Precision: [tensor(0.9126, device='cuda:0'), tensor(0.9137, device='cuda:0'), tensor(0.9145, device='cuda:0'), tensor(0.9130, device='cuda:0'), tensor(0.9142, device='cuda:0'), tensor(0.9114, device='cuda:0'), tensor(0.9122, device='cuda:0'), tensor(0.9133, device='cuda:0'), tensor(0.9128, device='cuda:0'), tensor(0.9135, device='cuda:0')]

Output distance: [tensor(564.3170, device='cuda:0'), tensor(560.1177, device='cuda:0'), tensor(546.9835, device='cuda:0'), tensor(559.4091, device='cuda:0'), tensor(552.7242, device='cuda:0'), tensor(562.8277, device='cuda:0'), tensor(566.1424, device='cuda:0'), tensor(557.7057, device='cuda:0'), tensor(560.8100, device='cuda:0'), tensor(558.4559, device='cuda:0')]

Prediction loss: [tensor(639.3405, device='cuda:0'), tensor(632.1683, device='cuda:0'), tensor(649.8630, device='cuda:0'), tensor(644.4431, device='cuda:0'), tensor(646.7222, device='cuda:0'), tensor(654.1914, device='cuda:0'), tensor(674.7113, device='cuda:0'), tensor(640.2701, device='cuda:0'), tensor(616.0264, device='cuda:0'), tensor(619.2504, device='cuda:0')]

Others: [{'num_positive': tensor(16622, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16613, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16639, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16606, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16616, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16623, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16588, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16636, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16643, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16615, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}]

Compressed training loss: [tensor(8855207., device='cuda:0'), tensor(8812971., device='cuda:0'), tensor(9039500., device='cuda:0'), tensor(8970720., device='cuda:0'), tensor(9009421., device='cuda:0'), tensor(9105874., device='cuda:0'), tensor(9325064., device='cuda:0'), tensor(8916954., device='cuda:0'), tensor(8655177., device='cuda:0'), tensor(8704072., device='cuda:0')]

Training loss: 8847222.0

Prediction time: [datetime.timedelta(seconds=94, microseconds=484135), datetime.timedelta(seconds=94, microseconds=628112), datetime.timedelta(seconds=94, microseconds=488218), datetime.timedelta(seconds=94, microseconds=527298), datetime.timedelta(seconds=93, microseconds=804152), datetime.timedelta(seconds=94, microseconds=425553), datetime.timedelta(seconds=92, microseconds=552048), datetime.timedelta(seconds=94, microseconds=186603), datetime.timedelta(seconds=94, microseconds=725394), datetime.timedelta(seconds=94, microseconds=2971)]

Phi time: [datetime.timedelta(seconds=1, microseconds=294356), datetime.timedelta(microseconds=700857), datetime.timedelta(microseconds=716920), datetime.timedelta(microseconds=727456), datetime.timedelta(microseconds=714348), datetime.timedelta(microseconds=708463), datetime.timedelta(microseconds=692956), datetime.timedelta(microseconds=700905), datetime.timedelta(microseconds=726804), datetime.timedelta(microseconds=719491)]

