code: def forward(self, x):
      x = self.feature_extractor(x)  # Already flattened
      x = self.classifier(x)
      return x
  
imports: from typing import Union, Sequence, Callable
  import torch
  from torch.nn import Module, Sequential, BatchNorm2d, Conv2d, ReLU, ConstantPad3d, Identity, AdaptiveAvgPool2d, Linear
  from torch import Tensor
  from torch.nn.init import zeros_, kaiming_normal_
  from torch.nn.modules.flatten import Flatten
  import torch.nn.functional
label_desc: Use image node_id 2 for calling the IcarlNet obj's underlying member method code with example usage: obj.forward(x) and returns: x