Precision: [tensor(0.9995, device='cuda:0'), tensor(0.9995, device='cuda:0'), tensor(0.9995, device='cuda:0'), tensor(0.9998, device='cuda:0'), tensor(0.9998, device='cuda:0'), tensor(0.9998, device='cuda:0'), tensor(0.9998, device='cuda:0'), tensor(0.9997, device='cuda:0'), tensor(0.9997, device='cuda:0'), tensor(0.9997, device='cuda:0')]

Output distance: [tensor(145777.8594, device='cuda:0'), tensor(144772.3125, device='cuda:0'), tensor(144303.4062, device='cuda:0'), tensor(144225.1875, device='cuda:0'), tensor(146941.1250, device='cuda:0'), tensor(142319.3594, device='cuda:0'), tensor(145097.7656, device='cuda:0'), tensor(142528.7969, device='cuda:0'), tensor(143337.1094, device='cuda:0'), tensor(142760.3281, device='cuda:0')]

Prediction loss: [tensor(135082.7969, device='cuda:0'), tensor(143290.4375, device='cuda:0'), tensor(147391.5469, device='cuda:0'), tensor(135122.0938, device='cuda:0'), tensor(149719.5469, device='cuda:0'), tensor(139529.5469, device='cuda:0'), tensor(140513.8438, device='cuda:0'), tensor(142644.0781, device='cuda:0'), tensor(135290.1719, device='cuda:0'), tensor(141265.0625, 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(1.8835e+08, device='cuda:0'), tensor(1.9236e+08, device='cuda:0'), tensor(1.9457e+08, device='cuda:0'), tensor(1.8756e+08, device='cuda:0'), tensor(1.9335e+08, device='cuda:0'), tensor(1.9166e+08, device='cuda:0'), tensor(1.9008e+08, device='cuda:0'), tensor(1.9400e+08, device='cuda:0'), tensor(1.8674e+08, device='cuda:0'), tensor(1.9109e+08, device='cuda:0')]

Training loss: 190954240.0

Prediction time: [datetime.timedelta(microseconds=78665), datetime.timedelta(microseconds=79662), datetime.timedelta(microseconds=78666), datetime.timedelta(microseconds=80658), datetime.timedelta(microseconds=78661), datetime.timedelta(microseconds=75679), datetime.timedelta(microseconds=78667), datetime.timedelta(microseconds=78667), datetime.timedelta(microseconds=78667), datetime.timedelta(microseconds=75679)]

Phi time: [datetime.timedelta(seconds=1, microseconds=460753), datetime.timedelta(microseconds=857525), datetime.timedelta(microseconds=849543), datetime.timedelta(microseconds=869925), datetime.timedelta(microseconds=870285), datetime.timedelta(microseconds=865777), datetime.timedelta(microseconds=868551), datetime.timedelta(microseconds=871796), datetime.timedelta(microseconds=870922), datetime.timedelta(microseconds=867090)]

