How to check Done/Termination condition in the Scalarised version of Coinrun

[Unimax]

Basically i need standard Scalar version of the Coinrun env (like a gym env) so i can apply various q-learning algos. (i will be using pytorch not that it matters)

From one of the resolved issue i get my hands on the Scalarise class but the level is not changing for some reason it's saying "CoinRun ignores resets" on the console probably becuase of "env.reset()"

example script (i placed it in train_agent.py):-

def testing():
    episodes = 10
    env = Scalarize(make('standard', num_envs=1))
    for i in range(episodes):
        start_state = env.reset()  
        while True:
            env.render()
            action = np.random.randint(0, env.action_space.n)
            next_state, reward, done, info = env.step(action)
            if done or reward > 0:
                break
        

[Unimax]

am sorry after writing this i figured out that i hardcoded the number of levels somewhere in my code.

closing the issue.