class_docstr: Runs WordPiece tokenization.
class_docstr_tok: ["Runs","WordPiece","tokenization","."]
code: def __init__(self, vocab, unk_token, max_input_chars_per_word=100):
      self.vocab = vocab
      self.unk_token = unk_token
      self.max_input_chars_per_word = max_input_chars_per_word
  
imports: import collections
  import itertools
  import json
  import os
  import unicodedata
  from typing import Dict, List, Optional, Tuple, Union
  from ...tokenization_utils import PreTrainedTokenizer, _is_control, _is_punctuation, _is_whitespace
  from ...tokenization_utils_base import ENCODE_KWARGS_DOCSTRING, ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING, BatchEncoding, EncodedInput, EncodedInputPair, PaddingStrategy, PreTokenizedInput, PreTokenizedInputPair, TensorType, TextInput, TextInputPair, TruncationStrategy
  from ...utils import add_end_docstrings, logging
label_desc: Use image node_id 1 to create a new RoCBertWordpieceTokenizer object from inherited base classes: object with example: obj = RoCBertWordpieceTokenizer(vocab, unk_token, max_input_chars_per_word)