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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.

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