docstr: Apply function to the final layer of the head.
  
  Typically, you can use this method to apply custom initialization
  to the final layer of the head.
  
  :param func: Function to apply to the final prediction layer. If head contains
  supervision layers, function can be applied to them as well.
docstr_tok: ["Apply","function","to","the","final","layer","of","the","head",".","Typically",",","you","can","use","this","method","to","apply","custom","initialization","to","the","final","layer","of","the","head",".",":","param","func",":","Function","to","apply","to","the","final","prediction","layer",".","If","head","contains","supervision","layers",",","function","can","be","applied","to","them","as","well","."]
code: def apply_to_final_layer(self, func: Callable[[nn.Module], None]):
      """
      Apply function to the final layer of the head.
  
      Typically, you can use this method to apply custom initialization
      to the final layer of the head.
  
      :param func: Function to apply to the final prediction layer. If head contains
      supervision layers, function can be applied to them as well.
  
      """
      raise NotImplementedError(
          "This method is not implemented in class "
          + self.__class__.__name__
      )
  
imports: import dataclasses
  from abc import abstractmethod
  from typing import Protocol, Tuple, List, Union, Mapping, Callable
  import numpy
  import torch.jit
  from torch import nn, Tensor
  from pytorch_toolbelt.utils import pytorch_toolbelt_deprecated
label_desc: Use image node_id 3 for calling the AbstractHead obj's underlying member method code with example usage: obj.apply_to_final_layer(func) without return types