## Bridge the gap between algorithms and implementations of deep learning

### Powerful

Chainer supports CUDA computation. It only requires few lines of codes to leverage a GPU. It also runs on multiple GPUs with a little effort.

### Flexible

Chainer supports various network architectures including feed-forward nets, convnets, recurrent nets and recursive nets. It also supports per-batch architectures.

### Intuitive

Forward computation can include any control flow statements of Python without lacking ability of backpropagation. It makes codes intuitive and easy to debug.

## Quick Start

Install Chainer:

pip install chainer

Run the MNIST example:

wget https://github.com/pfnet/chainer/archive/v1.18.0.tar.gz
tar xzf v1.18.0.tar.gz
python chainer-1.18.0/examples/mnist/train_mnist.py