class_docstr: TensorNormalizer with exponential moving avg. mean and var estimates.
docstr: Creates the variables needed for EMATensorNormalizer.
docstr_tok: ["Creates","the","variables","needed","for","EMATensorNormalizer","."]
code: def _create_variables(self):
      """Creates the variables needed for EMATensorNormalizer."""
      self._mean_moving_avg = tf.nest.map_structure(
          lambda spec: create_variable(
              "mean", 0, spec.shape, spec.dtype
          ),
          self._flat_variable_spec,
      )
      self._var_moving_avg = tf.nest.map_structure(
          lambda spec: create_variable(
              "var", 1, spec.shape, spec.dtype
          ),
          self._flat_variable_spec,
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import abc
  from typing import Tuple
  import six
  import tensorflow
  from tf_agents.specs import tensor_spec
  from tf_agents.typing import types
  from tf_agents.utils import common
  from tf_agents.utils import nest_utils
label_desc: Use image node_id 2 for calling the EMATensorNormalizer obj's underlying member method code with example usage: obj._create_variables() without return types