code: def test_two_inputs(self):
      tensor_kwargs = {
          "device": get_accelerator().current_device_name(),
          "dtype": torch.half,
      }
      inputs = [
          dist.get_rank() * torch.arange(0, 6, **tensor_kwargs),
          dist.get_rank() * torch.arange(6, 9, **tensor_kwargs),
      ]
  
      output1, output2 = reduce_scatter_coalesced(
          inputs, dist.get_world_group()
      )
  
      if dist.get_rank() == 0:
          assert output1.shape == (3,)
          assert torch.allclose(
              output1, torch.arange(0, 3, **tensor_kwargs) / 2
          )
          assert output2.shape == (2,)
          assert torch.allclose(
              output2, torch.arange(6, 8, **tensor_kwargs) / 2
          )
      elif dist.get_rank() == 1:
          assert output1.shape == (3,)
          assert torch.allclose(
              output1, torch.arange(3, 6, **tensor_kwargs) / 2
          )
          assert output2.shape == (1,)
          assert torch.allclose(
              output2, torch.arange(8, 9, **tensor_kwargs) / 2
          )
  
file_path: DeepSpeed/tests/unit/runtime/comm/test_coalesced_collectives.py
imports: import torch
  import deepspeed.comm
  from deepspeed.runtime.comm.coalesced_collectives import reduce_scatter_coalesced
  from deepspeed.accelerator import get_accelerator
  from unit.common import DistributedTest
label_desc: Use image node_id 2 for calling the TestReduceScatterCoalesced obj's underlying member method code with example usage: obj.test_two_inputs() without return types