Precision: [tensor(1., device='cuda:0'), tensor(1., device='cuda:0'), tensor(1., device='cuda:0'), tensor(0.9998, device='cuda:0'), tensor(1., device='cuda:0'), tensor(0.9977, device='cuda:0'), tensor(0.9998, device='cuda:0'), tensor(0.9998, device='cuda:0'), tensor(1., device='cuda:0'), tensor(1., device='cuda:0')]

Output distance: [tensor(38473.4922, device='cuda:0'), tensor(38075.1094, device='cuda:0'), tensor(39437.7070, device='cuda:0'), tensor(40022.2695, device='cuda:0'), tensor(38503.9883, device='cuda:0'), tensor(38657.8906, device='cuda:0'), tensor(38475.6172, device='cuda:0'), tensor(38255.1445, device='cuda:0'), tensor(38106.2031, device='cuda:0'), tensor(39230.1875, device='cuda:0')]

Prediction loss: [tensor(39876.2539, device='cuda:0'), tensor(36256.2461, device='cuda:0'), tensor(35396.2227, device='cuda:0'), tensor(37192.3086, device='cuda:0'), tensor(40729.3633, device='cuda:0'), tensor(31894.8320, device='cuda:0'), tensor(40637.6680, device='cuda:0'), tensor(38333.3672, device='cuda:0'), tensor(33801.2891, device='cuda:0'), tensor(36193.0742, 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': 15, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 15, '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': 13, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}]

Compressed training loss: [tensor(3718474.2500, device='cuda:0'), tensor(3409616.7500, device='cuda:0'), tensor(3419929.7500, device='cuda:0'), tensor(3518596., device='cuda:0'), tensor(3788357.5000, device='cuda:0'), tensor(3199879.5000, device='cuda:0'), tensor(3789181.5000, device='cuda:0'), tensor(3586432., device='cuda:0'), tensor(3324046.5000, device='cuda:0'), tensor(3556817., device='cuda:0')]

Training loss: 3569918.75

Prediction time: [datetime.timedelta(microseconds=525787), datetime.timedelta(microseconds=544707), datetime.timedelta(microseconds=670177), datetime.timedelta(microseconds=640304), datetime.timedelta(microseconds=549688), datetime.timedelta(microseconds=590514), datetime.timedelta(microseconds=549686), datetime.timedelta(microseconds=549688), datetime.timedelta(microseconds=548673), datetime.timedelta(microseconds=612405)]

Phi time: [datetime.timedelta(seconds=1, microseconds=220581), datetime.timedelta(microseconds=745090), datetime.timedelta(microseconds=653747), datetime.timedelta(microseconds=653130), datetime.timedelta(microseconds=655794), datetime.timedelta(microseconds=654910), datetime.timedelta(microseconds=671940), datetime.timedelta(microseconds=653172), datetime.timedelta(microseconds=654557), datetime.timedelta(microseconds=651292)]

