code: def kullback_leibler_divergence(y_true, y_pred):
      y_true = model_ops.clip(y_true, model_ops.epsilon(), 1)
      y_pred = model_ops.clip(y_pred, model_ops.epsilon(), 1)
      return model_ops.sum(y_true * tf.log(y_true / y_pred), axis=-1)
  
file_path: deepchem/contrib/nn/objectives.py
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import unicode_literals
  from __future__ import absolute_import
  import warnings
  import tensorflow
  from deepchem.nn import model_ops
label_desc: Use image node_id 10 for calling a global function with example usage: kullback_leibler_divergence(y_true, y_pred) and returns: model_ops