Precision: [tensor(0.0255), tensor(0.0257), tensor(0.0252), tensor(0.0289), tensor(0.0255)]
Output distance: [tensor(6.2552), tensor(6.2547), tensor(6.2557), tensor(6.2484), tensor(6.2552)]
Prediction loss: [tensor(3.0812), tensor(2.1226), tensor(2.1483), tensor(2.0872), tensor(3.5113)]
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)}]
Compressed training loss: [tensor(88783.0312), tensor(86937.6953), tensor(87421.2969), tensor(86932.7500), tensor(89661.4062)]
Training loss: 0
Prediction time: [datetime.timedelta(microseconds=487022), datetime.timedelta(microseconds=480249), datetime.timedelta(microseconds=486165), datetime.timedelta(microseconds=486565), datetime.timedelta(microseconds=485933)]
Phi time: [datetime.timedelta(seconds=10, microseconds=160696), datetime.timedelta(seconds=10, microseconds=277673), datetime.timedelta(seconds=10, microseconds=295725), datetime.timedelta(seconds=10, microseconds=287964), datetime.timedelta(seconds=10, microseconds=201681)]
