Precision: [tensor(0.5555, device='cuda:0'), tensor(0.5553, device='cuda:0'), tensor(0.5548, device='cuda:0'), tensor(0.5567, device='cuda:0'), tensor(0.5537, device='cuda:0'), tensor(0.5548, device='cuda:0'), tensor(0.5528, device='cuda:0'), tensor(0.5536, device='cuda:0'), tensor(0.5561, device='cuda:0'), tensor(0.5521, device='cuda:0')]
Output distance: [tensor(4.9730, device='cuda:0'), tensor(4.9745, device='cuda:0'), tensor(4.9772, device='cuda:0'), tensor(4.9661, device='cuda:0'), tensor(4.9840, device='cuda:0'), tensor(4.9772, device='cuda:0'), tensor(4.9892, device='cuda:0'), tensor(4.9845, device='cuda:0'), tensor(4.9698, device='cuda:0'), tensor(4.9934, device='cuda:0')]
Prediction loss: [tensor(19026986., device='cuda:0'), tensor(18992530., device='cuda:0'), tensor(17860366., device='cuda:0'), tensor(18060218., device='cuda:0'), tensor(17704314., device='cuda:0'), tensor(19699140., device='cuda:0'), tensor(17102464., device='cuda:0'), tensor(18380500., device='cuda:0'), tensor(18293430., device='cuda:0'), tensor(19259688., device='cuda:0')]
Others: [{'iter_num': 9, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}]
Compressed training loss: [tensor(40875.8789, device='cuda:0'), tensor(41043.3672, device='cuda:0'), tensor(40848.0195, device='cuda:0'), tensor(40730.2305, device='cuda:0'), tensor(40883.3398, device='cuda:0'), tensor(40679.1328, device='cuda:0'), tensor(40937.3750, device='cuda:0'), tensor(40682.8516, device='cuda:0'), tensor(40844.9727, device='cuda:0'), tensor(40819.6914, device='cuda:0')]
Training loss: 0
Prediction time: [datetime.timedelta(seconds=1, microseconds=113279), datetime.timedelta(seconds=1, microseconds=91372), datetime.timedelta(seconds=1, microseconds=62493), datetime.timedelta(seconds=1, microseconds=96350), datetime.timedelta(seconds=1, microseconds=84401), datetime.timedelta(seconds=1, microseconds=64484), datetime.timedelta(seconds=1, microseconds=74443), datetime.timedelta(seconds=1, microseconds=94358), datetime.timedelta(seconds=1, microseconds=84401), datetime.timedelta(seconds=1, microseconds=53531)]
Phi time: [datetime.timedelta(microseconds=235003), datetime.timedelta(microseconds=256910), datetime.timedelta(microseconds=235999), datetime.timedelta(microseconds=235003), datetime.timedelta(microseconds=253923), datetime.timedelta(microseconds=232016), datetime.timedelta(microseconds=233013), datetime.timedelta(microseconds=235004), datetime.timedelta(microseconds=234007), datetime.timedelta(microseconds=236995)]
