class_docstr: Transforms an input by replacing its words with synonyms in the word
  embedding space.
  
  Args:
      max_candidates (int): maximum number of synonyms to pick
      embedding (textattack.shared.AbstractWordEmbedding): Wrapper for word embedding
  >>> from textattack.transformations import WordSwapEmbedding
  >>> from textattack.augmentation import Augmenter
  
  >>> transformation = WordSwapEmbedding()
  >>> augmenter = Augmenter(transformation=transformation)
  >>> s = 'I am fabulous.'
  >>> augmenter.augment(s)
code: def __init__(self, max_candidates=15, embedding=None, **kwargs):
      super().__init__(**kwargs)
      if embedding is None:
          embedding = WordEmbedding.counterfitted_GLOVE_embedding()
      self.max_candidates = max_candidates
      if not isinstance(embedding, AbstractWordEmbedding):
          raise ValueError(
              "`embedding` object must be of type `textattack.shared.AbstractWordEmbedding`."
          )
      self.embedding = embedding
  
file_path: TextAttack/textattack/transformations/word_swaps/word_swap_embedding.py
imports: from textattack.shared import AbstractWordEmbedding, WordEmbedding
  from .word_swap import WordSwap
label_desc: Use image node_id 1 to create a new WordSwapEmbedding object from inherited base classes: WordSwap with example: obj = WordSwapEmbedding(max_candidates, embedding)