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Space Efficient Context Encoding for Non-Task-Oriented Dialogue Generation with Graph Attention Transformer

This is the repository for the above mentioned paper. It can be found here: LINK TO PAPER

Knowledge Graphs

We provide the generated knowledge graphs (depth 0 & 1) for the

  • KOMODIS dataset (Link to official repository)
  • and OpenDialKG dataset (Link to official repository)

in data/knowledge_graphs/. For KOMODIS please download the dataset in data/dataset/. It will not work with the version from the official repository. Please unzip all files before running scripts.

If you are interested in the graphs with depth > 1, please contact us. We will send you corresponding download links.

Data Processing and Model

To run the graph pre-processing described in Chapter 4.2 please use the following command:

python process_graphs.py --dataset komodis --depth 0 --encoding series

To run a training please use:

The train script is not implemented yet! It will be available soon.

python train.py --dataset komodis --depth 0 --encoding series

Reference

Following soon ...

License

MIT License

Copyright (c) 2021 Fabian Galetzka

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

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