original_docstring: 
      Compute the entropy for a diagonal Gaussian distribution.
  
      :param log_std: (tf.Tensor) Log of the standard deviation
      :return: (tf.Tensor)
      
docstring: Compute the entropy for a diagonal Gaussian distribution.
docstring_tokens: Compute the entropy for a diagonal Gaussian distribution .
code: def gaussian_entropy(log_std):
      """
      Compute the entropy for a diagonal Gaussian distribution.
  
      :param log_std: (tf.Tensor) Log of the standard deviation
      :return: (tf.Tensor)
      """
      return tf.reduce_sum(log_std + 0.5 * np.log(2.0 * np.pi * np.e), axis=-1)
code_tokens: def gaussian_entropy ( log_std ) : return tf . reduce_sum ( log_std + 0.5 * np . log ( 2.0 * np . pi * np . e ) , axis = - 1 )
short_docstring: Compute the entropy for a diagonal Gaussian distribution.
short_docstring_tokens: Compute the entropy for a diagonal Gaussian distribution .
comment: """
      Compute the entropy for a diagonal Gaussian distribution.
  
      :param log_std: (tf.Tensor) Log of the standard deviation
      :return: (tf.Tensor)
      """