Training on vehicle data set VERI

[KZYYYY]

Hello, I modified the single domain training based on the D-resnet.yml, but I encountered the following error, how should I solve it?

Traceback (most recent call last):
File "H:/re-id代码/MetaBIN-master/train_net.py", line 136, in
launch(
File "H:\re-id代码\MetaBIN-master\fastreid\engine\launch.py", line 71, in launch
main_func(*args)
File "H:/re-id代码/MetaBIN-master/train_net.py", line 131, in main
return trainer.train() # train_loop.py -> train
File "H:\re-id代码\MetaBIN-master\fastreid\engine\defaults.py", line 539, in train
super().train(self.start_iter, self.max_iter)
File "H:\re-id代码\MetaBIN-master\fastreid\engine\train_loop.py", line 144, in train
self.run_step_meta_learning2() # update balancing parameters (meta-learning)
File "H:\re-id代码\MetaBIN-master\fastreid\engine\train_loop.py", line 606, in run_step_meta_learning2
losses, loss_dict = self.basic_forward(data_mtrain, self.model, opt) # forward
File "H:\re-id代码\MetaBIN-master\fastreid\engine\train_loop.py", line 856, in basic_forward
loss_dict = model.losses(outs, opt)
File "H:\re-id代码\MetaBIN-master\fastreid\modeling\meta_arch\metalearning.py", line 163, in losses
loss_dict['loss_triplet_add'] = triplet_loss(
File "H:\re-id代码\MetaBIN-master\fastreid\modeling\losses\triplet_loss.py", line 174, in triplet_loss
dist_ap, dist_an = hard_example_mining(dist_mat, is_pos, is_neg)
File "H:\re-id代码\MetaBIN-master\fastreid\modeling\losses\triplet_loss.py", line 76, in hard_example_mining
dist_an.append(torch.min(dist_mat[i][is_neg[i]]))
RuntimeError: min(): Expected reduction dim to be specified for input.numel() == 0. Specify the reduction dim with the 'dim' argument.

Process finished with exit code 1