code: def prepare_mnist():
      # Pre-download the data onto each node.
      from benchmark_util import schedule_remote_fn_on_all_nodes
  
      print("Preparing Torch benchmark: Downloading MNIST")
  
      @ray.remote
      def _download_data():
          import torchvision
  
          torchvision.datasets.FashionMNIST(
              "/tmp/data_fashion_mnist", download=True
          )
          return True
  
      ray.get(schedule_remote_fn_on_all_nodes(_download_data))
  
file_path: ray/release/air_tests/air_benchmarks/workloads/tune_torch_benchmark.py
imports: import json
  import os
  import time
  import timeit
  from typing import Optional, Dict
  import click
  import numpy
  import ray
  from ray.train import ScalingConfig
  from ray.train.torch import TorchTrainer
label_desc: Use image node_id 1 for calling a global function with example usage: prepare_mnist() and returns: True