Precision: [tensor(0.0410, device='cuda:0'), tensor(0.0326, device='cuda:0'), tensor(0.0381, device='cuda:0'), tensor(0.0359, device='cuda:0'), tensor(0.0322, device='cuda:0'), tensor(0.0386, device='cuda:0'), tensor(0.0307, device='cuda:0'), tensor(0.0370, device='cuda:0'), tensor(0.0427, device='cuda:0'), tensor(0.0414, device='cuda:0')]

Output distance: [tensor(23.6158, device='cuda:0'), tensor(23.6992, device='cuda:0'), tensor(23.6445, device='cuda:0'), tensor(23.6663, device='cuda:0'), tensor(23.7031, device='cuda:0'), tensor(23.6391, device='cuda:0'), tensor(23.7180, device='cuda:0'), tensor(23.6554, device='cuda:0'), tensor(23.5979, device='cuda:0'), tensor(23.6112, device='cuda:0')]

Prediction loss: [tensor(92.4642, device='cuda:0'), tensor(89.7023, device='cuda:0'), tensor(92.8667, device='cuda:0'), tensor(90.9157, device='cuda:0'), tensor(88.9251, device='cuda:0'), tensor(89.3212, device='cuda:0'), tensor(88.8416, device='cuda:0'), tensor(91.2343, device='cuda:0'), tensor(92.4834, device='cuda:0'), tensor(89.6316, device='cuda:0')]

Others: [{'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}]

Compressed training loss: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]

Training loss: 0

Prediction time: [datetime.timedelta(seconds=1, microseconds=930809), datetime.timedelta(seconds=1, microseconds=920854), datetime.timedelta(seconds=1, microseconds=933798), datetime.timedelta(seconds=1, microseconds=931805), datetime.timedelta(seconds=1, microseconds=943756), datetime.timedelta(seconds=1, microseconds=928817), datetime.timedelta(seconds=1, microseconds=934792), datetime.timedelta(seconds=1, microseconds=913881), datetime.timedelta(seconds=1, microseconds=926827), datetime.timedelta(seconds=1, microseconds=939773)]

Phi time: [datetime.timedelta(seconds=4, microseconds=731933), datetime.timedelta(seconds=4, microseconds=636338), datetime.timedelta(seconds=4, microseconds=643309), datetime.timedelta(seconds=4, microseconds=636336), datetime.timedelta(seconds=4, microseconds=647292), datetime.timedelta(seconds=4, microseconds=643308), datetime.timedelta(seconds=4, microseconds=638324), datetime.timedelta(seconds=4, microseconds=660237), datetime.timedelta(seconds=4, microseconds=640322), datetime.timedelta(seconds=4, microseconds=661231)]

