class_docstr: Transforms an input by replacing its words with synonyms in the stored
  synonyms bank generated by the OpenHowNet.
docstr: Returns a list of possible 'candidate words' to replace a word in a
  sentence or phrase.
  
  Based on nearest neighbors selected word embeddings.
  >>> from textattack.transformations import WordSwapHowNet
  >>> from textattack.augmentation import Augmenter
  
  >>> transformation = WordSwapHowNet()
  >>> augmenter = Augmenter(transformation=transformation)
  >>> s = 'I am fabulous.'
  >>> augmenter.augment(s)
code: def _get_replacement_words(self, word, word_pos):
      """Returns a list of possible 'candidate words' to replace a word in a
      sentence or phrase.
  
      Based on nearest neighbors selected word embeddings.
      >>> from textattack.transformations import WordSwapHowNet
      >>> from textattack.augmentation import Augmenter
  
      >>> transformation = WordSwapHowNet()
      >>> augmenter = Augmenter(transformation=transformation)
      >>> s = 'I am fabulous.'
      >>> augmenter.augment(s)
      """
      word_pos = self.pos_dict.get(word_pos, None)
      if word_pos is None:
          return []
  
      try:
          candidate_words = self.candidates_bank[word.lower()][word_pos]
          if self.max_candidates > 0:
              candidate_words = candidate_words[: self.max_candidates]
          return [
              recover_word_case(candidate_word, word)
              for candidate_word in candidate_words
          ]
      except KeyError:
          # This word is not in our synonym bank, so return an empty list.
          return []
  
file_path: TextAttack/textattack/transformations/word_swaps/word_swap_hownet.py
imports: import pickle
  from textattack.shared import utils
  from .word_swap import WordSwap
label_desc: Use image node_id 2 for calling the WordSwapHowNet obj's underlying member method code with example usage: obj._get_replacement_words(word, word_pos) and returns: list, unknown, list