code: def get_num_classes(data) -> int:
      """Returns the number of classes (unique labels) in the dataset."""
      data_format = recognize_data_format(data)
      if data_format == "numpy":
          images, labels = data
          # TODO: Right now, we just assume that the labels are properly indexed (e.g.
          #   from 0 to 9), so we return the max value + 1 here. Instead, we should map
          #   the labels to a dictionary and then figure out the number of classes from
          #   there. E.g. so that labels can be [0, 2, 5] or even ["dog", "cat", "horse"].
          return np.max(labels) + 1
      elif data_format == "files":
          dataset = datasets.ImageFolder(data)
          return len(dataset.targets)
      else:
          raise RuntimeError()
  
imports: import numpy
  import torch
  from torch.utils.data import Dataset
  from torchvision import datasets, transforms
  from typing import List, Union
  from pathlib import Path
  from PIL import Image
label_desc: Use image node_id 13 for calling a global function with example usage: get_num_classes(data) and returns: unknown, len