TensorML 18.04

We provide our own OS image, TensorML 18.04, for machine learning.
It comes preinstalled with the most popular Python libraries: Jupyter Notebook, Jupyter Lab, TensorFlow, Keras, PyTorch, MxNet, Numpy, Pandas, NVIDIA drivers, CUDA, cuDNN, CUDA Toolkit, Docker, and NVIDIA Docker2.
To get started:
  1. 1.
    SSH into your server with the IP and username in the "Metadata section"
  2. 2.
    Run jupyter lab --ip= for a Jupyter Lab or jupyter notebook --ip= for a Jupyter Notebook
  3. 3.
    Connect to your Jupyter Lab or Notebook by typing the IP:8888 in your browser. You'll need to copy the token shown in your SSH session to login.
  4. 4.
    You should see a default Jupyter notebook. Run it. Reboot if there is an error doing so. If NVIDIA drivers update to a new version during the first boot, you'll have to reboot to have them working properly.
Note: If you receive a "successful NUMA node read"... verbose message, you can silence it by running: for a in /sys/bus/pci/devices/*; do echo 0 | sudo tee -a $a/numa_node; done
That's it! You're all set to immediately start ML-related work!