Precision: [tensor(0.4657, device='cuda:0'), tensor(0.4786, device='cuda:0'), tensor(0.4888, device='cuda:0'), tensor(0.4783, device='cuda:0'), tensor(0.4891, device='cuda:0'), tensor(0.4697, device='cuda:0'), tensor(0.4741, device='cuda:0'), tensor(0.4776, device='cuda:0'), tensor(0.4815, device='cuda:0'), tensor(0.4812, device='cuda:0')]

Output distance: [tensor(5.3746, device='cuda:0'), tensor(5.3489, device='cuda:0'), tensor(5.3284, device='cuda:0'), tensor(5.3494, device='cuda:0'), tensor(5.3279, device='cuda:0'), tensor(5.3668, device='cuda:0'), tensor(5.3578, device='cuda:0'), tensor(5.3510, device='cuda:0'), tensor(5.3431, device='cuda:0'), tensor(5.3437, device='cuda:0')]

Prediction loss: [tensor(20628438., device='cuda:0'), tensor(20803320., device='cuda:0'), tensor(24007546., device='cuda:0'), tensor(21461406., device='cuda:0'), tensor(18478404., device='cuda:0'), tensor(17738946., device='cuda:0'), tensor(23577496., device='cuda:0'), tensor(19273658., device='cuda:0'), tensor(17543938., device='cuda:0'), tensor(21556822., device='cuda:0')]

Others: [{'iter_num': 7, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(3809, 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=273656), datetime.timedelta(seconds=1, microseconds=135236), datetime.timedelta(seconds=1, microseconds=119304), datetime.timedelta(seconds=1, microseconds=63539), datetime.timedelta(seconds=1, microseconds=45614), datetime.timedelta(seconds=1, microseconds=28684), datetime.timedelta(seconds=1, microseconds=61547), datetime.timedelta(seconds=1, microseconds=127270), datetime.timedelta(seconds=1, microseconds=58561), datetime.timedelta(seconds=1, microseconds=30676)]

Phi time: [datetime.timedelta(microseconds=424218), datetime.timedelta(microseconds=226049), datetime.timedelta(microseconds=219078), datetime.timedelta(microseconds=231032), datetime.timedelta(microseconds=207132), datetime.timedelta(microseconds=201154), datetime.timedelta(microseconds=200160), datetime.timedelta(microseconds=225055), datetime.timedelta(microseconds=212110), datetime.timedelta(microseconds=211113)]

