docstr: This function queries a `spaCy` nlp model to find `n` similar words with the same
  part of speech for each word in the instance to be explained. For each word
  the search procedure returns a dictionary containing a `numpy` array of words (``'words'``)
  and a `numpy` array of word similarities (``'similarities'``).
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code: def find_similar_words(self) -> None:
      """
      This function queries a `spaCy` nlp model to find `n` similar words with the same
      part of speech for each word in the instance to be explained. For each word
      the search procedure returns a dictionary containing a `numpy` array of words (``'words'``)
      and a `numpy` array of word similarities (``'similarities'``).
      """
      for word, token in zip(self.words, self.tokens):
          if word not in self.synonyms:
              self.synonyms[word] = self._synonyms_generator.neighbors(
                  word, token.tag_, self.perturb_opts["top_n"]
              )
  
imports: import logging
  from abc import abstractmethod
  from typing import TYPE_CHECKING, Dict, List, Optional, Tuple, Union
  import numpy
  import spacy
label_desc: Use image node_id 3 for calling the SimilaritySampler obj's underlying member method code with example usage: obj.find_similar_words() without return types