Precision: [tensor(0.4873, device='cuda:0'), tensor(0.4930, device='cuda:0'), tensor(0.4879, device='cuda:0'), tensor(0.4890, device='cuda:0'), tensor(0.4832, device='cuda:0'), tensor(0.4913, device='cuda:0'), tensor(0.4857, device='cuda:0'), tensor(0.4881, device='cuda:0'), tensor(0.4876, device='cuda:0'), tensor(0.4895, device='cuda:0')]

Output distance: [tensor(5.3825, device='cuda:0'), tensor(5.3479, device='cuda:0'), tensor(5.3788, device='cuda:0'), tensor(5.3720, device='cuda:0'), tensor(5.4067, device='cuda:0'), tensor(5.3584, device='cuda:0'), tensor(5.3920, device='cuda:0'), tensor(5.3773, device='cuda:0'), tensor(5.3804, device='cuda:0'), tensor(5.3689, device='cuda:0')]

Prediction loss: [tensor(18209946., device='cuda:0'), tensor(19034462., device='cuda:0'), tensor(17304894., device='cuda:0'), tensor(21497246., device='cuda:0'), tensor(17557896., device='cuda:0'), tensor(18390444., device='cuda:0'), tensor(19755762., device='cuda:0'), tensor(19514720., device='cuda:0'), tensor(23578012., device='cuda:0'), tensor(20043968., 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(40604.5234, device='cuda:0'), tensor(41257.5156, device='cuda:0'), tensor(40847.7734, device='cuda:0'), tensor(41004.8242, device='cuda:0'), tensor(40901.4258, device='cuda:0'), tensor(41087.3828, device='cuda:0'), tensor(40456.7422, device='cuda:0'), tensor(40717.2969, device='cuda:0'), tensor(40988.3438, device='cuda:0'), tensor(40822.8086, device='cuda:0')]

Training loss: 0

Prediction time: [datetime.timedelta(seconds=38, microseconds=48455), datetime.timedelta(seconds=38, microseconds=524580), datetime.timedelta(seconds=37, microseconds=103654), datetime.timedelta(seconds=38, microseconds=612330), datetime.timedelta(seconds=37, microseconds=649038), datetime.timedelta(seconds=38, microseconds=399700), datetime.timedelta(seconds=38, microseconds=800418), datetime.timedelta(seconds=38, microseconds=776955), datetime.timedelta(seconds=38, microseconds=126817), datetime.timedelta(seconds=38, microseconds=866977)]

Phi time: [datetime.timedelta(microseconds=178836), datetime.timedelta(microseconds=237319), datetime.timedelta(microseconds=346062), datetime.timedelta(microseconds=350027), datetime.timedelta(microseconds=266555), datetime.timedelta(microseconds=248895), datetime.timedelta(microseconds=270609), datetime.timedelta(microseconds=266581), datetime.timedelta(microseconds=308799), datetime.timedelta(microseconds=349726)]

