Creates a fast.ai DL environment on Google Cloud

setup.sh

# Preare disk
# Here sdb is the device ID I get from lsblk
# Uncomment if you want to use a shared disk.
# Details on: # https://cloud.google.com/compute/docs/disks/add-persistent-disk
# You can add a persistent disk already when creating a computing instnance 

#echo "Format Disk"
#sudo mkfs.ext4 -m 0 -F -E lazy_itable_init=0,lazy_journal_init=0,discard /dev/sdb
#sudo mkdir -p /mnt/disks/data
#echo "Mount Disk"
#sudo mount -o discard,defaults /dev/sdb /mnt/disks/data
#echo UUID=`sudo blkid -s UUID -o value /dev/sdb` /mnt/disks/data ext4 discard,defaults,nofail 0 2 | sudo tee -a /etc/fstab
#ln -s /mnt/disks/data/ data
#echo "Done"

# install Anaconda for current user
echo "Install Anaconda"
mkdir downloads
cd downloads
wget "https://repo.continuum.io/archive/Anaconda3-5.0.0.1-Linux-x86_64.sh" -O "Anaconda3-5.0.0.1-Linux-x86_64.sh"

bash "Anaconda3-5.0.0.1-Linux-x86_64.sh" -b

echo "export PATH=\"$HOME/anaconda3/bin:\$PATH\"" >> ~/.bashrc
export PATH="$HOME/anaconda3/bin:$PATH"
conda install -y bcolzconda install -y bcolz
conda install -y pip
conda upgrade -y --all

python --version 
which python 

# Some students have reported GPU instances whose drivers disappear upon restarts. 
# And there is strong evidence to suggest that the issue happens when Ubuntu auto-installs security updates upon booting up. 
# To disable auto-updating, run
# http://cs231n.github.io/gce-tutorial-gpus/ 
sudo apt-get  update
 
sudo apt-get --assume-yes remove unattended-upgrades  

# ensure system is updated and has basic build tools
sudo apt-get --assume-yes install tmux libcupti-dev build-essential gcc g++ make binutils software-properties-common

# download and install GPU drivers

# see https://cloud.google.com/compute/docs/gpus/add-gpus#install-gpu-driver
echo "Checking for CUDA and installing."
# Check for CUDA and try to install.
if ! dpkg-query -W cuda-8-0; then
  # The 16.04 installer works with 16.10.
  echo "Installing  CUDA"
  curl -O http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/cuda-repo-ubuntu1604_8.0.61-1_amd64.deb
  sudo dpkg -i ./cuda-repo-ubuntu1604_8.0.61-1_amd64.deb
  sudo apt-get  update
  sudo apt-get install cuda-8-0 -y
fi

# verify that GPU driver installed
echo "verify GPU Driver"
sudo modprobe nvidia
nvidia-smi

# install cudnn libraries
echo "Install cudnn"
wget "http://files.fast.ai/files/cudnn.tgz" -O "cudnn.tgz"
tar -zxf cudnn.tgz
cd cuda
sudo cp lib64/* /usr/local/cuda/lib64/
sudo cp include/* /usr/local/cuda/include/


# install and configure theano
echo "install and configure theano"
conda install theano pygpu
clear

# install and configure keras
echo "install and configure keras"
conda install keras
mkdir ~/.keras
echo '{
    "epsilon": 1e-07,
    "floatx": "float32",
    "backend": "theano",
    "image_data_format": "channels_first"
}' > ~/.keras/keras.json

# install pytorch
echo "install pytorch"
conda install pytorch torchvision cuda80 -c soumith


# clone the fast.ai course repo and prompt to start notebook
echo "clone the fast.ai course repo"
cd ~
git clone https://github.com/fastai/courses.git

# configure jupyter and prompt for password
echo "install and configure jupyter"
conda install scikit-learn
conda install pandas
conda install jupyter

jupyter notebook --generate-config
jupass=`python -c "from notebook.auth import passwd; print(passwd())"`
echo "c.NotebookApp.ip = '*'
c.NotebookApp.password = u'"$jupass"'
c.NotebookApp.open_browser = False
c.NotebookApp.port = 8888" >> $HOME/.jupyter/jupyter_notebook_config.py

echo "Done. Setup completed"

Usage:

wget https://gist.github.com/marvin-hansen/333bf5f5d59fe25c27dc3e056872eb5d
chmod + x setup.sh
sudo ./setup.sh