Precision: [tensor(0.5541, device='cuda:0'), tensor(0.5536, device='cuda:0'), tensor(0.5562, device='cuda:0'), tensor(0.5505, device='cuda:0'), tensor(0.5535, device='cuda:0'), tensor(0.5585, device='cuda:0'), tensor(0.5570, device='cuda:0'), tensor(0.5544, device='cuda:0'), tensor(0.5545, device='cuda:0'), tensor(0.5503, device='cuda:0')]
Output distance: [tensor(997865.7500, device='cuda:0'), tensor(1032450.1250, device='cuda:0'), tensor(1181153., device='cuda:0'), tensor(948531., device='cuda:0'), tensor(968476.8125, device='cuda:0'), tensor(992849.6875, device='cuda:0'), tensor(878682.9375, device='cuda:0'), tensor(743913.8750, device='cuda:0'), tensor(1087371.5000, device='cuda:0'), tensor(796472.7500, device='cuda:0')]
Prediction loss: [tensor(17672164., device='cuda:0'), tensor(17212606., device='cuda:0'), tensor(16994478., device='cuda:0'), tensor(18732918., device='cuda:0'), tensor(17899480., device='cuda:0'), tensor(16940668., device='cuda:0'), tensor(18322010., device='cuda:0'), tensor(18817546., device='cuda:0'), tensor(17170150., device='cuda:0'), tensor(17837098., device='cuda:0')]
Others: [{'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': 9, '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')}, {'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': 5, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}]
Compressed training loss: [tensor(40822.1367, device='cuda:0'), tensor(40791.8203, device='cuda:0'), tensor(40951.7617, device='cuda:0'), tensor(40921.3203, device='cuda:0'), tensor(40828.8203, device='cuda:0'), tensor(40874.8633, device='cuda:0'), tensor(40825.7070, device='cuda:0'), tensor(40754.8633, device='cuda:0'), tensor(40692.9609, device='cuda:0'), tensor(40769.9375, device='cuda:0')]
Training loss: 0
Prediction time: [datetime.timedelta(microseconds=126461), datetime.timedelta(microseconds=130444), datetime.timedelta(microseconds=138410), datetime.timedelta(microseconds=112519), datetime.timedelta(microseconds=123472), datetime.timedelta(microseconds=125465), datetime.timedelta(microseconds=113516), datetime.timedelta(microseconds=115508), datetime.timedelta(microseconds=130445), datetime.timedelta(microseconds=114512)]
Phi time: [datetime.timedelta(microseconds=233013), datetime.timedelta(microseconds=242972), datetime.timedelta(microseconds=234011), datetime.timedelta(microseconds=236998), datetime.timedelta(microseconds=234011), datetime.timedelta(microseconds=235006), datetime.timedelta(microseconds=237993), datetime.timedelta(microseconds=234011), datetime.timedelta(microseconds=235006), datetime.timedelta(microseconds=246955)]
