code: def testNormalVariance(self):
      # sigma will be broadcast to [7, 7, 7]
      mu = [1.0, 2.0, 3.0]
      sigma = [7.0]
  
      dist = normal.Normal(loc=mu, scale=sigma, validate_args=True)
  
      self.assertAllEqual((3,), dist.variance().shape)
      self.assertAllEqual(
          [49.0, 49, 49], self.evaluate(dist.variance())
      )
  
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 21 for calling the NormalTest obj's underlying member method code with example usage: obj.testNormalVariance() without return types