code: def _dataset(is_train, transform):
      return datasets.MNIST(
          str(lab.get_data_path()),
          train=is_train,
          download=True,
          transform=transform,
      )
  
file_path: labml/helpers/labml_helpers/datasets/mnist.py
imports: from torch.utils.data import DataLoader
  from torchvision import datasets, transforms
  from labml import lab
  from labml.configs import BaseConfigs, aggregate, option
label_desc: Use image node_id 1 for calling a global function with example usage: _dataset(is_train, transform) and returns: datasets