class_docstr: ### MNIST dataset
class_docstr_tok: ["#","#","#","MNIST","dataset"]
code: def __init__(self, image_size):
      transform = torchvision.transforms.Compose(
          [
              torchvision.transforms.Resize(image_size),
              torchvision.transforms.ToTensor(),
          ]
      )
  
      super().__init__(
          str(lab.get_data_path()),
          train=True,
          download=True,
          transform=transform,
      )
  
imports: from typing import List
  import torch
  import torch.utils.data
  import torchvision
  from PIL import Image
  from labml import lab, tracker, experiment, monit
  from labml.configs import BaseConfigs, option
  from labml_helpers.device import DeviceConfigs
  from labml_nn.diffusion.ddpm import DenoiseDiffusion
  from labml_nn.diffusion.ddpm.unet import UNet
label_desc: Use image node_id 1 to create a new MNISTDataset object from inherited base classes: torchvision.datasets with example: obj = MNISTDataset(image_size)