code: def testNormalizationDictNest(self):
      means_var, variance_var = self._dict_tensor_normalizer.variables
      self.evaluate(  # For each var in nest, assign initial value.
          [
              tf.compat.v1.assign(var, [10.0] * 3)
              for var in means_var.values()
          ]
          + [
              tf.compat.v1.assign(var, [0.1] * 3)
              for var in variance_var.values()
          ]
      )
  
      vector = [9.0, 10.0, 11.0]
      expected = {
          "a": [-3.1622776601, 0.0, 3.1622776601],
          "b": [-3.1622776601, 0.0, 3.1622776601],
      }
      tensor = {"a": tf.constant(vector), "b": tf.constant(vector)}
  
      norm_obs = self._dict_tensor_normalizer.normalize(
          tensor, variance_epsilon=0.0
      )
      self.assertAllClose(
          expected, self.evaluate(norm_obs), atol=0.0001
      )
  
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 6 for calling the EMATensorNormalizerTest obj's underlying member method code with example usage: obj.testNormalizationDictNest() without return types