-
Notifications
You must be signed in to change notification settings - Fork 147
/
eval_ruler.py
72 lines (59 loc) · 2.44 KB
/
eval_ruler.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
import os
import json
import argparse
import numpy as np
from metrics import (
string_match_all
)
def parse_args(args=None):
parser = argparse.ArgumentParser()
parser.add_argument('--results_dir', type=str, default=None)
return parser.parse_args(args)
if __name__ == '__main__':
args = parse_args()
dataset_list = ["niah_single_1", "niah_single_2", "niah_single_3", "niah_multikey_1", "niah_multikey_2", "niah_multikey_3",
"niah_multiquery", "niah_multivalue", "cwe", "fwe", "vt"]
results_list = [
["dataset"],
["FullKV"],
["random"],
["SnapKV"],
["StreamingLLM"],
["H2O"],
["PyramidKV"],
["L2Norm"]
]
for dataset in dataset_list:
results_list[0].append(dataset)
for idx, method in enumerate(["FullKV", "random", "SnapKV", "StreamingLLM", "H2O", "PyramidKV", "L2Norm"]):
try:
args.method = method
args.dataset = dataset
args.eval_file = os.path.join(args.results_dir,dataset,f"{method}.json")
scores = dict()
predictions, answers, lengths = [], [], []
# dataset = filename.split('.')[0]
with open(args.eval_file, "r", encoding="utf-8") as f:
for line in f:
try:
data = json.loads(line)
predictions.append(data["pred"])
answers.append(data["answers"])
if "length" in data:
lengths.append(data["length"])
except:
print("error")
score = string_match_all(predictions, answers)
scores[args.dataset] = score
results_list[idx+1].append(score)
output_dir = os.path.dirname(args.eval_file)
with open(os.path.join(output_dir, "metrics.json"), "w") as f:
json.dump(scores, f, ensure_ascii=False, indent=4)
print(f"dataset {args.dataset} method {args.method} scores {scores}")
except:
results_list[idx+1].append(-1)
print(f"dataset {args.dataset} method {args.method} scores {None}")
import csv
with open(os.path.join(args.results_dir,f"results.csv"), 'w') as fp:
writer = csv.writer(fp)
writer.writerows(results_list)