class_docstr: Method from Chen et al., 2018 performing poisoning detection based on activations clustering.
  
  | Paper link: https://arxiv.org/abs/1811.03728
  
  | Please keep in mind the limitations of defences. For more information on the limitations of this
      defence, see https://arxiv.org/abs/1905.13409 . For details on how to evaluate classifier security
      in general, see https://arxiv.org/abs/1902.06705
docstr: Erases the pickle with the provided file name.
  
  :param file_name: File name without directory.
docstr_tok: ["Erases","the","pickle","with","the","provided","file","name",".",":","param","file_name",":","File","name","without","directory","."]
code: def _remove_pickle(file_name: str) -> None:
      """
      Erases the pickle with the provided file name.
  
      :param file_name: File name without directory.
      """
      full_path = os.path.join(config.ART_DATA_PATH, file_name)
      os.remove(full_path)
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  import os
  import pickle
  import time
  from typing import Any, Dict, List, Optional, Tuple, TYPE_CHECKING
  import numpy
  from sklearn.cluster import KMeans, MiniBatchKMeans
  from art import config
  from art.data_generators import DataGenerator
  from art.defences.detector.poison.clustering_analyzer import ClusteringAnalyzer
  from art.defences.detector.poison.ground_truth_evaluator import GroundTruthEvaluator
  from art.defences.detector.poison.poison_filtering_defence import PoisonFilteringDefence
  from art.utils import segment_by_class
  from art.visualization import create_sprite, save_image, plot_3d
label_desc: Use image node_id 11 for calling the ActivationDefence obj's underlying member method code with example usage: obj._remove_pickle(file_name) without return types