code: def test_pull_bundles_pinning(ray_start_cluster):
      cluster = ray_start_cluster
      object_size = int(50e6)
      num_objects = 10
      # Head node can fit all of the objects at once.
      cluster.add_node(num_cpus=0, object_store_memory=1000e6)
      cluster.wait_for_nodes()
      ray.init(address=cluster.address)
  
      # Worker node cannot even fit a single task.
      cluster.add_node(num_cpus=1, object_store_memory=200e6)
      cluster.wait_for_nodes()
  
      @ray.remote(num_cpus=1)
      def foo(*args):
          return
  
      task_args = [
          ray.put(np.zeros(object_size, dtype=np.uint8))
          for _ in range(num_objects)
      ]
      ray.get(foo.remote(*task_args))
  
imports: import multiprocessing
  import time
  import warnings
  from collections import defaultdict
  import numpy
  import pytest
  import ray
  from ray.cluster_utils import Cluster, cluster_not_supported
  from ray.util.scheduling_strategies import NodeAffinitySchedulingStrategy
label_desc: Use image node_id 9 for calling a global function with example usage: test_pull_bundles_pinning(ray_start_cluster) without return types