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.
code: def __repr__(self):
      ch = "-" * 30 + "\n"
      ch += "modelset: " + self.modelset.__repr__() + "\n"
      ch += "segset: " + self.segset.__repr__() + "\n"
      ch += "seg start:" + self.start.__repr__() + "\n"
      ch += "seg stop:" + self.stop.__repr__() + "\n"
      ch += "stat0:" + self.stat0.__repr__() + "\n"
      ch += "stat1:" + self.stat1.__repr__() + "\n"
      ch += "-" * 30 + "\n"
      return ch
  
imports: import numpy
  import copy
  import pickle
  from scipy import linalg
label_desc: Use image node_id 2 for calling the StatObject_SB obj's underlying member method code with example usage: obj.__repr__() and returns: ch