from evaluation import evalrank, evalrank2,evalrank3,evalrank_vse,evalrank_maxpool,evalrank_f_c,evalrank_avgpool,evalrank_f_c2
import numpy as np
from transformers import BertTokenizer
import os
os.environ["CUDA_VISIBLE_DEVICES"] = "5"
# os.environ['KMP_DUPLICATE_LIB_OK'] = 'TRUE'

#f30k数据集和coco数据集上实验
evalrank_f_c("../SCAN-master/data/f30k_precomp","f30k")
# evalrank_f_c("../SCAN-master/data/coco_precomp","coco")


#evalrank_f_c2("../SCAN-master/data/coco_precomp","f30k")
# evalrank_f_c2("../SCAN-master/data/f30k_precomp","coco")

#消融实验
#evalrank_vse("./runs/bert_adam_bcan_gpo_vseinfty_vse_data_3045_lr2_vse_gpo/model_best.pth.tar", "../SCAN-master/data/", "test")
#evalrank("./runs/bert_adam_bcan_gpo_vseinfty_union_2035/model_best.pth.tar", "../SCAN-master/data/", "test")

#池化方式对比实验
#evalrank_avgpool("./runs/bert_adam_bcan_gpo_vseinfty_bcan/model_best.pth.tar", "../SCAN-master/data/", "test")
#evalrank_maxpool("./runs/bert_adam_bcan_gpo_vseinfty_bcan/model_best.pth.tar", "../SCAN-master/data/", "test")