Precision: [tensor(0.0013, device='cuda:0'), tensor(0.0008, device='cuda:0'), tensor(0.0018, device='cuda:0'), tensor(0.0017, device='cuda:0'), tensor(0.0014, device='cuda:0'), tensor(0.0014, device='cuda:0'), tensor(0.0013, device='cuda:0'), tensor(0.0016, device='cuda:0'), tensor(0.0023, device='cuda:0'), tensor(0.0019, device='cuda:0')]

Output distance: [tensor(22.0178, device='cuda:0'), tensor(22.0206, device='cuda:0'), tensor(22.0145, device='cuda:0'), tensor(22.0151, device='cuda:0'), tensor(22.0172, device='cuda:0'), tensor(22.0172, device='cuda:0'), tensor(22.0175, device='cuda:0'), tensor(22.0157, device='cuda:0'), tensor(22.0118, device='cuda:0'), tensor(22.0142, device='cuda:0')]

Prediction loss: [tensor(116.8016, device='cuda:0'), tensor(118.1678, device='cuda:0'), tensor(118.9608, device='cuda:0'), tensor(117.7860, device='cuda:0'), tensor(120.7096, device='cuda:0'), tensor(118.4590, device='cuda:0'), tensor(117.7748, device='cuda:0'), tensor(118.3912, device='cuda:0'), tensor(122.8128, device='cuda:0'), tensor(119.3067, device='cuda:0')]

Others: [{'iter_num': 60, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, '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=5, microseconds=269650), datetime.timedelta(seconds=5, microseconds=251724), datetime.timedelta(seconds=5, microseconds=265667), datetime.timedelta(seconds=5, microseconds=270646), datetime.timedelta(seconds=5, microseconds=300517), datetime.timedelta(seconds=5, microseconds=247744), datetime.timedelta(seconds=5, microseconds=241856), datetime.timedelta(seconds=5, microseconds=242764), datetime.timedelta(seconds=5, microseconds=282594), datetime.timedelta(seconds=5, microseconds=248740)]

Phi time: [datetime.timedelta(seconds=4, microseconds=197263), datetime.timedelta(seconds=4, microseconds=236192), datetime.timedelta(seconds=4, microseconds=209807), datetime.timedelta(seconds=4, microseconds=223325), datetime.timedelta(seconds=4, microseconds=224068), datetime.timedelta(seconds=4, microseconds=230849), datetime.timedelta(seconds=4, microseconds=209703), datetime.timedelta(seconds=4, microseconds=221716), datetime.timedelta(seconds=4, microseconds=244761), datetime.timedelta(seconds=4, microseconds=225205)]

