DAML

Source code for the ACL 2019 paper entitled "Domain Adaptive Dialog Generation via Meta Learning" by Kun Qian and Zhou Yu https://arxiv.org/abs/1906.03520

@article{qian2019domain,
  title={Domain Adaptive Dialog Generation via Meta Learning},
  author={Qian, Kun and Yu, Zhou},
  journal={arXiv preprint arXiv:1906.03520},
  year={2019}
}

Simulated Data Generation

Please download the code here: https://github.com/qbetterk/SimDial

git clone https://github.com/qbetterk/SimDial.git
cd SimDial
python multiple_domains.py

Training with default parameters

python model.py -mode train_maml -model tsdf-camrest

(optional: configuring hyperparameters with cmdline)

python model.py -mode train_maml -model tsdf-camrest -cfg lr=0.003 batch_size=32

Testing

python model.py -mode test_maml -model tsdf-camrest

Before running

1. Install required python packages. We used pytorch 0.3.0 and python 3.6 under Linux operating system.

pip install -r requirements.txt

2. Make directories under PROJECT_ROOT.

mkdir vocab
mkdir log
mkdir results
mkdir models
mkdir sheets

3. Download pretrained Glove word vectors and place them in PROJECT_ROOT/data/glove.