code: def test_input_requiring_grad():
      dbn = DeferredBatchNorm(3, chunks=CHUNKS)
  
      input = torch.rand(16, 3, 224, 224)
      input = tilt_dist(input)
      input.requires_grad = True
  
      chunked_forward(dbn, input)
  
      assert not dbn.sum.requires_grad
      assert dbn.sum.grad_fn is None
  
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 9 for calling a global function with example usage: test_input_requiring_grad() without return types