Precision: [tensor(0.2392), tensor(0.5663), tensor(0.5645), tensor(0.2360), tensor(0.5718)]
Output distance: [tensor(5.8278), tensor(5.1735), tensor(5.1772), tensor(5.8341), tensor(5.1625)]
Prediction loss: [tensor(3.1642), tensor(3.9124), tensor(3.9113), tensor(3.2364), tensor(3.9090)]
Others: [{'iter_num': 5, 'num_positive': tensor(3809), 'num_positive_true': tensor(20211)}, {'iter_num': 6, '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': 6, 'num_positive': tensor(3809), 'num_positive_true': tensor(20211)}]
Compressed training loss: [tensor(89150.4453), tensor(74428.0078), tensor(74258.3984), tensor(89232.3438), tensor(74166.3828)]
Training loss: 0
Prediction time: [datetime.timedelta(microseconds=487680), datetime.timedelta(microseconds=577382), datetime.timedelta(microseconds=485641), datetime.timedelta(microseconds=484583), datetime.timedelta(microseconds=573674)]
Phi time: [datetime.timedelta(seconds=10, microseconds=366460), datetime.timedelta(seconds=9, microseconds=946125), datetime.timedelta(seconds=10, microseconds=39357), datetime.timedelta(seconds=9, microseconds=828367), datetime.timedelta(seconds=10, microseconds=100224)]
