Precision: [tensor(1., device='cuda:0'), tensor(1., device='cuda:0'), tensor(1., device='cuda:0'), tensor(1., device='cuda:0'), tensor(1., device='cuda:0'), tensor(1., device='cuda:0'), tensor(1., device='cuda:0'), tensor(1., device='cuda:0'), tensor(1., device='cuda:0'), tensor(1., device='cuda:0')]

Output distance: [tensor(38756.4570, device='cuda:0'), tensor(38803.0156, device='cuda:0'), tensor(38972.2305, device='cuda:0'), tensor(38789.7070, device='cuda:0'), tensor(38908.1328, device='cuda:0'), tensor(38616.5664, device='cuda:0'), tensor(38727.8477, device='cuda:0'), tensor(38810.2070, device='cuda:0'), tensor(38787.8867, device='cuda:0'), tensor(39331.2031, device='cuda:0')]

Prediction loss: [tensor(40852.4297, device='cuda:0'), tensor(37650.2539, device='cuda:0'), tensor(38902.5234, device='cuda:0'), tensor(38094.8008, device='cuda:0'), tensor(36079.0586, device='cuda:0'), tensor(38224.7734, device='cuda:0'), tensor(38216.9961, device='cuda:0'), tensor(38328.9297, device='cuda:0'), tensor(40317.7539, device='cuda:0'), tensor(37906.4297, device='cuda:0')]

Others: [{'iter_num': 9, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 13, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}]

Compressed training loss: [tensor(3738490.2500, device='cuda:0'), tensor(3482064., device='cuda:0'), tensor(3605343.7500, device='cuda:0'), tensor(3544456.2500, device='cuda:0'), tensor(3426152.2500, device='cuda:0'), tensor(3575511.7500, device='cuda:0'), tensor(3603201.5000, device='cuda:0'), tensor(3615726., device='cuda:0'), tensor(3678619., device='cuda:0'), tensor(3516304.7500, device='cuda:0')]

Training loss: 3612970.25

Prediction time: [datetime.timedelta(microseconds=649248), datetime.timedelta(microseconds=734882), datetime.timedelta(microseconds=727913), datetime.timedelta(microseconds=742851), datetime.timedelta(microseconds=803642), datetime.timedelta(microseconds=663187), datetime.timedelta(microseconds=705009), datetime.timedelta(microseconds=722987), datetime.timedelta(microseconds=648254), datetime.timedelta(microseconds=729904)]

Phi time: [datetime.timedelta(seconds=1, microseconds=417079), datetime.timedelta(microseconds=906683), datetime.timedelta(microseconds=872978), datetime.timedelta(microseconds=852684), datetime.timedelta(microseconds=852793), datetime.timedelta(microseconds=868511), datetime.timedelta(microseconds=854188), datetime.timedelta(microseconds=858492), datetime.timedelta(microseconds=861031), datetime.timedelta(microseconds=852455)]

