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

Output distance: [tensor(141712.5781, device='cuda:0'), tensor(141973.8594, device='cuda:0'), tensor(145226.3438, device='cuda:0'), tensor(139648.4688, device='cuda:0'), tensor(140610.7969, device='cuda:0'), tensor(140296.1562, device='cuda:0'), tensor(141049.4688, device='cuda:0'), tensor(154285.2344, device='cuda:0'), tensor(141668.6875, device='cuda:0'), tensor(140963.2188, device='cuda:0')]

Prediction loss: [tensor(141458.7969, device='cuda:0'), tensor(135355.2188, device='cuda:0'), tensor(135352.9219, device='cuda:0'), tensor(137604.5625, device='cuda:0'), tensor(138692.9219, device='cuda:0'), tensor(136709.3125, device='cuda:0'), tensor(141208.0156, device='cuda:0'), tensor(143109.8750, device='cuda:0'), tensor(139990.2344, device='cuda:0'), tensor(134589.4844, 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(1.9382e+08, device='cuda:0'), tensor(1.8704e+08, device='cuda:0'), tensor(1.8885e+08, device='cuda:0'), tensor(1.9102e+08, device='cuda:0'), tensor(1.9122e+08, device='cuda:0'), tensor(1.9158e+08, device='cuda:0'), tensor(1.9323e+08, device='cuda:0'), tensor(1.9010e+08, device='cuda:0'), tensor(1.9142e+08, device='cuda:0'), tensor(1.8822e+08, device='cuda:0')]

Training loss: 191942512.0

Prediction time: [datetime.timedelta(microseconds=65724), datetime.timedelta(microseconds=64729), datetime.timedelta(microseconds=65725), datetime.timedelta(microseconds=64728), datetime.timedelta(microseconds=65723), datetime.timedelta(microseconds=65722), datetime.timedelta(microseconds=65723), datetime.timedelta(microseconds=65723), datetime.timedelta(microseconds=65722), datetime.timedelta(microseconds=64729)]

Phi time: [datetime.timedelta(seconds=1, microseconds=554502), datetime.timedelta(microseconds=934308), datetime.timedelta(microseconds=928678), datetime.timedelta(microseconds=948327), datetime.timedelta(microseconds=967602), datetime.timedelta(microseconds=986086), datetime.timedelta(microseconds=982585), datetime.timedelta(microseconds=980628), datetime.timedelta(microseconds=951633), datetime.timedelta(microseconds=950104)]

