Precision: [tensor(0.7088), tensor(0.7120), tensor(0.7036), tensor(0.7057), tensor(0.7010), tensor(0.7075), tensor(0.7107), tensor(0.7067), tensor(0.7088), tensor(0.6997)]
Output distance: [tensor(4.8884), tensor(4.8821), tensor(4.8989), tensor(4.8947), tensor(4.9042), tensor(4.8910), tensor(4.8847), tensor(4.8926), tensor(4.8884), tensor(4.9068)]
Prediction loss: [tensor(34.9442), tensor(37.6264), tensor(36.6907), tensor(38.0109), tensor(36.6661), tensor(34.8992), tensor(37.8729), tensor(36.9415), tensor(36.4723), tensor(36.5345)]
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': 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': 5, '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(48551.9414), tensor(48685.9336), tensor(48680.5625), tensor(48777.4609), tensor(48927.9180), tensor(48618.2852), tensor(48890.2344), tensor(48757.7305), tensor(48746.8398), tensor(48898.0938)]
Training loss: 0
Prediction time: [datetime.timedelta(seconds=1, microseconds=21190), datetime.timedelta(seconds=1, microseconds=5679), datetime.timedelta(microseconds=970264), datetime.timedelta(microseconds=963997), datetime.timedelta(seconds=1, microseconds=20300), datetime.timedelta(microseconds=978580), datetime.timedelta(microseconds=986951), datetime.timedelta(microseconds=993124), datetime.timedelta(microseconds=981676), datetime.timedelta(seconds=1, microseconds=54529)]
Phi time: [datetime.timedelta(seconds=89, microseconds=492036), datetime.timedelta(seconds=87, microseconds=115558), datetime.timedelta(seconds=87, microseconds=595808), datetime.timedelta(seconds=87, microseconds=439573), datetime.timedelta(seconds=87, microseconds=110417), datetime.timedelta(seconds=87, microseconds=943696), datetime.timedelta(seconds=87, microseconds=64579), datetime.timedelta(seconds=87, microseconds=157262), datetime.timedelta(seconds=86, microseconds=987440), datetime.timedelta(seconds=88, microseconds=979019)]
