code: def forward(self, x):
      x = self.conv1(x)
      x = self.conv2(x)
      x = self.conv3(x)
      x = self.pool(x)
      x = self.flatten(x)
      x = self.fc1(x)
      x = self.relu(x)
      x = self.fc2(x)
      x = self.relu(x)
      x = self.fc3(x)
      x = self.relu(x)
      x = self.fc4(x)
      return x
  
imports: import functools
  import os
  import tempfile
  from parameterized import parameterized
  import pytest
  import torch
  import torch.distributed
  import torch.multiprocessing
  import torch.nn
  from torch.optim import Adam
  from fairscale.fair_dev.testing.testing import in_temporary_directory, skip_if_single_gpu, temp_files_ctx
  from fairscale.nn import FullyShardedDataParallel
  from tests.nn.data_parallel.test_fsdp import DistributedTest, MixtureOfExperts, rename_test, spawn_and_init
label_desc: Use image node_id 3 for calling the ConvolutionalModel obj's underlying member method code with example usage: obj.forward(x) and returns: x