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DevOps

A bunch of DevOps files.

TODOS

  • create a CI environment to check that those environments work correctly, by testing against numpy, scipy, pandas, and h5py. (seems that I can't test matplotlib due to lack of test data; and I believe testing that could be very fragile since it's a display issue).

Things to remember for Docker images.

if possible, specify versions of numpy and scipy (I think specifying numpy is enough) for Docker containers. I found that tests on them are pretty fragile and I simply want the container to run some really stable verisons which won't fail when running the following lines.

  • python -c 'import numpy as np;np.test()'
  • python -c 'import scipy as sp;sp.test()'

Note that it seems it's required to install build-essential before you can pass all scipy tests.

MATLAB related ansible scripts

In ansible/roles/matlab/files, you should have R2012b_UNIX.tar.gz and R2014a_UNIX_original.tar.gz to make the matlab Ansible role really work. They can be generated from the corresponding ISO files I obtained from somewhere like tpb... These ISO file are available in Yimeng's 128G Flash Drive (TODO: move them to somewhere permanent in lab server)

How to build Bazel and TensorFlow

for bazel, cd to relevant directory containing Dockerfile, and then run command like

sudo docker build -t leelabcnbc/bazel:0.4.4-cuda8.0-cudnn5-centos6 .

for TF, run command like

sudo docker build -t leelabcnbc/tensorflow:0.12.1-centos6-py27-gpu .

then run command like

sudo docker run leelabcnbc/tensorflow:0.12.1-centos6-py27-gpu

to know the path of the wheel file, and then sudo docker ps -a to get the name of container.

finally run command like

sudo docker cp musing_hawking:/tmp/tensorflow_pkg/tensorflow-0.12.1-cp27-cp27mu-linux_x86_64.whl ~

to get the wheel file.

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