code: def forward(self, x, y):
      x1 = self.mlp(x)
      x2 = self.mlp(y)
      return torch.cat((x1, x2), dim=1)
  
imports: from contextlib import suppress
  import numpy
  import pytest
  import torch
  import torch.distributed
  import torch.multiprocessing
  from torch.nn import Linear, Sequential
  from fairscale.fair_dev.testing.testing import GPT2, SGDWithPausingCompute, available_devices, check_same_models_across_ranks, skip_if_less_than_four_gpu, skip_if_no_cuda, skip_if_single_gpu, temp_files_ctx
  from fairscale.nn.data_parallel import ShardedDataParallel
  from fairscale.optim import OSS
label_desc: Use image node_id 2 for calling the _DoubleInput obj's underlying member method code with example usage: obj.forward(x, y) and returns: torch