class_docstr: CLEAR Base Dataset for downloading / loading metadata
docstr: Creates an instance of the CLEAR dataset.
  This base class simply download and unzip the CLEAR dataset.
  
  This serves as a base class for _CLEARImage/_CLEARFeature dataset.
  
  :param root: The directory where the dataset can be found or downloaded.
      Defaults to None, which means that the default location for
      str(data_name) will be used.
  :param data_name: Data module name with the google drive url and md5
  :param download: If True, the dataset will be downloaded if needed.
docstr_tok: ["Creates","an","instance","of","the","CLEAR","dataset",".","This","base","class","simply","download","and","unzip","the","CLEAR","dataset",".","This","serves","as","a","base","class","for","_CLEARImage\/_CLEARFeature","dataset",".",":","param","root",":","The","directory","where","the","dataset","can","be","found","or","downloaded",".","Defaults","to","None",",","which","means","that","the","default","location","for","str","(","data_name",")","will","be","used",".",":","param","data_name",":","Data","module","name","with","the","google","drive","url","and","md5",":","param","download",":","If","True",",","the","dataset","will","be","downloaded","if","needed","."]
code: def __init__(
      self,
      root: Optional[Union[str, Path]] = None,
      *,
      data_name: str = "clear10",
      download: bool = True,
      verbose: bool = False,
  ):
      """
      Creates an instance of the CLEAR dataset.
      This base class simply download and unzip the CLEAR dataset.
  
      This serves as a base class for _CLEARImage/_CLEARFeature dataset.
  
      :param root: The directory where the dataset can be found or downloaded.
          Defaults to None, which means that the default location for
          str(data_name) will be used.
      :param data_name: Data module name with the google drive url and md5
      :param download: If True, the dataset will be downloaded if needed.
      """
  
      if root is None:
          root = default_dataset_location(data_name)
  
      assert data_name in _CLEAR_DATA_SPLITS
      self.data_name = data_name
      self.module = clear_data
      self._paths_and_targets: List[List[Tuple[str, int]]] = []
  
      super(CLEARDataset, self).__init__(
          root, download=download, verbose=True
      )
      self._load_dataset()
  
imports: from pathlib import Path
  from typing import Optional, Sequence, Tuple, Union, List
  import json
  import os
  import torch
  from torchvision.datasets.folder import default_loader
  from avalanche.benchmarks.datasets import DownloadableDataset, default_dataset_location
  from avalanche.benchmarks.utils import default_flist_reader
  from avalanche.benchmarks.datasets.clear import clear_data
label_desc: Use image node_id 1 to create a new CLEARDataset object from inherited base classes: DownloadableDataset with example: obj = CLEARDataset(root)