code: def main():
      args = parse_args()
  
      torch_devices = [int(d) for d in args.torch_devices.split(",")]
  
      train_args = (
          torch_devices,
          args.torch_manager_ip,
          args.torch_manager_port,
          args.dask_scheduler_file,
          args.num_epochs,
          args.features_on_gpu,
      )
  
      tmp.spawn(train, args=train_args, nprocs=len(torch_devices))
  
imports: from ogb.nodeproppred import NodePropPredDataset
  import time
  import argparse
  import gc
  import torch
  import numpy
  from torch_geometric.nn import CuGraphSAGEConv
  import torch.nn
  import torch.nn.functional
  import torch.distributed
  import torch.multiprocessing
  from torch.nn.parallel import DistributedDataParallel
  from typing import List
label_desc: Use image node_id 7 for calling a global function with example usage: main() without return types