Precision: [tensor(0.9232, device='cuda:0'), tensor(0.9209, device='cuda:0'), tensor(0.9185, device='cuda:0'), tensor(0.9226, device='cuda:0'), tensor(0.9198, device='cuda:0'), tensor(0.9214, device='cuda:0'), tensor(0.9231, device='cuda:0'), tensor(0.9218, device='cuda:0'), tensor(0.9231, device='cuda:0'), tensor(0.9223, device='cuda:0')]
Output distance: [tensor(1640.7710, device='cuda:0'), tensor(1739.1849, device='cuda:0'), tensor(1780.7153, device='cuda:0'), tensor(1660.6873, device='cuda:0'), tensor(1697.8533, device='cuda:0'), tensor(1684.1145, device='cuda:0'), tensor(1674.7506, device='cuda:0'), tensor(1675.7372, device='cuda:0'), tensor(1669.9503, device='cuda:0'), tensor(1637.6980, device='cuda:0')]
Prediction loss: [tensor(4073.0127, device='cuda:0'), tensor(4008.8779, device='cuda:0'), tensor(4011.7185, device='cuda:0'), tensor(3956.3423, device='cuda:0'), tensor(4012.6890, device='cuda:0'), tensor(4087.6445, device='cuda:0'), tensor(4077.0327, device='cuda:0'), tensor(4110.8677, device='cuda:0'), tensor(4006.4470, device='cuda:0'), tensor(3966.0903, device='cuda:0')]
Others: [{'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': 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')}, {'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')}]
Compressed training loss: [tensor(40361076., device='cuda:0'), tensor(40000268., device='cuda:0'), tensor(39881804., device='cuda:0'), tensor(39169512., device='cuda:0'), tensor(39891708., device='cuda:0'), tensor(40577664., device='cuda:0'), tensor(40434740., device='cuda:0'), tensor(40906556., device='cuda:0'), tensor(39615104., device='cuda:0'), tensor(39290776., device='cuda:0')]
Training loss: Not calculated
Prediction time: [datetime.timedelta(microseconds=584599), datetime.timedelta(microseconds=670206), datetime.timedelta(microseconds=582555), datetime.timedelta(microseconds=673171), datetime.timedelta(microseconds=595494), datetime.timedelta(microseconds=585541), datetime.timedelta(microseconds=597490), datetime.timedelta(microseconds=590522), datetime.timedelta(microseconds=583469), datetime.timedelta(microseconds=581553)]
Phi time: [datetime.timedelta(microseconds=859802), datetime.timedelta(microseconds=862392), datetime.timedelta(microseconds=861845), datetime.timedelta(microseconds=856168), datetime.timedelta(microseconds=858377), datetime.timedelta(microseconds=862551), datetime.timedelta(microseconds=861143), datetime.timedelta(microseconds=860005), datetime.timedelta(microseconds=864751), datetime.timedelta(microseconds=865338)]
