It sounds like the line just above didn’t run for some reason:
jupyter notebook --generate-config
That should create the directory that’s missing. Oh I know - perhaps you’re not currently in your home directory? You run be running from within your home dir. So:
Right, but if you run the script when you’re not in the home directory, it won’t work, since the script has ‘.jupyter/jupyter_notebook_config.py’, instead of ‘~/.jupyter/jupyter_notebook_config.py’. So either cd to your home dir, or update the script to add ‘~/’ in both places.
Haha … I can now see why you are saying that!
Any chance you believe nvcc needs to be installed? I ask because when I do import theano I get this: ERROR (theano.sandbox.cuda): nvcc compiler not found on $PATH. Check your nvcc installation and try again.
After I installed nvcc that error went away.
import utils; reload(utils)
from utils import plots
I get this:
Using Theano backend.
Using gpu device 0: Tesla K80 (CNMeM is disabled, cuDNN 5103)
/home/ubuntu/anaconda2/lib/python2.7/site-packages/theano/sandbox/cuda/__init__.py:600: UserWarning: Your cuDNN version is more recent than the one Theano officially supports. If you see any problems, try updating Theano or downgrading cuDNN to version 5.
warnings.warn(warn)
Is gpu device being used here? I am running a p2 instance.
Edit: I guess it did … because it finished the training fast … .
Your next challenge, if you choose to accept it, is to create an AMI that others can use. To do so, remove all data, .bash_history, personal files, etc from the instance, and then logout. Then login and remove .bash_history again, and remove the .ssh directory, then stop the instance. Then you can right-click on the instance in the console and choose ‘create image’. Then you should terminate your original image (since you remove the .ssh directory, you can’t login to it anymore anyway!) Once it’s finished creating, you can try to launch a new instance using that image. If that works, you can set the image sharing to ‘public’ and let everyone know the id!
You may prefer to create a whole new instance for this, in order to both ensure that everything is setup the way you want, and in order to avoid breaking your working instance…
Sounds good … i am going to start working on it … I kept the storage volume to 30GB … hope that suffices for the remainder of the course? I guess if not we can download old exercise data or transfer it to S3 ($0.03 per GB)
If I create this AMI and launch it with a t2 instance should it still work even though I installed all the gpu related driver software? I ask because at the moment I only have access to one p2 instance - which means I cannot test a new p2 instance with AMI. Will using the t2 instance work to test the correctness of the AMI?
You can just use the AMI that @vshets created He announced it on Slack and I sent a notification about it to @channel , so hopefully you can find it there.