Precision: [tensor(0.0298, device='cuda:0'), tensor(0.0356, device='cuda:0'), tensor(0.0280, device='cuda:0'), tensor(0.0288, device='cuda:0'), tensor(0.0267, device='cuda:0'), tensor(0.0268, device='cuda:0'), tensor(0.0265, device='cuda:0'), tensor(0.0340, device='cuda:0'), tensor(0.0297, device='cuda:0'), tensor(0.0228, device='cuda:0')]

Output distance: [tensor(21.8467, device='cuda:0'), tensor(21.8120, device='cuda:0'), tensor(21.8573, device='cuda:0'), tensor(21.8525, device='cuda:0'), tensor(21.8652, device='cuda:0'), tensor(21.8646, device='cuda:0'), tensor(21.8664, device='cuda:0'), tensor(21.8213, device='cuda:0'), tensor(21.8473, device='cuda:0'), tensor(21.8888, device='cuda:0')]

Prediction loss: [tensor(102.7288, device='cuda:0'), tensor(103.3990, device='cuda:0'), tensor(102.6793, device='cuda:0'), tensor(101.7114, device='cuda:0'), tensor(104.9951, device='cuda:0'), tensor(104.6872, device='cuda:0'), tensor(103.0425, device='cuda:0'), tensor(104.2845, device='cuda:0'), tensor(102.0845, device='cuda:0'), tensor(103.8624, device='cuda:0')]

Others: [{'iter_num': 60, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, '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=4, microseconds=376439), datetime.timedelta(seconds=4, microseconds=372455), datetime.timedelta(seconds=4, microseconds=387393), datetime.timedelta(seconds=4, microseconds=388386), datetime.timedelta(seconds=4, microseconds=392373), datetime.timedelta(seconds=4, microseconds=383409), datetime.timedelta(seconds=4, microseconds=385402), datetime.timedelta(seconds=4, microseconds=399341), datetime.timedelta(seconds=4, microseconds=364490), datetime.timedelta(seconds=4, microseconds=377433)]

Phi time: [datetime.timedelta(seconds=4, microseconds=230918), datetime.timedelta(seconds=4, microseconds=208708), datetime.timedelta(seconds=4, microseconds=228514), datetime.timedelta(seconds=4, microseconds=269128), datetime.timedelta(seconds=4, microseconds=209869), datetime.timedelta(seconds=4, microseconds=242439), datetime.timedelta(seconds=4, microseconds=236964), datetime.timedelta(seconds=4, microseconds=264498), datetime.timedelta(seconds=4, microseconds=270295), datetime.timedelta(seconds=4, microseconds=202665)]

