Adversarial Discriminative Domain Adaptation

Getting started

This code requires Python 3, and is implemented in Tensorflow.

Hopefully things should be fairly easy to run out of the box:

pip install -r requirements.txt
mkdir data snapshot
export PYTHONPATH="$PWD:$PYTHONPATH"
scripts/svhn-mnist.sh

The provided script does the following things:

• Train a base LeNet model on SVHN (downloading SVHN under

  data/svhn

  in the process)
• Use ADDA to adapt the SVHN model to MNIST (downloading MNIST under

  data/mnist

  in the process)
• Run an evaluation on MNIST using the source-only model (stored at

  snapshot/lenet_svhn

  )
• Run an evaluation on MNIST using the ADDA model (stored at

  snapshot/adda_lenet_svhn_mnist

  )

Areas of interest

• Check

  scripts/svhn-mnist.sh

  for hyperparameters.
• The LeNet model definition is in

  adda/models/lenet.py

  .
• The model is annotated with data preprocessing info, which is used in the

  preprocessing

  function in

  adda/models/model.py

  .
• The main ADDA logic happens in

  tools/train_adda.py

  .
• The adversarial discriminator model definition is in

  adda/adversary.py

  .