class_docstr: This module implements resizing for images and object detection bounding boxes in PyTorch.
code: def _check_params(self) -> None:
      if self.height <= 0:
          raise ValueError("The desired image height must be positive.")
  
      if self.width <= 0:
          raise ValueError("The desired image width must be positive")
  
      if self.clip_values is not None:
          if len(self.clip_values) != 2:
              raise ValueError(
                  "`clip_values` should be a tuple of 2 floats containing the allowed data range."
              )
  
          if self.clip_values[0] >= self.clip_values[1]:
              raise ValueError("Invalid `clip_values`: min >= max.")
  
file_path: adversarial-robustness-toolbox/art/preprocessing/image/image_resize/pytorch.py
imports: import logging
  from typing import Dict, List, Optional, TYPE_CHECKING, Tuple, Union
  from tqdm.auto import tqdm
  from art.preprocessing.preprocessing import PreprocessorPyTorch
label_desc: Use image node_id 3 for calling the ImageResizePyTorch obj's underlying member method code with example usage: obj._check_params() without return types