class_docstr: TensorNormalizer with exponential moving avg. mean and var estimates.
code: def __init__(
      self,
      tensor_spec,
      scope="normalize_tensor",
      norm_update_rate=0.001,
  ):
      super(EMATensorNormalizer, self).__init__(tensor_spec, scope)
      self._norm_update_rate = norm_update_rate
  
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 1 to create a new EMATensorNormalizer object from inherited base classes: TensorNormalizer with example: obj = EMATensorNormalizer(tensor_spec, scope, norm_update_rate)