Skip to content

fungtion/DANN_py3

Repository files navigation

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

Environment

  • Pytorch 1.6
  • Python 3.8.5

Network Structure

p8KTyD.md.jpg

Dataset

First, download target dataset mnist_m from pan.quark.com or Google Drive, and put mnist_m dataset into dataset/mnist_m, the structure is as follows:

--dataset--mnist_m--mnist_m_train
                 |--mnist_m_test
                 |--mnist_m_train_labels.txt
                 |--mnist_m_test_labels.txt
                 |--.gitkeep

Training

Then, run python main.py

Docker

  • 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

Releases

No releases published

Packages

No packages published