How to disable Ray Tune Trial controller checkpointing?

Ray Libraries (Data, Train, Tune, Serve)
1

I am trying to run a second piece of Ray code after Ray Tune completes, but I am met with this error:

2023-12-14 22:10:04,454	WARNING tune_controller.py:746 -- Trial controller checkpointing failed: [Errno 2] No such file or directory:

If I run this and stop here, no problems:

analysis = tune.run(  
    tune.with_parameters(tune_obj, df=df, horizon=horizon, freq=freq),  
    num_samples=2,
    config=config,
    scheduler=scheduler,
    local_dir=output_path,
    checkpoint_config=CheckpointConfig(
                num_to_keep=1, checkpoint_frequency=0),  # tried fiddling with checkpoint opts
    storage_path=output_path,
    resume=False,
    search_alg=HyperOptSearch(metric='mse', mode='min'),
    max_concurrent_trials=2,
    progress_reporter=reporter,
    resources_per_trial={"gpu": 1}    
)

# get the best hyperparameters  
best_config = analysis.get_best_config(metric="mse", mode="min")
print("Best Config:", best_config)

After tuning, I want to run this second stage. But any other ray operation after this will yield Ray Tune checkpoint errors.

@ray.remote(num_gpus=1)
class BatchPredictor:
    def __init__(self, model, data):
        self.model = model
        ...

        
    def predict(self, feature_name):
        ...
        return forecasts  

# storage model / df
model_ref = ray.put(nf_best)
test_df_ref = ray.put(test_df)

num_actors = 24
actors = [BatchPredictor.remote(model_ref, test_df_ref) for _ in range(num_actors)]
pool = ActorPool(actors)
feature_names = test_df['unique_id'].unique()

# submit
for name in feature_names:
    pool.submit(lambda a, v: a.predict.remote(v), name)

# get results
while pool.has_next():
    tdf = pool.get_next()