import json import argparse import sys from rouge import Rouge import numpy as np import jieba def rouge_score(data): """ compute rouge score Args: data (list of dict including reference and candidate): Returns: res (dict of list of scores): rouge score """ rouge_name = ["rouge-1", "rouge-2", "rouge-l"] item_name = ["f", "p", "r"] res = {} for name1 in rouge_name: for name2 in item_name: res["%s-%s"%(name1, name2)] = [] for tmp_data in data: origin_candidate = tmp_data['candidate'] origin_reference = tmp_data['reference'] assert isinstance(origin_candidate, str) if not isinstance(origin_reference, list): origin_reference = [origin_reference] tmp_res = [] for r in origin_reference: tmp_res.append(Rouge().get_scores(refs=r, hyps=origin_candidate)[0]) for name1 in rouge_name: for name2 in item_name: res["%s-%s"%(name1, name2)].append(max([tr[name1][name2] for tr in tmp_res])) for name1 in rouge_name: for name2 in item_name: res["%s-%s"%(name1, name2)] = np.mean(res["%s-%s"%(name1, name2)]) return res def load_file(filename): data = [] with open(filename, "r") as f: for line in f.readlines(): data.append(json.loads(line)) f.close() return data def proline(line): return " ".join([w for w in jieba.cut("".join(line.strip().split()))]) def compute(golden_file, pred_file, return_dict=True): golden_data = load_file(golden_file) pred_data = load_file(pred_file) if len(golden_data) != len(pred_data): raise RuntimeError("Wrong Predictions") eval_data = [{"reference": proline(g["summary"]), "candidate": proline(p["summary"])} for g, p in zip(golden_data, pred_data)] return rouge_score(eval_data) def main(): argv = sys.argv print("预测结果:{}, 测试集: {}".format(argv[1], argv[2])) print(compute(argv[2], argv[1])) if __name__ == '__main__': main()