class_docstr: Run CUDA BERT subword tokenizer on cuDF strings column.
  Encodes words to token ids using vocabulary from a pretrained
  tokenizer.
  This function requires about 21x the number of character bytes
  in the input strings column as working memory.
  
  Parameters
  ----------
  hash_file : str
      Path to hash file containing vocabulary of words with token-ids.
      This can be created from the raw vocabulary
      using the ``cudf.utils.hash_vocab_utils.hash_vocab`` function
  
  do_lower : bool, Default is True
      If set to True, original text will be lowercased before encoding.
  
  Returns
  -------
  SubwordTokenizer
class_docstr_tok: ["Run","CUDA","BERT","subword","tokenizer","on","cuDF","strings","column",".","Encodes","words","to","token","ids","using","vocabulary","from","a","pretrained","tokenizer",".","This","function","requires","about","21x","the","number","of","character","bytes","in","the","input","strings","column","as","working","memory",".","Parameters","--","--","--","--","--","hash_file",":","str","Path","to","hash","file","containing","vocabulary","of","words","with","token-ids",".","This","can","be","created","from","the","raw","vocabulary","using","the","``","cudf.utils.hash_vocab_utils.hash_vocab","``","function","do_lower",":","bool",",","Default","is","True","If","set","to","True",",","original","text","will","be","lowercased","before","encoding",".","Returns","--","--","--","-","SubwordTokenizer"]
code: def __init__(self, hash_file: str, do_lower_case: bool = True):
      self.do_lower_case = do_lower_case
      self.vocab_file = cpp_hashed_vocabulary(hash_file)
  
file_path: cudf/python/cudf/cudf/core/subword_tokenizer.py
imports: from __future__ import annotations
  import warnings
  from typing import Union
  import cupy
  from cudf._lib.nvtext.subword_tokenize import Hashed_Vocabulary, subword_tokenize_inmem_hash
label_desc: Use image node_id 1 to create a new SubwordTokenizer object  with example: obj = SubwordTokenizer(hash_file, do_lower_case)