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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()
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