class_docstr: Class defining categorical distribution type functionality
docstr: Update tabu_edges taking into account expanded columns.
  
  Args:
      tabu_edges: The original tabu_edges.
  
  Returns:
      Preprocessed tabu_edges.
docstr_tok: ["Update","tabu_edges","taking","into","account","expanded","columns",".","Args",":","tabu_edges",":","The","original","tabu_edges",".","Returns",":","Preprocessed","tabu_edges","."]
code: def preprocess_tabu_edges(
      self, tabu_edges: List[Tuple[int, int]]
  ) -> List[Tuple[int, int]]:
      """
      Update tabu_edges taking into account expanded columns.
  
      Args:
          tabu_edges: The original tabu_edges.
  
      Returns:
          Preprocessed tabu_edges.
      """
      return self.update_tabu_edges(
          idx_group=self.idx_group,
          tabu_edges=tabu_edges,
          tabu_idx_group=True,
      )
  
imports: from copy import deepcopy
  from typing import Dict, List, Tuple
  import numpy
  import torch
  from sklearn.preprocessing import OneHotEncoder
  from torch import nn
  from causalnex.structure.pytorch.dist_type._base import DistTypeBase, ExpandColumnsMixin
  from causalnex.structure.structuremodel import StructureModel
label_desc: Use image node_id 3 for calling the DistTypeCategorical obj's underlying member method code with example usage: obj.preprocess_tabu_edges(tabu_edges) and returns: self