code: def forward(self, x: Any) -> torch.Tensor:  # type: ignore
      x = self.relu(self.fc1(x))
      x = self.relu(self.fc2(x))
      x = self.fc3(x)
      return F.softmax(x, dim=1)
  
imports: import copy
  import os
  import tempfile
  from typing import Any, Dict, List, Tuple, Type
  import unittest
  import pytest
  import torch
  from torch import nn
  import torch.distributed
  import torch.nn.functional
  import fairscale.experimental.nn.data_parallel.gossip
  from fairscale.fair_dev.testing.testing import skip_if_single_gpu, spawn_for_all_world_sizes
label_desc: Use image node_id 2 for calling the Net obj's underlying member method code with example usage: obj.forward(x) and returns: F