Log locally with tensorboard when wandb is disabled.

[dirkmcpherson]

What this does

This PR adds support for locally logging metrics and videos using tensorboard when wandb is disabled.

How it was tested

• Ran with a short eval_freq and log_freq to ensure metric and video logging worked through multiple periods.
• Tested with tensorboard.active = true / false and wandb.active = true / false
• ran pytests (passed)

How to checkout & try? (for the reviewer)

Run with wandb.enable=false and short eval / log freqs. e.g.
python lerobot/scripts/train.py policy=diffusion env=pusht env.task=PushT-v0 dataset_repo_id=lerobot/pusht training.log_freq=10 training.eval_freq=100 wandb.enable=false tensorboard.enable=true

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This change is 

[Cadene]

Thanks, we should probably add option for tensorboard logging as it is quite used.
Anyone knows what is the usage for these kind of logging/viz tools in the community?
Is wandb more popular than tensorboard? What are the alternatives?

[Cadene]

Why not add a cfg.tensorboard.enable argument to support both?

[dirkmcpherson]

Good idea! Will do.

[kashyapakshay]

Thanks, we should probably add option for tensorboard logging as it is quite used. Anyone knows what is the usage for these kind of logging/viz tools in the community? Is wandb more popular than tensorboard? What are the alternatives?

Both are quite popular and could be preferable in different scenarios I think. A lot of people prefer Tensorboard (including myself) because of how little overhead there is to spin up and start using it, especially when you just want to visualize loss curves and maybe some input/output samples. Even some teams who don't mind managing some infra use it (my previous ML team had Tensorboard instances hosted on K8s backed by S3 storage for artifacts). Wandb of course is a managed platform with more sophisticated workflows around tracking, hosting, sharing results, etc., but comes at a cost (although the free plan is pretty generous for small-scale experimentation). In any case, think it would be great to have Tensorboard support!