code: def forward(self, x):
      x = self.pool(F.relu(self.conv1(x)))
      x = self.pool(F.relu(self.conv2(x)))
      x = x.view(-1, 16 * 5 * 5)
      x = F.relu(self.fc1(x))
      x = F.relu(self.fc2(x))
      x = self.fc3(x)
      return x
  
imports: import numpy
  import os
  import tempfile
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.optim
  from filelock import FileLock
  from torch.utils.data import random_split
  import torchvision
  import torchvision.transforms
  from typing import Dict
  import ray
  from ray import train, tune
  from ray.train import Checkpoint
  from ray.tune.schedulers import ASHAScheduler
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: x