-
Notifications
You must be signed in to change notification settings - Fork 6
Expand file tree
/
Copy patheval_bwt.py
More file actions
129 lines (103 loc) · 4.92 KB
/
eval_bwt.py
File metadata and controls
129 lines (103 loc) · 4.92 KB
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
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
import os
import sys
import json
from glob import glob
import argparse
from utils.dataset_order import get_dataset_order
def get_jga_scores(output_dir, dataset_order):
JGA_list = []
#print("Calculating JGA score for each service.....")
for service_id in range(0, len(dataset_order)-1):
print(service_id)
result_file = os.path.join(output_dir, str(service_id)+"-"+dataset_order[service_id] +"_result.txt")
if not os.path.exists(output_dir):
print(f"result_file {result_file} not find!")
sys.exit(1)
model_results = open(result_file, "r").readlines()
testfile_idx = "./data/SGD_single_service_test/" + dataset_order[service_id] + "-test.idx"
testfile_name = "./data/SGD_single_service_test/" + dataset_order[service_id] + "-test-LLM.json"
idx_lines = open(testfile_idx).readlines()
test_lines = json.load(open(testfile_name))
# assert len(model_results) == len(idx_lines) == len(test_lines), "line number error!"
dial_dic = {}
# dia_dic['state'] = {}
# dia_dic['pred_state'] = {}
for idx_ in range(0, len(idx_lines)):
true_state = test_lines[idx_]['output']
result_line = model_results[idx_].strip().lower()
idx_line = idx_lines[idx_].strip()
if idx_line not in result_line:
print(idx_line,result_line )
sys.exit(1)
pred_state = result_line.split("|||")[-1]
pred_state = eval(pred_state)[0]
if "</s>" in pred_state:
pred_state = pred_state.replace("</s>","")
dial_json_n, dial_idx, turn_idx, frame_idx, d_name, s_name = idx_line.split("|||")
dic_key_name = dial_idx + "-" + turn_idx
if dic_key_name not in dial_dic:
dial_dic[dic_key_name] = {}
dial_dic[dic_key_name]['state'] = {}
dial_dic[dic_key_name]['pred_state'] = {}
dial_dic[dic_key_name]['state'][d_name + "-" + s_name] = true_state
dial_dic[dic_key_name]['pred_state'][d_name + "-" + s_name] = pred_state
else:
dial_dic[dic_key_name]['state'][d_name + "-" + s_name] = true_state
dial_dic[dic_key_name]['pred_state'][d_name + "-" + s_name] = pred_state
# with open("pred.json", 'w') as f:
# json.dump(dial_dic, f, indent=4)
joint_total = 0
joint_acc = 0
for turn_id in dial_dic:
joint_total += 1
true_state_dic = dial_dic[turn_id]['state']
pred_state_dic = dial_dic[turn_id]['pred_state']
if set(true_state_dic.items()) == set(pred_state_dic.items()):
joint_acc += 1
joint_accuracy = joint_acc / joint_total
#print('{} JGA: {}'.format(dataset_order[service_id], joint_accuracy))
JGA_list.append(joint_accuracy)
#break
return JGA_list
def main(args):
dataset_order = get_dataset_order(args.dataset_id)
if args.with_replay:
output_dir = os.path.join("./output", args.test_data_name + "_with_memoryreplay")
else:
output_dir = os.path.join("./output", args.test_data_name,)
if not os.path.exists(output_dir):
print(f"results dir {output_dir} not find!")
sys.exit(1)
if args.with_replay:
output_dir2 = os.path.join("./output", args.test_data_name2 + "_with_memoryreplay")
else:
output_dir2 = os.path.join("./output", args.test_data_name2 ,)
if not os.path.exists(output_dir2):
print(f"results dir2 {output_dir2} not find!")
sys.exit(1)
JGA_list1 = get_jga_scores(output_dir, dataset_order) # Houyibufen
print(f"JGA_list1: {JGA_list1}")
JGA_list2 = get_jga_scores(output_dir2, dataset_order)
JGA_list = [JGA_list2[i]-JGA_list1[i] for i in range(len(JGA_list1))]
print(JGA_list)
print(f"average JGA is {sum(JGA_list) / len(JGA_list)}")
print()
average_JGA = sum(JGA_list) / len(JGA_list)
JGA_list.append(average_JGA)
dataset_order.pop()
dataset_order.append("Average")
import pandas as pd
return average_JGA
if __name__=='__main__':
mean_list = []
for data_id in range(1):
parser = argparse.ArgumentParser()
parser.add_argument("--dataset_id", default=data_id+1, type=int)
parser.add_argument("--test_data_name", type=str, default="t5small_importance_dataset_id_1_bwt-averaging", help = "_with_memoryreplay")
parser.add_argument("--test_data_name2", type=str, default="t5small_importance_dataset_id_1_avgJGA-averaging", help = "_with_memoryreplay")
parser.add_argument("--with_replay", default=False, type=bool)
args = parser.parse_args()
average_JGA = main(args)
mean_list.append(average_JGA)
import numpy as np
print(np.mean(mean_list))