mlpractical/kernel_issue_fix.md

How to fix notebook's "kernel issues" on DICE

Some people in MLP have been affected by a recent update to the numpy and numerical libraries on DICE on 3 October. The problem affects you if you get a message stating that the kernel was restarted when you run code involving numpy.

If you have experienced these issues you have either:

1. ended up using the default atlas libraries with numpy (which have been updated in the meantime)
2. or re-compiled numpy with the new DICE OpenBLAS that is available, but the LD_LIBRARY_PATH that you set during the first lab last week gave priority to load the OpenBLAS libraries compiled last time - which could introduce some unexepcted behaviour at runtime.

The Fix

Follow the below steps before you activate the old virtual environment (or deactivate it if it is activated). The fix basically involves rebuilding the virtual environments. But the whole process is now much simpler due to the fact OpenBLAS is now a default numerical library on DICE.

1. Comment out (or remove) the export=$LD_LIBRARY_PATH... line in your ~/.bashrc file. Then type

unset LD_LIBRARY_PATH

in the terminal. To make sure this variable is not set, type export and check visually in the printed list of variables

2. Go to ~/mlpractical/repos-3rd/virtualenv and install the new virtual environment (venv2) by typing:

./virtualenv.py --python /usr/bin/python2.7 --no-site-packages $MLP_WDIR/venv2

3. Activate your new virtual environment by typing:

source $MLP_WDIR/venv2/bin/activate 

and install the usual packages required by MLP using pip:

pip install pip --upgrade
pip install numpy
pip install ipython
pip install notebook
pip install matplotlib

4. Change directory to ~/mlpractical/repo-mlp and check that numpy is linked to the DICE-standard OpenBLAS (and works) by starting ipython notebook:

ipython notebook

then run the first two interactive examples from 00_Introduction.py. If they run, then you can simply modify the activate_mlp alias in ./bashrc to point to venv2 instead of venv

5. You can also remove both the old venv and the other unrequired directories that contain numpy and OpenBLAS sources in the ~/mlpractical/repos-3rd directory.