Language Model GRU with Python and Theano
Python TeX
Switch branches/tags
Nothing to show
Clone or download
Latest commit 444ec93 Nov 10, 2015
Failed to load latest commit information.
data update pretrained model Oct 26, 2015
latex Clean up notebook Oct 26, 2015
.gitignore Bugfix in utils Oct 25, 2015 Fix README - ref #3 Nov 10, 2015 Pretrained model update Oct 26, 2015
requirements.txt Fix func tools Nov 10, 2015
rnn-tutorial-gru.ipynb Clear outputs Oct 26, 2015 Remove unused var Oct 25, 2015 Clean up notebook Oct 26, 2015

This repositoriy belongs to Part 4 of the WildML RNN Tutorial. The previous parts are here:

Jupyter Notebook Setup

System Requirements:

  • Python, pip
  • virtualenv (optional, but recommended)

To start the Jupyter Notebook:

# Clone the repo
git clone
cd rnn-tutorial-lstm

# Create a new virtual environment (optional, but recommended)
virtualenv venv
source venv/bin/activate

# Install requirements
pip install -r requirements.txt
# Start the notebook server
jupyter notebook

Setting up a CUDA-enabled GPU instance on EC2:

# Install build tools
sudo apt-get update
sudo apt-get install -y build-essential git python-pip libfreetype6-dev libxft-dev libncurses-dev libopenblas-dev  gfortran python-matplotlib libblas-dev liblapack-dev libatlas-base-dev python-dev python-pydot linux-headers-generic linux-image-extra-virtual
sudo pip install -U pip

# Install CUDA 7
sudo dpkg -i cuda-repo-ubuntu1410_7.0-28_amd64.deb
sudo apt-get update
sudo apt-get install -y cuda
sudo reboot

# Clone the repo and install requirements
git clone
cd nn-theano
sudo pip install -r requirements.txt

# Set Environment variables
export CUDA_ROOT=/usr/local/cuda-7.0
export PATH=$PATH:$CUDA_ROOT/bin
export THEANO_FLAGS=mode=FAST_RUN,device=gpu,floatX=float32
# For profiling only

# Startup jupyter noteboook
jupyter notebook

To start a public notebook server that is accessible over the network you can follow the official instructions.