code: def get_cifar100(
      dataset_name,
      data_dir,
      split,
      transform=None,
      imsize=None,
      bucket="pytorch-data",
      **kwargs,
  ):
      if imsize == 224:
          transform = get_transform(
              split, transform=transform, imsize=imsize, aug="large"
          )
      else:
          transform = get_transform(
              split, transform=transform, imsize=imsize, aug="small"
          )
      return datasets.CIFAR100(
          data_dir,
          train=(split == "train"),
          transform=transform,
          download=True,
          **kwargs,
      )
  
file_path: deepspeedexamples/training/data_efficiency/vit_finetuning/utils/get_data.py
imports: import torch
  import os
  import torchvision.transforms
  import torchvision.datasets
label_desc: Use image node_id 5 for calling a global function with example usage: get_cifar100(dataset_name, data_dir, split, transform, imsize, bucket) and returns: datasets