convert_deferred_batch_norm(
          dbn, chunks=CHUNKS
      )
      assert dbn is dbn_again
  
      dbn_again = DeferredBatchNorm.convert_deferred_batch_norm(
          dbn, chunks=CHUNKS + 1
      )
      assert dbn is not dbn_again
  
file_path: fairscale/tests/nn/pipe/test_deferred_batch_norm.py
imports: from copy import deepcopy
  from itertools import chain
  import pytest
  import torch
  from torch import nn, optim
  from fairscale.nn.pipe.batchnorm import DeferredBatchNorm
label_desc: Use image node_id 5 for calling a global function with example usage: test_convert_deferred_batch_norm() without return types