class_docstr: This module implements Expectation over Transformation preprocessing for image center crop in PyTorch.
code: def _check_params(self) -> None:
      if not isinstance(self.size, int) or self.size <= 0:
          raise ValueError("The size be a positive integer.")
  
      if self.label_type not in self.label_types:
          raise ValueError(
              f"The input for label_type needs to be one of {self.label_types},"
              f"currently receiving `{self.label_type}`."
          )
  
file_path: adversarial-robustness-toolbox/art/preprocessing/expectation_over_transformation/image_center_crop/pytorch.py
imports: import logging
  from typing import Dict, List, Optional, TYPE_CHECKING, Tuple, Union
  import numpy
  from art.preprocessing.expectation_over_transformation.pytorch import EoTPyTorch
label_desc: Use image node_id 3 for calling the EoTImageCenterCropPyTorch obj's underlying member method code with example usage: obj._check_params() without return types