code: def testNormalMeanAndMode(self):
      # Mu will be broadcast to [7, 7, 7].
      mu = [7.0]
      sigma = [11.0, 12.0, 13.0]
  
      dist = normal.Normal(loc=mu, scale=sigma, validate_args=True)
  
      self.assertAllEqual((3,), dist.mean().shape)
      self.assertAllEqual([7.0, 7, 7], self.evaluate(dist.mean()))
  
      self.assertAllEqual((3,), dist.mode().shape)
      self.assertAllEqual([7.0, 7, 7], self.evaluate(dist.mode()))
  
imports: import math
  import numpy
  from scipy import stats
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 16 for calling the NormalTest obj's underlying member method code with example usage: obj.testNormalMeanAndMode() without return types