class_docstr: The TinyImageNet classification dataset, with 200 classes and 500 images
  per class. See https://tiny-imagenet.herokuapp.com/.
  
  It produces [image, label] where image is a 64x64x3(BGR) image, label is an
  integer in [0, 200).
class_docstr_tok: ["The","TinyImageNet","classification","dataset",",","with","200","classes","and","500","images","per","class",".","See","https",":","\/\/tiny-imagenet.herokuapp.com\/",".","It","produces","[","image",",","label","]","where","image","is","a","64x64x3","(","BGR",")","image",",","label","is","an","integer","in","[","0",",","200",")","."]
code: def __len__(self):
      return len(self.imglist)
  
imports: import numpy
  import os
  import tarfile
  import tqdm
  from pathlib import Path
  from ...utils import logger
  from ...utils.fs import download, get_dataset_path, mkdir_p
  from ...utils.loadcaffe import get_caffe_pb
  from ...utils.timer import timed_operation
  from ..base import RNGDataFlow
label_desc: Use image node_id 2 for calling the TinyImageNet obj's underlying member method code with example usage: obj.__len__() and returns: len