This is a pytorch implementation of the paper Unsupervised Domain Adaptation by Backpropagation
- Pytorch 1.0
- Python 3.7
First, download target dataset mnist_m from pan.baidu.com fetch code: kjan or Google Drive
cd DANN_py3
mkdir dataset
cd dataset
mkdir mnist_m
cd mnist_m
tar -zvxf mnist_m.tar.gz
mkdir models
Then, run python main.py
- build image
docker build -t pytorch_dann .- run docker container
docker run -it --runtime=nvidia \
-u $(id -u):$(id -g) \
-v /YOUR/DANN/PROJECT/dataset:/DANN/dataset \
-v /YOUR/DANN/PROJECT/models:/DANN/models \
pytorch_dann:latest \
python main.py