Precision: [tensor(0.9982, device='cuda:0'), tensor(0.9982, device='cuda:0'), tensor(0.9980, device='cuda:0'), tensor(0.9975, device='cuda:0'), tensor(0.9982, device='cuda:0'), tensor(0.9983, device='cuda:0'), tensor(0.9978, device='cuda:0'), tensor(0.9985, device='cuda:0'), tensor(0.9987, device='cuda:0'), tensor(0.9983, device='cuda:0')]
Output distance: [tensor(18999.1094, device='cuda:0'), tensor(18951.4180, device='cuda:0'), tensor(18923.0020, device='cuda:0'), tensor(18996.3301, device='cuda:0'), tensor(18967.0820, device='cuda:0'), tensor(18976.6055, device='cuda:0'), tensor(18933.4688, device='cuda:0'), tensor(18908.2773, device='cuda:0'), tensor(18914.5117, device='cuda:0'), tensor(18959.1133, device='cuda:0')]
Prediction loss: [tensor(18633.4590, device='cuda:0'), tensor(19367.5938, device='cuda:0'), tensor(19221.9746, device='cuda:0'), tensor(19284.6680, device='cuda:0'), tensor(20141.8027, device='cuda:0'), tensor(19935.9219, device='cuda:0'), tensor(19713.2910, device='cuda:0'), tensor(19138.7754, device='cuda:0'), tensor(19525.3867, device='cuda:0'), tensor(18959.6309, device='cuda:0')]
Others: [{'iter_num': 5, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}]
Compressed training loss: [tensor(19347722., device='cuda:0'), tensor(19345526., device='cuda:0'), tensor(19158176., device='cuda:0'), tensor(19938310., device='cuda:0'), tensor(20083024., device='cuda:0'), tensor(19783888., device='cuda:0'), tensor(19613138., device='cuda:0'), tensor(19318192., device='cuda:0'), tensor(19545052., device='cuda:0'), tensor(19339526., device='cuda:0')]
Training loss: Not calculated
Prediction time: [datetime.timedelta(microseconds=493906), datetime.timedelta(microseconds=506847), datetime.timedelta(microseconds=599458), datetime.timedelta(microseconds=470005), datetime.timedelta(microseconds=517805), datetime.timedelta(microseconds=591492), datetime.timedelta(microseconds=484945), datetime.timedelta(microseconds=593483), datetime.timedelta(microseconds=552650), datetime.timedelta(microseconds=554647)]
Phi time: [datetime.timedelta(microseconds=870659), datetime.timedelta(microseconds=883487), datetime.timedelta(microseconds=904893), datetime.timedelta(microseconds=865124), datetime.timedelta(microseconds=896863), datetime.timedelta(microseconds=904325), datetime.timedelta(microseconds=868343), datetime.timedelta(microseconds=892517), datetime.timedelta(microseconds=866826), datetime.timedelta(microseconds=863406)]
