class_docstr: LVIS PyTorch Object Detection Dataset
class_docstr_tok: ["LVIS","PyTorch","Object","Detection","Dataset"]
code: def _download_dataset(self) -> None:
      data2download = lvis_archives
  
      for name, url, checksum in data2download:
          if self.verbose:
              print("Downloading " + name + "...")
  
          result_file = self._download_file(url, name, checksum)
          if self.verbose:
              print("Download completed. Extracting...")
  
          self._extract_archive(result_file)
          if self.verbose:
              print("Extraction completed!")
  
imports: from pathlib import Path
  from typing import Optional, Union, List, Sequence
  import torch
  from PIL import Image
  from torchvision.datasets.folder import default_loader
  from torchvision.transforms import ToTensor
  from typing_extensions import TypedDict
  from avalanche.benchmarks.datasets import DownloadableDataset, default_dataset_location
  from avalanche.benchmarks.datasets.lvis_dataset.lvis_data import lvis_archives
label_desc: Use image node_id 2 for calling the LvisDataset obj's underlying member method code with example usage: obj._download_dataset() without return types