IndexError: too many indices for tensor of dimension 2

[Halo754]

Setting up a new session...
E:\MyPaper\TargetDetection\Ours_SSD\Code\SSD\ssd_-repulsion_-loss\ssd.py:35: UserWarning: volatile was removed and now has no effect. Use with torch.no_grad(): instead.
self.priors = Variable(self.priorbox.forward(), volatile=True)
E:\MyPaper\TargetDetection\Ours_SSD\Code\SSD\ssd_-repulsion_-loss\layers\modules\l2norm.py:17: UserWarning: nn.init.constant is now deprecated in favor of nn.init.constant_.
init.constant(self.weight,self.gamma)
Loading base network...
Initializing weights...
Loading the dataset...
Training SSD on: VOC0712
Using the specified args:
Namespace(basenet='vgg16_reducedfc.pth', batch_size=16, cuda=True, dataset='VOC', dataset_root='E:\MyPaper\TargetDetection\Ours_SSD\Code\SSD\ssd_-repulsion_-loss\data/VOCdevkit/', gamma=0.1, lr=0.0001, momentum=0.9, num_workers=0, resume=None, save_folder='weights/', start_iter=0, visdom=False, weight_decay=0.0005)
E:\MyPaper\TargetDetection\Ours_SSD\Code\SSD\ssd_-repulsion_-loss\utils\augmentations.py:238: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray.
mode = random.choice(self.sample_options)
E:/MyPaper/TargetDetection/Ours_SSD/Code/SSD/ssd_-repulsion_-loss/train.py:178: UserWarning: volatile was removed and now has no effect. Use with torch.no_grad(): instead.
targets = [Variable(ann.cuda(), volatile=True) for ann in targets]
Traceback (most recent call last):
File "E:/MyPaper/TargetDetection/Ours_SSD/Code/SSD/ssd_-repulsion_-loss/train.py", line 265, in
train()
File "E:/MyPaper/TargetDetection/Ours_SSD/Code/SSD/ssd_-repulsion_-loss/train.py", line 187, in train
loss_l, loss_l_repul, loss_c = criterion(out, targets)
File "D:\anaconda3\envs\pytorch\lib\site-packages\torch\nn\modules\module.py", line 532, in call
result = self.forward(*input, **kwargs)
File "E:\MyPaper\TargetDetection\Ours_SSD\Code\SSD\ssd_-repulsion_-loss\layers\modules\multibox_loss.py", line 97, in forward
priors = priors[pos_idx].view(-1, 4)
IndexError: too many indices for tensor of dimension 2

[SeokminJang]

#1 (comment)

check this comment

[hskfn]

priors = torch.concat([priors[pos_idx[index]] for index in range(pos_idx.shape[0])]).view(-1, 4)
torch=1.11.0