Precision: [tensor(0.9995, device='cuda:0'), tensor(0.9993, device='cuda:0'), tensor(0.9995, device='cuda:0'), tensor(0.9995, device='cuda:0'), tensor(0.9993, device='cuda:0'), tensor(0.9993, device='cuda:0'), tensor(0.9993, device='cuda:0'), tensor(0.9995, device='cuda:0'), tensor(0.9993, device='cuda:0'), tensor(0.9993, device='cuda:0')]

Output distance: [tensor(144621.8281, device='cuda:0'), tensor(139317.0156, device='cuda:0'), tensor(140656.2500, device='cuda:0'), tensor(142782.4062, device='cuda:0'), tensor(139478.5938, device='cuda:0'), tensor(139428.0625, device='cuda:0'), tensor(141309.2188, device='cuda:0'), tensor(145383.0781, device='cuda:0'), tensor(140338.8125, device='cuda:0'), tensor(140543.8281, device='cuda:0')]

Prediction loss: [tensor(136040.4531, device='cuda:0'), tensor(138588.9219, device='cuda:0'), tensor(139104.0781, device='cuda:0'), tensor(142688.6406, device='cuda:0'), tensor(138792.5625, device='cuda:0'), tensor(138615.4688, device='cuda:0'), tensor(140173.5312, device='cuda:0'), tensor(135460.0312, device='cuda:0'), tensor(135172.7188, device='cuda:0'), tensor(138781.7188, device='cuda:0')]

Others: [{'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}]

Compressed training loss: [tensor(1.9207e+08, device='cuda:0'), tensor(1.9447e+08, device='cuda:0'), tensor(1.9176e+08, device='cuda:0'), tensor(1.9392e+08, device='cuda:0'), tensor(1.9462e+08, device='cuda:0'), tensor(1.9458e+08, device='cuda:0'), tensor(1.9364e+08, device='cuda:0'), tensor(1.9232e+08, device='cuda:0'), tensor(1.9138e+08, device='cuda:0'), tensor(1.9290e+08, device='cuda:0')]

Training loss: 192766272.0

Prediction time: [datetime.timedelta(microseconds=55760), datetime.timedelta(microseconds=56759), datetime.timedelta(microseconds=64725), datetime.timedelta(microseconds=59750), datetime.timedelta(microseconds=55761), datetime.timedelta(microseconds=61739), datetime.timedelta(microseconds=56759), datetime.timedelta(microseconds=55763), datetime.timedelta(microseconds=55764), datetime.timedelta(microseconds=53772)]

Phi time: [datetime.timedelta(seconds=1, microseconds=443989), datetime.timedelta(microseconds=848856), datetime.timedelta(microseconds=927790), datetime.timedelta(microseconds=959016), datetime.timedelta(microseconds=959919), datetime.timedelta(microseconds=929839), datetime.timedelta(microseconds=929422), datetime.timedelta(microseconds=885899), datetime.timedelta(microseconds=870966), datetime.timedelta(microseconds=879108)]

