Submarine for K8s supports distributed TensorFlow and PyTorch.
Submarine can run on K8s >= 1.14, supports features like GPU isolation.
Submarine can be deployed on any K8s environment if version matches. If you don't have a running K8s, you can follow the steps to set up a K8s using kind, Kubernetes-in-Docker for testing purpose, we provides simple tutorial.
After you have an up-and-running K8s, you can follow Submarine Helm Charts Guide to deploy Submarine services on K8s cluster in minutes.
Submarine SDK assumes Python3.7+ is ready. It's better to use a new Python environment created by Anoconda
or Python virtualenv
to try this to avoid trouble to existing Python environment. A sample Python virtual env can be setup like this:
wget https://files.pythonhosted.org/packages/33/bc/fa0b5347139cd9564f0d44ebd2b147ac97c36b2403943dbee8a25fd74012/virtualenv-16.0.0.tar.gz tar xf virtualenv-16.0.0.tar.gz # Make sure to install using Python 3 python3 virtualenv-16.0.0/virtualenv.py venv . venv/bin/activate
Starting from 0.4.0, Submarine provides Python SDK. Please change it to a proper version needed.
pip install submarine-sdk==0.4.0
Please first clone code from github or go to http://submarine.apache.org/download.html
to download released source code.
git clone https://github.com/apache/submarine.git git checkout <correct release tag/branch> cd submarine/submarine-sdk/pysubmarine pip install .
Assuming you've installed submarine on K8s and forward the service to localhost, now you can open a Python shell, Jupyter notebook or any tools with Submarine SDK installed.
Follow SDK experiment example to try the SDK.