Precision: [tensor(0.8719, device='cuda:0'), tensor(0.8733, device='cuda:0'), tensor(0.8694, device='cuda:0'), tensor(0.8731, device='cuda:0'), tensor(0.8702, device='cuda:0'), tensor(0.8711, device='cuda:0'), tensor(0.8681, device='cuda:0'), tensor(0.8697, device='cuda:0'), tensor(0.8677, device='cuda:0'), tensor(0.8732, device='cuda:0')]

Output distance: [tensor(14178.7773, device='cuda:0'), tensor(13889.4414, device='cuda:0'), tensor(14353.7129, device='cuda:0'), tensor(13793.9746, device='cuda:0'), tensor(14128.5996, device='cuda:0'), tensor(14166.7754, device='cuda:0'), tensor(14632.0361, device='cuda:0'), tensor(14149.8994, device='cuda:0'), tensor(14303.7754, device='cuda:0'), tensor(13825.4814, device='cuda:0')]

Prediction loss: [tensor(10283.9033, device='cuda:0'), tensor(11226.5264, device='cuda:0'), tensor(10692.8916, device='cuda:0'), tensor(10812.7373, device='cuda:0'), tensor(11051.5801, device='cuda:0'), tensor(11105.0615, device='cuda:0'), tensor(10589.9336, device='cuda:0'), tensor(10604.3096, device='cuda:0'), tensor(10545.9980, device='cuda:0'), tensor(10776.3916, device='cuda:0')]

Others: [{'num_positive': tensor(16710, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16814, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16789, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16835, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16791, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16783, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16634, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16809, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16782, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16840, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}]

Compressed training loss: [tensor(1.8402e+08, device='cuda:0'), tensor(2.0077e+08, device='cuda:0'), tensor(1.9307e+08, device='cuda:0'), tensor(1.9383e+08, device='cuda:0'), tensor(1.9678e+08, device='cuda:0'), tensor(1.9923e+08, device='cuda:0'), tensor(1.8831e+08, device='cuda:0'), tensor(1.9245e+08, device='cuda:0'), tensor(1.9048e+08, device='cuda:0'), tensor(1.9325e+08, device='cuda:0')]

Training loss: 192276592.0

Prediction time: [datetime.timedelta(seconds=60, microseconds=338036), datetime.timedelta(seconds=61, microseconds=31389), datetime.timedelta(seconds=61, microseconds=589500), datetime.timedelta(seconds=61, microseconds=398319), datetime.timedelta(seconds=61, microseconds=219836), datetime.timedelta(seconds=58, microseconds=403287), datetime.timedelta(seconds=52, microseconds=22126), datetime.timedelta(seconds=49, microseconds=667373), datetime.timedelta(seconds=60, microseconds=442474), datetime.timedelta(seconds=60, microseconds=388048)]

Phi time: [datetime.timedelta(seconds=1, microseconds=93821), datetime.timedelta(microseconds=554966), datetime.timedelta(microseconds=550000), datetime.timedelta(microseconds=566945), datetime.timedelta(microseconds=548920), datetime.timedelta(microseconds=553893), datetime.timedelta(microseconds=581534), datetime.timedelta(microseconds=643839), datetime.timedelta(microseconds=577680), datetime.timedelta(microseconds=568445)]

