original_docstring: 
      Helper to computer log likelihood of a gaussian.
      Here we assume this is a Diagonal Gaussian.
  
      :param input_: (tf.Tensor)
      :param mu_: (tf.Tensor)
      :param log_std: (tf.Tensor)
      :return: (tf.Tensor)
      
docstring: Helper to computer log likelihood of a gaussian.
  Here we assume this is a Diagonal Gaussian.
docstring_tokens: Helper to computer log likelihood of a gaussian . Here we assume this is a Diagonal Gaussian .
code: def gaussian_likelihood(input_, mu_, log_std):
      """
      Helper to computer log likelihood of a gaussian.
      Here we assume this is a Diagonal Gaussian.
  
      :param input_: (tf.Tensor)
      :param mu_: (tf.Tensor)
      :param log_std: (tf.Tensor)
      :return: (tf.Tensor)
      """
      pre_sum = -0.5 * (((input_ - mu_) / (tf.exp(log_std) + EPS)) ** 2 + 2 * log_std + np.log(2 * np.pi))
      return tf.reduce_sum(pre_sum, axis=1)
code_tokens: def gaussian_likelihood ( input_ , mu_ , log_std ) : pre_sum = - 0.5 * ( ( ( input_ - mu_ ) / ( tf . exp ( log_std ) + EPS ) ) ** 2 + 2 * log_std + np . log ( 2 * np . pi ) ) return tf . reduce_sum ( pre_sum , axis = 1 )
short_docstring: Helper to computer log likelihood of a gaussian.
short_docstring_tokens: Helper to computer log likelihood of a gaussian .
comment: """
      Helper to computer log likelihood of a gaussian.
      Here we assume this is a Diagonal Gaussian.
  
      :param input_: (tf.Tensor)
      :param mu_: (tf.Tensor)
      :param log_std: (tf.Tensor)
      :return: (tf.Tensor)
      """