Precision: [tensor(0.6621, device='cuda:0'), tensor(0.6600, device='cuda:0'), tensor(0.6584, device='cuda:0'), tensor(0.6569, device='cuda:0'), tensor(0.6511, device='cuda:0'), tensor(0.6626, device='cuda:0'), tensor(0.6621, device='cuda:0'), tensor(0.6521, device='cuda:0'), tensor(0.6542, device='cuda:0'), tensor(0.6558, device='cuda:0')]

Output distance: [tensor(4.9819, device='cuda:0'), tensor(4.9861, device='cuda:0'), tensor(4.9892, device='cuda:0'), tensor(4.9924, device='cuda:0'), tensor(5.0039, device='cuda:0'), tensor(4.9808, device='cuda:0'), tensor(4.9819, device='cuda:0'), tensor(5.0018, device='cuda:0'), tensor(4.9976, device='cuda:0'), tensor(4.9945, device='cuda:0')]

Prediction loss: [tensor(17770716., device='cuda:0'), tensor(18173760., device='cuda:0'), tensor(16788686., device='cuda:0'), tensor(18734272., device='cuda:0'), tensor(18619996., device='cuda:0'), tensor(17065352., device='cuda:0'), tensor(19389780., device='cuda:0'), tensor(18069158., device='cuda:0'), tensor(20363408., device='cuda:0'), tensor(21545456., device='cuda:0')]

Others: [{'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}]

Compressed training loss: [tensor(40907.3516, device='cuda:0'), tensor(40717.7969, device='cuda:0'), tensor(40779.4141, device='cuda:0'), tensor(41059.9023, device='cuda:0'), tensor(40632.6133, device='cuda:0'), tensor(40791.4258, device='cuda:0'), tensor(40961.6797, device='cuda:0'), tensor(41031.0703, device='cuda:0'), tensor(40803.1602, device='cuda:0'), tensor(41105.0742, device='cuda:0')]

Training loss: 0

Prediction time: [datetime.timedelta(seconds=27, microseconds=846165), datetime.timedelta(seconds=27, microseconds=979831), datetime.timedelta(seconds=28, microseconds=51803), datetime.timedelta(seconds=28, microseconds=72766), datetime.timedelta(seconds=28, microseconds=15486), datetime.timedelta(seconds=27, microseconds=997815), datetime.timedelta(seconds=27, microseconds=725774), datetime.timedelta(seconds=27, microseconds=886313), datetime.timedelta(seconds=27, microseconds=723623), datetime.timedelta(seconds=28, microseconds=78828)]

Phi time: [datetime.timedelta(microseconds=192651), datetime.timedelta(microseconds=360999), datetime.timedelta(microseconds=323632), datetime.timedelta(microseconds=439060), datetime.timedelta(microseconds=415605), datetime.timedelta(microseconds=278401), datetime.timedelta(microseconds=271605), datetime.timedelta(microseconds=347264), datetime.timedelta(microseconds=363490), datetime.timedelta(microseconds=357896)]

