Precision: [tensor(0.9341, device='cuda:0'), tensor(0.9279, device='cuda:0'), tensor(0.9309, device='cuda:0'), tensor(0.9318, device='cuda:0'), tensor(0.9299, device='cuda:0'), tensor(0.9296, device='cuda:0'), tensor(0.9323, device='cuda:0'), tensor(0.9308, device='cuda:0'), tensor(0.9315, device='cuda:0'), tensor(0.9319, device='cuda:0')]
Output distance: [tensor(2399.7720, device='cuda:0'), tensor(2755.5952, device='cuda:0'), tensor(2558.3799, device='cuda:0'), tensor(2553.9233, device='cuda:0'), tensor(2607.2893, device='cuda:0'), tensor(2654.6882, device='cuda:0'), tensor(2466.0554, device='cuda:0'), tensor(2619.7690, device='cuda:0'), tensor(2527.9568, device='cuda:0'), tensor(2592.0415, device='cuda:0')]
Prediction loss: [tensor(6458.1040, device='cuda:0'), tensor(6406.4678, device='cuda:0'), tensor(6484.1694, device='cuda:0'), tensor(6443.7080, device='cuda:0'), tensor(6712.0107, device='cuda:0'), tensor(6595.9585, device='cuda:0'), tensor(6603.6030, device='cuda:0'), tensor(6475.8833, device='cuda:0'), tensor(6547.6187, device='cuda:0'), tensor(6526.1504, 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': 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': 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(64101924., device='cuda:0'), tensor(63725708., device='cuda:0'), tensor(64444268., device='cuda:0'), tensor(64036804., device='cuda:0'), tensor(66653744., device='cuda:0'), tensor(65427112., device='cuda:0'), tensor(65562636., device='cuda:0'), tensor(64565064., device='cuda:0'), tensor(65227872., device='cuda:0'), tensor(64962032., device='cuda:0')]
Training loss: Not calculated
Prediction time: [datetime.timedelta(microseconds=575562), datetime.timedelta(microseconds=585515), datetime.timedelta(microseconds=574563), datetime.timedelta(microseconds=658147), datetime.timedelta(microseconds=585518), datetime.timedelta(microseconds=602446), datetime.timedelta(microseconds=580629), datetime.timedelta(microseconds=591441), datetime.timedelta(microseconds=662191), datetime.timedelta(microseconds=583526)]
Phi time: [datetime.timedelta(microseconds=884882), datetime.timedelta(microseconds=861063), datetime.timedelta(microseconds=876315), datetime.timedelta(microseconds=862449), datetime.timedelta(microseconds=858121), datetime.timedelta(microseconds=865169), datetime.timedelta(microseconds=865756), datetime.timedelta(microseconds=898343), datetime.timedelta(microseconds=858587), datetime.timedelta(microseconds=860134)]
