code: def get_embeddings(
      self,
  ):
      if self.w2v_model is None:
          print("model not train")
          return {}
  
      self._embeddings = {}
      for word in self.graph.nodes():
          self._embeddings[word] = self.w2v_model.wv[word]
  
      return self._embeddings
  
imports: from gensim.models import Word2Vec
  from ..walker import RandomWalker
label_desc: Use image node_id 3 for calling the DeepWalk obj's underlying member method code with example usage: obj.get_embeddings() and returns: self, dict