code: def testVariableLocation(self):
      loc = tf.Variable([1.0, 1.0])
      cov_base_diag = tf.Variable([2.0, 2.0])
      cov_operator = tf.linalg.LinearOperatorLowRankUpdate(
          base_operator=tf.linalg.LinearOperatorDiag(
              cov_base_diag, is_positive_definite=True
          ),
          u=tf.ones((2, 2)),
      )
      d = MultivariateNormalLowRankUpdateLinearOperatorCovariance(
          loc, cov_operator, validate_args=True
      )
      self.evaluate([loc.initializer, cov_base_diag.initializer])
  
      with tf.GradientTape() as tape:
          lp = d.log_prob([0.0, 0.0])
      self.assertIsNotNone(tape.gradient(lp, loc))
  
      with tf.GradientTape() as tape:
          lp = d.log_prob([0.0, 0.0])
      self.assertIsNotNone(tape.gradient(lp, cov_base_diag))
  
imports: import collections
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import mvn_low_rank_update_linear_operator_covariance
  from tensorflow_probability.python.distributions import mvn_tril
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.stats import sample_stats
label_desc: Use image node_id 6 for calling the MultivariateNormalLowRankUpdateLinearOperatorCovarianceTest obj's underlying member method code with example usage: obj.testVariableLocation() without return types