code: def _create_model(
      with_fsdp, with_nested_trunk, freeze_after_wrap_fsdp
  ):
      if with_nested_trunk:
          model = NestedTrunkModel(with_fsdp, freeze_after_wrap_fsdp)
      else:
          model = Model(with_fsdp, freeze_after_wrap_fsdp)
      return model
  
imports: from enum import Enum
  from itertools import product
  import tempfile
  import pytest
  import torch
  import torch.multiprocessing
  import torch.nn
  from torch.nn.parallel import DistributedDataParallel
  import torch.optim
  from fairscale.fair_dev.testing.testing import dist_init, objects_are_equal, rmf, skip_if_single_gpu, teardown
  from fairscale.nn.data_parallel import FullyShardedDataParallel
label_desc: Use image node_id 3 for calling a global function with example usage: _create_model(with_fsdp, with_nested_trunk, freeze_after_wrap_fsdp) and returns: model