class_docstr: DEPRECATED.
code: def __init__(
      self,
      num_words=None,
      filters='!"#$%&()*+,-./:;<=>?@[\\]^_`{|}~\t\n',
      lower=True,
      split=" ",
      char_level=False,
      oov_token=None,
      analyzer=None,
      **kwargs,
  ):
      # Legacy support
      if "nb_words" in kwargs:
          warnings.warn(
              "The `nb_words` argument in `Tokenizer` "
              "has been renamed `num_words`."
          )
          num_words = kwargs.pop("nb_words")
      document_count = kwargs.pop("document_count", 0)
      if kwargs:
          raise TypeError(
              "Unrecognized keyword arguments: " + str(kwargs)
          )
  
      self.word_counts = collections.OrderedDict()
      self.word_docs = collections.defaultdict(int)
      self.filters = filters
      self.split = split
      self.lower = lower
      self.num_words = num_words
      self.document_count = document_count
      self.char_level = char_level
      self.oov_token = oov_token
      self.index_docs = collections.defaultdict(int)
      self.word_index = {}
      self.index_word = {}
      self.analyzer = analyzer
  
imports: import collections
  import hashlib
  import json
  import warnings
  import numpy
  from keras.api_export import keras_export
label_desc: Use image node_id 1 to create a new Tokenizer object from inherited base classes: object with example: obj = Tokenizer(num_words, filters, lower, split, char_level, oov_token, analyzer)