Precision: [tensor(0.2965, device='cuda:0'), tensor(0.2848, device='cuda:0'), tensor(0.2831, device='cuda:0'), tensor(0.2921, device='cuda:0'), tensor(0.2860, device='cuda:0'), tensor(0.2834, device='cuda:0'), tensor(0.2881, device='cuda:0'), tensor(0.2783, device='cuda:0'), tensor(0.2897, device='cuda:0'), tensor(0.2856, device='cuda:0')]

Output distance: [tensor(6.5272, device='cuda:0'), tensor(6.5975, device='cuda:0'), tensor(6.6075, device='cuda:0'), tensor(6.5534, device='cuda:0'), tensor(6.5902, device='cuda:0'), tensor(6.6059, device='cuda:0'), tensor(6.5776, device='cuda:0'), tensor(6.6364, device='cuda:0'), tensor(6.5681, device='cuda:0'), tensor(6.5923, device='cuda:0')]

Prediction loss: [tensor(18526786., device='cuda:0'), tensor(16249069., device='cuda:0'), tensor(22498496., device='cuda:0'), tensor(24029070., device='cuda:0'), tensor(24044354., device='cuda:0'), tensor(17430722., device='cuda:0'), tensor(20890520., device='cuda:0'), tensor(16666526., device='cuda:0'), tensor(14415507., device='cuda:0'), tensor(18153794., device='cuda:0')]

Others: [{'iter_num': 11, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 13, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 13, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 13, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 13, '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=118307), datetime.timedelta(seconds=1, microseconds=115320), datetime.timedelta(seconds=1, microseconds=94406), datetime.timedelta(seconds=1, microseconds=79471), datetime.timedelta(seconds=1, microseconds=97393), datetime.timedelta(seconds=1, microseconds=84448), datetime.timedelta(seconds=1, microseconds=88434), datetime.timedelta(seconds=1, microseconds=190991), datetime.timedelta(seconds=1, microseconds=101330), datetime.timedelta(seconds=1, microseconds=111288)]

Phi time: [datetime.timedelta(microseconds=208126), datetime.timedelta(microseconds=211115), datetime.timedelta(microseconds=206136), datetime.timedelta(microseconds=214102), datetime.timedelta(microseconds=210121), datetime.timedelta(microseconds=193190), datetime.timedelta(microseconds=193189), datetime.timedelta(microseconds=196179), datetime.timedelta(microseconds=194169), datetime.timedelta(microseconds=195174)]

