Yufeng Gao

> hello, > i think there is a misconception between seed, used for pseudo random generator and scenarios. Thanks. Do you mean the seed data[0] in this file ``` https://github.com/DLR-RM/stable-baselines3/blob/285e01f64aa8ba4bd15aa339c45876d56ed0c3b4/stable_baselines3/common/vec_env/subproc_vec_env.py#L46...

> why not sample the scenario idx? > > ```python > scenario_idx = np.random.randint(0,10) > ``` May I ask where to put this line of code?

> In the reset method of your env. Yeah, this also works. But It's the same with changing my env wrapper. If I add a sample scheme in the reset...

I see what you mean. Thank you. At the beginning of training, there's "seed" parameter in make_vec_env function, which is the initial seed for the random number generator. And if...

Hello @younesbelkada, I met a similar problem. I tried your code, it outputs the same texts. But when I try VQA, it outputs nothing again. I've only added one question...

And if I print the out, ``` out = model.generate(**inputs) print(out) ``` I always get the same tokens ``` tensor([[ 2, 50118]], device='cuda:0') ``` no matter what image or text...