Precision: [tensor(0.5692), tensor(0.1785), tensor(0.2071), tensor(0.1846), tensor(0.5610)]
Output distance: [tensor(5.1678), tensor(5.9491), tensor(5.8918), tensor(5.9370), tensor(5.1840)]
Prediction loss: [tensor(3.8365), tensor(2.0370), tensor(1.9922), tensor(3.1684), tensor(3.8507)]
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': 30, 'num_positive': tensor(3809), 'num_positive_true': tensor(20211)}, {'iter_num': 30, '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(74055.9844), tensor(87484.4922), tensor(86866.6406), tensor(89288.6328), tensor(74162.1094)]
Training loss: 0
Prediction time: [datetime.timedelta(seconds=2, microseconds=331308), datetime.timedelta(seconds=2, microseconds=354986), datetime.timedelta(seconds=2, microseconds=329198), datetime.timedelta(seconds=2, microseconds=345355), datetime.timedelta(seconds=2, microseconds=315537)]
Phi time: [datetime.timedelta(seconds=10, microseconds=665948), datetime.timedelta(seconds=9, microseconds=313220), datetime.timedelta(seconds=9, microseconds=282428), datetime.timedelta(seconds=10, microseconds=132363), datetime.timedelta(seconds=10, microseconds=147613)]
