code: def start_cugraph_dask_client(rank, dask_scheduler_file):
      print(
          "Connecting to dask... "
          "(warning: this may take a while depending on your configuration)"
      )
      start_time_connect_dask = time.perf_counter_ns()
      from distributed import Client
      from cugraph.dask.comms import comms as Comms
  
      client = Client(scheduler_file=dask_scheduler_file)
      Comms.initialize(p2p=True)
  
      end_time_connect_dask = time.perf_counter_ns()
      print(
          f"Successfully connected to dask on rank {rank}, took "
          f"{(end_time_connect_dask - start_time_connect_dask) / 1e9:3.4f} s"
      )
      return client
  
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 3 for calling a global function with example usage: start_cugraph_dask_client(rank, dask_scheduler_file) and returns: client