docstr: Configure the normalization functions used to normalize reference and test data to zero mean and unit variance.
  The reference data `x_ref` is also normalized here.
docstr_tok: ["Configure","the","normalization","functions","used","to","normalize","reference","and","test","data","to","zero","mean","and","unit","variance",".","The","reference","data","`","x_ref","`","is","also","normalized","here","."]
code: def _configure_normalization(self, eps: float = 1e-12):
      """
      Configure the normalization functions used to normalize reference and test data to zero mean and unit variance.
      The reference data `x_ref` is also normalized here.
      """
      x_ref_means = tf.reduce_mean(self.x_ref, axis=0)
      x_ref_stds = tf.math.reduce_std(self.x_ref, axis=0)
      self._normalize = lambda x: (x - x_ref_means) / (x_ref_stds + eps)
      self._unnormalize = lambda x: (
          x * (x_ref_stds + eps) + x_ref_means
      ).numpy()
      self.x_ref = self._normalize(self.x_ref)
  
file_path: alibi-detect/alibi_detect/cd/tensorflow/lsdd_online.py
imports: from tqdm import tqdm
  import numpy
  import tensorflow
  from typing import Any, Callable, Optional, Union
  from alibi_detect.cd.base_online import BaseMultiDriftOnline
  from alibi_detect.utils.tensorflow import GaussianRBF, quantile, permed_lsdds
  from alibi_detect.utils.frameworks import Framework
label_desc: Use image node_id 2 for calling the LSDDDriftOnlineTF obj's underlying member method code with example usage: obj._configure_normalization(eps) without return types