Python>=3.10.pip install -r requirements.txt.The project is now in commercial usage, so the full code is not disclosed. This repository aims to provide the code skeleton and reproduces the main logic for IRG. It is still executable, but some functions are filled with placeholders that do not do the same thing as what is described in the paper, and some core parameters are not exposed.
Methods that are filled by placeholders are annotated with @placeholder.
The evaluation framework is also not exposed for the same reason.
To train and generate a synthetic database, run the following command:
python main.py -c CONFIG_FILE -i DATA_DIR -o OUT_DIR
where CONFIG_FILE is the configuration yaml file, with a sample in config/sample.yaml, DATA_DIR is the directory
where real data is stored, and each table name mentioned in the config should have the file TABLE_NAME.csv found
in this directory, and OUT_DIR be the directory where trained results can be found.
The generated synthetic data can be found in OUT_DIR/generated csv files.
Commands and scripts to reproduce the results shown in our paper, the commands are shown in the Makefile.