class_docstr: A word-level tokenizer with GloVe 200-dimensional vectors.
  
  Lowercased, since GloVe vectors are lowercased.
class_docstr_tok: ["A","word-level","tokenizer","with","GloVe","200-dimensional","vectors",".","Lowercased",",","since","GloVe","vectors","are","lowercased","."]
code: def __init__(
      self,
      word_id_map={},
      pad_token_id=None,
      unk_token_id=None,
      max_length=256,
  ):
      super().__init__(
          word_id_map=word_id_map,
          unk_token_id=unk_token_id,
          pad_token_id=pad_token_id,
          lowercase=True,
      )
      self.pad_token_id = pad_token_id
      self.oov_token_id = unk_token_id
      self.convert_id_to_word = self.id_to_token
      # Set defaults.
      self.enable_padding(length=max_length, pad_id=pad_token_id)
      self.enable_truncation(max_length=max_length)
  
file_path: textflint/textflint/input/model/tokenizers/glove_tokenizer.py
imports: import json
  import tempfile
  import tokenizers
label_desc: Use image node_id 1 to create a new GloveTokenizer object from inherited base classes: WordLevelTokenizer with example: obj = GloveTokenizer(word_id_map, pad_token_id, unk_token_id, max_length)