[Question] About the logger

DLR-RM / stable-baselines3

PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

MIT License

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In the doc https://stable-baselines3.readthedocs.io/en/master/common/logger.html, there is a warning

I am wondering that if I a custom logger object like

logger = configure(f'results_{job_data.env}')
model = PPO(job_data.policy, env,  verbose=1,
                    tensorboard_log=f"wandb/{run.id}",
                    learning_rate=job_data.learning_rate, 
                    batch_size=job_data.batch_size, 
                    policy_kwargs=policy_kwargs,
                    gamma=job_data.gamma, **job_data.alg_hyper_params)
...
model.set_logger(logger)
model.learn(
    total_timesteps=config["total_timesteps"],
    callback=callback,
)

How should I set tensorboard_log and verbose? Because I notice that in the code below, the settings is overwritten and no info is logged.

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[X] I have checked that there is no similar issue in the repo
[X] I have read the documentation
[X] If code there is, it is minimal and working
[X] If code there is, it is formatted using the markdown code blocks for both code and stack traces.

DLR-RM / stable-baselines3

[Question] About the logger #1997

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