Precision: [tensor(0.1749, device='cuda:0'), tensor(0.1852, device='cuda:0'), tensor(0.1860, device='cuda:0'), tensor(0.1797, device='cuda:0'), tensor(0.1830, device='cuda:0'), tensor(0.1794, device='cuda:0'), tensor(0.1781, device='cuda:0'), tensor(0.1688, device='cuda:0'), tensor(0.1753, device='cuda:0'), tensor(0.1884, device='cuda:0')]

Output distance: [tensor(22.2760, device='cuda:0'), tensor(22.1738, device='cuda:0'), tensor(22.1654, device='cuda:0'), tensor(22.2279, device='cuda:0'), tensor(22.1950, device='cuda:0'), tensor(22.2319, device='cuda:0'), tensor(22.2440, device='cuda:0'), tensor(22.3371, device='cuda:0'), tensor(22.2724, device='cuda:0'), tensor(22.1412, device='cuda:0')]

Prediction loss: [tensor(97.7173, device='cuda:0'), tensor(97.7492, device='cuda:0'), tensor(98.3380, device='cuda:0'), tensor(99.1395, device='cuda:0'), tensor(98.1444, device='cuda:0'), tensor(97.9989, device='cuda:0'), tensor(98.5955, device='cuda:0'), tensor(98.8665, device='cuda:0'), tensor(99.4160, device='cuda:0'), tensor(98.7629, 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=1, microseconds=918861), datetime.timedelta(seconds=1, microseconds=900935), datetime.timedelta(seconds=1, microseconds=937782), datetime.timedelta(seconds=1, microseconds=923843), datetime.timedelta(seconds=1, microseconds=932884), datetime.timedelta(seconds=1, microseconds=931888), datetime.timedelta(seconds=1, microseconds=938864), datetime.timedelta(seconds=1, microseconds=948816), datetime.timedelta(seconds=2, microseconds=6574), datetime.timedelta(seconds=1, microseconds=984666)]

Phi time: [datetime.timedelta(seconds=4, microseconds=920618), datetime.timedelta(seconds=4, microseconds=909179), datetime.timedelta(seconds=4, microseconds=885362), datetime.timedelta(seconds=4, microseconds=890257), datetime.timedelta(seconds=4, microseconds=873311), datetime.timedelta(seconds=4, microseconds=880502), datetime.timedelta(seconds=4, microseconds=881499), datetime.timedelta(seconds=4, microseconds=896437), datetime.timedelta(seconds=4, microseconds=915356), datetime.timedelta(seconds=4, microseconds=923324)]

