class_docstr: Abstract base class for preprocessing defences implemented in PyTorch that support efficient preprocessor-chaining.
docstr: Type of device on which the classifier is run, either `gpu` or `cpu`.
docstr_tok: ["Type","of","device","on","which","the","classifier","is","run",",","either","`","gpu","`","or","`","cpu","`","."]
code: def device(self):
      """
      Type of device on which the classifier is run, either `gpu` or `cpu`.
      """
      return self._device
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import abc
  from typing import List, Optional, Tuple, Any, TYPE_CHECKING
  import numpy
  from art import config
label_desc: Use image node_id 4 for calling the PreprocessorPyTorch obj's underlying member method code with example usage: obj.device() and returns: self