Precision: [tensor(0.9198, device='cuda:0'), tensor(0.9215, device='cuda:0'), tensor(0.9197, device='cuda:0'), tensor(0.9211, device='cuda:0'), tensor(0.9225, device='cuda:0'), tensor(0.9214, device='cuda:0'), tensor(0.9228, device='cuda:0'), tensor(0.9206, device='cuda:0'), tensor(0.9229, device='cuda:0'), tensor(0.9197, device='cuda:0')]
Output distance: [tensor(1624.0673, device='cuda:0'), tensor(1606.4526, device='cuda:0'), tensor(1638.9937, device='cuda:0'), tensor(1609.0876, device='cuda:0'), tensor(1584.7944, device='cuda:0'), tensor(1603.9111, device='cuda:0'), tensor(1564.8071, device='cuda:0'), tensor(1652.1881, device='cuda:0'), tensor(1577.0704, device='cuda:0'), tensor(1672.3215, device='cuda:0')]
Prediction loss: [tensor(3908.2322, device='cuda:0'), tensor(3931.3486, device='cuda:0'), tensor(3882.1492, device='cuda:0'), tensor(3940.6572, device='cuda:0'), tensor(3955.2566, device='cuda:0'), tensor(4000.5254, device='cuda:0'), tensor(3960.9199, device='cuda:0'), tensor(3902.8149, device='cuda:0'), tensor(4031.9734, device='cuda:0'), tensor(3996.2356, device='cuda:0')]
Others: [{'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': 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(39543524., device='cuda:0'), tensor(39777184., device='cuda:0'), tensor(39139828., device='cuda:0'), tensor(39870788., device='cuda:0'), tensor(39992512., device='cuda:0'), tensor(40439272., device='cuda:0'), tensor(40123272., device='cuda:0'), tensor(39413620., device='cuda:0'), tensor(40815732., device='cuda:0'), tensor(40458148., device='cuda:0')]
Training loss: Not calculated
Prediction time: [datetime.timedelta(microseconds=681083), datetime.timedelta(microseconds=675111), datetime.timedelta(microseconds=591514), datetime.timedelta(microseconds=597492), datetime.timedelta(microseconds=596495), datetime.timedelta(microseconds=579564), datetime.timedelta(microseconds=591514), datetime.timedelta(microseconds=592510), datetime.timedelta(microseconds=597490), datetime.timedelta(microseconds=576576)]
Phi time: [datetime.timedelta(microseconds=875171), datetime.timedelta(microseconds=857160), datetime.timedelta(microseconds=856640), datetime.timedelta(microseconds=881154), datetime.timedelta(microseconds=857223), datetime.timedelta(microseconds=854154), datetime.timedelta(microseconds=861701), datetime.timedelta(microseconds=863742), datetime.timedelta(microseconds=857981), datetime.timedelta(microseconds=863646)]
