code: def jensen_shannon_divergence(self, dist1, dist2):
      assert dist1.shape == dist2.shape
      dist1[dist1 < EPS] = EPS
      dist2[dist2 < EPS] = EPS
      mean = (dist1 + dist2) * 0.5
      jsd = (
          self.kullback_leibler_divergence(dist1, mean) * 0.5
          + self.kullback_leibler_divergence(dist2, mean) * 0.5
      )
      return jsd
  
file_path: PaddleHub/modules/text/language_model/lda_news/semantic_matching.py
imports: import numpy
  from lda_news.vocab import OOV
label_desc: Use image node_id 6 for calling the SemanticMatching obj's underlying member method code with example usage: obj.jensen_shannon_divergence(dist1, dist2) and returns: jsd