class_docstr: Base class for all propagation rule classes, also called Z-Rule.
  STABILITY_FACTOR is used to assure that no zero divison occurs.
class_docstr_tok: ["Base","class","for","all","propagation","rule","classes",",","also","called","Z-Rule",".","STABILITY_FACTOR","is","used","to","assure","that","no","zero","divison","occurs","."]
code: def _create_backward_hook_output(self, outputs):
      def _backward_hook_output(grad):
          sign = torch.sign(outputs)
          sign[sign == 0] = 1
          relevance = grad / (outputs + sign * self.STABILITY_FACTOR)
          self.relevance_output[grad.device] = grad.data
          return relevance
  
      return _backward_hook_output
  
imports: from abc import ABC, abstractmethod
  import torch
  from ..._utils.common import _format_tensor_into_tuples
label_desc: Use image node_id 4 for calling the PropagationRule obj's underlying member method code with example usage: obj._create_backward_hook_output(outputs) and returns: _backward_hook_output, relevance