code: def initialize_icarl_net(m: Module):
      """Initialize the input network based on `kaiming_normal`
      with `mode=fan_in` for `Conv2d` and `Linear` blocks.
      Biases are initialized to zero.
      :param m: input network (should be IcarlNet).
      """
      if isinstance(m, Conv2d):
          kaiming_normal_(
              m.weight.data, mode="fan_in", nonlinearity="relu"
          )
          if m.bias is not None:
              zeros_(m.bias.data)
  
      elif isinstance(m, Linear):
          kaiming_normal_(
              m.weight.data, mode="fan_in", nonlinearity="sigmoid"
          )
          if m.bias is not None:
              zeros_(m.bias.data)
  
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 4 for calling a global function with example usage: initialize_icarl_net(m) without return types