code: def __init__(self):
      super().__init__()
      self.trunk = nn.Sequential(
          nn.Conv2d(3, 64, kernel_size=3),
          nn.ReLU(inplace=True),
          nn.AdaptiveAvgPool2d(output_size=(1, 1)),
          nn.Flatten(),
      )
      self.head = nn.Linear(64, 10)
  
      self.trunk = FSDP(self.trunk)
  
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 1 to create a new FreezeModel object from inherited base classes: nn with example: obj = FreezeModel()