Precision: [tensor(0.1395, device='cuda:0'), tensor(0.1396, device='cuda:0'), tensor(0.1406, device='cuda:0'), tensor(0.1410, device='cuda:0'), tensor(0.1388, device='cuda:0'), tensor(0.1384, device='cuda:0'), tensor(0.1394, device='cuda:0'), tensor(0.1410, device='cuda:0'), tensor(0.1385, device='cuda:0'), tensor(0.1383, device='cuda:0')]
Output distance: [tensor(19722164., device='cuda:0'), tensor(19745484., device='cuda:0'), tensor(19724132., device='cuda:0'), tensor(19707932., device='cuda:0'), tensor(19763940., device='cuda:0'), tensor(19728934., device='cuda:0'), tensor(19746916., device='cuda:0'), tensor(19723766., device='cuda:0'), tensor(19741138., device='cuda:0'), tensor(19769690., device='cuda:0')]
Prediction loss: [tensor(12121882., device='cuda:0'), tensor(12226842., device='cuda:0'), tensor(12258630., device='cuda:0'), tensor(12173380., device='cuda:0'), tensor(12232148., device='cuda:0'), tensor(12155482., device='cuda:0'), tensor(12160943., device='cuda:0'), tensor(12220354., device='cuda:0'), tensor(12192652., device='cuda:0'), tensor(12241550., device='cuda:0')]
Others: [{'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')}, {'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')}]
Compressed training loss: [tensor(2.4591e+11, device='cuda:0'), tensor(2.4880e+11, device='cuda:0'), tensor(2.4858e+11, device='cuda:0'), tensor(2.4694e+11, device='cuda:0'), tensor(2.4853e+11, device='cuda:0'), tensor(2.4660e+11, device='cuda:0'), tensor(2.4722e+11, device='cuda:0'), tensor(2.4806e+11, device='cuda:0'), tensor(2.4781e+11, device='cuda:0'), tensor(2.4851e+11, device='cuda:0')]
Training loss: Not calculated
Prediction time: [datetime.timedelta(microseconds=678177), datetime.timedelta(microseconds=660200), datetime.timedelta(microseconds=663182), datetime.timedelta(microseconds=674137), datetime.timedelta(microseconds=665179), datetime.timedelta(microseconds=664183), datetime.timedelta(microseconds=591492), datetime.timedelta(microseconds=679120), datetime.timedelta(microseconds=667171), datetime.timedelta(microseconds=663188)]
Phi time: [datetime.timedelta(microseconds=869273), datetime.timedelta(microseconds=855676), datetime.timedelta(microseconds=857049), datetime.timedelta(microseconds=865650), datetime.timedelta(microseconds=863332), datetime.timedelta(microseconds=865672), datetime.timedelta(microseconds=862153), datetime.timedelta(microseconds=869145), datetime.timedelta(microseconds=856783), datetime.timedelta(microseconds=859319)]
