code: def test_put_error2(ray_start_object_store_memory):
      # This is the same as the previous test, but it calls ray.put directly.
      num_objects = 3
      object_size = 4 * 10**5
  
      # Define a task with a single dependency, a numpy array, that returns
      # another array.
      @ray.remote
      def single_dependency(i, arg):
          arg = np.copy(arg)
          arg[0] = i
          return arg
  
      @ray.remote
      def put_task():
          # Launch num_objects instances of the remote task, each dependent
          # on the one before it. The result of the first task should get
          # evicted.
          args = []
          arg = ray.put(np.zeros(object_size, dtype=np.uint8))
          for i in range(num_objects):
              arg = single_dependency.remote(i, arg)
              args.append(arg)
  
          # Get the last value to force all tasks to finish.
          value = ray.get(args[-1])
          assert value[0] == i
  
          # Get the first value (which should have been evicted) to force
          # reconstruction. Currently, since we're not able to reconstruct
          # `ray.put` objects that were evicted and whose originating tasks
          # are still running, this for-loop should hang and push an error to
          # the driver.
          ray.get(args[0])
  
      put_task.remote()
  
imports: import os
  import signal
  import sys
  import time
  import numpy
  import pytest
  import ray
  import ray._private.gcs_utils
  import ray._private.ray_constants
  import ray._private.utils
  from ray._private.test_utils import SignalActor, convert_actor_state, get_error_message, init_error_pubsub, wait_for_condition
  from ray.exceptions import GetTimeoutError, RayActorError, RayTaskError
label_desc: Use image node_id 15 for calling a global function with example usage: test_put_error2(ray_start_object_store_memory) and returns: arg