Precision: [tensor(0.5525, device='cuda:0'), tensor(0.5546, device='cuda:0'), tensor(0.5542, device='cuda:0'), tensor(0.5532, device='cuda:0'), tensor(0.5554, device='cuda:0'), tensor(0.5554, device='cuda:0'), tensor(0.5550, device='cuda:0'), tensor(0.5512, device='cuda:0'), tensor(0.5523, device='cuda:0'), tensor(0.5515, device='cuda:0')]

Output distance: [tensor(4.9913, device='cuda:0'), tensor(4.9787, device='cuda:0'), tensor(4.9808, device='cuda:0'), tensor(4.9871, device='cuda:0'), tensor(4.9740, device='cuda:0'), tensor(4.9735, device='cuda:0'), tensor(4.9761, device='cuda:0'), tensor(4.9987, device='cuda:0'), tensor(4.9924, device='cuda:0'), tensor(4.9971, device='cuda:0')]

Prediction loss: [tensor(18928858., device='cuda:0'), tensor(18715302., device='cuda:0'), tensor(19436322., device='cuda:0'), tensor(19016524., device='cuda:0'), tensor(18884518., device='cuda:0'), tensor(18705204., device='cuda:0'), tensor(18821200., device='cuda:0'), tensor(18839510., device='cuda:0'), tensor(18975928., device='cuda:0'), tensor(18857950., device='cuda:0')]

Others: [{'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}]

Compressed training loss: [tensor(40871.0664, device='cuda:0'), tensor(40798.6484, device='cuda:0'), tensor(40860.3281, device='cuda:0'), tensor(40762.8945, device='cuda:0'), tensor(40762.7500, device='cuda:0'), tensor(40874.2461, device='cuda:0'), tensor(40725.3555, device='cuda:0'), tensor(40828.8047, device='cuda:0'), tensor(40903.4766, device='cuda:0'), tensor(40820.1094, device='cuda:0')]

Training loss: 0

Prediction time: [datetime.timedelta(seconds=76, microseconds=50450), datetime.timedelta(seconds=76, microseconds=53144), datetime.timedelta(seconds=76, microseconds=273144), datetime.timedelta(seconds=76, microseconds=408104), datetime.timedelta(seconds=75, microseconds=931751), datetime.timedelta(seconds=75, microseconds=836031), datetime.timedelta(seconds=76, microseconds=96757), datetime.timedelta(seconds=76, microseconds=64671), datetime.timedelta(seconds=76, microseconds=712872), datetime.timedelta(seconds=76, microseconds=318837)]

Phi time: [datetime.timedelta(microseconds=293684), datetime.timedelta(microseconds=531694), datetime.timedelta(microseconds=296381), datetime.timedelta(microseconds=285792), datetime.timedelta(microseconds=512412), datetime.timedelta(microseconds=513355), datetime.timedelta(microseconds=295652), datetime.timedelta(microseconds=301449), datetime.timedelta(microseconds=479261), datetime.timedelta(microseconds=449918)]

