Precision: [tensor(0.9990, device='cuda:0'), tensor(0.9995, device='cuda:0'), tensor(0.9997, device='cuda:0'), tensor(0.9995, device='cuda:0'), tensor(0.9997, device='cuda:0'), tensor(0.9995, device='cuda:0'), tensor(0.9997, device='cuda:0'), tensor(0.9995, device='cuda:0'), tensor(0.9997, device='cuda:0'), tensor(0.9998, device='cuda:0')]

Output distance: [tensor(142690.3906, device='cuda:0'), tensor(143833.7188, device='cuda:0'), tensor(139426.2031, device='cuda:0'), tensor(140562.1406, device='cuda:0'), tensor(141534.2188, device='cuda:0'), tensor(140452.4219, device='cuda:0'), tensor(142250.5000, device='cuda:0'), tensor(139688.8125, device='cuda:0'), tensor(139012.6094, device='cuda:0'), tensor(140040.2031, device='cuda:0')]

Prediction loss: [tensor(133540.6250, device='cuda:0'), tensor(132082.0156, device='cuda:0'), tensor(132351.4219, device='cuda:0'), tensor(136418.4688, device='cuda:0'), tensor(129627.5938, device='cuda:0'), tensor(125241.8047, device='cuda:0'), tensor(132070.4062, device='cuda:0'), tensor(130240.9609, device='cuda:0'), tensor(127837.7344, device='cuda:0'), tensor(132432.8750, device='cuda:0')]

Others: [{'num_positive': tensor(5991, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(5996, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(5998, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(5992, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(5994, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(5995, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(5996, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(5990, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(5997, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(5991, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}]

Compressed training loss: [tensor(1.9084e+08, device='cuda:0'), tensor(1.8915e+08, device='cuda:0'), tensor(1.9020e+08, device='cuda:0'), tensor(1.9236e+08, device='cuda:0'), tensor(1.8667e+08, device='cuda:0'), tensor(1.8191e+08, device='cuda:0'), tensor(1.9007e+08, device='cuda:0'), tensor(1.8619e+08, device='cuda:0'), tensor(1.8848e+08, device='cuda:0'), tensor(1.9013e+08, device='cuda:0')]

Training loss: 190988192.0

Prediction time: [datetime.timedelta(seconds=86, microseconds=354785), datetime.timedelta(seconds=86, microseconds=365912), datetime.timedelta(seconds=86, microseconds=176342), datetime.timedelta(seconds=86, microseconds=103409), datetime.timedelta(seconds=86, microseconds=98586), datetime.timedelta(seconds=86, microseconds=35721), datetime.timedelta(seconds=86, microseconds=511956), datetime.timedelta(seconds=85, microseconds=892606), datetime.timedelta(seconds=86, microseconds=288922), datetime.timedelta(seconds=86, microseconds=85286)]

Phi time: [datetime.timedelta(seconds=1, microseconds=191919), datetime.timedelta(microseconds=639463), datetime.timedelta(microseconds=641595), datetime.timedelta(microseconds=641443), datetime.timedelta(microseconds=637844), datetime.timedelta(microseconds=639350), datetime.timedelta(microseconds=639890), datetime.timedelta(microseconds=635595), datetime.timedelta(microseconds=640550), datetime.timedelta(microseconds=640256)]

