Precision: [tensor(0.6344, device='cuda:0'), tensor(0.6324, device='cuda:0'), tensor(0.6316, device='cuda:0'), tensor(0.6253, device='cuda:0'), tensor(0.6267, device='cuda:0'), tensor(0.6290, device='cuda:0'), tensor(0.6275, device='cuda:0'), tensor(0.6240, device='cuda:0'), tensor(0.6319, device='cuda:0'), tensor(0.6331, device='cuda:0')]
Output distance: [tensor(4.9073, device='cuda:0'), tensor(4.9134, device='cuda:0'), tensor(4.9155, device='cuda:0'), tensor(4.9333, device='cuda:0'), tensor(4.9268, device='cuda:0'), tensor(4.9252, device='cuda:0'), tensor(4.9281, device='cuda:0'), tensor(4.9367, device='cuda:0'), tensor(4.9144, device='cuda:0'), tensor(4.9139, device='cuda:0')]
Prediction loss: [tensor(17893746., device='cuda:0'), tensor(18471470., device='cuda:0'), tensor(17213646., device='cuda:0'), tensor(19604106., device='cuda:0'), tensor(19312538., device='cuda:0'), tensor(17978010., device='cuda:0'), tensor(19368996., device='cuda:0'), tensor(18301286., device='cuda:0'), tensor(20466908., device='cuda:0'), tensor(18400602., device='cuda:0')]
Others: [{'iter_num': 5, 'num_positive': tensor(5653, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(5650, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(5654, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(5666, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(5703, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(5623, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(5646, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(5675, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(5654, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(5614, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}]
Compressed training loss: [tensor(40762.0781, device='cuda:0'), tensor(40702.4844, device='cuda:0'), tensor(40870.5781, device='cuda:0'), tensor(40731.7578, device='cuda:0'), tensor(40937.5117, device='cuda:0'), tensor(40897.5391, device='cuda:0'), tensor(40743.2227, device='cuda:0'), tensor(40936.6016, device='cuda:0'), tensor(40807.1055, device='cuda:0'), tensor(40895.2383, device='cuda:0')]
Training loss: 0
Prediction time: [datetime.timedelta(seconds=1, microseconds=18633), datetime.timedelta(seconds=1, microseconds=49599), datetime.timedelta(seconds=1, microseconds=37605), datetime.timedelta(microseconds=990782), datetime.timedelta(seconds=1, microseconds=24610), datetime.timedelta(seconds=1, microseconds=38648), datetime.timedelta(seconds=1, microseconds=60505), datetime.timedelta(seconds=1, microseconds=6782), datetime.timedelta(seconds=1, microseconds=47610), datetime.timedelta(seconds=1, microseconds=36607)]
Phi time: [datetime.timedelta(microseconds=234007), datetime.timedelta(microseconds=242967), datetime.timedelta(microseconds=249001), datetime.timedelta(microseconds=248966), datetime.timedelta(microseconds=243961), datetime.timedelta(microseconds=231962), datetime.timedelta(microseconds=246952), datetime.timedelta(microseconds=228978), datetime.timedelta(microseconds=241926), datetime.timedelta(microseconds=242965)]
