code: def testUpdateVariables(self):
      # Get original mean and variance.
      original_means, original_variances = self.evaluate(
          self._tensor_normalizer.variables
      )
  
      # Construct and evaluate normalized tensor. Should update mean &
      #   variance.
      tensor = tf.constant([[1.3, 4.2, 7.5]], dtype=tf.float32)
      update_norm_vars = self._tensor_normalizer.update(tensor)
      self.evaluate(update_norm_vars)
  
      # Get new mean and variance, and make sure they changed.
      new_means, new_variances = self.evaluate(
          self._tensor_normalizer.variables
      )
      for new_val, old_val in list(
          zip(new_means, original_means)
      ) + list(zip(new_variances, original_variances)):
          self.assertNotEqual(new_val, old_val)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import functools
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tf_agents.specs import tensor_spec
  from tf_agents.utils import tensor_normalizer
label_desc: Use image node_id 3 for calling the EMATensorNormalizerTest obj's underlying member method code with example usage: obj.testUpdateVariables() without return types