Precision: [tensor(0.2413), tensor(0.2234), tensor(0.2347), tensor(0.5642), tensor(0.7057)]
Output distance: [tensor(5.8236), tensor(5.8593), tensor(5.8367), tensor(5.1777), tensor(4.8947)]
Prediction loss: [tensor(2.0325), tensor(3.0742), tensor(1.9673), tensor(3.8759), tensor(41.5444)]
Others: [{'iter_num': 5, 'num_positive': tensor(3809), 'num_positive_true': tensor(20211)}, {'iter_num': 5, 'num_positive': tensor(3809), 'num_positive_true': tensor(20211)}, {'iter_num': 5, 'num_positive': tensor(3809), 'num_positive_true': tensor(20211)}, {'iter_num': 6, 'num_positive': tensor(3809), 'num_positive_true': tensor(20211)}, {'iter_num': 5, 'num_positive': tensor(3809), 'num_positive_true': tensor(20211)}]
Compressed training loss: [tensor(87345.4688), tensor(88919.8984), tensor(87151.8594), tensor(74389.1328), tensor(49568.3945)]
Training loss: 0
Prediction time: [datetime.timedelta(microseconds=525778), datetime.timedelta(microseconds=515320), datetime.timedelta(microseconds=525959), datetime.timedelta(microseconds=587292), datetime.timedelta(microseconds=554221)]
Phi time: [datetime.timedelta(seconds=10, microseconds=515312), datetime.timedelta(seconds=10, microseconds=591087), datetime.timedelta(seconds=10, microseconds=698855), datetime.timedelta(seconds=10, microseconds=610395), datetime.timedelta(seconds=28, microseconds=424029)]
