Precision: [tensor(0.5933, device='cuda:0'), tensor(0.5857, device='cuda:0'), tensor(0.5815, device='cuda:0'), tensor(0.5844, device='cuda:0'), tensor(0.5862, device='cuda:0'), tensor(0.5870, device='cuda:0'), tensor(0.5967, device='cuda:0'), tensor(0.5886, device='cuda:0'), tensor(0.5928, device='cuda:0'), tensor(0.5747, device='cuda:0')]

Output distance: [tensor(5.1195, device='cuda:0'), tensor(5.1347, device='cuda:0'), tensor(5.1431, device='cuda:0'), tensor(5.1373, device='cuda:0'), tensor(5.1336, device='cuda:0'), tensor(5.1321, device='cuda:0'), tensor(5.1126, device='cuda:0'), tensor(5.1289, device='cuda:0'), tensor(5.1205, device='cuda:0'), tensor(5.1567, device='cuda:0')]

Prediction loss: [tensor(19929422., device='cuda:0'), tensor(17847996., device='cuda:0'), tensor(14641455., device='cuda:0'), tensor(15630904., device='cuda:0'), tensor(17110442., device='cuda:0'), tensor(21198018., device='cuda:0'), tensor(20358272., device='cuda:0'), tensor(19054238., device='cuda:0'), tensor(20258510., device='cuda:0'), tensor(18996944., device='cuda:0')]

Others: [{'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}]

Compressed training loss: [tensor(41157.4492, device='cuda:0'), tensor(40391.8359, device='cuda:0'), tensor(40987.9922, device='cuda:0'), tensor(40963.0391, device='cuda:0'), tensor(40872.9922, device='cuda:0'), tensor(40711.3359, device='cuda:0'), tensor(40825.8633, device='cuda:0'), tensor(40109.4727, device='cuda:0'), tensor(40641.8008, device='cuda:0'), tensor(40590.4023, device='cuda:0')]

Training loss: 0

Prediction time: [datetime.timedelta(seconds=15, microseconds=838016), datetime.timedelta(seconds=15, microseconds=999483), datetime.timedelta(seconds=16, microseconds=158007), datetime.timedelta(seconds=15, microseconds=923749), datetime.timedelta(seconds=16, microseconds=335374), datetime.timedelta(seconds=16, microseconds=52349), datetime.timedelta(seconds=16, microseconds=205004), datetime.timedelta(seconds=15, microseconds=869990), datetime.timedelta(seconds=16, microseconds=197053), datetime.timedelta(seconds=15, microseconds=951277)]

Phi time: [datetime.timedelta(microseconds=218076), datetime.timedelta(microseconds=243967), datetime.timedelta(microseconds=255917), datetime.timedelta(microseconds=242969), datetime.timedelta(microseconds=251932), datetime.timedelta(microseconds=243966), datetime.timedelta(microseconds=259898), datetime.timedelta(microseconds=246953), datetime.timedelta(microseconds=256911), datetime.timedelta(microseconds=249941)]

