class_docstr: Base class defining the methods used for the ablators.
docstr: Ablate batch of data at locations specified by column_pos and row_pos
  
  :param x: input image.
  :param column_pos: column position to specify where to retain the image
  :param row_pos: row position to specify where to retain the image. Not used for ablation type "column".
code: def forward(
      self,
      x: np.ndarray,
      column_pos: Optional[int] = None,
      row_pos: Optional[int] = None,
  ) -> Union[np.ndarray, "torch.Tensor"]:
      """
      Ablate batch of data at locations specified by column_pos and row_pos
  
      :param x: input image.
      :param column_pos: column position to specify where to retain the image
      :param row_pos: row position to specify where to retain the image. Not used for ablation type "column".
      """
      raise NotImplementedError
  
file_path: adversarial-robustness-toolbox/art/estimators/certification/derandomized_smoothing/ablators/ablate.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  from abc import ABC, abstractmethod
  from typing import Optional, Tuple, Union, TYPE_CHECKING
  import numpy
label_desc: Use image node_id 4 for calling the BaseAblator obj's underlying member method code with example usage: obj.forward(x, column_pos, row_pos) without return types