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(38842.1758, device='cuda:0'), tensor(38564.7969, device='cuda:0'), tensor(39066.0078, device='cuda:0'), tensor(38895.9609, device='cuda:0'), tensor(38482.9023, device='cuda:0'), tensor(38989.6133, device='cuda:0'), tensor(38458.6914, device='cuda:0'), tensor(39359.6680, device='cuda:0'), tensor(38867.5273, device='cuda:0'), tensor(38574.7461, device='cuda:0')]

Prediction loss: [tensor(36709.1172, device='cuda:0'), tensor(38056.7930, device='cuda:0'), tensor(37894.4648, device='cuda:0'), tensor(36383.5742, device='cuda:0'), tensor(36977.5352, device='cuda:0'), tensor(38344.3125, device='cuda:0'), tensor(36150.9414, device='cuda:0'), tensor(39685.6328, device='cuda:0'), tensor(38547.8438, device='cuda:0'), tensor(37286.7578, 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': 13, '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')}, {'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')}]

Compressed training loss: [tensor(3475287.5000, device='cuda:0'), tensor(3551419.5000, device='cuda:0'), tensor(3660305., device='cuda:0'), tensor(3413438.5000, device='cuda:0'), tensor(3422370.2500, device='cuda:0'), tensor(3568422., device='cuda:0'), tensor(3538300.2500, device='cuda:0'), tensor(3650859.2500, device='cuda:0'), tensor(3563041.5000, device='cuda:0'), tensor(3602225.2500, device='cuda:0')]

Training loss: 3614825.0

Prediction time: [datetime.timedelta(microseconds=604437), datetime.timedelta(microseconds=638291), datetime.timedelta(microseconds=693059), datetime.timedelta(microseconds=633314), datetime.timedelta(microseconds=633314), datetime.timedelta(microseconds=637298), datetime.timedelta(microseconds=636301), datetime.timedelta(microseconds=576553), datetime.timedelta(microseconds=634310), datetime.timedelta(microseconds=618378)]

Phi time: [datetime.timedelta(seconds=1, microseconds=287484), datetime.timedelta(microseconds=795424), datetime.timedelta(microseconds=720543), datetime.timedelta(microseconds=718588), datetime.timedelta(microseconds=720483), datetime.timedelta(microseconds=723962), datetime.timedelta(microseconds=720538), datetime.timedelta(microseconds=730941), datetime.timedelta(microseconds=730008), datetime.timedelta(microseconds=725327)]

