tensor2struct is a package that contains a set of neural semantic parsers based on the encoder-decoder framework. Currently, it supports the following datasets:
- Overnight
- Spider
- Chinese Spider
- SCAN
- COGS
Create a virtual environment and run the setup script.
conda create --name tensor2struct python=3.7
conda activate tensor2struct
./setup.sh
wandb is used for logging. To enable it you can create your own account and wandb login to enable logging.
Or you could just wandb off to only allow for dryrun locally.
In general, the raw data is expected to be placed under "/data/TASK_NAME/raw" where TASK_NAME could be spider/ssp/overnight.
Make log/ and ie_dir/ which will be used for storing checkpoints and predictions (during inference).
Tensor2struct has been the backbone architecture for implementing new models, objectives, algorithms proposed in the following papers. To reproduce experiments from a paticular paper, the corresponding link below will take to detailed instructions.
- Meta-Learning for Domain Generalization
- Learning from Executions for Semantic Parsing
- Learning to Synthesize Data for Semantic Parsing
- Meta-Learning to Compositionally Generalize
- Structured Reordering for Modeling Latent Alignments in Sequence Transduction
If you use tensor2struct, please cite one of the following papers.
bibtex
@inproceedings{wang-etal-2021-meta,
title = "Meta-Learning for Domain Generalization in Semantic Parsing",
author = "Wang, Bailin and
Lapata, Mirella and
Titov, Ivan",
booktitle = "Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies",
month = jun,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/2021.naacl-main.33",
doi = "10.18653/v1/2021.naacl-main.33",
pages = "366--379",
}bibtex
@inproceedings{wang-etal-2021-learning-executions,
title = "Learning from Executions for Semantic Parsing",
author = "Wang, Bailin and
Lapata, Mirella and
Titov, Ivan",
booktitle = "Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies",
month = jun,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/2021.naacl-main.219",
doi = "10.18653/v1/2021.naacl-main.219",
pages = "2747--2759",
}bibtex
@inproceedings{wang-etal-2021-learning-synthesize,
title = "Learning to Synthesize Data for Semantic Parsing",
author = "Wang, Bailin and
Yin, Wenpeng and
Lin, Xi Victoria and
Xiong, Caiming",
booktitle = "Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies",
month = jun,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/2021.naacl-main.220",
doi = "10.18653/v1/2021.naacl-main.220",
pages = "2760--2766",
}bibtex
@inproceedings{conklin-etal-2021-meta,
title = "Meta-Learning to Compositionally Generalize",
author = "Conklin, Henry and
Wang, Bailin and
Smith, Kenny and
Titov, Ivan",
booktitle = "Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)",
month = aug,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.acl-long.258",
doi = "10.18653/v1/2021.acl-long.258",
pages = "3322--3335",
}bibtex
@inproceedings{
wang2021structured,
title={Structured Reordering for Modeling Latent Alignments in Sequence Transduction},
author={bailin wang and Mirella Lapata and Ivan Titov},
booktitle={Thirty-Fifth Conference on Neural Information Processing Systems},
year={2021},
url={https://openreview.net/forum?id=X2Cxixkcpx}
}Tensor2struct is a generalization of RAT-SQL.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent