class_docstr: `Challenge on Learned Image Compression (CLIC) 2020
  <http://compression.cc/tasks/>`_ Image Dataset.
  
  Args:
      root: Root directory where images are downloaded to.
          Expects the following folder structure if download=False:
  
          .. code::
  
              <root>
                  └── clic2020
                      ├── test
                      │   ├── *.png
                      ├── train
                      │   ├── *.png
                      └── val
                          └── *.png
      split: The dataset split to use. One of
          {``train``, ``val``, ``test``}.
          Defaults to ``train``.
      download: If true, downloads the dataset from the
          internet and puts it in root directory. If dataset is already
          downloaded, it is not downloaded again.
      transform: A function/transform that takes in a
          PIL image and returns a transformed version.  E.g,
          ``transforms.RandomCrop``.
code: def __len__(self) -> int:
      return len(self.paths)
  
file_path: NeuralCompression/neuralcompression/data/_clic_2020_image.py
imports: import os
  import os.path
  import shutil
  from pathlib import Path
  from typing import Callable, Optional, Union
  import torchvision.datasets.folder
  import torchvision.datasets.utils
  from PIL.Image import Image
  from torch import Tensor
  from torch.utils.data import Dataset
label_desc: Use image node_id 3 for calling the CLIC2020Image obj's underlying member method code with example usage: obj.__len__() and returns: len