Precision: [tensor(0.9977, device='cuda:0'), tensor(0.9983, device='cuda:0'), tensor(0.9988, device='cuda:0'), tensor(0.9985, device='cuda:0'), tensor(0.9983, device='cuda:0'), tensor(0.9980, device='cuda:0'), tensor(0.9987, device='cuda:0'), tensor(0.9980, device='cuda:0'), tensor(0.9978, device='cuda:0'), tensor(0.9978, device='cuda:0')]
Output distance: [tensor(19275.8848, device='cuda:0'), tensor(19212.5859, device='cuda:0'), tensor(19192.9941, device='cuda:0'), tensor(19167.6348, device='cuda:0'), tensor(19194.9961, device='cuda:0'), tensor(19249.4766, device='cuda:0'), tensor(19207.7695, device='cuda:0'), tensor(19219.8984, device='cuda:0'), tensor(19293.3711, device='cuda:0'), tensor(19224.4258, device='cuda:0')]
Prediction loss: [tensor(20544.7383, device='cuda:0'), tensor(19414.5156, device='cuda:0'), tensor(20282.0684, device='cuda:0'), tensor(20362.8887, device='cuda:0'), tensor(19171.7441, device='cuda:0'), tensor(19247.3867, device='cuda:0'), tensor(19710.2051, device='cuda:0'), tensor(20169.5176, device='cuda:0'), tensor(19595.4629, device='cuda:0'), tensor(19572.8809, device='cuda:0')]
Others: [{'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')}, {'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')}, {'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')}]
Compressed training loss: [tensor(20150726., device='cuda:0'), tensor(19212098., device='cuda:0'), tensor(19665950., device='cuda:0'), tensor(19651882., device='cuda:0'), tensor(18943500., device='cuda:0'), tensor(18835028., device='cuda:0'), tensor(18873288., device='cuda:0'), tensor(19695718., device='cuda:0'), tensor(20077952., device='cuda:0'), tensor(19257120., device='cuda:0')]
Training loss: Not calculated
Prediction time: [datetime.timedelta(microseconds=493903), datetime.timedelta(microseconds=622360), datetime.timedelta(microseconds=577551), datetime.timedelta(microseconds=566581), datetime.timedelta(microseconds=577552), datetime.timedelta(microseconds=570579), datetime.timedelta(microseconds=593483), datetime.timedelta(microseconds=562666), datetime.timedelta(microseconds=491918), datetime.timedelta(microseconds=532790)]
Phi time: [datetime.timedelta(microseconds=877281), datetime.timedelta(microseconds=931052), datetime.timedelta(microseconds=864333), datetime.timedelta(microseconds=897534), datetime.timedelta(microseconds=858360), datetime.timedelta(microseconds=869314), datetime.timedelta(microseconds=867661), datetime.timedelta(microseconds=860396), datetime.timedelta(microseconds=897296), datetime.timedelta(microseconds=890366)]
