class_docstr: A utility class for PLDA class used for statistics calculations.
  
  This is also used to pack deep embeddings and meta-information in one object.
  
  Arguments
  ---------
  modelset : list
      List of model IDs for each session as an array of strings.
  segset : list
      List of session IDs as an array of strings.
  start : int
      Index of the first frame of the segment.
  stop : int
      Index of the last frame of the segment.
  stat0 : tensor
      An ndarray of float64. Each line contains 0-th order statistics
      from the corresponding session.
  stat1 : tensor
      An ndarray of float64. Each line contains 1-st order statistics
      from the corresponding session.
docstr: Divide all first-order statistics by their Euclidean norm.
          
docstr_tok: ["Divide","all","first-order","statistics","by","their","Euclidean","norm","."]
code: def norm_stat1(self):
      """Divide all first-order statistics by their Euclidean norm."""
  
      vect_norm = numpy.clip(
          numpy.linalg.norm(self.stat1, axis=1), 1e-08, numpy.inf
      )
      self.stat1 = (self.stat1.transpose() / vect_norm).transpose()
  
imports: import numpy
  import copy
  import pickle
  from scipy import linalg
label_desc: Use image node_id 13 for calling the StatObject_SB obj's underlying member method code with example usage: obj.norm_stat1() without return types