Precision: [tensor(0.2352), tensor(0.2287), tensor(0.2352), tensor(0.5595), tensor(0.5778)]
Output distance: [tensor(5.8357), tensor(5.8488), tensor(5.8357), tensor(5.1872), tensor(5.1504)]
Prediction loss: [tensor(1.9666), tensor(2.0632), tensor(1.9676), tensor(3.9057), tensor(3.9029)]
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': 5, 'num_positive': tensor(3809), 'num_positive_true': tensor(20211)}, {'iter_num': 30, 'num_positive': tensor(3809), 'num_positive_true': tensor(20211)}]
Compressed training loss: [tensor(87161.2109), tensor(87437.2344), tensor(87068.8828), tensor(74390.9141), tensor(74300.2969)]
Training loss: 0
Prediction time: [datetime.timedelta(microseconds=467586), datetime.timedelta(microseconds=475480), datetime.timedelta(microseconds=491252), datetime.timedelta(microseconds=451674), datetime.timedelta(seconds=2, microseconds=321736)]
Phi time: [datetime.timedelta(seconds=9, microseconds=224047), datetime.timedelta(seconds=10, microseconds=436933), datetime.timedelta(seconds=10, microseconds=524674), datetime.timedelta(seconds=10, microseconds=259135), datetime.timedelta(seconds=10, microseconds=358373)]
