docstr: Test to ensure excluded modules are not wrapped, regardless if the total param size is greater than the
  min_num_params.
docstr_tok: ["Test","to","ensure","excluded","modules","are","not","wrapped",",","regardless","if","the","total","param","size","is","greater","than","the","min_num_params","."]
code: def test_auto_wrap_preset_exclude_wrap(self):
      """
      Test to ensure excluded modules are not wrapped, regardless if the total param size is greater than the
      min_num_params.
      """
      with enable_wrap(
          wrapper_cls=FSDP,
          process_group=self.process_group,
          flatten_parameters=False,
      ):
          sequential = nn.ModuleList([nn.Linear(5, 5), nn.Linear(5, 5)])
          my_auto_wrap_policy = functools.partial(
              default_auto_wrap_policy, min_num_params=40
          )
          model = auto_wrap(
              sequential, auto_wrap_policy=my_auto_wrap_policy
          )
      assert isinstance(model, nn.ModuleList)
      assert isinstance(model[0], nn.Linear)
      assert isinstance(model[1], nn.Linear)
  
imports: import functools
  import os
  import random
  import unittest
  import torch
  import torch.nn
  import torch.nn.functional
  from fairscale.fair_dev.testing.testing import DummyProcessGroup
  from fairscale.nn import FullyShardedDataParallel
  from fairscale.nn import auto_wrap, default_auto_wrap_policy, enable_wrap, wrap
label_desc: Use image node_id 7 for calling the TestAutoWrap obj's underlying member method code with example usage: obj.test_auto_wrap_preset_exclude_wrap() without return types