code: def rpc_multiple_tensors():
      class FuseTwo(nn.Module):
          def forward(self, left, right):
              return left + right
  
      class SplitTwo(nn.Module):
          def forward(self, inputs):
              return (inputs, 2 * inputs)
  
file_path: fairscale/tests/nn/pipe_process/test_rpc.py
imports: import copy
  import os
  import pytest
  import torch
  from torch import nn
  from torch.distributed import rpc
  from fairscale.fair_dev.testing.testing import get_worker_map, torch_spawn
  from fairscale.internal import torch_version
  from fairscale.nn.model_parallel.initialize import get_pipeline_parallel_group
  from fairscale.nn.pipe import PipeRPCWrapper
label_desc: Use image node_id 9 for calling a global function with example usage: rpc_multiple_tensors() and returns: unknown, inputs,  unknown