Precision: [tensor(0.7911, device='cuda:0'), tensor(0.7894, device='cuda:0'), tensor(0.7816, device='cuda:0'), tensor(0.7834, device='cuda:0'), tensor(0.7869, device='cuda:0'), tensor(0.8067, device='cuda:0'), tensor(0.7982, device='cuda:0'), tensor(0.7829, device='cuda:0'), tensor(0.7760, device='cuda:0'), tensor(0.7794, device='cuda:0')]

Output distance: [tensor(29452.1309, device='cuda:0'), tensor(25962.8457, device='cuda:0'), tensor(26610.6133, device='cuda:0'), tensor(27931.5508, device='cuda:0'), tensor(31163.5684, device='cuda:0'), tensor(22695.8906, device='cuda:0'), tensor(28401.8281, device='cuda:0'), tensor(25830.3145, device='cuda:0'), tensor(30057.5996, device='cuda:0'), tensor(30063.4043, device='cuda:0')]

Prediction loss: [tensor(30167.8340, device='cuda:0'), tensor(24579.2852, device='cuda:0'), tensor(24637.5469, device='cuda:0'), tensor(26983.0879, device='cuda:0'), tensor(26550.6074, device='cuda:0'), tensor(21383.1641, device='cuda:0'), tensor(24541.9668, device='cuda:0'), tensor(25165.6797, device='cuda:0'), tensor(28679.9336, device='cuda:0'), tensor(29707.9004, device='cuda:0')]

Others: [{'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}]

Compressed training loss: [tensor(1.9578e+08, device='cuda:0'), tensor(1.9169e+08, device='cuda:0'), tensor(1.8865e+08, device='cuda:0'), tensor(1.9371e+08, device='cuda:0'), tensor(1.8735e+08, device='cuda:0'), tensor(1.9429e+08, device='cuda:0'), tensor(1.9204e+08, device='cuda:0'), tensor(1.9325e+08, device='cuda:0'), tensor(1.9312e+08, device='cuda:0'), tensor(1.9147e+08, device='cuda:0')]

Training loss: 191562528.0

Prediction time: [datetime.timedelta(microseconds=58751), datetime.timedelta(microseconds=59744), datetime.timedelta(microseconds=65722), datetime.timedelta(microseconds=64726), datetime.timedelta(microseconds=57755), datetime.timedelta(microseconds=55768), datetime.timedelta(microseconds=58751), datetime.timedelta(microseconds=59779), datetime.timedelta(microseconds=60744), datetime.timedelta(microseconds=62735)]

Phi time: [datetime.timedelta(seconds=1, microseconds=371158), datetime.timedelta(microseconds=853967), datetime.timedelta(microseconds=871524), datetime.timedelta(microseconds=935965), datetime.timedelta(microseconds=870223), datetime.timedelta(microseconds=856481), datetime.timedelta(microseconds=877660), datetime.timedelta(microseconds=853005), datetime.timedelta(microseconds=857154), datetime.timedelta(microseconds=853202)]

