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

Output distance: [tensor(143457.4219, device='cuda:0'), tensor(145152.8906, device='cuda:0'), tensor(144554.5156, device='cuda:0'), tensor(143555.5312, device='cuda:0'), tensor(144609.5312, device='cuda:0'), tensor(142459.5469, device='cuda:0'), tensor(148680.8906, device='cuda:0'), tensor(144812.1719, device='cuda:0'), tensor(146632.3750, device='cuda:0'), tensor(144081.7812, device='cuda:0')]

Prediction loss: [tensor(143690.2500, device='cuda:0'), tensor(140712.7031, device='cuda:0'), tensor(139429.4844, device='cuda:0'), tensor(138370.8281, device='cuda:0'), tensor(136790.5625, device='cuda:0'), tensor(140354.5938, device='cuda:0'), tensor(147630.0312, device='cuda:0'), tensor(131864.0156, device='cuda:0'), tensor(138923.7812, device='cuda:0'), tensor(136441.0781, 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(1.9555e+08, device='cuda:0'), tensor(1.9497e+08, device='cuda:0'), tensor(1.8932e+08, device='cuda:0'), tensor(1.8998e+08, device='cuda:0'), tensor(1.8899e+08, device='cuda:0'), tensor(1.9353e+08, device='cuda:0'), tensor(1.9476e+08, device='cuda:0'), tensor(1.8536e+08, device='cuda:0'), tensor(1.8999e+08, device='cuda:0'), tensor(1.8920e+08, device='cuda:0')]

Training loss: 192246032.0

Prediction time: [datetime.timedelta(microseconds=41823), datetime.timedelta(microseconds=39831), datetime.timedelta(microseconds=38836), datetime.timedelta(microseconds=42812), datetime.timedelta(microseconds=39829), datetime.timedelta(microseconds=38835), datetime.timedelta(microseconds=41826), datetime.timedelta(microseconds=42821), datetime.timedelta(microseconds=38832), datetime.timedelta(microseconds=41825)]

Phi time: [datetime.timedelta(seconds=1, microseconds=394147), datetime.timedelta(microseconds=786519), datetime.timedelta(microseconds=780115), datetime.timedelta(microseconds=790799), datetime.timedelta(microseconds=794809), datetime.timedelta(microseconds=793007), datetime.timedelta(microseconds=791625), datetime.timedelta(microseconds=797009), datetime.timedelta(microseconds=791405), datetime.timedelta(microseconds=788258)]

