Precision: [tensor(0.5356, device='cuda:0'), tensor(0.5375, device='cuda:0'), tensor(0.5331, device='cuda:0'), tensor(0.5319, device='cuda:0'), tensor(0.5354, device='cuda:0'), tensor(0.5379, device='cuda:0'), tensor(0.5357, device='cuda:0'), tensor(0.5378, device='cuda:0'), tensor(0.5335, device='cuda:0'), tensor(0.5327, device='cuda:0')]

Output distance: [tensor(5.0927, device='cuda:0'), tensor(5.0811, device='cuda:0'), tensor(5.1074, device='cuda:0'), tensor(5.1147, device='cuda:0'), tensor(5.0937, device='cuda:0'), tensor(5.0785, device='cuda:0'), tensor(5.0916, device='cuda:0'), tensor(5.0790, device='cuda:0'), tensor(5.1053, device='cuda:0'), tensor(5.1100, device='cuda:0')]

Prediction loss: [tensor(20807098., device='cuda:0'), tensor(18821006., device='cuda:0'), tensor(20434860., device='cuda:0'), tensor(19610450., device='cuda:0'), tensor(17261400., device='cuda:0'), tensor(18016734., device='cuda:0'), tensor(20197896., device='cuda:0'), tensor(17240952., device='cuda:0'), tensor(17458562., device='cuda:0'), tensor(17339580., 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(40829.5703, device='cuda:0'), tensor(40583.7500, device='cuda:0'), tensor(40866.7656, device='cuda:0'), tensor(40959.5508, device='cuda:0'), tensor(40823.3047, device='cuda:0'), tensor(40749.4727, device='cuda:0'), tensor(40760.1328, device='cuda:0'), tensor(40715.7578, device='cuda:0'), tensor(40691.7969, device='cuda:0'), tensor(40868.2969, device='cuda:0')]

Training loss: 0

Prediction time: [datetime.timedelta(seconds=45, microseconds=721398), datetime.timedelta(seconds=46, microseconds=356341), datetime.timedelta(seconds=46, microseconds=349662), datetime.timedelta(seconds=44, microseconds=811788), datetime.timedelta(seconds=45, microseconds=218165), datetime.timedelta(seconds=45, microseconds=872275), datetime.timedelta(seconds=46, microseconds=136193), datetime.timedelta(seconds=45, microseconds=494525), datetime.timedelta(seconds=46, microseconds=118467), datetime.timedelta(seconds=45, microseconds=616822)]

Phi time: [datetime.timedelta(microseconds=205973), datetime.timedelta(microseconds=377739), datetime.timedelta(microseconds=315052), datetime.timedelta(microseconds=336853), datetime.timedelta(microseconds=268265), datetime.timedelta(microseconds=425934), datetime.timedelta(microseconds=359330), datetime.timedelta(microseconds=344800), datetime.timedelta(microseconds=234318), datetime.timedelta(microseconds=288060)]

