Precision: [tensor(0.8766, device='cuda:0'), tensor(0.8796, device='cuda:0'), tensor(0.8797, device='cuda:0'), tensor(0.8777, device='cuda:0'), tensor(0.8812, device='cuda:0'), tensor(0.8786, device='cuda:0'), tensor(0.8792, device='cuda:0'), tensor(0.8776, device='cuda:0'), tensor(0.8741, device='cuda:0'), tensor(0.8783, device='cuda:0')]
Output distance: [tensor(1021.8600, device='cuda:0'), tensor(991.8508, device='cuda:0'), tensor(994.8859, device='cuda:0'), tensor(1000.4976, device='cuda:0'), tensor(972.3760, device='cuda:0'), tensor(1004.6770, device='cuda:0'), tensor(999.5430, device='cuda:0'), tensor(1005.7051, device='cuda:0'), tensor(1036.3040, device='cuda:0'), tensor(1006.6500, device='cuda:0')]
Prediction loss: [tensor(1744.6931, device='cuda:0'), tensor(1783.9955, device='cuda:0'), tensor(1790.9596, device='cuda:0'), tensor(1719.0430, device='cuda:0'), tensor(1736.9589, device='cuda:0'), tensor(1760.5476, device='cuda:0'), tensor(1751.1689, device='cuda:0'), tensor(1738.2454, device='cuda:0'), tensor(1733.6112, device='cuda:0'), tensor(1779.9823, 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': 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': 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')}]
Compressed training loss: [tensor(19607586., device='cuda:0'), tensor(19893090., device='cuda:0'), tensor(20019406., device='cuda:0'), tensor(19130684., device='cuda:0'), tensor(19333188., device='cuda:0'), tensor(19650290., device='cuda:0'), tensor(19580228., device='cuda:0'), tensor(19468222., device='cuda:0'), tensor(19414522., device='cuda:0'), tensor(19880914., device='cuda:0')]
Training loss: Not calculated
Prediction time: [datetime.timedelta(microseconds=608420), datetime.timedelta(microseconds=580537), datetime.timedelta(microseconds=603443), datetime.timedelta(microseconds=589500), datetime.timedelta(microseconds=588505), datetime.timedelta(microseconds=574563), datetime.timedelta(microseconds=581480), datetime.timedelta(microseconds=578547), datetime.timedelta(microseconds=577551), datetime.timedelta(microseconds=582482)]
Phi time: [datetime.timedelta(microseconds=890276), datetime.timedelta(microseconds=864380), datetime.timedelta(microseconds=864314), datetime.timedelta(microseconds=864154), datetime.timedelta(microseconds=863894), datetime.timedelta(microseconds=866133), datetime.timedelta(microseconds=863290), datetime.timedelta(microseconds=862194), datetime.timedelta(microseconds=869745), datetime.timedelta(microseconds=869313)]
