| |
| |
| import os |
| import logging |
| import argparse |
| from bleu import _bleu |
| import json |
|
|
| logger = logging.getLogger(__name__) |
| logging.basicConfig(level=logging.INFO) |
|
|
| def main(): |
| parser = argparse.ArgumentParser(description='Evaluate leaderboard predictions for code completion (line level).') |
| parser.add_argument('--answers', '-a', required=True, help="filename of the labels, in json format.") |
| parser.add_argument('--predictions', '-p', required=True, help="filename of the leaderboard predictions, in txt format.") |
| args = parser.parse_args() |
|
|
| preds = open(args.predictions, "r").readlines() |
| gts = open(args.answers, "r").readlines() |
|
|
| assert len(preds) == len(gts), f"Samples of predictions and answers are not equal, {len(preds)}: {len(gts)}" |
|
|
| total = len(gts) |
| EM = 0.0 |
| with open("ground_truth.txt", "w") as wf: |
| for pred, gt in zip(preds, gts): |
| pred = pred.strip() |
| gt = json.loads(gt)["code"] |
| wf.write(gt+"\n") |
| if pred.split() == gt.split(): |
| EM += 1 |
|
|
| bleu_score = round(_bleu("ground_truth.txt", args.predictions), 2) |
| logger.info(f"BLEU: {bleu_score}, EM: {round(EM/total*100, 2)}") |
|
|
| try: |
| os.remove("ground_truth.txt") |
| except Exception: |
| pass |
|
|
| if __name__ == "__main__": |
| main() |
|
|
