class_docstr: Simple and fast white-space tokenizer. Splits sentence based on white spaces.
  Punctuation are stripped from tokens.
class_docstr_tok: ["Simple","and","fast","white-space","tokenizer",".","Splits","sentence","based","on","white","spaces",".","Punctuation","are","stripped","from","tokens","."]
code: def get_vocab(self):
      return self.vocab
  
file_path: sentence-transformers/sentence_transformers/models/tokenizer/WhitespaceTokenizer.py
imports: from typing import List, Iterable
  import collections
  import string
  import os
  import json
  from .WordTokenizer import WordTokenizer, ENGLISH_STOP_WORDS
label_desc: Use image node_id 2 for calling the WhitespaceTokenizer obj's underlying member method code with example usage: obj.get_vocab() and returns: self