Precision: [tensor(0.1344, device='cuda:0'), tensor(0.1350, device='cuda:0'), tensor(0.1332, device='cuda:0'), tensor(0.1339, device='cuda:0'), tensor(0.1333, device='cuda:0'), tensor(0.1339, device='cuda:0'), tensor(0.1353, device='cuda:0'), tensor(0.1338, device='cuda:0'), tensor(0.1366, device='cuda:0'), tensor(0.1339, device='cuda:0')]
Output distance: [tensor(19753430., device='cuda:0'), tensor(19755080., device='cuda:0'), tensor(19770670., device='cuda:0'), tensor(19742678., device='cuda:0'), tensor(19765844., device='cuda:0'), tensor(19771344., device='cuda:0'), tensor(19728274., device='cuda:0'), tensor(19756912., device='cuda:0'), tensor(19728952., device='cuda:0'), tensor(19735590., device='cuda:0')]
Prediction loss: [tensor(12114058., device='cuda:0'), tensor(12159317., device='cuda:0'), tensor(12173442., device='cuda:0'), tensor(12146923., device='cuda:0'), tensor(12165153., device='cuda:0'), tensor(12148965., device='cuda:0'), tensor(12161081., device='cuda:0'), tensor(12090241., device='cuda:0'), tensor(12146684., device='cuda:0'), tensor(12163410., device='cuda:0')]
Others: [{'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')}, {'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': 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': 9, 'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}]
Compressed training loss: [tensor(2.4724e+11, device='cuda:0'), tensor(2.4754e+11, device='cuda:0'), tensor(2.4754e+11, device='cuda:0'), tensor(2.4743e+11, device='cuda:0'), tensor(2.4728e+11, device='cuda:0'), tensor(2.4730e+11, device='cuda:0'), tensor(2.4715e+11, device='cuda:0'), tensor(2.4555e+11, device='cuda:0'), tensor(2.4690e+11, device='cuda:0'), tensor(2.4707e+11, device='cuda:0')]
Training loss: Not calculated
Prediction time: [datetime.timedelta(microseconds=595479), datetime.timedelta(microseconds=592438), datetime.timedelta(microseconds=678124), datetime.timedelta(microseconds=656164), datetime.timedelta(microseconds=673146), datetime.timedelta(microseconds=591487), datetime.timedelta(microseconds=664189), datetime.timedelta(microseconds=667170), datetime.timedelta(microseconds=680116), datetime.timedelta(microseconds=660200)]
Phi time: [datetime.timedelta(microseconds=864884), datetime.timedelta(microseconds=859486), datetime.timedelta(microseconds=861921), datetime.timedelta(microseconds=857869), datetime.timedelta(microseconds=859708), datetime.timedelta(microseconds=858902), datetime.timedelta(microseconds=865167), datetime.timedelta(microseconds=893581), datetime.timedelta(microseconds=860039), datetime.timedelta(microseconds=864766)]
