Precision: [tensor(0.4379, device='cuda:0'), tensor(0.4318, device='cuda:0'), tensor(0.4270, device='cuda:0'), tensor(0.4292, device='cuda:0'), tensor(0.4307, device='cuda:0'), tensor(0.4321, device='cuda:0'), tensor(0.4324, device='cuda:0'), tensor(0.4386, device='cuda:0'), tensor(0.4356, device='cuda:0'), tensor(0.4327, device='cuda:0')]

Output distance: [tensor(19.3978, device='cuda:0'), tensor(19.4344, device='cuda:0'), tensor(19.4631, device='cuda:0'), tensor(19.4501, device='cuda:0'), tensor(19.4411, device='cuda:0'), tensor(19.4329, device='cuda:0'), tensor(19.4311, device='cuda:0'), tensor(19.3939, device='cuda:0'), tensor(19.4117, device='cuda:0'), tensor(19.4290, device='cuda:0')]

Prediction loss: [tensor(105.7070, device='cuda:0'), tensor(104.7920, device='cuda:0'), tensor(104.5311, device='cuda:0'), tensor(104.6780, device='cuda:0'), tensor(104.4731, device='cuda:0'), tensor(104.3771, device='cuda:0'), tensor(104.6661, device='cuda:0'), tensor(104.6076, device='cuda:0'), tensor(105.1568, device='cuda:0'), tensor(104.9095, device='cuda:0')]

Others: [{'iter_num': 7, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}]

Compressed training loss: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]

Training loss: 0

Prediction time: [datetime.timedelta(seconds=2, microseconds=624863), datetime.timedelta(seconds=2, microseconds=616901), datetime.timedelta(seconds=2, microseconds=834978), datetime.timedelta(seconds=2, microseconds=840952), datetime.timedelta(seconds=2, microseconds=645781), datetime.timedelta(seconds=2, microseconds=760292), datetime.timedelta(seconds=2, microseconds=638808), datetime.timedelta(seconds=2, microseconds=666691), datetime.timedelta(seconds=2, microseconds=660766), datetime.timedelta(seconds=2, microseconds=765269)]

Phi time: [datetime.timedelta(seconds=5, microseconds=163650), datetime.timedelta(seconds=5, microseconds=105514), datetime.timedelta(seconds=5, microseconds=161745), datetime.timedelta(seconds=5, microseconds=147365), datetime.timedelta(seconds=5, microseconds=174848), datetime.timedelta(seconds=5, microseconds=125911), datetime.timedelta(seconds=5, microseconds=104450), datetime.timedelta(seconds=5, microseconds=135744), datetime.timedelta(seconds=5, microseconds=209863), datetime.timedelta(seconds=5, microseconds=120817)]

