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(39519.1133, device='cuda:0'), tensor(38649.3789, device='cuda:0'), tensor(38124.6484, device='cuda:0'), tensor(40354.3945, device='cuda:0'), tensor(38502.4805, device='cuda:0'), tensor(38212.2148, device='cuda:0'), tensor(38084.9531, device='cuda:0'), tensor(38461.6523, device='cuda:0'), tensor(38539.8438, device='cuda:0'), tensor(38786.4492, device='cuda:0')]

Prediction loss: [tensor(41911.8164, device='cuda:0'), tensor(36323.0547, device='cuda:0'), tensor(38190.0742, device='cuda:0'), tensor(35225.0430, device='cuda:0'), tensor(39816.9258, device='cuda:0'), tensor(39446.9609, device='cuda:0'), tensor(40756.4141, device='cuda:0'), tensor(36065.1055, device='cuda:0'), tensor(35704.6133, device='cuda:0'), tensor(40650.4492, device='cuda:0')]

Others: [{'iter_num': 13, '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': 13, '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': 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')}]

Compressed training loss: [tensor(3856179.7500, device='cuda:0'), tensor(3649638.5000, device='cuda:0'), tensor(3629368.7500, device='cuda:0'), tensor(3443723., device='cuda:0'), tensor(3931603.5000, device='cuda:0'), tensor(3788773.5000, device='cuda:0'), tensor(3965660., device='cuda:0'), tensor(3479928.5000, device='cuda:0'), tensor(3594310.5000, device='cuda:0'), tensor(3887949.2500, device='cuda:0')]

Training loss: 3605798.5

Prediction time: [datetime.timedelta(microseconds=598483), datetime.timedelta(microseconds=642296), datetime.timedelta(microseconds=528774), datetime.timedelta(microseconds=628354), datetime.timedelta(microseconds=578562), datetime.timedelta(microseconds=533755), datetime.timedelta(microseconds=529781), datetime.timedelta(microseconds=569601), datetime.timedelta(microseconds=580554), datetime.timedelta(microseconds=580558)]

Phi time: [datetime.timedelta(seconds=1, microseconds=219281), datetime.timedelta(microseconds=725915), datetime.timedelta(microseconds=654794), datetime.timedelta(microseconds=651787), datetime.timedelta(microseconds=650438), datetime.timedelta(microseconds=649894), datetime.timedelta(microseconds=657078), datetime.timedelta(microseconds=652469), datetime.timedelta(microseconds=655233), datetime.timedelta(microseconds=650924)]

