Potential bugs in train_itm.py when generating negative samples

[ghost]

As the following codes show,

mmnas/train_itm.py

Lines 335 to 353 in 552e29e

	for step, (frcn_feat_iter_list, bbox_feat_iter_list, rel_img_iter_list, cap_ix_iter_list, rel_cap_iter_list, neg_idx_list) in enumerate(tqdm.tqdm(neg_imgs_loader)):
	frcn_feat_iter_list = all_frcn_feat_iter_list[neg_idx_list, :]
	bbox_feat_iter_list = all_bbox_feat_iter_list[neg_idx_list, :]
	rel_img_iter_list = all_rel_img_iter_list[neg_idx_list, :]
	frcn_feat_iter_list = frcn_feat_iter_list.view(-1, self.__C.FRCNFEAT_LEN, self.__C.FRCNFEAT_SIZE)
	bbox_feat_iter_list = bbox_feat_iter_list.view(-1, self.__C.FRCNFEAT_LEN, 5)
	rel_img_iter_list = rel_img_iter_list.view(-1, self.__C.FRCNFEAT_LEN, self.__C.FRCNFEAT_LEN, 4)
	cap_ix_iter_list = cap_ix_iter_list.view(-1, neg_caps_loader.dataset.max_token)
	rel_cap_iter_list = rel_cap_iter_list.view(-1, neg_caps_loader.dataset.max_token, neg_caps_loader.dataset.max_token, 3)
	input = (frcn_feat_iter_list, bbox_feat_iter_list, rel_img_iter_list, cap_ix_iter_list, rel_cap_iter_list)
	scores = net(input)
	scores = scores.view(-1, self.__C.NEG_RANDSIZE)
	arg_scores = torch.argsort(scores, dim=-1, descending=True)[:, :self.__C.NEG_HARDSIZE]
	arg_scores_bi = torch.arange(arg_scores.size(0)).unsqueeze(1).expand_as(arg_scores)
	scores_ind = neg_idx_list[arg_scores_bi, arg_scores].to(scores.device)
	neg_imgs_idx_list.append(scores_ind)

And here is what confuses me,

mmnas/train_itm.py

Lines 336 to 338 in 552e29e

	frcn_feat_iter_list = all_frcn_feat_iter_list[neg_idx_list, :]
	bbox_feat_iter_list = all_bbox_feat_iter_list[neg_idx_list, :]
	rel_img_iter_list = all_rel_img_iter_list[neg_idx_list, :]

Why use negative caption indices to get corresponding image features?
I think the three lines of codes should be removed.