Precision: [tensor(0.2313), tensor(0.7036), tensor(0.2339), tensor(0.5634), tensor(0.5652)]
Output distance: [tensor(5.8435), tensor(4.8989), tensor(5.8383), tensor(5.1793), tensor(5.1756)]
Prediction loss: [tensor(1.9709), tensor(39.4238), tensor(3.0780), tensor(3.8603), tensor(3.8446)]
Others: [{'iter_num': 5, 'num_positive': tensor(3809), 'num_positive_true': tensor(20211)}, {'iter_num': 4, 'num_positive': tensor(3809), 'num_positive_true': tensor(20211)}, {'iter_num': 7, 'num_positive': tensor(3809), 'num_positive_true': tensor(20211)}, {'iter_num': 4, '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(86749.9141), tensor(49665.9531), tensor(88974.6016), tensor(74274.9453), tensor(74235.1797)]
Training loss: 0
Prediction time: [datetime.timedelta(microseconds=762014), datetime.timedelta(microseconds=624462), datetime.timedelta(seconds=1, microseconds=45892), datetime.timedelta(microseconds=617065), datetime.timedelta(microseconds=653660)]
Phi time: [datetime.timedelta(seconds=10, microseconds=299786), datetime.timedelta(seconds=27, microseconds=149920), datetime.timedelta(seconds=10, microseconds=156278), datetime.timedelta(seconds=9, microseconds=949379), datetime.timedelta(seconds=10, microseconds=164948)]
