Tune and custom logger fails

RLlib
1

Hi,

I am using a custom callback that works fine when I train an RL model without using tune:

config = ppo.PPOConfig(
        ).environment(MyCustomEnv, env_config=env_config, disable_env_checking=True
        ).training(
            model={
                'custom_model': model_class_name,
                'custom_model_config': custom_model_config
                },
        ).framework(eager_tracing=True, framework=framework
        ).resources(num_gpus=1, num_cpus_per_worker=1, num_cpus_per_learner_worker=2,
        ).rollouts(enable_connectors=False, num_rollout_workers=2).callbacks(MyCallbacks
        ).reporting(keep_per_episode_custom_metrics=True)
    
    algo = config.build()
    
    num_iterations = 2
    for _ in range(num_iterations):
        result = algo.train()

However, when I try to use tune. Namely:

    tuner = tune.Tuner(
        "PPO",
        run_config=air.RunConfig(
            storage_path=run_path,
            stop={
                "training_iteration": num_iterations,
            },
            # callbacks=[MyCallbacks],
        ),
        param_space=config,
    )
result = tuner.fit()

The custom callback is ignored. As stated above, the custom callback works fine when tune is not used.
If I try to include the custom callback also in my air.RunConfig by commenting out the line above, I receive the following error:

AttributeError: type object 'MyCallbacks' has no attribute 'setup'

I also tried the following variation: callbacks=[MyCallbacks()]. This leads to the same error.

My current ray version is 2.5.1 (pip install ray[default,rllib]==2.5.1)