class_docstr: A simple token representation, keeping track of the token's text, offset in the passage it was
  taken from, POS tag, dependency relation, and similar information.  These fields match spacy's
  exactly, so we can just use a spacy token for this.
  
  Parameters
  ----------
  text : ``str``, optional
      The original text represented by this token.
  idx : ``int``, optional
      The character offset of this token into the tokenized passage.
  lemma : ``str``, optional
      The lemma of this token.
  pos : ``str``, optional
      The coarse-grained part of speech of this token.
  tag : ``str``, optional
      The fine-grained part of speech of this token.
  dep : ``str``, optional
      The dependency relation for this token.
  ent_type : ``str``, optional
      The entity type (i.e., the NER tag) for this token.
  text_id : ``int``, optional
      If your tokenizer returns integers instead of strings (e.g., because you're doing byte
      encoding, or some hash-based embedding), set this with the integer.  If this is set, we
      will bypass the vocabulary when indexing this token, regardless of whether ``text`` is also
      set.  You can `also` set ``text`` with the original text, if you want, so that you can
      still use a character-level representation in addition to a hash-based word embedding.
  
      The other fields on ``Token`` follow the fields on spacy's ``Token`` object; this is one we
      added, similar to spacy's ``lex_id``.
class_docstr_tok: ["A","simple","token","representation",",","keeping","track","of","the","token","'s","text",",","offset","in","the","passage","it","was","taken","from",",","POS","tag",",","dependency","relation",",","and","similar","information",".","These","fields","match","spacy's","exactly",",","so","we","can","just","use","a","spacy","token","for","this",".","Parameters","--","--","--","--","--","text",":","``","str","``",",","optional","The","original","text","represented","by","this","token",".","idx",":","``","int","``",",","optional","The","character","offset","of","this","token","into","the","tokenized","passage",".","lemma",":","``","str","``",",","optional","The","lemma","of","this","token",".","pos",":","``","str","``",",","optional","The","coarse-grained","part","of","speech","of","this","token",".","tag",":","``","str","``",",","optional","The","fine-grained","part","of","speech","of","this","token",".","dep",":","``","str","``",",","optional","The","dependency","relation","for","this","token",".","ent_type",":","``","str","``",",","optional","The","entity","type","(","i.e.",",","the","NER","tag",")","for","this","token",".","text_id",":","``","int","``",",","optional","If","your","tokenizer","returns","integers","instead","of","strings","(","e.g.",",","because","you","'re","doing","byte","encoding",",","or","some","hash-based","embedding",")",",","set","this","with","the","integer",".","If","this","is","set",",","we","will","bypass","the","vocabulary","when","indexing","this","token",",","regardless","of","whether","``","text","``","is","also","set",".","You","can","`","also","`","set","``","text","``","with","the","original","text",",","if","you","want",",","so","that","you","can","still","use","a","character-level","representation","in","addition","to","a","hash-based","word","embedding",".","The","other","fields","on","``","Token","``","follow","the","fields","on","spacy","'s","``","Token","``","object",";","this","is","one","we","added",",","similar","to","spacy","'s","``","lex_id","``","."]
code: def __repr__(self):
      return self.__str__()
  
label_desc: Use image node_id 3 for calling the Token obj's underlying member method code with example usage: obj.__repr__() and returns: self