class_docstr: test all input tensors without grad
class_docstr_tok: ["test","all","input","tensors","without","grad"]
code: def test_ckpt_non_tensor_output_ordering(self, non_tensor_output):
      module = LinearNonTensorOutput(non_tensor_output)
      inputs = torch.rand(HIDDEN_DIM)
  
      # First return is a tensor
      ordering = [True]
      if type(non_tensor_output) in [list, tuple]:
          ordering += [torch.is_tensor(t) for t in non_tensor_output]
      else:
          ordering += [torch.is_tensor(non_tensor_output)]
      _test_activation_checkpoint_ordering(module, ordering, inputs)
  
imports: import sys
  import torch
  import pytest
  from importlib import util
  from deepspeed.runtime.activation_checkpointing.checkpointing import non_reentrant_checkpoint
  from unit.common import DistributedTest
label_desc: Use image node_id 1 for calling the TestCheckpointNonTensorOutputOrderingWithoutGrad obj's underlying member method code with example usage: obj.test_ckpt_non_tensor_output_ordering(non_tensor_output) without return types