Precision: [tensor(0.4382, device='cuda:0'), tensor(0.4349, device='cuda:0'), tensor(0.4406, device='cuda:0'), tensor(0.4382, device='cuda:0'), tensor(0.4415, device='cuda:0'), tensor(0.4385, device='cuda:0'), tensor(0.4400, device='cuda:0'), tensor(0.4364, device='cuda:0'), tensor(0.4445, device='cuda:0'), tensor(0.4444, device='cuda:0')]

Output distance: [tensor(5.6771, device='cuda:0'), tensor(5.6965, device='cuda:0'), tensor(5.6624, device='cuda:0'), tensor(5.6771, device='cuda:0'), tensor(5.6571, device='cuda:0'), tensor(5.6750, device='cuda:0'), tensor(5.6661, device='cuda:0'), tensor(5.6876, device='cuda:0'), tensor(5.6393, device='cuda:0'), tensor(5.6398, device='cuda:0')]

Prediction loss: [tensor(20132268., device='cuda:0'), tensor(18774088., device='cuda:0'), tensor(20310402., device='cuda:0'), tensor(16764001., device='cuda:0'), tensor(17366278., device='cuda:0'), tensor(19825944., device='cuda:0'), tensor(18712642., device='cuda:0'), tensor(20577276., device='cuda:0'), tensor(18824082., device='cuda:0'), tensor(21030824., 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(41009.9883, device='cuda:0'), tensor(41136.4336, device='cuda:0'), tensor(40890.7734, device='cuda:0'), tensor(41117.1641, device='cuda:0'), tensor(40886.8242, device='cuda:0'), tensor(40868.0273, device='cuda:0'), tensor(40743.6055, device='cuda:0'), tensor(41207.9141, device='cuda:0'), tensor(40842.2539, device='cuda:0'), tensor(40724.1328, device='cuda:0')]

Training loss: 0

Prediction time: [datetime.timedelta(seconds=35, microseconds=449362), datetime.timedelta(seconds=36, microseconds=326930), datetime.timedelta(seconds=36, microseconds=386501), datetime.timedelta(seconds=36, microseconds=98165), datetime.timedelta(seconds=36, microseconds=165359), datetime.timedelta(seconds=36, microseconds=466407), datetime.timedelta(seconds=36, microseconds=533149), datetime.timedelta(seconds=34, microseconds=970106), datetime.timedelta(seconds=36, microseconds=304592), datetime.timedelta(seconds=36, microseconds=209274)]

Phi time: [datetime.timedelta(microseconds=191314), datetime.timedelta(microseconds=392886), datetime.timedelta(microseconds=349852), datetime.timedelta(microseconds=299941), datetime.timedelta(microseconds=382442), datetime.timedelta(microseconds=315101), datetime.timedelta(microseconds=399905), datetime.timedelta(microseconds=345924), datetime.timedelta(microseconds=323987), datetime.timedelta(microseconds=366684)]

