docstr: Converts a sequence of ids in Tabular tokens using the vocab.
docstr_tok: ["Converts","a","sequence","of","ids","in","Tabular","tokens","using","the","vocab","."]
code: def ids_to_tokens(self, ids, skip_special_tokens=False):
      """Converts a sequence of ids in Tabular tokens using the vocab."""
      tokens = []
      sizes = self.code_column.sizes
      ids_size = sum(sizes)
      cindex = 0
      eor_pos = find_index_of(ids, self.eor)
      eod_pos = find_index_of(ids, self.eod)
      if eor_pos >= 0 and eod_pos >= 0:
          idd = min(eor_pos, eod_pos)
          cindex = (ids_size - idd) % ids_size
      elif eor_pos >= 0 and eod_pos < 0:
          idd = eor_pos
          cindex = (ids_size - idd) % ids_size
      elif eod_pos >= 0 and eor_pos < 0:
          idd = eod_pos
          cindex = (ids_size - idd) % ids_size
      cum_sizes = numpy.cumsum(sizes)
      old_column_index = -1
      token_ids = []
      for i in ids:
          if i in self.special_tokens_decoder:
              if not skip_special_tokens:
                  tokens.append(self.special_tokens_decoder[i])
          else:
              index = cindex % ids_size
              column_index = numpy.where(index < cum_sizes)[0][0]
              column = self.code_column.columns[column_index]
              if old_column_index != column_index:
                  token_ids = [i]
                  old_column_index = column_index
              else:
                  token_ids.append(i)
              if len(token_ids) == sizes[column_index]:
                  tokens.append(
                      self.code_column.decode(column, token_ids)
                  )
              cindex += 1
      return tokens
  
imports: import pickle
  from typing import List
  import numpy
  from nemo.collections.common.tokenizers.column_coder import ColumnCodes
  from nemo.collections.common.tokenizers.tokenizer_spec import TokenizerSpec
label_desc: Use image node_id 11 for calling the TabularTokenizer obj's underlying member method code with example usage: obj.ids_to_tokens(ids, skip_special_tokens) and returns: tokens