Precision: [tensor(0.1340, device='cuda:0'), tensor(0.1348, device='cuda:0'), tensor(0.1363, device='cuda:0'), tensor(0.1366, device='cuda:0'), tensor(0.1350, device='cuda:0'), tensor(0.1353, device='cuda:0'), tensor(0.1354, device='cuda:0'), tensor(0.1355, device='cuda:0'), tensor(0.1354, device='cuda:0'), tensor(0.1372, device='cuda:0')]
Output distance: [tensor(20003450., device='cuda:0'), tensor(19997394., device='cuda:0'), tensor(19974502., device='cuda:0'), tensor(19959366., device='cuda:0'), tensor(20001190., device='cuda:0'), tensor(19990044., device='cuda:0'), tensor(19966716., device='cuda:0'), tensor(19992776., device='cuda:0'), tensor(19964980., device='cuda:0'), tensor(19971758., device='cuda:0')]
Prediction loss: [tensor(12326629., device='cuda:0'), tensor(12327681., device='cuda:0'), tensor(12288594., device='cuda:0'), tensor(12385720., device='cuda:0'), tensor(12337904., device='cuda:0'), tensor(12333225., device='cuda:0'), tensor(12361478., device='cuda:0'), tensor(12383531., device='cuda:0'), tensor(12308831., device='cuda:0'), tensor(12312316., 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': 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': 9, 'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}]
Compressed training loss: [tensor(2.4985e+11, device='cuda:0'), tensor(2.4961e+11, device='cuda:0'), tensor(2.4889e+11, device='cuda:0'), tensor(2.5116e+11, device='cuda:0'), tensor(2.5014e+11, device='cuda:0'), tensor(2.5032e+11, device='cuda:0'), tensor(2.5101e+11, device='cuda:0'), tensor(2.5098e+11, device='cuda:0'), tensor(2.4954e+11, device='cuda:0'), tensor(2.4951e+11, device='cuda:0')]
Training loss: Not calculated
Prediction time: [datetime.timedelta(microseconds=691040), datetime.timedelta(microseconds=600474), datetime.timedelta(microseconds=689105), datetime.timedelta(microseconds=676156), datetime.timedelta(microseconds=685120), datetime.timedelta(microseconds=600476), datetime.timedelta(microseconds=614471), datetime.timedelta(microseconds=597542), datetime.timedelta(microseconds=602469), datetime.timedelta(microseconds=695131)]
Phi time: [datetime.timedelta(microseconds=864643), datetime.timedelta(microseconds=863903), datetime.timedelta(microseconds=861321), datetime.timedelta(microseconds=862105), datetime.timedelta(microseconds=875777), datetime.timedelta(microseconds=864058), datetime.timedelta(microseconds=896654), datetime.timedelta(microseconds=859122), datetime.timedelta(microseconds=857377), datetime.timedelta(microseconds=861173)]
