class_docstr: Implements the Sign-OPT attack `SignOPTAttack`. This is a query-efficient
  hard-label adversarial attack.
  
  Paper link: https://arxiv.org/pdf/1909.10773.pdf
docstr: Apply clipping to input array
  
  :param x_0: An array to be clipped
  :return: The array after clipping if clipping is enabled
docstr_tok: ["Apply","clipping","to","input","array",":","param","x_0",":","An","array","to","be","clipped",":","return",":","The","array","after","clipping","if","clipping","is","enabled"]
code: def _clip_value(self, x_0: np.ndarray) -> np.ndarray:
      """
      Apply clipping to input array
  
      :param x_0: An array to be clipped
      :return: The array after clipping if clipping is enabled
      """
      if self.enable_clipped:
          x_0 = np.clip(x_0, self.clip_min, self.clip_max)
      return x_0
  
imports: import logging
  from typing import Optional, TYPE_CHECKING, Tuple
  import time
  import numpy
  from tqdm.auto import tqdm
  from art.attacks.attack import EvasionAttack
  from art.config import ART_NUMPY_DTYPE
  from art.estimators.estimator import BaseEstimator
  from art.estimators.classification.classifier import ClassifierMixin
  from art.utils import compute_success, check_and_transform_label_format, get_labels_np_array
label_desc: Use image node_id 9 for calling the SignOPTAttack obj's underlying member method code with example usage: obj._clip_value(x_0) and returns: x_0