Precision: [tensor(0.9231, device='cuda:0'), tensor(0.9227, device='cuda:0'), tensor(0.9232, device='cuda:0'), tensor(0.9194, device='cuda:0'), tensor(0.9218, device='cuda:0'), tensor(0.9212, device='cuda:0'), tensor(0.9239, device='cuda:0'), tensor(0.9248, device='cuda:0'), tensor(0.9236, device='cuda:0'), tensor(0.9188, device='cuda:0')]
Output distance: [tensor(1564.6503, device='cuda:0'), tensor(1563.8654, device='cuda:0'), tensor(1588.2527, device='cuda:0'), tensor(1673.9650, device='cuda:0'), tensor(1609.9526, device='cuda:0'), tensor(1631.8773, device='cuda:0'), tensor(1545.3595, device='cuda:0'), tensor(1527.4233, device='cuda:0'), tensor(1538.6545, device='cuda:0'), tensor(1676.4338, device='cuda:0')]
Prediction loss: [tensor(4082.1509, device='cuda:0'), tensor(3923.3955, device='cuda:0'), tensor(3987.5469, device='cuda:0'), tensor(3878.9067, device='cuda:0'), tensor(4009.0767, device='cuda:0'), tensor(3928.3320, device='cuda:0'), tensor(4009.2202, device='cuda:0'), tensor(3944.0874, device='cuda:0'), tensor(4089.9771, device='cuda:0'), tensor(3958.2046, 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': 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': 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')}]
Compressed training loss: [tensor(41093056., device='cuda:0'), tensor(39544356., device='cuda:0'), tensor(40043380., device='cuda:0'), tensor(38965648., device='cuda:0'), tensor(40446524., device='cuda:0'), tensor(39621008., device='cuda:0'), tensor(40348892., device='cuda:0'), tensor(39770780., device='cuda:0'), tensor(41166336., device='cuda:0'), tensor(39859480., device='cuda:0')]
Training loss: Not calculated
Prediction time: [datetime.timedelta(microseconds=684125), datetime.timedelta(microseconds=592510), datetime.timedelta(microseconds=693087), datetime.timedelta(microseconds=679146), datetime.timedelta(microseconds=594504), datetime.timedelta(microseconds=605454), datetime.timedelta(microseconds=681205), datetime.timedelta(microseconds=605460), datetime.timedelta(microseconds=595504), datetime.timedelta(microseconds=608450)]
Phi time: [datetime.timedelta(microseconds=873154), datetime.timedelta(microseconds=859982), datetime.timedelta(microseconds=860674), datetime.timedelta(microseconds=865297), datetime.timedelta(microseconds=860704), datetime.timedelta(microseconds=895190), datetime.timedelta(microseconds=870292), datetime.timedelta(microseconds=862375), datetime.timedelta(microseconds=859534), datetime.timedelta(microseconds=853299)]
