Precision: [tensor(0.1076, device='cuda:0'), tensor(0.0973, device='cuda:0'), tensor(0.1013, device='cuda:0'), tensor(0.0910, device='cuda:0'), tensor(0.1025, device='cuda:0'), tensor(0.0989, device='cuda:0'), tensor(0.1032, device='cuda:0'), tensor(0.1204, device='cuda:0'), tensor(0.1397, device='cuda:0'), tensor(0.1147, device='cuda:0')]

Output distance: [tensor(7.6603, device='cuda:0'), tensor(7.7222, device='cuda:0'), tensor(7.6981, device='cuda:0'), tensor(7.7600, device='cuda:0'), tensor(7.6913, device='cuda:0'), tensor(7.7128, device='cuda:0'), tensor(7.6871, device='cuda:0'), tensor(7.5836, device='cuda:0'), tensor(7.4681, device='cuda:0'), tensor(7.6177, device='cuda:0')]

Prediction loss: [tensor(19370084., device='cuda:0'), tensor(18698592., device='cuda:0'), tensor(16650846., device='cuda:0'), tensor(17660280., device='cuda:0'), tensor(18006404., device='cuda:0'), tensor(20508056., device='cuda:0'), tensor(19871502., device='cuda:0'), tensor(22368356., device='cuda:0'), tensor(22256042., device='cuda:0'), tensor(17760946., device='cuda:0')]

Others: [{'iter_num': 60, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 55, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, 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=453834), datetime.timedelta(seconds=1, microseconds=449853), datetime.timedelta(seconds=1, microseconds=440888), datetime.timedelta(seconds=1, microseconds=372182), datetime.timedelta(seconds=1, microseconds=412011), datetime.timedelta(seconds=1, microseconds=397076), datetime.timedelta(seconds=1, microseconds=376165), datetime.timedelta(seconds=1, microseconds=414005), datetime.timedelta(seconds=1, microseconds=349279), datetime.timedelta(seconds=1, microseconds=386124)]

Phi time: [datetime.timedelta(microseconds=207119), datetime.timedelta(microseconds=202141), datetime.timedelta(microseconds=215090), datetime.timedelta(microseconds=207121), datetime.timedelta(microseconds=198163), datetime.timedelta(microseconds=190193), datetime.timedelta(microseconds=207122), datetime.timedelta(microseconds=196169), datetime.timedelta(microseconds=193181), datetime.timedelta(microseconds=204136)]

