Precision: [tensor(0.4000, device='cuda:0'), tensor(0.4048, device='cuda:0'), tensor(0.4021, device='cuda:0'), tensor(0.4057, device='cuda:0'), tensor(0.4063, device='cuda:0'), tensor(0.3991, device='cuda:0'), tensor(0.4023, device='cuda:0'), tensor(0.3997, device='cuda:0'), tensor(0.3987, device='cuda:0'), tensor(0.4069, device='cuda:0')]

Output distance: [tensor(19.6255, device='cuda:0'), tensor(19.5967, device='cuda:0'), tensor(19.6128, device='cuda:0'), tensor(19.5910, device='cuda:0'), tensor(19.5874, device='cuda:0'), tensor(19.6306, device='cuda:0'), tensor(19.6119, device='cuda:0'), tensor(19.6273, device='cuda:0'), tensor(19.6330, device='cuda:0'), tensor(19.5840, device='cuda:0')]

Prediction loss: [tensor(103.4728, device='cuda:0'), tensor(104.8059, device='cuda:0'), tensor(103.8489, device='cuda:0'), tensor(103.7262, device='cuda:0'), tensor(105.1516, device='cuda:0'), tensor(104.0830, device='cuda:0'), tensor(104.0106, device='cuda:0'), tensor(104.6192, device='cuda:0'), tensor(104.4982, device='cuda:0'), tensor(103.8666, device='cuda:0')]

Others: [{'iter_num': 13, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 13, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 13, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 13, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 13, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 13, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 13, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 13, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 15, '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=773308), datetime.timedelta(seconds=2, microseconds=639016), datetime.timedelta(seconds=2, microseconds=753949), datetime.timedelta(seconds=2, microseconds=750025), datetime.timedelta(seconds=2, microseconds=742656), datetime.timedelta(seconds=2, microseconds=750163), datetime.timedelta(seconds=2, microseconds=826341), datetime.timedelta(seconds=2, microseconds=746322), datetime.timedelta(seconds=2, microseconds=749926), datetime.timedelta(seconds=2, microseconds=886088)]

Phi time: [datetime.timedelta(seconds=4, microseconds=678086), datetime.timedelta(seconds=4, microseconds=612539), datetime.timedelta(seconds=4, microseconds=610480), datetime.timedelta(seconds=4, microseconds=631624), datetime.timedelta(seconds=4, microseconds=635033), datetime.timedelta(seconds=4, microseconds=683282), datetime.timedelta(seconds=4, microseconds=610872), datetime.timedelta(seconds=4, microseconds=642500), datetime.timedelta(seconds=4, microseconds=598749), datetime.timedelta(seconds=4, microseconds=703399)]

