timoklein / car_racer Goto Github PK
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Deep reinforcement learning in autonomous driving
I run carracing with sac algorithm in my own project, and the effect is very poor.
I ran your code and found that the results were also very poor. Can you show me your training results (distance, reward)?
Game of openAI "CarRacing-v0" has actions of 3 dimensions, relatively in rage [-1,1], [0,1] and [0,1].
But from your code, There is only code that bounds action and log_Prob into range [-1,1], no code for in range [0,1].
Did you ignore it?
Hi,
I've just cloned your project, and I want to try to train the weights.pt and VAE_weights.pt again, but can't seem to find the 2 files color_data.pt and grayscale_data.pt from the internet. Can you share those files to me?
Sorry if this is a stupid question. I'm really new at Machine learning.
Thank you very much!
if __name__ == '__main__':
# get data
path_to_x = "/home/jupyter/tutorials/praktikum_ml/color_data.pt"
path_to_y = "/home/jupyter/tutorials/praktikum_ml/grayscale_data.pt"
train_loader, valid_loader = get_data(path_to_x, path_to_y)
# instantiate model and optimizer
vae = ConvBetaVAE()
vae.to(DEVICE)
train_model(20)
# save model
vae.cpu()
torch.save(vae.state_dict(), 'weights.pt')
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