class_docstr: :class:`DecisionTreeDataset` is based on :class:`~recbole.data.dataset.dataset.Dataset`,
  and
  
  Attributes:
code: def _judge_token_and_convert(self, feat):
      # get columns whose type is token
      col_list = []
      for col_name in feat:
          if col_name == self.uid_field or col_name == self.iid_field:
              continue
          if self.field2type[col_name] == FeatureType.TOKEN:
              col_list.append(col_name)
          elif self.field2type[col_name] in {
              FeatureType.TOKEN_SEQ,
              FeatureType.FLOAT_SEQ,
          }:
              feat = feat.drop([col_name], axis=1, inplace=False)
  
      # get hash map
      for col in col_list:
          self.hash_map[col] = dict({})
          self.hash_count[col] = 0
  
      del_col = []
      for col in self.hash_map:
          if col in feat.keys():
              for value in feat[col]:
                  # print(value)
                  if value not in self.hash_map[col]:
                      self.hash_map[col][value] = self.hash_count[col]
                      self.hash_count[col] = self.hash_count[col] + 1
                      if (
                          self.hash_count[col]
                          > self.config["token_num_threshold"]
                      ):
                          del_col.append(col)
                          break
  
      for col in del_col:
          del self.hash_count[col]
          del self.hash_map[col]
          col_list.remove(col)
      self.convert_col_list.extend(col_list)
  
      # transform the original data
      for col in self.hash_map.keys():
          if col in feat.keys():
              feat[col] = feat[col].map(self.hash_map[col])
  
      return feat
  
file_path: RecBole/recbole/data/dataset/decisiontree_dataset.py
imports: from recbole.data.dataset import Dataset
  from recbole.utils import FeatureType
label_desc: Use image node_id 2 for calling the DecisionTreeDataset obj's underlying member method code with example usage: obj._judge_token_and_convert(feat) and returns: feat