This repo has the code accompanying the CodeRanker NeurIPS'22 paper.
pip install -r requirements.txt
The ranker datasets are available through GIT LFS in dataset/ directory
First, cd into src directory
- Training rankers
bash finetune.sh DATADIR MODELDIR CACHEDIR TASK
where DATADIR is the location of the directory containing the desired ranker dataset
MODELDIR is the location of the output dirctory where the trained model will be stored
CACHEDIR is the location of the cache directory both for caching the model and for caching the dataset
TASK is one of binary, ternary, intent_error, execution_error, execution_error_with_line
- Inference with rankers
bash eval.sh DATADIR MODELDIR CACHEDIR TASK {val|test}.json PREDICT_FILENAME
where PREDICT_FILENAME is the name of the file inside MODELDIR where the inferenced logits will be stored.
- Computing the ranked metrics
python3 compute_metrics.py --data_file=DATADIR/{val|test}.json --logits_prediction_file=MODELDIR/PREDICT_FILENAME --labels_file=DATADIR/labels_TASK.txt --task=TASK
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