code: def forward(self, x):
      x = F.relu(self.net1(x))
      x = F.relu(self.net2(x))
      x = F.relu(self.net3(x))
      x = F.relu(self.net4(x))
      return x
  
imports: import time
  from enum import auto, Enum
  import torch
  import torch.distributed
  import torch.distributed.checkpoint
  import torch.nn
  import torch.nn.functional
  from torch.distributed._tensor.device_mesh import init_device_mesh
  from torch.distributed.checkpoint.filesystem import _FileSystemCheckpointer
  from torch.distributed.checkpoint.state_dict import _patch_model_state_dict, _patch_optimizer_state_dict, get_state_dict
  from torch.distributed.distributed_c10d import ReduceOp
  from torch.distributed.fsdp import FullyShardedDataParallel
  from torch.distributed.fsdp.api import ShardingStrategy
  from torch.distributed.tensor.parallel import ColwiseParallel, parallelize_module, RowwiseParallel
  from torch.testing._internal.common_utils import instantiate_parametrized_tests, parametrize, run_tests
  from torch.testing._internal.distributed._tensor.common_dtensor import DTensorTestBase, skip_if_lt_x_gpu, with_comms
  from torch.testing._internal.distributed.checkpoint_utils import with_temp_dir
  from torch.testing._internal.distributed.common_state_dict import VerifyStateDictMixin
label_desc: Use image node_id 2 for calling the TestDummyModel obj's underlying member method code with example usage: obj.forward(x) and returns: x