Cannot start cuda GPU mode in Jupyter Notebook. 03_atari_gan.py
philippwulff opened this issue · comments
Philipp Wulff commented
I am currently reading the chapter regarding the Atari-GAN-Project.
This is the corresponding code: Deep-Reinforcement-Learning-Hands-On/Chapter03/03_atari_gan.py
.
I wanted to follow along in a Jupyter Notebook and would basically just copy the code as I read it. However that leads to this error:
---------------------------------------------------------------------------
SystemExit Traceback (most recent call last)
<ipython-input-7-26c989fdc6f0> in <module>
1 parser = argparse.ArgumentParser()
2 parser.add_argument("--cuda", default=False, action="store_true", help="Enable cuda computation")
----> 3 args = parser.parse_args()
4
5 device = torch.device("cuda" if args.cuda else "cpu")
~/anaconda3/envs/sumo_rl/lib/python3.8/argparse.py in parse_args(self, args, namespace)
1769 if argv:
1770 msg = _('unrecognized arguments: %s')
-> 1771 self.error(msg % ' '.join(argv))
1772 return args
1773
~/anaconda3/envs/sumo_rl/lib/python3.8/argparse.py in error(self, message)
2519 self.print_usage(_sys.stderr)
2520 args = {'prog': self.prog, 'message': message}
-> 2521 self.exit(2, _('%(prog)s: error: %(message)s\n') % args)
~/anaconda3/envs/sumo_rl/lib/python3.8/argparse.py in exit(self, status, message)
2506 if message:
2507 self._print_message(message, _sys.stderr)
-> 2508 _sys.exit(status)
2509
2510 def error(self, message):
SystemExit: 2
usage: ipykernel_launcher.py [-h] [--cuda]
ipykernel_launcher.py: error: unrecognized arguments: -f /home/philipp/.local/share/jupyter/runtime/kernel-46443f22-af17-4453-8fc7-bc0795cd4ab1.json
An exception has occurred, use %tb to see the full traceback.
SystemExit: 2
Do you know what this is about? Because running the pure Python script in the terminal worked for me just fine.
Philipp Wulff commented
I am not sure, why one needs to check for cuda
in the terminal in the first place and ended up with the following code.
if torch.cuda.is_available():
device = torch.device("cuda")
else:
device = torch.device("cpu")
torch.cuda.is_available()
returns True for me, so I think, I am using my GPU =).