Code for "Learning Structural Edits via Incremental Tree Transformations" (ICLR'21)
We recommend using conda to manage the environment:
conda env create -n "structural_edits" -f structural_edits.yml
conda activate structural_edits
Install the punkt tokenizer:
python
import nltk
nltk.download('punkt')
<ctrl-D>
Please extract the dataset and vocabulary files by:
cd source_data
tar -xzvf githubedits.tar.gz
Download the complete GitHubEdits and Fixers data from Yin et al., (2019) and place the files as the following:
| --source_data
| |-- githubedits
| |-- githubedits.{train|train_20p|dev|test}.jsonl
| |-- csharp_fixers.jsonl
| |-- vocab.from_repo.{080910.freq10|edit}.json
| |-- Syntax.xml
| |-- configs
| |-- ...(model config json files)
A 20% sample from the GitHubEdits training set has been included as source_data/githubedits/githubedits.train_20p.jsonl.
The vocabulary files for both Graph2Tree (Yin et al., 2019) and our proposed Graph2Edit model have been included.
To create your own vocabulary, see edit_components/vocab.py.
See training and test scripts in scripts/githubedits/. Please configure the PYTHONPATH environment variable in line 6.
For training, uncomment the setting in scripts/githubedits/train.sh and run:
bash scripts/githubedits/train.sh source_data/githubedits/configs/CONFIGURATION_FILE
Please replace CONFIGURATION_FILE with the json file of your setting.
For example, if you want to train Graph2Edit + Sequence Edit Encoder on GitHubEdits's 20% sample data, run:
bash scripts/githubedits/train.sh source_data/githubedits/configs/graph2iteredit.seq_edit_encoder.20p.json
To further train the model with PostRefine imitation learning,
replace FOLDER_OF_SUPERVISED_PRETRAINED_MODEL with your model dir in source_data/githubedits/configs/graph2iteredit.seq_edit_encoder.20p.postrefine.imitation.json,
and run:
bash scripts/githubedits/train.sh source_data/githubedits/configs/graph2iteredit.seq_edit_encoder.20p.postrefine.imitation.json
To test a trained model, first uncomment the setting in scripts/githubedits/test.sh and replace work_dir with your model directory,
and then run:
bash scripts/githubedits/test.sh
If you use our code and data, please cite our paper:
@inproceedings{yao2021learning,
title={Learning Structural Edits via Incremental Tree Transformations},
author={Ziyu Yao and Frank F. Xu and Pengcheng Yin and Huan Sun and Graham Neubig},
booktitle={International Conference on Learning Representations},
year={2021},
url={https://openreview.net/forum?id=v9hAX77--cZ}
}
Our implementation is adapted from TranX and Graph2Tree. We are grateful to the two work!
@inproceedings{yin18emnlpdemo,
title = {{TRANX}: A Transition-based Neural Abstract Syntax Parser for Semantic Parsing and Code Generation},
author = {Pengcheng Yin and Graham Neubig},
booktitle = {Conference on Empirical Methods in Natural Language Processing (EMNLP) Demo Track},
year = {2018}
}
@inproceedings{yin2018learning,
title={Learning to Represent Edits},
author={Pengcheng Yin and Graham Neubig and Miltiadis Allamanis and Marc Brockschmidt and Alexander L. Gaunt},
booktitle={International Conference on Learning Representations},
year={2019},
url={https://openreview.net/forum?id=BJl6AjC5F7},
}
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