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 __call__(self, input_texts):
      if isinstance(input_texts, list):
          return self.batch_encode(input_texts)
      else:
          return self.encode(input_texts)
  
file_path: TextAttack/textattack/models/tokenizers/glove_tokenizer.py
imports: import json
  import tempfile
  import tokenizers
label_desc: Use image node_id 5 for calling the GloveTokenizer obj's underlying member method code with example usage: obj.__call__(input_texts) and returns: self, self