Precision: [tensor(0.8724, device='cuda:0'), tensor(0.8769, device='cuda:0'), tensor(0.8784, device='cuda:0'), tensor(0.8739, device='cuda:0'), tensor(0.8758, device='cuda:0'), tensor(0.8757, device='cuda:0'), tensor(0.8782, device='cuda:0'), tensor(0.8809, device='cuda:0'), tensor(0.8783, device='cuda:0'), tensor(0.8784, device='cuda:0')]
Output distance: [tensor(1039.8362, device='cuda:0'), tensor(991.5341, device='cuda:0'), tensor(1008.5493, device='cuda:0'), tensor(1025.0546, device='cuda:0'), tensor(1013.5037, device='cuda:0'), tensor(1013.0541, device='cuda:0'), tensor(1000.8942, device='cuda:0'), tensor(968.9489, device='cuda:0'), tensor(994.4747, device='cuda:0'), tensor(1005.2461, device='cuda:0')]
Prediction loss: [tensor(1728.0004, device='cuda:0'), tensor(1737.7863, device='cuda:0'), tensor(1695.5479, device='cuda:0'), tensor(1728.2974, device='cuda:0'), tensor(1739.2091, device='cuda:0'), tensor(1731.6860, device='cuda:0'), tensor(1766.5457, device='cuda:0'), tensor(1677.3533, device='cuda:0'), tensor(1719.3378, device='cuda:0'), tensor(1696.2518, device='cuda:0')]
Others: [{'iter_num': 7, 'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}]
Compressed training loss: [tensor(19716136., device='cuda:0'), tensor(19711896., device='cuda:0'), tensor(19223288., device='cuda:0'), tensor(19677156., device='cuda:0'), tensor(19750938., device='cuda:0'), tensor(19707174., device='cuda:0'), tensor(19995102., device='cuda:0'), tensor(19027278., device='cuda:0'), tensor(19579044., device='cuda:0'), tensor(19233154., device='cuda:0')]
Training loss: Not calculated
Prediction time: [datetime.timedelta(microseconds=594477), datetime.timedelta(microseconds=574516), datetime.timedelta(microseconds=583478), datetime.timedelta(microseconds=596470), datetime.timedelta(microseconds=592488), datetime.timedelta(microseconds=584521), datetime.timedelta(microseconds=583526), datetime.timedelta(microseconds=672148), datetime.timedelta(microseconds=592491), datetime.timedelta(microseconds=611407)]
Phi time: [datetime.timedelta(microseconds=871659), datetime.timedelta(microseconds=862493), datetime.timedelta(microseconds=864729), datetime.timedelta(microseconds=853216), datetime.timedelta(microseconds=858572), datetime.timedelta(microseconds=855615), datetime.timedelta(microseconds=858879), datetime.timedelta(microseconds=854582), datetime.timedelta(microseconds=859326), datetime.timedelta(microseconds=864308)]
