Precision: [tensor(0.5540, device='cuda:0'), tensor(0.5537, device='cuda:0'), tensor(0.5558, device='cuda:0'), tensor(0.5554, device='cuda:0'), tensor(0.5501, device='cuda:0'), tensor(0.5565, device='cuda:0'), tensor(0.5561, device='cuda:0'), tensor(0.5550, device='cuda:0'), tensor(0.5560, device='cuda:0'), tensor(0.5526, device='cuda:0')]
Output distance: [tensor(876623.1250, device='cuda:0'), tensor(930352.5000, device='cuda:0'), tensor(1097667.6250, device='cuda:0'), tensor(1549543.6250, device='cuda:0'), tensor(829897.5625, device='cuda:0'), tensor(923333.3125, device='cuda:0'), tensor(882163.9375, device='cuda:0'), tensor(1234504.5000, device='cuda:0'), tensor(1055457.7500, device='cuda:0'), tensor(944198.3750, device='cuda:0')]
Prediction loss: [tensor(17080760., device='cuda:0'), tensor(19255394., device='cuda:0'), tensor(18154968., device='cuda:0'), tensor(17151804., device='cuda:0'), tensor(18497864., device='cuda:0'), tensor(18818010., device='cuda:0'), tensor(18025066., device='cuda:0'), tensor(18919554., device='cuda:0'), tensor(18213874., device='cuda:0'), tensor(17665008., 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': 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': 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')}]
Compressed training loss: [tensor(40987.4609, device='cuda:0'), tensor(40841.3594, device='cuda:0'), tensor(40902.0391, device='cuda:0'), tensor(40835.0117, device='cuda:0'), tensor(41004.0234, device='cuda:0'), tensor(40841.5430, device='cuda:0'), tensor(40698.6250, device='cuda:0'), tensor(40759.8750, device='cuda:0'), tensor(40850.4219, device='cuda:0'), tensor(40966.0156, device='cuda:0')]
Training loss: 0
Prediction time: [datetime.timedelta(microseconds=126460), datetime.timedelta(microseconds=131446), datetime.timedelta(microseconds=124470), datetime.timedelta(microseconds=110529), datetime.timedelta(microseconds=112520), datetime.timedelta(microseconds=127457), datetime.timedelta(microseconds=127456), datetime.timedelta(microseconds=127457), datetime.timedelta(microseconds=129448), datetime.timedelta(microseconds=126461)]
Phi time: [datetime.timedelta(microseconds=240980), datetime.timedelta(microseconds=241977), datetime.timedelta(microseconds=236001), datetime.timedelta(microseconds=236002), datetime.timedelta(microseconds=236003), datetime.timedelta(microseconds=239985), datetime.timedelta(microseconds=237994), datetime.timedelta(microseconds=241976), datetime.timedelta(microseconds=237994), datetime.timedelta(microseconds=239985)]
