Precision: [tensor(0.4542, device='cuda:0'), tensor(0.4560, device='cuda:0'), tensor(0.4642, device='cuda:0'), tensor(0.4636, device='cuda:0'), tensor(0.4592, device='cuda:0'), tensor(0.4502, device='cuda:0'), tensor(0.4542, device='cuda:0'), tensor(0.4571, device='cuda:0'), tensor(0.4531, device='cuda:0'), tensor(0.4489, device='cuda:0')]

Output distance: [tensor(5.3977, device='cuda:0'), tensor(5.3941, device='cuda:0'), tensor(5.3778, device='cuda:0'), tensor(5.3788, device='cuda:0'), tensor(5.3878, device='cuda:0'), tensor(5.4056, device='cuda:0'), tensor(5.3977, device='cuda:0'), tensor(5.3920, device='cuda:0'), tensor(5.3998, device='cuda:0'), tensor(5.4082, device='cuda:0')]

Prediction loss: [tensor(14418607., device='cuda:0'), tensor(16099907., device='cuda:0'), tensor(16521409., device='cuda:0'), tensor(18106120., device='cuda:0'), tensor(18978198., device='cuda:0'), tensor(23916398., device='cuda:0'), tensor(16156726., device='cuda:0'), tensor(14699289., device='cuda:0'), tensor(21025734., device='cuda:0'), tensor(19029522., 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(40880.9570, device='cuda:0'), tensor(40492.2656, device='cuda:0'), tensor(41067.2188, device='cuda:0'), tensor(41279.4258, device='cuda:0'), tensor(40798.9688, device='cuda:0'), tensor(40862.7930, device='cuda:0'), tensor(41253.5039, device='cuda:0'), tensor(40208.8477, device='cuda:0'), tensor(40704.7812, device='cuda:0'), tensor(41207.4688, device='cuda:0')]

Training loss: 0

Prediction time: [datetime.timedelta(seconds=8, microseconds=676901), datetime.timedelta(seconds=12, microseconds=554912), datetime.timedelta(seconds=11, microseconds=204911), datetime.timedelta(seconds=9, microseconds=316774), datetime.timedelta(seconds=11, microseconds=728870), datetime.timedelta(seconds=15, microseconds=369851), datetime.timedelta(seconds=8, microseconds=845355), datetime.timedelta(seconds=11, microseconds=217994), datetime.timedelta(seconds=8, microseconds=205999), datetime.timedelta(seconds=9, microseconds=423488)]

Phi time: [datetime.timedelta(microseconds=179239), datetime.timedelta(microseconds=307694), datetime.timedelta(microseconds=403302), datetime.timedelta(microseconds=273847), datetime.timedelta(microseconds=207126), datetime.timedelta(microseconds=196175), datetime.timedelta(microseconds=222064), datetime.timedelta(microseconds=197170), datetime.timedelta(microseconds=199161), datetime.timedelta(microseconds=205136)]

