Precision: [tensor(0.4195, device='cuda:0'), tensor(0.4130, device='cuda:0'), tensor(0.4250, device='cuda:0'), tensor(0.4379, device='cuda:0'), tensor(0.4232, device='cuda:0'), tensor(0.4350, device='cuda:0'), tensor(0.4153, device='cuda:0'), tensor(0.4159, device='cuda:0'), tensor(0.4148, device='cuda:0'), tensor(0.4156, device='cuda:0')]

Output distance: [tensor(5.4671, device='cuda:0'), tensor(5.4802, device='cuda:0'), tensor(5.4560, device='cuda:0'), tensor(5.4303, device='cuda:0'), tensor(5.4597, device='cuda:0'), tensor(5.4361, device='cuda:0'), tensor(5.4755, device='cuda:0'), tensor(5.4744, device='cuda:0'), tensor(5.4765, device='cuda:0'), tensor(5.4749, device='cuda:0')]

Prediction loss: [tensor(20247182., device='cuda:0'), tensor(15193225., device='cuda:0'), tensor(18690444., device='cuda:0'), tensor(20080950., device='cuda:0'), tensor(19513494., device='cuda:0'), tensor(15958061., device='cuda:0'), tensor(20296656., device='cuda:0'), tensor(21716058., device='cuda:0'), tensor(18598266., device='cuda:0'), tensor(19820524., device='cuda:0')]

Others: [{'iter_num': 60, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 60, '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=346351), datetime.timedelta(seconds=1, microseconds=236811), datetime.timedelta(seconds=1, microseconds=211913), datetime.timedelta(seconds=1, microseconds=241788), datetime.timedelta(seconds=1, microseconds=217888), datetime.timedelta(seconds=1, microseconds=246767), datetime.timedelta(seconds=1, microseconds=224858), datetime.timedelta(seconds=1, microseconds=223863), datetime.timedelta(seconds=1, microseconds=224861), datetime.timedelta(seconds=1, microseconds=237807)]

Phi time: [datetime.timedelta(microseconds=195180), datetime.timedelta(microseconds=203147), datetime.timedelta(microseconds=214100), datetime.timedelta(microseconds=193192), datetime.timedelta(microseconds=206138), datetime.timedelta(microseconds=193191), datetime.timedelta(microseconds=203150), datetime.timedelta(microseconds=201158), datetime.timedelta(microseconds=197173), datetime.timedelta(microseconds=194187)]

