I was previously using the AMI from the fast.ai course for my deep learning needs, but recently decided to try out the AWS Deep Learning AMI and I wanted to document a few tips for a few issues I encountered when I first set it up.


The AWS Deep Learning AMI does not come with the latest version of Keras, so you’ll need to update the keras package using:

sudo pip install keras --upgrade

Or, if you’re using Python 3, you can update it using pip3 instead:

sudo pip3 install keras --upgrade

You’ll also need to remove older Keras configurations (if any) using:

rm ~/.keras/keras.json


I ran into some issues with CUDA initially, which turned out to be a configuration problem. If you encounter the following error (or something similar):

ImportError: libcusolver.so.8.0: cannot open shared object file: No such file or directory
Failed to load the native TensorFlow runtime.
See https://www.tensorflow.org/install/install_sources#common_installation_problems
for some common reasons and solutions.  Include the entire stack trace
above this error message when asking for help.

Try updating the LD_LIBRARY_PATH using the following:

sudo ldconfig /usr/local/cuda/lib64

Bonus: Autostarting Jupyter Notebook

Since I usually turn off my instance when I’m not using it, I wanted to autostart Jupyter whenever the instance was re-started to avoid SSHing everytime to start it up manually. Luckily, there’s a way to do that!

Create a new file called jupyter_start.sh in your home directory, and add the following:

export PATH="$PATH:/home/ubuntu/anaconda2/bin"
jupyter notebook --notebook-dir=/home/ubuntu/ --profile=nbserver > /tmp/ipynb.out 2>&1 &

Change anaconda2 to anaconda3 if you’re using Python 3. You can also change notebook-dir to the location of your Jupyter notebooks.

Next, edit the /etc/rc.local file and add the following line before exit 0:

su ubuntu -c 'bash /home/ubuntu/jupyter_start.sh'

Let me know if you encounter any issues, or have any additional useful tips!