kinredon / DANN

pytorch implementation of Domain-Adversarial Training of Neural Networks

This is a pytorch implementation of the paper Unsupervised Domain Adaptation by Backpropagation

Environment

• Pytorch 0.4.0
• Python 2.7

Network Structure

Dataset

First, you need download two datasets: source dataset mnist,

cd dataset
mkdir mnist
cd mnist
wget http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz
wget http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz
wget http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz
wget http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz

and target dataset mnist_m from pan.baidu.com or Google Drive

cd dataset
mkdir mnist_m
cd mnist_m
tar -zvxf mnist_m.tar.gz

Training

Then, run main.py