class_docstr: Considers those perturbed inputs adversarial whose predicted class
  matches the target class.
  
  Args:
      target_classes: Tensor with target classes ``(batch,)``.
code: def __init__(self, target_classes: Any):
      super().__init__()
      self.target_classes: ep.Tensor = ep.astensor(target_classes)
  
imports: from typing import TypeVar, Any
  from abc import ABC, abstractmethod
  import eagerpy
label_desc: Use image node_id 1 to create a new TargetedMisclassification object from inherited base classes: Criterion with example: obj = TargetedMisclassification(target_classes)