class_docstr: This class implements a regressor with the PyTorch framework.
class_docstr_tok: ["This","class","implements","a","regressor","with","the","PyTorch","framework","."]
docstr: Return a string specifying a pure or mixed precision optimization level.
  
  :return: A string specifying a pure or mixed precision optimization level. Possible
           values are `O0`, `O1`, `O2`, and `O3`.
docstr_tok: ["Return","a","string","specifying","a","pure","or","mixed","precision","optimization","level",".",":","return",":","A","string","specifying","a","pure","or","mixed","precision","optimization","level",".","Possible","values","are","`","O0","`",",","`","O1","`",",","`","O2","`",",","and","`","O3","`","."]
code: def opt_level(self) -> str:
      """
      Return a string specifying a pure or mixed precision optimization level.
  
      :return: A string specifying a pure or mixed precision optimization level. Possible
               values are `O0`, `O1`, `O2`, and `O3`.
      """
      return self._opt_level
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import copy
  import logging
  import os
  import time
  from typing import Any, Dict, List, Optional, Tuple, Union, TYPE_CHECKING
  import numpy
  import six
  from art import config
  from art.estimators.regression.regressor import RegressorMixin
  from art.estimators.pytorch import PyTorchEstimator
label_desc: Use image node_id 8 for calling the PyTorchRegressor obj's underlying member method code with example usage: obj.opt_level() and returns: self