Precision: [tensor(0.1511, device='cuda:0'), tensor(0.1583, device='cuda:0'), tensor(0.1522, device='cuda:0'), tensor(0.1565, device='cuda:0'), tensor(0.1678, device='cuda:0'), tensor(0.1551, device='cuda:0'), tensor(0.1616, device='cuda:0'), tensor(0.1483, device='cuda:0'), tensor(0.1781, device='cuda:0'), tensor(0.1590, device='cuda:0')]

Output distance: [tensor(21.1188, device='cuda:0'), tensor(21.0759, device='cuda:0'), tensor(21.1125, device='cuda:0'), tensor(21.0862, device='cuda:0'), tensor(21.0184, device='cuda:0'), tensor(21.0949, device='cuda:0'), tensor(21.0556, device='cuda:0'), tensor(21.1354, device='cuda:0'), tensor(20.9568, device='cuda:0'), tensor(21.0716, device='cuda:0')]

Prediction loss: [tensor(100.6141, device='cuda:0'), tensor(102.8186, device='cuda:0'), tensor(100.6001, device='cuda:0'), tensor(101.1778, device='cuda:0'), tensor(103.1899, device='cuda:0'), tensor(100.2968, device='cuda:0'), tensor(101.8520, device='cuda:0'), tensor(101.7569, device='cuda:0'), tensor(101.7299, device='cuda:0'), tensor(101.5503, device='cuda:0')]

Others: [{'iter_num': 11, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(19848, 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=527378), datetime.timedelta(seconds=2, microseconds=458666), datetime.timedelta(seconds=2, microseconds=553270), datetime.timedelta(seconds=2, microseconds=467630), datetime.timedelta(seconds=2, microseconds=480629), datetime.timedelta(seconds=2, microseconds=468625), datetime.timedelta(seconds=2, microseconds=447720), datetime.timedelta(seconds=2, microseconds=579158), datetime.timedelta(seconds=2, microseconds=556257), datetime.timedelta(seconds=2, microseconds=442733)]

Phi time: [datetime.timedelta(seconds=4, microseconds=356600), datetime.timedelta(seconds=4, microseconds=353986), datetime.timedelta(seconds=4, microseconds=361121), datetime.timedelta(seconds=4, microseconds=337886), datetime.timedelta(seconds=4, microseconds=394536), datetime.timedelta(seconds=4, microseconds=338430), datetime.timedelta(seconds=4, microseconds=350916), datetime.timedelta(seconds=4, microseconds=340521), datetime.timedelta(seconds=4, microseconds=331488), datetime.timedelta(seconds=4, microseconds=345312)]

