class_docstr: Abstract base class to implement new criteria.
docstr: Returns a boolean tensor indicating which perturbed inputs are adversarial.
  
  Args:
      perturbed: Tensor with perturbed inputs ``(batch, ...)``.
      outputs: Tensor with model outputs for the perturbed inputs ``(batch, ...)``.
  
  Returns:
      A boolean tensor indicating which perturbed inputs are adversarial ``(batch,)``.
docstr_tok: ["Returns","a","boolean","tensor","indicating","which","perturbed","inputs","are","adversarial",".","Args",":","perturbed",":","Tensor","with","perturbed","inputs","``","(","batch",",","...",")","``",".","outputs",":","Tensor","with","model","outputs","for","the","perturbed","inputs","``","(","batch",",","...",")","``",".","Returns",":","A","boolean","tensor","indicating","which","perturbed","inputs","are","adversarial","``","(","batch",",",")","``","."]
code: def __call__(self, perturbed: T, outputs: T) -> T:
      """Returns a boolean tensor indicating which perturbed inputs are adversarial.
  
      Args:
          perturbed: Tensor with perturbed inputs ``(batch, ...)``.
          outputs: Tensor with model outputs for the perturbed inputs ``(batch, ...)``.
  
      Returns:
          A boolean tensor indicating which perturbed inputs are adversarial ``(batch,)``.
      """
      ...
  
imports: from typing import TypeVar, Any
  from abc import ABC, abstractmethod
  import eagerpy
label_desc: Use image node_id 2 for calling the Criterion obj's underlying member method code with example usage: obj.__call__(perturbed, outputs) without return types