docstr: Check if `word` or any character ngrams in `word` are present in the vocabulary.
  A vector for the word is guaranteed to exist if current method returns True.
  
  Parameters
  ----------
  word : str
      Input word.
  
  Returns
  -------
  bool
      True if `word` or any character ngrams in `word` are present in the vocabulary, False otherwise.
  
  Note
  ----
  This method **always** returns True with char ngrams, because of the way FastText works.
  
  If you want to check if a word is an in-vocabulary term, use this instead:
  
  .. pycon:
  
      >>> from gensim.test.utils import datapath
      >>> from gensim.models import FastText
      >>> cap_path = datapath("crime-and-punishment.bin")
      >>> model = FastText.load_fasttext_format(cap_path, full_model=False)
      >>> 'steamtrain' in model.wv.key_to_index  # If False, is an OOV term
      False
docstr_tok: ["Check","if","`","word","`","or","any","character","ngrams","in","`","word","`","are","present","in","the","vocabulary",".","A","vector","for","the","word","is","guaranteed","to","exist","if","current","method","returns","True",".","Parameters","--","--","--","--","--","word",":","str","Input","word",".","Returns","--","--","--","-","bool","True","if","`","word","`","or","any","character","ngrams","in","`","word","`","are","present","in","the","vocabulary",",","False","otherwise",".","Note","--","--","This","method","*","*","always","*","*","returns","True","with","char","ngrams",",","because","of","the","way","FastText","works",".","If","you","want","to","check","if","a","word","is","an","in-vocabulary","term",",","use","this","instead",":","..","pycon",":",">",">",">","from","gensim.test.utils","import","datapath",">",">",">","from","gensim.models","import","FastText",">",">",">","cap_path","=","datapath","(","``","crime-and-punishment.bin","''",")",">",">",">","model","=","FastText.load_fasttext_format","(","cap_path",",","full_model=False",")",">",">",">","'steamtrain","'","in","model.wv.key_to_index","#","If","False",",","is","an","OOV","term","False"]
code: def __contains__(self, word):
      """Check if `word` or any character ngrams in `word` are present in the vocabulary.
      A vector for the word is guaranteed to exist if current method returns True.
  
      Parameters
      ----------
      word : str
          Input word.
  
      Returns
      -------
      bool
          True if `word` or any character ngrams in `word` are present in the vocabulary, False otherwise.
  
      Note
      ----
      This method **always** returns True with char ngrams, because of the way FastText works.
  
      If you want to check if a word is an in-vocabulary term, use this instead:
  
      .. pycon:
  
          >>> from gensim.test.utils import datapath
          >>> from gensim.models import FastText
          >>> cap_path = datapath("crime-and-punishment.bin")
          >>> model = FastText.load_fasttext_format(cap_path, full_model=False)
          >>> 'steamtrain' in model.wv.key_to_index  # If False, is an OOV term
          False
  
      """
      if (
          self.bucket == 0
      ):  # check for the case when char ngrams not used
          return word in self.key_to_index
      else:
          return True
  
imports: import logging
  import numpy
  from numpy import ones, vstack, float32
  import gensim.models._fasttext_bin
  from gensim.models.word2vec import Word2Vec
  from gensim.models.keyedvectors import KeyedVectors, prep_vectors
  from gensim import utils
  from gensim.utils import deprecated
  from gensim.models import keyedvectors
label_desc: Use image node_id 4 for calling the FastTextKeyedVectors obj's underlying member method code with example usage: obj.__contains__(word) and returns: unknown, True