Precision: [tensor(0.6826, device='cuda:0'), tensor(0.6876, device='cuda:0'), tensor(0.6852, device='cuda:0'), tensor(0.6781, device='cuda:0'), tensor(0.6784, device='cuda:0'), tensor(0.6826, device='cuda:0'), tensor(0.6758, device='cuda:0'), tensor(0.6850, device='cuda:0'), tensor(0.6847, device='cuda:0'), tensor(0.6865, device='cuda:0')]

Output distance: [tensor(4.9409, device='cuda:0'), tensor(4.9310, device='cuda:0'), tensor(4.9357, device='cuda:0'), tensor(4.9499, device='cuda:0'), tensor(4.9493, device='cuda:0'), tensor(4.9409, device='cuda:0'), tensor(4.9546, device='cuda:0'), tensor(4.9362, device='cuda:0'), tensor(4.9367, device='cuda:0'), tensor(4.9331, device='cuda:0')]

Prediction loss: [tensor(19438354., device='cuda:0'), tensor(20885702., device='cuda:0'), tensor(18543968., device='cuda:0'), tensor(18418382., device='cuda:0'), tensor(17789962., device='cuda:0'), tensor(18829798., device='cuda:0'), tensor(19180892., device='cuda:0'), tensor(17806918., device='cuda:0'), tensor(17483950., device='cuda:0'), tensor(19044284., 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(40812.8789, device='cuda:0'), tensor(40814.6328, device='cuda:0'), tensor(40735.5977, device='cuda:0'), tensor(40789.2422, device='cuda:0'), tensor(40982.4727, device='cuda:0'), tensor(41008.4180, device='cuda:0'), tensor(40860.8086, device='cuda:0'), tensor(40762.2969, device='cuda:0'), tensor(40821.5273, device='cuda:0'), tensor(40876.3594, device='cuda:0')]

Training loss: 0

Prediction time: [datetime.timedelta(microseconds=916227), datetime.timedelta(microseconds=914430), datetime.timedelta(microseconds=895760), datetime.timedelta(microseconds=900117), datetime.timedelta(microseconds=890381), datetime.timedelta(microseconds=892259), datetime.timedelta(microseconds=869113), datetime.timedelta(microseconds=909995), datetime.timedelta(microseconds=894481), datetime.timedelta(microseconds=899986)]

Phi time: [datetime.timedelta(microseconds=441113), datetime.timedelta(microseconds=207684), datetime.timedelta(microseconds=236526), datetime.timedelta(microseconds=201912), datetime.timedelta(microseconds=199992), datetime.timedelta(microseconds=227067), datetime.timedelta(microseconds=204639), datetime.timedelta(microseconds=221033), datetime.timedelta(microseconds=199882), datetime.timedelta(microseconds=199897)]

