Precision: [tensor(0.9278, device='cuda:0'), tensor(0.9287, device='cuda:0'), tensor(0.9288, device='cuda:0'), tensor(0.9299, device='cuda:0'), tensor(0.9307, device='cuda:0'), tensor(0.9294, device='cuda:0'), tensor(0.9323, device='cuda:0'), tensor(0.9317, device='cuda:0'), tensor(0.9289, device='cuda:0'), tensor(0.9310, device='cuda:0')]
Output distance: [tensor(2645.7529, device='cuda:0'), tensor(2580.2505, device='cuda:0'), tensor(2591.0847, device='cuda:0'), tensor(2502.4844, device='cuda:0'), tensor(2532.2163, device='cuda:0'), tensor(2597.0769, device='cuda:0'), tensor(2461.5947, device='cuda:0'), tensor(2483.0332, device='cuda:0'), tensor(2604.6123, device='cuda:0'), tensor(2503.4736, device='cuda:0')]
Prediction loss: [tensor(6322.6938, device='cuda:0'), tensor(6506.5859, device='cuda:0'), tensor(6511.4917, device='cuda:0'), tensor(6533.4458, device='cuda:0'), tensor(6573.9219, device='cuda:0'), tensor(6469.1479, device='cuda:0'), tensor(6560.7104, device='cuda:0'), tensor(6574.3579, device='cuda:0'), tensor(6781.3921, device='cuda:0'), tensor(6370.5879, 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': 9, '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': 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')}]
Compressed training loss: [tensor(62544880., device='cuda:0'), tensor(64438920., device='cuda:0'), tensor(64405656., device='cuda:0'), tensor(64428112., device='cuda:0'), tensor(64991600., device='cuda:0'), tensor(63793520., device='cuda:0'), tensor(64634368., device='cuda:0'), tensor(64884796., device='cuda:0'), tensor(67141768., device='cuda:0'), tensor(62816872., device='cuda:0')]
Training loss: Not calculated
Prediction time: [datetime.timedelta(microseconds=658208), datetime.timedelta(microseconds=580542), datetime.timedelta(microseconds=572573), datetime.timedelta(microseconds=587502), datetime.timedelta(microseconds=667171), datetime.timedelta(microseconds=657213), datetime.timedelta(microseconds=650242), datetime.timedelta(microseconds=599455), datetime.timedelta(microseconds=670157), datetime.timedelta(microseconds=577544)]
Phi time: [datetime.timedelta(microseconds=905012), datetime.timedelta(microseconds=857859), datetime.timedelta(microseconds=870356), datetime.timedelta(microseconds=859806), datetime.timedelta(microseconds=856675), datetime.timedelta(microseconds=862043), datetime.timedelta(microseconds=857798), datetime.timedelta(microseconds=865116), datetime.timedelta(microseconds=858544), datetime.timedelta(microseconds=859669)]
