code: def dask_client():
      dask_scheduler_file = os.environ.get("SCHEDULER_FILE")
      cuda_visible_devices = get_visible_devices()
  
      if dask_scheduler_file is not None:
          dask_initialize()
          dask_client = Client(scheduler_file=dask_scheduler_file)
      else:
          # The tempdir created by tempdir_object should be cleaned up once
          # tempdir_object goes out-of-scope and is deleted.
          tempdir_object = tempfile.TemporaryDirectory()
          cluster = LocalCUDACluster(
              local_directory=tempdir_object.name,
              protocol="tcp",
              CUDA_VISIBLE_DEVICES=cuda_visible_devices,
          )
  
          dask_client = Client(cluster)
          dask_client.wait_for_workers(len(cuda_visible_devices))
  
      if not Comms.is_initialized():
          Comms.initialize(p2p=True)
  
      yield dask_client
  
      stop_dask_client(dask_client)
      print("\ndask_client fixture: client.close() called")
  
imports: import os
  import pytest
  from dask_cuda.initialize import initialize
  from dask_cuda import LocalCUDACluster
  from dask.distributed import Client
  from cugraph.dask.comms import comms
  from cugraph.dask.common.mg_utils import get_visible_devices
  from cugraph.testing.mg_utils import stop_dask_client
  import torch
  import numpy
  from cugraph.gnn import FeatureStore
  from cugraph.datasets import karate
  import tempfile
label_desc: Use image node_id 1 for calling a global function with example usage: dask_client() without return types