class_docstr: Normalizes mean & variance based on full history of tensor values.
docstr: Returns this normalizer's current estimates for mean & var (flat).
docstr_tok: ["Returns","this","normalizer","'s","current","estimates","for","mean","&","var","(","flat",")","."]
code: def _get_mean_var_estimates(self):
      """Returns this normalizer's current estimates for mean & var (flat)."""
      var = [
          m2_ab / n_ab for (m2_ab, n_ab) in zip(self._m2, self._count)
      ]
      return (self._avg, var)
  
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 4 for calling the StreamingTensorNormalizer obj's underlying member method code with example usage: obj._get_mean_var_estimates() and returns: self,  var