class_docstr: Helper class for aggregating and building `Vocabulary` objects.
class_docstr_tok: ["Helper","class","for","aggregating","and","building","`","Vocabulary","`","objects","."]
code: def __init__(self, delimiter=" ", lowercase_tokens=False):
      self._counter = Counter()
      self.use_unk = True
      self.unk_index = UNK_INDEX
      self.use_pad = True
      self.pad_index = PAD_INDEX
      self.use_bos = False
      self.bos_index = 2
      self.use_eos = False
      self.eos_index = 3
      self.use_bol = False
      self.bol_index = 4
      self.use_eol = False
      self.eol_index = 5
      self.use_mask = False
      self.mask_index = 6
      self.lowercase_tokens = lowercase_tokens
  
      # Some tokenization libraries use special tokens, expose them so they
      # can be configured
      self.unk_token = SpecialTokens.UNK
      self.pad_token = SpecialTokens.PAD
      self.bos_token = SpecialTokens.BOS
      self.eos_token = SpecialTokens.EOS
      self.mask_token = SpecialTokens.MASK
  
      self.delimiter = delimiter
  
imports: import itertools
  from collections import Counter
  from typing import Dict, List, Optional, Tuple
  import torch
  from pytext.common.constants import SpecialTokens, Token
  from pytext.utils import cuda, precision
label_desc: Use image node_id 1 to create a new VocabBuilder object  with example: obj = VocabBuilder(delimiter, lowercase_tokens)