Precision: [tensor(0.8062, device='cuda:0'), tensor(0.7998, device='cuda:0'), tensor(0.8052, device='cuda:0'), tensor(0.8043, device='cuda:0'), tensor(0.8012, device='cuda:0'), tensor(0.7986, device='cuda:0'), tensor(0.8014, device='cuda:0'), tensor(0.8112, device='cuda:0'), tensor(0.7893, device='cuda:0'), tensor(0.8182, device='cuda:0')]

Output distance: [tensor(1572.2750, device='cuda:0'), tensor(1763.5809, device='cuda:0'), tensor(1685.6064, device='cuda:0'), tensor(1489.0132, device='cuda:0'), tensor(1530.3717, device='cuda:0'), tensor(1678.8815, device='cuda:0'), tensor(1813.5137, device='cuda:0'), tensor(1363.6936, device='cuda:0'), tensor(1590.0566, device='cuda:0'), tensor(1287.1847, device='cuda:0')]

Prediction loss: [tensor(1766.7999, device='cuda:0'), tensor(1925.1748, device='cuda:0'), tensor(1853.5841, device='cuda:0'), tensor(1577.7157, device='cuda:0'), tensor(1630.8074, device='cuda:0'), tensor(1868.8905, device='cuda:0'), tensor(1878.8795, device='cuda:0'), tensor(1507.3098, device='cuda:0'), tensor(1744.2288, device='cuda:0'), tensor(1440.2246, 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(8956338., device='cuda:0'), tensor(8738487., device='cuda:0'), tensor(8903535., device='cuda:0'), tensor(8703928., device='cuda:0'), tensor(8795524., device='cuda:0'), tensor(8855120., device='cuda:0'), tensor(8676044., device='cuda:0'), tensor(8866121., device='cuda:0'), tensor(8877107., device='cuda:0'), tensor(8773777., device='cuda:0')]

Training loss: 8811360.0

Prediction time: [datetime.timedelta(microseconds=125468), datetime.timedelta(microseconds=128457), datetime.timedelta(microseconds=125468), datetime.timedelta(microseconds=125468), datetime.timedelta(microseconds=125465), datetime.timedelta(microseconds=124472), datetime.timedelta(microseconds=125468), datetime.timedelta(microseconds=126464), datetime.timedelta(microseconds=127461), datetime.timedelta(microseconds=125471)]

Phi time: [datetime.timedelta(seconds=1, microseconds=929889), datetime.timedelta(seconds=1, microseconds=299330), datetime.timedelta(seconds=1, microseconds=269286), datetime.timedelta(seconds=1, microseconds=328923), datetime.timedelta(seconds=1, microseconds=327305), datetime.timedelta(seconds=1, microseconds=326229), datetime.timedelta(seconds=1, microseconds=348068), datetime.timedelta(seconds=1, microseconds=313783), datetime.timedelta(seconds=1, microseconds=333574), datetime.timedelta(seconds=1, microseconds=321401)]

