Precision: [tensor(0.5538, device='cuda:0'), tensor(0.5529, device='cuda:0'), tensor(0.5547, device='cuda:0'), tensor(0.5541, device='cuda:0'), tensor(0.5548, device='cuda:0'), tensor(0.5551, device='cuda:0'), tensor(0.5565, device='cuda:0'), tensor(0.5569, device='cuda:0'), tensor(0.5542, device='cuda:0'), tensor(0.5547, device='cuda:0')]
Output distance: [tensor(1352180.7500, device='cuda:0'), tensor(980121., device='cuda:0'), tensor(979763., device='cuda:0'), tensor(866416.3125, device='cuda:0'), tensor(931371.4375, device='cuda:0'), tensor(1350430., device='cuda:0'), tensor(1318530.3750, device='cuda:0'), tensor(1137910.7500, device='cuda:0'), tensor(877464.9375, device='cuda:0'), tensor(1287951., device='cuda:0')]
Prediction loss: [tensor(17195434., device='cuda:0'), tensor(19095914., device='cuda:0'), tensor(19014086., device='cuda:0'), tensor(16331890., device='cuda:0'), tensor(17204754., device='cuda:0'), tensor(17824140., device='cuda:0'), tensor(19518500., device='cuda:0'), tensor(17626656., device='cuda:0'), tensor(16643425., device='cuda:0'), tensor(17501892., 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': 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': 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(40793.2852, device='cuda:0'), tensor(40985.7305, device='cuda:0'), tensor(40876.1523, device='cuda:0'), tensor(40809.5312, device='cuda:0'), tensor(40703.1875, device='cuda:0'), tensor(40844.1523, device='cuda:0'), tensor(40883.1172, device='cuda:0'), tensor(41002.9453, device='cuda:0'), tensor(40708.8555, device='cuda:0'), tensor(40705.3047, device='cuda:0')]
Training loss: 0
Prediction time: [datetime.timedelta(microseconds=123474), datetime.timedelta(microseconds=122477), datetime.timedelta(microseconds=111524), datetime.timedelta(microseconds=125465), datetime.timedelta(microseconds=113516), datetime.timedelta(microseconds=124470), datetime.timedelta(microseconds=124469), datetime.timedelta(microseconds=110528), datetime.timedelta(microseconds=124469), datetime.timedelta(microseconds=113516)]
Phi time: [datetime.timedelta(microseconds=238989), datetime.timedelta(microseconds=240981), datetime.timedelta(microseconds=236998), datetime.timedelta(microseconds=237994), datetime.timedelta(microseconds=236001), datetime.timedelta(microseconds=236997), datetime.timedelta(microseconds=237994), datetime.timedelta(microseconds=236002), datetime.timedelta(microseconds=238989), datetime.timedelta(microseconds=237993)]
