class_docstr: Abstract base class for all evasion detectors.
docstr: Fit the detection classifier if necessary.
  
  :param x: Training set to fit the detector.
  :param y: Labels for the training set.
  :param batch_size: Size of batches.
  :param nb_epochs: Number of epochs to use for training.
  :param kwargs: Other parameters.
code: def fit(
      self,
      x: np.ndarray,
      y: np.ndarray,
      batch_size: int = 128,
      nb_epochs: int = 20,
      **kwargs,
  ) -> None:
      """
      Fit the detection classifier if necessary.
  
      :param x: Training set to fit the detector.
      :param y: Labels for the training set.
      :param batch_size: Size of batches.
      :param nb_epochs: Number of epochs to use for training.
      :param kwargs: Other parameters.
      """
      raise NotImplementedError
  
file_path: adversarial-robustness-toolbox/art/defences/detector/evasion/evasion_detector.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import abc
  from typing import Any, Dict, List, Tuple
  import numpy
label_desc: Use image node_id 2 for calling the EvasionDetector obj's underlying member method code with example usage: obj.fit(x, y, batch_size, nb_epochs) without return types