[HANDS-ON BUG] The environment ``CartPole-v1`` used in unit 4 has weird configurations about deep-rl-class HOT 9 CLOSED

Hmmmmm, it seems that the code runs well on Colab but not locally!!

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Hey there 👋 sorry for the delay. But you're the first to encounter this issue. That might be also the version of Cartpole you use. For this we use Gym not Gymnasium "You may be wondering why we install gym and not gymnasium, a more recent version of gym? Because the gym-games we are using are not updated yet with gymnasium."

from deep-rl-class.

No problem at all, as I said the problem comes when running this code locally, dk why, maybe I made a mistake.

from deep-rl-class.

I think it's because you might not use the same environment. Unit 4 uses gym == 0.21 not gymnasium 😄

from deep-rl-class.

Hmmm, you may be right yeah, I will check and confirm.

from deep-rl-class.

Hey there 👋 Did you found if it was because of that?

from deep-rl-class.

Sorry for being late, yeah, it is definitely because of inconsistent versions so I am closing this.
Thank you.

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Even I have been running this locally and using gymnasium. I made respective changes for env.reset() and env.step(action).

Training and evaluation went fine.

However, I am struck at record_video() while pushing to Hub. I get an error "The image must have at least two spatial dimensions".

I did change eval_env to include render_mode.
eval_env = gym.make(env_id, render_mode="rgb_array")

Any suggestions ?

unit4.zip

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Restarted the system / notebook and this error does not show up. However, "push to hub" process takes up all the memory and finally crashes.

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