Precision: [tensor(0.9982, device='cuda:0'), tensor(0.9987, device='cuda:0'), tensor(0.9985, device='cuda:0'), tensor(0.9987, device='cuda:0'), tensor(0.9983, device='cuda:0'), tensor(0.9982, device='cuda:0'), tensor(0.9985, device='cuda:0'), tensor(0.9983, device='cuda:0'), tensor(0.9985, device='cuda:0'), tensor(0.9987, device='cuda:0')]
Output distance: [tensor(19223.0938, device='cuda:0'), tensor(19214.2539, device='cuda:0'), tensor(19276.1445, device='cuda:0'), tensor(19237.9629, device='cuda:0'), tensor(19211.2754, device='cuda:0'), tensor(19263.2500, device='cuda:0'), tensor(19296.4375, device='cuda:0'), tensor(19208.9551, device='cuda:0'), tensor(19261.6914, device='cuda:0'), tensor(19223.5312, device='cuda:0')]
Prediction loss: [tensor(19418.5957, device='cuda:0'), tensor(19314.9121, device='cuda:0'), tensor(19384.3887, device='cuda:0'), tensor(20631.9219, device='cuda:0'), tensor(20585.3301, device='cuda:0'), tensor(20107.9375, device='cuda:0'), tensor(19939.0449, device='cuda:0'), tensor(20443.0938, device='cuda:0'), tensor(20872.1250, device='cuda:0'), tensor(19294.0078, device='cuda:0')]
Others: [{'iter_num': 7, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}]
Compressed training loss: [tensor(19118962., device='cuda:0'), tensor(19156916., device='cuda:0'), tensor(19635618., device='cuda:0'), tensor(20166914., device='cuda:0'), tensor(19801930., device='cuda:0'), tensor(19915714., device='cuda:0'), tensor(19850406., device='cuda:0'), tensor(19705246., device='cuda:0'), tensor(19618178., device='cuda:0'), tensor(18696588., device='cuda:0')]
Training loss: Not calculated
Prediction time: [datetime.timedelta(microseconds=576554), datetime.timedelta(microseconds=588504), datetime.timedelta(microseconds=484942), datetime.timedelta(microseconds=524775), datetime.timedelta(microseconds=525784), datetime.timedelta(microseconds=523775), datetime.timedelta(microseconds=520790), datetime.timedelta(microseconds=516808), datetime.timedelta(microseconds=630327), datetime.timedelta(microseconds=576558)]
Phi time: [datetime.timedelta(microseconds=904698), datetime.timedelta(microseconds=864002), datetime.timedelta(microseconds=864334), datetime.timedelta(microseconds=882506), datetime.timedelta(microseconds=881836), datetime.timedelta(microseconds=890400), datetime.timedelta(microseconds=905484), datetime.timedelta(microseconds=886200), datetime.timedelta(microseconds=877561), datetime.timedelta(microseconds=869198)]
