Precision: [tensor(0.5634), tensor(0.2363), tensor(0.2400), tensor(0.5718), tensor(0.2182)]
Output distance: [tensor(5.1793), tensor(5.8336), tensor(5.8262), tensor(5.1625), tensor(5.8698)]
Prediction loss: [tensor(3.8779), tensor(1.9752), tensor(2.0193), tensor(3.8991), tensor(2.0963)]
Others: [{'iter_num': 30, 'num_positive': tensor(3809), 'num_positive_true': tensor(20211)}, {'iter_num': 30, 'num_positive': tensor(3809), 'num_positive_true': tensor(20211)}, {'iter_num': 4, 'num_positive': tensor(3809), 'num_positive_true': tensor(20211)}, {'iter_num': 5, 'num_positive': tensor(3809), 'num_positive_true': tensor(20211)}, {'iter_num': 4, 'num_positive': tensor(3809), 'num_positive_true': tensor(20211)}]
Compressed training loss: [tensor(74424.6484), tensor(86797.3984), tensor(87211.4766), tensor(74049.9531), tensor(87655.6406)]
Training loss: 0
Prediction time: [datetime.timedelta(seconds=2, microseconds=515243), datetime.timedelta(seconds=2, microseconds=338766), datetime.timedelta(microseconds=386871), datetime.timedelta(microseconds=644786), datetime.timedelta(microseconds=372216)]
Phi time: [datetime.timedelta(seconds=10, microseconds=54254), datetime.timedelta(seconds=10, microseconds=347851), datetime.timedelta(seconds=9, microseconds=281388), datetime.timedelta(seconds=10, microseconds=357274), datetime.timedelta(seconds=10, microseconds=357441)]
