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: Return segments of a given model.
  
  Arguments
  ---------
  mod_id : str
      ID of the model for which segments will be returned.
docstr_tok: ["Return","segments","of","a","given","model",".","Arguments","--","--","--","--","-","mod_id",":","str","ID","of","the","model","for","which","segments","will","be","returned","."]
code: def get_model_segsets(self, mod_id):
      """Return segments of a given model.
  
      Arguments
      ---------
      mod_id : str
          ID of the model for which segments will be returned.
      """
      return self.segset[self.modelset == mod_id]
  
imports: import numpy
  import copy
  import pickle
  from scipy import linalg
label_desc: Use image node_id 4 for calling the StatObject_SB obj's underlying member method code with example usage: obj.get_model_segsets(mod_id) and returns: self