class_docstr: ATTENTION:
      Currently, innvestigating a network only works if all
      layers that have to be inverted are specified explicitly
      and registered as a module. If., for example,
      only the functional max_poolnd is used, the inversion will not work.
class_docstr_tok: ["ATTENTION",":","Currently",",","innvestigating","a","network","only","works","if","all","layers","that","have","to","be","inverted","are","specified","explicitly","and","registered","as","a","module",".","If.",",","for","example",",","only","the","functional","max_poolnd","is","used",",","the","inversion","will","not","work","."]
docstr: Set the extra representation of the module
  
  To print customized extra information, you should re-implement
  this method in your own modules. Both single-line and multi-line
  strings are acceptable.
docstr_tok: ["Set","the","extra","representation","of","the","module","To","print","customized","extra","information",",","you","should","re-implement","this","method","in","your","own","modules",".","Both","single-line","and","multi-line","strings","are","acceptable","."]
code: def extra_repr(self):
      r"""Set the extra representation of the module
  
      To print customized extra information, you should re-implement
      this method in your own modules. Both single-line and multi-line
      strings are acceptable.
      """
      return self.model.extra_repr()
  
file_path: tensorwatch/tensorwatch/saliency/epsilon_lrp.py
imports: import torch
  import numpy
  from .inverter_util import RelevancePropagator
label_desc: Use image node_id 11 for calling the InnvestigateModel obj's underlying member method code with example usage: obj.extra_repr() and returns: self