Troubleshooting
Last updated
Last updated
This page lists common errors and ways to address them.
Run nvidia-smi
This should display your GPU information.
Otherwise, you will need to use the following to install your GPU:
Run python3 -c "import torch; print(torch.cuda.is_available())"
or python -c "import torch; print(torch.cuda.is_available())"
This should print True
Otherwise, reboot your server or ensure you have torch installed.
I get this error: hypermind.dht.protocol.ValidationError: local time must be within 3 seconds of others
on WSL. What should I do?
All clocks on all nodes need to be synchronized. Please set the date using an :
The server starts loading blocks and then prints: Killed
. What should I do?
This happens since Windows doesn't allocate much RAM to WSL by default, so the server gets OOM-killed.
To increase the memory limit, go to C:/Users/username
and create the .wslconfig
with this contents:
Then reboot WSL (run sudo reboot
in the WSL console) and it should work fine.
I get this error: torch.cuda.OutOfMemoryError: CUDA out of memory
. What should I do?
If you use an Anaconda env, run this before starting the server:
If you use Docker, add this argument after --rm
in the Docker command:
WSL clock tends to get out of synch, which prevents the server from launching with the error hypermind.dht.protocol.ValidationError: local time must be within 3 seconds of others
.
To sync the WSL clock run sudo ntpdate pool.ntp.org
. See more fixes .