Precision: [tensor(0.5566, device='cuda:0'), tensor(0.5521, device='cuda:0'), tensor(0.5533, device='cuda:0'), tensor(0.5527, device='cuda:0'), tensor(0.5559, device='cuda:0'), tensor(0.5512, device='cuda:0'), tensor(0.5502, device='cuda:0'), tensor(0.5549, device='cuda:0'), tensor(0.5538, device='cuda:0'), tensor(0.5518, device='cuda:0')]
Output distance: [tensor(812799.5000, device='cuda:0'), tensor(1099825., device='cuda:0'), tensor(929584.5625, device='cuda:0'), tensor(866831., device='cuda:0'), tensor(960745.9375, device='cuda:0'), tensor(974916.5000, device='cuda:0'), tensor(1036234.7500, device='cuda:0'), tensor(1397755.3750, device='cuda:0'), tensor(854323.4375, device='cuda:0'), tensor(1220842.3750, device='cuda:0')]
Prediction loss: [tensor(18303708., device='cuda:0'), tensor(17172286., device='cuda:0'), tensor(17450144., device='cuda:0'), tensor(18772996., device='cuda:0'), tensor(17896100., device='cuda:0'), tensor(17282680., device='cuda:0'), tensor(18423560., device='cuda:0'), tensor(17883426., device='cuda:0'), tensor(18282402., device='cuda:0'), tensor(17522158., device='cuda:0')]
Others: [{'iter_num': 7, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}]
Compressed training loss: [tensor(41001.7188, device='cuda:0'), tensor(40865.7383, device='cuda:0'), tensor(40849.9648, device='cuda:0'), tensor(40833.9453, device='cuda:0'), tensor(40921.9766, device='cuda:0'), tensor(40858.0273, device='cuda:0'), tensor(40954.1953, device='cuda:0'), tensor(40918.2461, device='cuda:0'), tensor(40841.3828, device='cuda:0'), tensor(40885.0625, device='cuda:0')]
Training loss: 0
Prediction time: [datetime.timedelta(microseconds=119490), datetime.timedelta(microseconds=122478), datetime.timedelta(microseconds=127457), datetime.timedelta(microseconds=111525), datetime.timedelta(microseconds=112520), datetime.timedelta(microseconds=112520), datetime.timedelta(microseconds=129449), datetime.timedelta(microseconds=112519), datetime.timedelta(microseconds=123474), datetime.timedelta(microseconds=119492)]
Phi time: [datetime.timedelta(microseconds=237993), datetime.timedelta(microseconds=247951), datetime.timedelta(microseconds=240981), datetime.timedelta(microseconds=239985), datetime.timedelta(microseconds=235006), datetime.timedelta(microseconds=237994), datetime.timedelta(microseconds=236998), datetime.timedelta(microseconds=238990), datetime.timedelta(microseconds=239986), datetime.timedelta(microseconds=237993)]
