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(38250.6914, device='cuda:0'), tensor(37891.6484, device='cuda:0'), tensor(38446.1914, device='cuda:0'), tensor(37988.9922, device='cuda:0'), tensor(38062.8672, device='cuda:0'), tensor(38151.5156, device='cuda:0'), tensor(38180.0898, device='cuda:0'), tensor(37956.8945, device='cuda:0'), tensor(37986.6250, device='cuda:0'), tensor(38138.7695, device='cuda:0')]

Prediction loss: [tensor(36945.5508, device='cuda:0'), tensor(35916.0898, device='cuda:0'), tensor(36623.9805, device='cuda:0'), tensor(40042.4531, device='cuda:0'), tensor(38020.6719, device='cuda:0'), tensor(36708.5586, device='cuda:0'), tensor(36489.6914, device='cuda:0'), tensor(37611.3516, device='cuda:0'), tensor(36415.4297, device='cuda:0'), tensor(38531.6875, 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': 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')}, {'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')}]

Compressed training loss: [tensor(3466308.5000, device='cuda:0'), tensor(3365322.2500, device='cuda:0'), tensor(3557218.5000, device='cuda:0'), tensor(3692476.5000, device='cuda:0'), tensor(3528589., device='cuda:0'), tensor(3427642.2500, device='cuda:0'), tensor(3483778., device='cuda:0'), tensor(3494864.5000, device='cuda:0'), tensor(3355678.2500, device='cuda:0'), tensor(3634410.5000, device='cuda:0')]

Training loss: 3564021.25

Prediction time: [datetime.timedelta(microseconds=622362), datetime.timedelta(microseconds=665179), datetime.timedelta(microseconds=634311), datetime.timedelta(microseconds=590497), datetime.timedelta(microseconds=568589), datetime.timedelta(microseconds=645265), datetime.timedelta(microseconds=655221), datetime.timedelta(microseconds=567593), datetime.timedelta(microseconds=646255), datetime.timedelta(microseconds=592485)]

Phi time: [datetime.timedelta(seconds=1, microseconds=344033), datetime.timedelta(microseconds=843275), datetime.timedelta(microseconds=783529), datetime.timedelta(microseconds=783442), datetime.timedelta(microseconds=782879), datetime.timedelta(microseconds=786252), datetime.timedelta(microseconds=783635), datetime.timedelta(microseconds=778047), datetime.timedelta(microseconds=780754), datetime.timedelta(microseconds=785472)]

