code: def test_non_grad_output():
      class ForkNonGrad(nn.Module):
          def forward(self, input):
              return (input * 2, torch.rand(1))
  
      model = ForkNonGrad()
      input = torch.rand(1, requires_grad=True)
  
      output = make_checkpoint(model, input, 0)
      output[0].backward()
  
file_path: fairscale/tests/nn/pipe/test_checkpoint.py
imports: from functools import partial
  import pytest
  import torch
  from torch import nn
  import torch.cuda
  from fairscale.nn.pipe.checkpoint import Checkpointing, Function, TensorOrTensors, is_checkpointing, is_recomputing
  from fairscale.nn.pipe.dependency import fork, join
  from fairscale.nn.pipe.microbatch import Batch
label_desc: Use image node_id 8 for calling a global function with example usage: test_non_grad_output() and returns: unknown,  torch