Precision: [tensor(0.9339, device='cuda:0'), tensor(0.9356, device='cuda:0'), tensor(0.9329, device='cuda:0'), tensor(0.9304, device='cuda:0'), tensor(0.9313, device='cuda:0'), tensor(0.9309, device='cuda:0'), tensor(0.9316, device='cuda:0'), tensor(0.9348, device='cuda:0'), tensor(0.9331, device='cuda:0'), tensor(0.9311, device='cuda:0')]
Output distance: [tensor(2422.1907, device='cuda:0'), tensor(2387.7539, device='cuda:0'), tensor(2434.8364, device='cuda:0'), tensor(2571.2214, device='cuda:0'), tensor(2504.5696, device='cuda:0'), tensor(2593.0461, device='cuda:0'), tensor(2520.7444, device='cuda:0'), tensor(2406.2827, device='cuda:0'), tensor(2446.0027, device='cuda:0'), tensor(2544.2944, device='cuda:0')]
Prediction loss: [tensor(6743.0679, device='cuda:0'), tensor(6510.0571, device='cuda:0'), tensor(6620.5068, device='cuda:0'), tensor(6750.8706, device='cuda:0'), tensor(6458.3452, device='cuda:0'), tensor(6591.3159, device='cuda:0'), tensor(6416.9722, device='cuda:0'), tensor(6618.4658, device='cuda:0'), tensor(6539.7432, device='cuda:0'), tensor(6567.6187, device='cuda:0')]
Others: [{'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')}, {'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(65933780., device='cuda:0'), tensor(63633480., device='cuda:0'), tensor(64858612., device='cuda:0'), tensor(66427576., device='cuda:0'), tensor(63392388., device='cuda:0'), tensor(64920688., device='cuda:0'), tensor(62905996., device='cuda:0'), tensor(64893252., device='cuda:0'), tensor(64175168., device='cuda:0'), tensor(64387344., device='cuda:0')]
Training loss: Not calculated
Prediction time: [datetime.timedelta(microseconds=706055), datetime.timedelta(microseconds=601448), datetime.timedelta(microseconds=602399), datetime.timedelta(microseconds=647254), datetime.timedelta(microseconds=605432), datetime.timedelta(microseconds=599455), datetime.timedelta(microseconds=604436), datetime.timedelta(microseconds=597465), datetime.timedelta(microseconds=595474), datetime.timedelta(microseconds=598462)]
Phi time: [datetime.timedelta(microseconds=894740), datetime.timedelta(microseconds=868655), datetime.timedelta(microseconds=865718), datetime.timedelta(microseconds=898415), datetime.timedelta(microseconds=862749), datetime.timedelta(microseconds=860669), datetime.timedelta(microseconds=858732), datetime.timedelta(microseconds=862704), datetime.timedelta(microseconds=872990), datetime.timedelta(microseconds=861750)]
