Precision: [tensor(0.6989, device='cuda:0'), tensor(0.7004, device='cuda:0'), tensor(0.7007, device='cuda:0'), tensor(0.6965, device='cuda:0'), tensor(0.6915, device='cuda:0'), tensor(0.6931, device='cuda:0'), tensor(0.6970, device='cuda:0'), tensor(0.6976, device='cuda:0'), tensor(0.6902, device='cuda:0'), tensor(0.6955, device='cuda:0')]

Output distance: [tensor(4.9084, device='cuda:0'), tensor(4.9052, device='cuda:0'), tensor(4.9047, device='cuda:0'), tensor(4.9131, device='cuda:0'), tensor(4.9231, device='cuda:0'), tensor(4.9199, device='cuda:0'), tensor(4.9121, device='cuda:0'), tensor(4.9110, device='cuda:0'), tensor(4.9257, device='cuda:0'), tensor(4.9152, device='cuda:0')]

Prediction loss: [tensor(18419032., device='cuda:0'), tensor(19280202., device='cuda:0'), tensor(18000876., device='cuda:0'), tensor(18627676., device='cuda:0'), tensor(18306432., device='cuda:0'), tensor(18364176., device='cuda:0'), tensor(18273500., device='cuda:0'), tensor(18859352., device='cuda:0'), tensor(18123554., device='cuda:0'), tensor(18108152., 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(40808.6797, device='cuda:0'), tensor(40867.9102, device='cuda:0'), tensor(40789.8828, device='cuda:0'), tensor(40874.6836, device='cuda:0'), tensor(40878.0312, device='cuda:0'), tensor(40941.8242, device='cuda:0'), tensor(40886.1328, device='cuda:0'), tensor(40920.7969, device='cuda:0'), tensor(40898.9453, device='cuda:0'), tensor(40792.5039, device='cuda:0')]

Training loss: 0

Prediction time: [datetime.timedelta(microseconds=901525), datetime.timedelta(microseconds=925430), datetime.timedelta(microseconds=912672), datetime.timedelta(microseconds=908265), datetime.timedelta(microseconds=905912), datetime.timedelta(microseconds=913578), datetime.timedelta(microseconds=905668), datetime.timedelta(microseconds=908353), datetime.timedelta(microseconds=909056), datetime.timedelta(microseconds=898422)]

Phi time: [datetime.timedelta(microseconds=313997), datetime.timedelta(microseconds=299893), datetime.timedelta(microseconds=304151), datetime.timedelta(microseconds=289626), datetime.timedelta(microseconds=293108), datetime.timedelta(microseconds=299923), datetime.timedelta(microseconds=290252), datetime.timedelta(microseconds=297023), datetime.timedelta(microseconds=293797), datetime.timedelta(microseconds=301574)]

