class_docstr: Local Search Attack
  Algorithm 3 in https://arxiv.org/pdf/1612.06299.pdf
  
  :param predict: forward pass function.
  :param clip_min: mininum value per input dimension.
  :param clip_max: maximum value per input dimension.
  :param p: parameter controls pixel complexity
  :param r: perturbation value
  :param loss_fn: loss function
  :param d: the half side length of the neighbourhood square
  :param t: the number of pixels perturbed at each round
  :param k: the threshold for k-misclassification
  :param round_ub: an upper bound on the number of rounds
code: def _revert_rescale(self, x, vmin=0.0, vmax=1.0):
      x_revert = x.clone()
      x_revert = x_revert * (vmax - vmin)
      x_revert = x_revert + (vmin + vmax) / 2
      return x_revert
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  import numpy
  import torch
  import torch.nn
  from advertorch.utils import clamp
  from advertorch.utils import replicate_input
  from .base import Attack
  from .base import LabelMixin
  from .utils import is_successful
label_desc: Use image node_id 5 for calling the LocalSearchAttack obj's underlying member method code with example usage: obj._revert_rescale(x, vmin, vmax) and returns: x_revert