code: def make_icarl_net(num_classes: int, n=5, c=3) -> IcarlNet:
      """Create :py:class:`IcarlNet` network, the ResNet used in
      ICarl.
      :param num_classes: number of classes, network output size
      :param n: depth of each residual blocks stack
      :param c: number of input channels
      """
      return IcarlNet(num_classes, n=n, c=c)
  
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 3 for calling a global function with example usage: make_icarl_net(num_classes, n, c) and returns: IcarlNet