class_docstr: Augments text by transforming words with their embeddings.
class_docstr_tok: ["Augments","text","by","transforming","words","with","their","embeddings","."]
code: def __init__(self, **kwargs):
      from textattack.transformations import WordSwapEmbedding
  
      transformation = WordSwapEmbedding(max_candidates=50)
      from textattack.constraints.semantics import WordEmbeddingDistance
  
      constraints = DEFAULT_CONSTRAINTS + [
          WordEmbeddingDistance(min_cos_sim=0.8)
      ]
      super().__init__(
          transformation, constraints=constraints, **kwargs
      )
  
imports: import random
  from textattack.constraints.pre_transformation import RepeatModification, StopwordModification
  from textattack.constraints.semantics.sentence_encoders import UniversalSentenceEncoder
  from .None import Augmenter
label_desc: Use image node_id 1 to create a new EmbeddingAugmenter object from inherited base classes: Augmenter with example: obj = EmbeddingAugmenter()