Precision: [tensor(0.4580, device='cuda:0'), tensor(0.4607, device='cuda:0'), tensor(0.4543, device='cuda:0'), tensor(0.4556, device='cuda:0'), tensor(0.4551, device='cuda:0'), tensor(0.4563, device='cuda:0'), tensor(0.4568, device='cuda:0'), tensor(0.4621, device='cuda:0'), tensor(0.4557, device='cuda:0'), tensor(0.4573, device='cuda:0')]

Output distance: [tensor(5.5584, device='cuda:0'), tensor(5.5421, device='cuda:0'), tensor(5.5805, device='cuda:0'), tensor(5.5726, device='cuda:0'), tensor(5.5757, device='cuda:0'), tensor(5.5684, device='cuda:0'), tensor(5.5652, device='cuda:0'), tensor(5.5337, device='cuda:0'), tensor(5.5721, device='cuda:0'), tensor(5.5626, device='cuda:0')]

Prediction loss: [tensor(17198498., device='cuda:0'), tensor(18127090., device='cuda:0'), tensor(18353376., device='cuda:0'), tensor(19308926., device='cuda:0'), tensor(19148386., device='cuda:0'), tensor(15272181., device='cuda:0'), tensor(17719564., device='cuda:0'), tensor(20258086., device='cuda:0'), tensor(19109744., device='cuda:0'), tensor(18025638., device='cuda:0')]

Others: [{'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': 17, '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')}, {'iter_num': 15, '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': 11, '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=104319), datetime.timedelta(seconds=1, microseconds=62495), datetime.timedelta(seconds=1, microseconds=102327), datetime.timedelta(seconds=1, microseconds=60505), datetime.timedelta(seconds=1, microseconds=64487), datetime.timedelta(seconds=1, microseconds=59509), datetime.timedelta(seconds=1, microseconds=73450), datetime.timedelta(seconds=1, microseconds=80421), datetime.timedelta(seconds=1, microseconds=168049), datetime.timedelta(seconds=1, microseconds=157094)]

Phi time: [datetime.timedelta(microseconds=240977), datetime.timedelta(microseconds=241974), datetime.timedelta(microseconds=234007), datetime.timedelta(microseconds=258901), datetime.timedelta(microseconds=227037), datetime.timedelta(microseconds=230023), datetime.timedelta(microseconds=243965), datetime.timedelta(microseconds=232015), datetime.timedelta(microseconds=240977), datetime.timedelta(microseconds=278818)]

