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))
      if args.moe:
          for layer in self.moe_layer_list:
              x, _, _ = layer(x)
          x = self.fc4(x)
      else:
          x = self.fc3(x)
      return x
  
file_path: deepspeedexamples/training/cifar/cifar10_deepspeed.py
imports: import torch
  import torchvision
  import torchvision.transforms
  import argparse
  import deepspeed
  from deepspeed.accelerator import get_accelerator
  import matplotlib.pyplot
  import numpy
  import torch.nn
  import torch.nn.functional
  import torch.optim
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