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(38350.3789, device='cuda:0'), tensor(38545.7188, device='cuda:0'), tensor(38158.0273, device='cuda:0'), tensor(39131.2383, device='cuda:0'), tensor(38224.6328, device='cuda:0'), tensor(39118.1641, device='cuda:0'), tensor(38425.3242, device='cuda:0'), tensor(38349.3750, device='cuda:0'), tensor(38143.2891, device='cuda:0'), tensor(38310.4336, device='cuda:0')]

Prediction loss: [tensor(36954.3516, device='cuda:0'), tensor(34019.7031, device='cuda:0'), tensor(41640.7109, device='cuda:0'), tensor(36397.2734, device='cuda:0'), tensor(40591.6406, device='cuda:0'), tensor(37069.4062, device='cuda:0'), tensor(40749.5234, device='cuda:0'), tensor(36603.8164, device='cuda:0'), tensor(37530.6914, device='cuda:0'), tensor(37937.4922, device='cuda:0')]

Others: [{'iter_num': 11, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 13, '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': 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': 11, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}]

Compressed training loss: [tensor(3433503.5000, device='cuda:0'), tensor(3235533.5000, device='cuda:0'), tensor(3788052., device='cuda:0'), tensor(3466130., device='cuda:0'), tensor(3796875.2500, device='cuda:0'), tensor(3420290.5000, device='cuda:0'), tensor(3760758.2500, device='cuda:0'), tensor(3442611.5000, device='cuda:0'), tensor(3510841.5000, device='cuda:0'), tensor(3535543.5000, device='cuda:0')]

Training loss: 3590395.25

Prediction time: [datetime.timedelta(microseconds=581482), datetime.timedelta(microseconds=665177), datetime.timedelta(microseconds=555636), datetime.timedelta(microseconds=609413), datetime.timedelta(microseconds=550671), datetime.timedelta(microseconds=612435), datetime.timedelta(microseconds=555627), datetime.timedelta(microseconds=609425), datetime.timedelta(microseconds=616387), datetime.timedelta(microseconds=606427)]

Phi time: [datetime.timedelta(seconds=1, microseconds=299291), datetime.timedelta(microseconds=796913), datetime.timedelta(microseconds=721912), datetime.timedelta(microseconds=722937), datetime.timedelta(microseconds=727397), datetime.timedelta(microseconds=722368), datetime.timedelta(microseconds=728575), datetime.timedelta(microseconds=728115), datetime.timedelta(microseconds=722429), datetime.timedelta(microseconds=728150)]

