class_docstr: Base class for parametric objects with tags in sktime.
  
  Extends skbase BaseObject with additional features.
class_docstr_tok: ["Base","class","for","parametric","objects","with","tags","in","sktime",".","Extends","skbase","BaseObject","with","additional","features","."]
docstr: Load object from serialized memory container.
  
  Parameters
  ----------
  serial : 1st element of output of `cls.save(None)`
  
  Returns
  -------
  deserialized self resulting in output `serial`, of `cls.save(None)`
docstr_tok: ["Load","object","from","serialized","memory","container",".","Parameters","--","--","--","--","--","serial",":","1st","element","of","output","of","`","cls.save","(","None",")","`","Returns","--","--","--","-","deserialized","self","resulting","in","output","`","serial","`",",","of","`","cls.save","(","None",")","`"]
code: def load_from_serial(cls, serial):
      """Load object from serialized memory container.
  
      Parameters
      ----------
      serial : 1st element of output of `cls.save(None)`
  
      Returns
      -------
      deserialized self resulting in output `serial`, of `cls.save(None)`
      """
      import pickle
  
      return pickle.loads(serial)
  
imports: import warnings
  from copy import deepcopy
  from skbase.base import BaseObject
  from sklearn import clone
  from sklearn.base import BaseEstimator
  from sktime.exceptions import NotFittedError
  from sktime.utils.random_state import set_random_state
label_desc: Use image node_id 5 for calling the BaseObject obj's underlying member method code with example usage: obj.load_from_serial(cls, serial) and returns: pickle