code: def get_images(dataset, image_mode, transformations=None):
      """Get the images from the dataset.
  
      If transformations are provided as a callable, the images
      are transformed. If transformations are provided as a string,
      the images are retrieved from that column name in the test dataset.
  
      :param dataset: The dataset to get the images from.
      :type dataset: numpy.ndarray
      :param image_mode: The mode to open the image in.
          See pillow documentation for all modes:
          https://pillow.readthedocs.io/en/stable/handbook/concepts.html
      :type image_mode: str
      :param transformations: The transformations to apply to the images.
      :type transformations: torchvision.transforms
      :return: The images.
      :rtype: numpy.ndarray
      """
      column_names = dataset.columns
      is_transformations_str = isinstance(transformations, str)
      if is_transformations_str:
          images = dataset[transformations]
      else:
          if IMAGE in column_names:
              images = dataset[IMAGE]
          elif IMAGE_URL in column_names:
              images = dataset[IMAGE_URL]
          else:
              raise ValueError("No image column found in test data")
  
      images = np.array(images.tolist())
      converted_images = convert_images(images, image_mode)
  
      if not is_transformations_str and transformations is not None:
          converted_images = transformations(converted_images)
  
      return converted_images
  
imports: import numpy
  from responsibleai_vision.common.constants import ImageColumns
  from responsibleai_vision.utils.image_reader import get_image_from_path
label_desc: Use image node_id 2 for calling a global function with example usage: get_images(dataset, image_mode, transformations) and returns: converted_images