code: def forward(self, x):
      with self.autograd_ctx():
          x = self.trunk(x)
      return self.head(x)
  
imports: import contextlib
  import sys
  from enum import Enum
  import torch
  import torch.nn
  import torch.optim
  from torch import distributed
  from torch.distributed.fsdp import FullyShardedDataParallel
  from torch.nn.parallel import DistributedDataParallel
  from torch.testing._internal.common_distributed import skip_if_lt_x_gpu
  from torch.testing._internal.common_fsdp import FSDPTest, get_full_params
  from torch.testing._internal.common_utils import instantiate_parametrized_tests, parametrize, run_tests, TEST_WITH_DEV_DBG_ASAN
label_desc: Use image node_id 3 for calling the Model obj's underlying member method code with example usage: obj.forward(x) and returns: self