code: def test_non_tensor_tuple():
      class NonTensorTuple(nn.Module):
          def forward(self, x):
              return (x, "hello")
  
      model = nn.Sequential(NonTensorTuple())
      model = Pipe(model, balance=[1], devices=["cpu"])
      x = torch.rand(1)
  
      # TypeError: CheckpointBackward.forward: expected Variable (got str) for return value 1
      with pytest.raises(TypeError):
          model(x)
  
      # TypeError: expected Tensor to scatter, but got str
      with pytest.raises(TypeError):
          model((x, "hello"))
  
imports: from collections import OrderedDict
  from copy import deepcopy
  import time
  import pytest
  import torch
  from torch import nn
  from fairscale.nn.pipe import Pipe
label_desc: Use image node_id 22 for calling a global function with example usage: test_non_tensor_tuple() and returns: x,  str