Precision: [tensor(0.2464, device='cuda:0'), tensor(0.2556, device='cuda:0'), tensor(0.2539, device='cuda:0'), tensor(0.2638, device='cuda:0'), tensor(0.2471, device='cuda:0'), tensor(0.2361, device='cuda:0'), tensor(0.2452, device='cuda:0'), tensor(0.2364, device='cuda:0'), tensor(0.2526, device='cuda:0'), tensor(0.2443, device='cuda:0')]

Output distance: [tensor(20.5469, device='cuda:0'), tensor(20.4915, device='cuda:0'), tensor(20.5018, device='cuda:0'), tensor(20.4429, device='cuda:0'), tensor(20.5429, device='cuda:0'), tensor(20.6088, device='cuda:0'), tensor(20.5541, device='cuda:0'), tensor(20.6070, device='cuda:0'), tensor(20.5100, device='cuda:0'), tensor(20.5599, device='cuda:0')]

Prediction loss: [tensor(101.4722, device='cuda:0'), tensor(102.5023, device='cuda:0'), tensor(102.2211, device='cuda:0'), tensor(101.3842, device='cuda:0'), tensor(101.9449, device='cuda:0'), tensor(102.5042, device='cuda:0'), tensor(102.7478, device='cuda:0'), tensor(101.2321, device='cuda:0'), tensor(104.3413, device='cuda:0'), tensor(102.8971, device='cuda:0')]

Others: [{'iter_num': 15, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 17, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 17, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 17, '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')}, {'iter_num': 19, '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')}, {'iter_num': 17, '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')}, {'iter_num': 17, '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=775228), datetime.timedelta(seconds=2, microseconds=699978), datetime.timedelta(seconds=2, microseconds=699983), datetime.timedelta(seconds=2, microseconds=723348), datetime.timedelta(seconds=2, microseconds=626568), datetime.timedelta(seconds=2, microseconds=778836), datetime.timedelta(seconds=2, microseconds=634561), datetime.timedelta(seconds=2, microseconds=711500), datetime.timedelta(seconds=2, microseconds=616552), datetime.timedelta(seconds=2, microseconds=708315)]

Phi time: [datetime.timedelta(seconds=4, microseconds=578842), datetime.timedelta(seconds=4, microseconds=537764), datetime.timedelta(seconds=4, microseconds=305085), datetime.timedelta(seconds=4, microseconds=240122), datetime.timedelta(seconds=4, microseconds=226092), datetime.timedelta(seconds=4, microseconds=238571), datetime.timedelta(seconds=4, microseconds=281919), datetime.timedelta(seconds=4, microseconds=253872), datetime.timedelta(seconds=4, microseconds=250622), datetime.timedelta(seconds=4, microseconds=249935)]

