def standard_normal_ll(input_):
 res = ((-0.5) * (tf.square(input_) + numpy.log((2.0 * numpy.pi))))
 return res

def standard_normal_ll ( input_ ) : res = ( ( - 0.5 ) * ( tf . square ( input_ ) + numpy . log ( ( 2.0 * numpy . pi ) ) ) ) return res
log-likelihood of standard gaussian distribution .