Precision: [tensor(0.3993, device='cuda:0'), tensor(0.3924, device='cuda:0'), tensor(0.3927, device='cuda:0'), tensor(0.3886, device='cuda:0'), tensor(0.3912, device='cuda:0'), tensor(0.3922, device='cuda:0'), tensor(0.3944, device='cuda:0'), tensor(0.3932, device='cuda:0'), tensor(0.3903, device='cuda:0'), tensor(0.3920, device='cuda:0')]

Output distance: [tensor(20.0326, device='cuda:0'), tensor(20.1013, device='cuda:0'), tensor(20.0985, device='cuda:0'), tensor(20.1397, device='cuda:0'), tensor(20.1137, device='cuda:0'), tensor(20.1034, device='cuda:0'), tensor(20.0816, device='cuda:0'), tensor(20.0931, device='cuda:0'), tensor(20.1224, device='cuda:0'), tensor(20.1052, device='cuda:0')]

Prediction loss: [tensor(102.6175, device='cuda:0'), tensor(102.1735, device='cuda:0'), tensor(102.2539, device='cuda:0'), tensor(102.8014, device='cuda:0'), tensor(102.1651, device='cuda:0'), tensor(102.3934, device='cuda:0'), tensor(102.6358, device='cuda:0'), tensor(101.8191, device='cuda:0'), tensor(101.7417, device='cuda:0'), tensor(102.3483, device='cuda:0')]

Others: [{'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}]

Compressed training loss: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]

Training loss: 0

Prediction time: [datetime.timedelta(seconds=2, microseconds=121004), datetime.timedelta(seconds=2, microseconds=100093), datetime.timedelta(seconds=2, microseconds=93122), datetime.timedelta(seconds=2, microseconds=186727), datetime.timedelta(seconds=2, microseconds=209627), datetime.timedelta(seconds=2, microseconds=146896), datetime.timedelta(seconds=2, microseconds=91131), datetime.timedelta(seconds=2, microseconds=195688), datetime.timedelta(seconds=2, microseconds=191706), datetime.timedelta(seconds=2, microseconds=217592)]

Phi time: [datetime.timedelta(seconds=6, microseconds=837936), datetime.timedelta(seconds=6, microseconds=720781), datetime.timedelta(seconds=6, microseconds=706968), datetime.timedelta(seconds=6, microseconds=724295), datetime.timedelta(seconds=6, microseconds=781601), datetime.timedelta(seconds=6, microseconds=785824), datetime.timedelta(seconds=6, microseconds=744169), datetime.timedelta(seconds=6, microseconds=721788), datetime.timedelta(seconds=6, microseconds=801621), datetime.timedelta(seconds=6, microseconds=829858)]

