code: def testKlWithDynamicShapes(self):
      dist1 = independent.Independent(
          normal.Normal(
              loc=np.zeros((4, 5, 2, 3)), scale=1.0, validate_args=True
          ),
          reinterpreted_batch_ndims=2,
          validate_args=True,
      )
  
      loc2 = tf.Variable(
          np.zeros((4, 5, 2, 3)), shape=tf.TensorShape(None)
      )
      scale2 = tf.Variable(np.ones([]), shape=tf.TensorShape(None))
      ndims2 = tf.Variable(
          2, trainable=False, shape=tf.TensorShape(None)
      )
      dist2 = independent.Independent(
          normal.Normal(loc=loc2, scale=scale2, validate_args=True),
          reinterpreted_batch_ndims=ndims2,
          validate_args=True,
      )
  
      self.evaluate(
          [v.initializer for v in dist1.variables]
          + [v.initializer for v in dist2.variables]
      )
      kl = self.evaluate(dist1.kl_divergence(dist2))
      self.assertAllEqual((4, 5), kl.shape)
  
      with tf.control_dependencies(
          [loc2.assign(np.zeros((4, 5, 3, 2)))]
      ):
          with self.assertRaisesRegexp(
              Exception, "Event shapes do not match"
          ):
              self.evaluate(dist1.kl_divergence(dist2))
  
imports: import functools
  import os
  from absl.testing import parameterized
  import numpy
  from scipy import stats
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import bernoulli
  from tensorflow_probability.python.distributions import exponential
  from tensorflow_probability.python.distributions import independent
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import log_prob_ratio
  from tensorflow_probability.python.distributions import logistic
  from tensorflow_probability.python.distributions import lognormal
  from tensorflow_probability.python.distributions import mvn_diag
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import poisson
  from tensorflow_probability.python.internal import hypothesis_testlib
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 8 for calling the IndependentDistributionTest obj's underlying member method code with example usage: obj.testKlWithDynamicShapes() without return types