Precision: [tensor(0.3040, device='cuda:0'), tensor(0.3104, device='cuda:0'), tensor(0.3039, device='cuda:0'), tensor(0.3095, device='cuda:0'), tensor(0.2985, device='cuda:0'), tensor(0.2989, device='cuda:0'), tensor(0.3061, device='cuda:0'), tensor(0.3040, device='cuda:0'), tensor(0.3127, device='cuda:0'), tensor(0.3088, device='cuda:0')]

Output distance: [tensor(6.4820, device='cuda:0'), tensor(6.4437, device='cuda:0'), tensor(6.4825, device='cuda:0'), tensor(6.4489, device='cuda:0'), tensor(6.5151, device='cuda:0'), tensor(6.5125, device='cuda:0'), tensor(6.4694, device='cuda:0'), tensor(6.4820, device='cuda:0'), tensor(6.4300, device='cuda:0'), tensor(6.4531, device='cuda:0')]

Prediction loss: [tensor(15081661., device='cuda:0'), tensor(21831504., device='cuda:0'), tensor(17296998., device='cuda:0'), tensor(19633132., device='cuda:0'), tensor(17572776., device='cuda:0'), tensor(17810624., device='cuda:0'), tensor(16030284., device='cuda:0'), tensor(12902703., device='cuda:0'), tensor(19057902., device='cuda:0'), tensor(18666568., device='cuda:0')]

Others: [{'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}]

Compressed training loss: [tensor(41146.3555, device='cuda:0'), tensor(41040.7891, device='cuda:0'), tensor(40986.5742, device='cuda:0'), tensor(41090.6094, device='cuda:0'), tensor(40576.1211, device='cuda:0'), tensor(40685.3750, device='cuda:0'), tensor(40847.6016, device='cuda:0'), tensor(40859.3516, device='cuda:0'), tensor(40773.1328, device='cuda:0'), tensor(41127.0664, device='cuda:0')]

Training loss: 0

Prediction time: [datetime.timedelta(seconds=1, microseconds=59538), datetime.timedelta(seconds=1, microseconds=52568), datetime.timedelta(seconds=1, microseconds=31625), datetime.timedelta(seconds=1, microseconds=39591), datetime.timedelta(seconds=1, microseconds=38595), datetime.timedelta(seconds=1, microseconds=35607), datetime.timedelta(seconds=1, microseconds=43573), datetime.timedelta(seconds=1, microseconds=41583), datetime.timedelta(seconds=1, microseconds=31623), datetime.timedelta(seconds=1, microseconds=28637)]

Phi time: [datetime.timedelta(microseconds=218083), datetime.timedelta(microseconds=202150), datetime.timedelta(microseconds=195175), datetime.timedelta(microseconds=193180), datetime.timedelta(microseconds=194176), datetime.timedelta(microseconds=193180), datetime.timedelta(microseconds=198160), datetime.timedelta(microseconds=196168), datetime.timedelta(microseconds=192185), datetime.timedelta(microseconds=194176)]

