Precision: [tensor(1., device='cuda:0'), tensor(1., device='cuda:0'), tensor(1., device='cuda:0'), tensor(1., device='cuda:0'), tensor(1., device='cuda:0'), tensor(1., device='cuda:0'), tensor(1., device='cuda:0'), tensor(1., device='cuda:0'), tensor(1., device='cuda:0'), tensor(1., device='cuda:0')]

Output distance: [tensor(38643.5898, device='cuda:0'), tensor(38629.8086, device='cuda:0'), tensor(38572.2461, device='cuda:0'), tensor(38637.5703, device='cuda:0'), tensor(38772.4805, device='cuda:0'), tensor(38541.3320, device='cuda:0'), tensor(38962.5273, device='cuda:0'), tensor(38632.8828, device='cuda:0'), tensor(38720.5000, device='cuda:0'), tensor(38858.7852, device='cuda:0')]

Prediction loss: [tensor(36935.8086, device='cuda:0'), tensor(38472.9453, device='cuda:0'), tensor(39848.0898, device='cuda:0'), tensor(37138.9375, device='cuda:0'), tensor(37021.0977, device='cuda:0'), tensor(39604.5000, device='cuda:0'), tensor(39018.6797, device='cuda:0'), tensor(38359.5742, device='cuda:0'), tensor(38669.6992, device='cuda:0'), tensor(38404.1719, device='cuda:0')]

Others: [{'iter_num': 11, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}]

Compressed training loss: [tensor(3497794., device='cuda:0'), tensor(3595562.7500, device='cuda:0'), tensor(3700651.5000, device='cuda:0'), tensor(3480970.7500, device='cuda:0'), tensor(3473436.2500, device='cuda:0'), tensor(3648509.5000, device='cuda:0'), tensor(3561589.5000, device='cuda:0'), tensor(3564477.2500, device='cuda:0'), tensor(3570548.7500, device='cuda:0'), tensor(3593460.2500, device='cuda:0')]

Training loss: 3598289.0

Prediction time: [datetime.timedelta(microseconds=792640), datetime.timedelta(microseconds=829482), datetime.timedelta(microseconds=717956), datetime.timedelta(microseconds=819525), datetime.timedelta(microseconds=799609), datetime.timedelta(microseconds=719949), datetime.timedelta(microseconds=802598), datetime.timedelta(microseconds=727862), datetime.timedelta(microseconds=717955), datetime.timedelta(microseconds=824500)]

Phi time: [datetime.timedelta(seconds=1, microseconds=515045), datetime.timedelta(microseconds=981656), datetime.timedelta(microseconds=939010), datetime.timedelta(microseconds=945379), datetime.timedelta(microseconds=960963), datetime.timedelta(microseconds=942128), datetime.timedelta(microseconds=946173), datetime.timedelta(microseconds=946611), datetime.timedelta(microseconds=949126), datetime.timedelta(microseconds=942352)]

