class_docstr: This module contains an implementation of the Over-the-Air Adversarial Flickering attack on video recognition
  networks.
  
  | Paper link: https://arxiv.org/abs/2002.05123
class_docstr_tok: ["This","module","contains","an","implementation","of","the","Over-the-Air","Adversarial","Flickering","attack","on","video","recognition","networks",".","|","Paper","link",":","https",":","\/\/arxiv.org\/abs\/2002.05123"]
code: def _check_params(self) -> None:
      if (
          not isinstance(self.eps_step, (int, float))
          or self.eps_step <= 0.0
      ):
          raise ValueError(
              "The argument `eps_step` must be positive of type int or float."
          )
  
      if not isinstance(self.max_iter, int) or self.max_iter <= 0:
          raise ValueError(
              "The argument `max_iter` must be positive of type int."
          )
  
      if not isinstance(self.beta_0, (int, float)) or self.beta_0 < 0.0:
          raise ValueError(
              "The argument `beta_0` must be 0.0 or positive of type int or float."
          )
  
      if not isinstance(self.beta_1, (int, float)) or self.beta_1 < 0.0:
          raise ValueError(
              "The argument `beta_1` must be 0.0 or positive of type int or float."
          )
  
      if not isinstance(self.beta_2, (int, float)) or self.beta_2 < 0.0:
          raise ValueError(
              "The argument `beta_2` must be 0.0 or positive of type int or float."
          )
  
      if (
          not isinstance(self.loss_margin, (int, float))
          or self.loss_margin <= 0.0
      ):
          raise ValueError(
              "The argument `loss_margin` must be positive of type int or float."
          )
  
      if not isinstance(self.batch_size, int) or self.batch_size <= 0:
          raise ValueError(
              "The argument `batch_size` must be positive of type int."
          )
  
      if (
          not isinstance(self.start_frame_index, int)
          or self.start_frame_index < 0
      ):
          raise ValueError(
              "The argument `start_frame_index` must be 0 or positive of type int."
          )
  
      if self.num_frames is not None and (
          not isinstance(self.num_frames, int) or self.num_frames <= 0
      ):
          raise ValueError(
              "The argument `num_frames` must be positive of type int."
          )
  
      if (
          not isinstance(self.round_samples, (int, float))
          or self.round_samples < 0.0
      ):
          raise ValueError(
              "The argument `round_samples` must be 0.0 or positive of type int or float."
          )
  
file_path: adversarial-robustness-toolbox/art/attacks/evasion/over_the_air_flickering/over_the_air_flickering_pytorch.py
imports: import logging
  from typing import Optional, TYPE_CHECKING
  import numpy
  from tqdm.auto import tqdm
  from art.config import ART_NUMPY_DTYPE
  from art.estimators.estimator import BaseEstimator
  from art.estimators.classification.classifier import ClassifierMixin, LossGradientsMixin
  from art.attacks.attack import EvasionAttack
  from art.utils import check_and_transform_label_format, get_labels_np_array
label_desc: Use image node_id 9 for calling the OverTheAirFlickeringPyTorch obj's underlying member method code with example usage: obj._check_params() without return types