class_docstr: python -m pytorch_toolbelt.datasets.providers.inria_aerial inria_dataset
code: def sha256digest(cls, filename: str) -> str:
      blocksize = 4096
      sha = hashlib.sha256()
      with open(filename, "rb") as f:
          file_buffer = f.read(blocksize)
          while len(file_buffer) > 0:
              sha.update(file_buffer)
              file_buffer = f.read(blocksize)
      readable_hash = sha.hexdigest()
      return readable_hash
  
imports: import os
  import subprocess
  import warnings
  from pathlib import Path
  from typing import Union, Optional, Tuple
  import hashlib
  import numpy
  import pandas
  import torch
  import zipfile
  from sklearn.model_selection import GroupKFold
  from pytorch_toolbelt.utils import fs
label_desc: Use image node_id 3 for calling the InriaAerialImageDataset obj's underlying member method code with example usage: obj.sha256digest(cls, filename) and returns: readable_hash