code: def __init__(
      self,
      exclude_ngram_filter=None,
      ngram_sizes=None,
      text_from_token=None,
      validate_token=None,
  ):
      self.ngram_sizes = (
          [1, 2, 3] if ngram_sizes is None else ngram_sizes
      )
      self.exclude_ngram_filter = (
          (lambda x: False)
          if exclude_ngram_filter is None
          else exclude_ngram_filter
      )
      self.text_from_token = (
          (lambda tok: tok.lower_)
          if text_from_token is None
          else text_from_token
      )
      self.validate_token = (
          (lambda tok: tok.tag_ != "_SP")
          if validate_token is None
          else validate_token
      )
  
imports: from typing import List, Tuple, Union, Optional, Callable, Dict
  from collections import deque
  from scattertext.features.FeatsFromSpacyDoc import FeatsFromSpacyDoc
  from scattertext.features.featoffsets.feat_and_offset_getter import FeatAndOffsetGetter
  from scattertext.Common import MY_ENGLISH_STOP_WORDS
label_desc: Use image node_id 1 to create a new FlexibleNGramFeaturesBase object  with example: obj = FlexibleNGramFeaturesBase(exclude_ngram_filter, ngram_sizes, text_from_token, validate_token)