class_docstr: Reduces the contrast of the input using a linear search to find the
  smallest adversarial perturbation
class_docstr_tok: ["Reduces","the","contrast","of","the","input","using","a","linear","search","to","find","the","smallest","adversarial","perturbation"]
code: def __init__(
      self,
      *,
      distance: Optional[Distance] = None,
      steps: int = 1000,
      target: float = 0.5,
  ):
      super().__init__(distance=distance)
      self.steps = steps
      self.target = target
  
file_path: foolbox/foolbox/attacks/contrast_min.py
imports: from typing import Union, Any, Optional
  import eagerpy
  from ..devutils import atleast_kd
  from ..models import Model
  from ..criteria import Criterion
  from ..distances import Distance
  from .base import FlexibleDistanceMinimizationAttack
  from .base import T
  from .base import get_is_adversarial
  from .base import get_criterion
  from .base import raise_if_kwargs
  from .base import verify_input_bounds
label_desc: Use image node_id 1 to create a new LinearSearchContrastReductionAttack object from inherited base classes: FlexibleDistanceMinimizationAttack with example: obj = LinearSearchContrastReductionAttack()