Precision: [tensor(0.5852, device='cuda:0'), tensor(0.6070, device='cuda:0'), tensor(0.5904, device='cuda:0'), tensor(0.6028, device='cuda:0'), tensor(0.5828, device='cuda:0'), tensor(0.5939, device='cuda:0'), tensor(0.5876, device='cuda:0'), tensor(0.6017, device='cuda:0'), tensor(0.5844, device='cuda:0'), tensor(0.5986, device='cuda:0')]

Output distance: [tensor(5.1357, device='cuda:0'), tensor(5.0921, device='cuda:0'), tensor(5.1252, device='cuda:0'), tensor(5.1006, device='cuda:0'), tensor(5.1405, device='cuda:0'), tensor(5.1184, device='cuda:0'), tensor(5.1310, device='cuda:0'), tensor(5.1027, device='cuda:0'), tensor(5.1373, device='cuda:0'), tensor(5.1090, device='cuda:0')]

Prediction loss: [tensor(21936114., device='cuda:0'), tensor(19516036., device='cuda:0'), tensor(15774067., device='cuda:0'), tensor(22314244., device='cuda:0'), tensor(20596542., device='cuda:0'), tensor(15896539., device='cuda:0'), tensor(17343210., device='cuda:0'), tensor(17994704., device='cuda:0'), tensor(20246840., device='cuda:0'), tensor(19556772., device='cuda:0')]

Others: [{'iter_num': 60, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 13, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}]

Compressed training loss: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]

Training loss: 0

Prediction time: [datetime.timedelta(seconds=1, microseconds=250699), datetime.timedelta(seconds=1, microseconds=10715), datetime.timedelta(seconds=1, microseconds=247711), datetime.timedelta(microseconds=989804), datetime.timedelta(seconds=1, microseconds=231778), datetime.timedelta(seconds=1, microseconds=59509), datetime.timedelta(seconds=1, microseconds=199912), datetime.timedelta(microseconds=992791), datetime.timedelta(seconds=1, microseconds=200908), datetime.timedelta(seconds=1, microseconds=5737)]

Phi time: [datetime.timedelta(microseconds=231021), datetime.timedelta(microseconds=240978), datetime.timedelta(microseconds=236994), datetime.timedelta(microseconds=241974), datetime.timedelta(microseconds=224049), datetime.timedelta(microseconds=262884), datetime.timedelta(microseconds=233012), datetime.timedelta(microseconds=236995), datetime.timedelta(microseconds=237989), datetime.timedelta(microseconds=223054)]

