code: def on_workers_recreated(
      self,
      *,
      algorithm,
      worker_set,
      worker_ids,
      is_evaluation,
      **kwargs,
  ):
      # Store in the algorithm object's counters the number of times, this worker
      # (ID'd by index and whether eval or not) has been recreated/restarted.
      for id_ in worker_ids:
          key = f"{'eval_' if is_evaluation else ''}worker_{id_}_recreated"
          # Increase the counter.
          algorithm._counters[key] += 1
          print(f"changed {key} to {algorithm._counters[key]}")
  
      # Execute some dummy code on each of the recreated workers.
      results = worker_set.foreach_worker(lambda w: w.ping())
      print(results)
  
imports: import tempfile
  import unittest
  import ray
  from ray.rllib.algorithms.appo import APPOConfig
  from ray.rllib.algorithms.callbacks import DefaultCallbacks
  from ray.rllib.algorithms.ppo import PPOConfig
  from ray.rllib.examples.env.cartpole_crashing import CartPoleCrashing
  from ray.rllib.utils.test_utils import framework_iterator
  from ray import tune
label_desc: Use image node_id 1 for calling the OnWorkersRecreatedCallbacks obj's underlying member method code with example usage: obj.on_workers_recreated() without return types