Precision: [tensor(0.8205, device='cuda:0'), tensor(0.7967, device='cuda:0'), tensor(0.7899, device='cuda:0'), tensor(0.8146, device='cuda:0'), tensor(0.7968, device='cuda:0'), tensor(0.7940, device='cuda:0'), tensor(0.7959, device='cuda:0'), tensor(0.7840, device='cuda:0'), tensor(0.7819, device='cuda:0'), tensor(0.7949, device='cuda:0')]

Output distance: [tensor(3742.1345, device='cuda:0'), tensor(5487.0259, device='cuda:0'), tensor(4738.0537, device='cuda:0'), tensor(4479.2080, device='cuda:0'), tensor(5194.5464, device='cuda:0'), tensor(4405.3574, device='cuda:0'), tensor(5493.9785, device='cuda:0'), tensor(4872.1328, device='cuda:0'), tensor(5720.4927, device='cuda:0'), tensor(4780.0991, device='cuda:0')]

Prediction loss: [tensor(4101.4453, device='cuda:0'), tensor(5861.6128, device='cuda:0'), tensor(4793.1309, device='cuda:0'), tensor(5062.5513, device='cuda:0'), tensor(5955.5361, device='cuda:0'), tensor(4436.5342, device='cuda:0'), tensor(5732.4648, device='cuda:0'), tensor(5200.2070, device='cuda:0'), tensor(6196.4697, device='cuda:0'), tensor(5278.2212, device='cuda:0')]

Others: [{'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}]

Compressed training loss: [tensor(3687729.5000, device='cuda:0'), tensor(3633934.7500, device='cuda:0'), tensor(3492098.7500, device='cuda:0'), tensor(3777435.2500, device='cuda:0'), tensor(3713469.2500, device='cuda:0'), tensor(3565561.2500, device='cuda:0'), tensor(3703782., device='cuda:0'), tensor(3712664.7500, device='cuda:0'), tensor(3632369.7500, device='cuda:0'), tensor(3662213.7500, device='cuda:0')]

Training loss: 3614272.5

Prediction time: [datetime.timedelta(microseconds=87628), datetime.timedelta(microseconds=84640), datetime.timedelta(microseconds=83642), datetime.timedelta(microseconds=81655), datetime.timedelta(microseconds=84642), datetime.timedelta(microseconds=82650), datetime.timedelta(microseconds=80658), datetime.timedelta(microseconds=82652), datetime.timedelta(microseconds=83643), datetime.timedelta(microseconds=82650)]

Phi time: [datetime.timedelta(seconds=1, microseconds=484821), datetime.timedelta(microseconds=864977), datetime.timedelta(microseconds=862257), datetime.timedelta(microseconds=874832), datetime.timedelta(microseconds=875664), datetime.timedelta(microseconds=868409), datetime.timedelta(microseconds=912826), datetime.timedelta(microseconds=889733), datetime.timedelta(microseconds=889525), datetime.timedelta(microseconds=890867)]

