Precision: [tensor(0.7362, device='cuda:0'), tensor(0.7364, device='cuda:0'), tensor(0.7258, device='cuda:0'), tensor(0.7396, device='cuda:0'), tensor(0.7348, device='cuda:0'), tensor(0.7289, device='cuda:0'), tensor(0.7361, device='cuda:0'), tensor(0.7320, device='cuda:0'), tensor(0.7430, device='cuda:0'), tensor(0.7353, device='cuda:0')]
Output distance: [tensor(361966.3438, device='cuda:0'), tensor(630047.9375, device='cuda:0'), tensor(263956.2812, device='cuda:0'), tensor(277859.9688, device='cuda:0'), tensor(422553.2500, device='cuda:0'), tensor(266599.3125, device='cuda:0'), tensor(468336.4062, device='cuda:0'), tensor(375315.7812, device='cuda:0'), tensor(546010., device='cuda:0'), tensor(289337.4688, device='cuda:0')]
Prediction loss: [tensor(19259946., device='cuda:0'), tensor(18205462., device='cuda:0'), tensor(17734188., device='cuda:0'), tensor(18827624., device='cuda:0'), tensor(19100088., device='cuda:0'), tensor(18263096., device='cuda:0'), tensor(18663662., device='cuda:0'), tensor(18573508., device='cuda:0'), tensor(18398388., device='cuda:0'), tensor(17275886., device='cuda:0')]
Others: [{'iter_num': 7, 'num_positive': tensor(2195, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(2193, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(2163, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(2197, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(2161, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(2180, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(2152, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(2220, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(2140, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(2187, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}]
Compressed training loss: [tensor(40896.2500, device='cuda:0'), tensor(40903.3477, device='cuda:0'), tensor(40778.2109, device='cuda:0'), tensor(40898.6172, device='cuda:0'), tensor(40804.9180, device='cuda:0'), tensor(40786.3203, device='cuda:0'), tensor(40760.2383, device='cuda:0'), tensor(40818.2656, device='cuda:0'), tensor(40684.0664, device='cuda:0'), tensor(40734.0078, device='cuda:0')]
Training loss: 0
Prediction time: [datetime.timedelta(microseconds=97584), datetime.timedelta(microseconds=86630), datetime.timedelta(microseconds=90613), datetime.timedelta(microseconds=99576), datetime.timedelta(microseconds=89618), datetime.timedelta(microseconds=85636), datetime.timedelta(microseconds=95592), datetime.timedelta(microseconds=98580), datetime.timedelta(microseconds=97584), datetime.timedelta(microseconds=87626)]
Phi time: [datetime.timedelta(microseconds=237993), datetime.timedelta(microseconds=235005), datetime.timedelta(microseconds=241975), datetime.timedelta(microseconds=236997), datetime.timedelta(microseconds=236001), datetime.timedelta(microseconds=239984), datetime.timedelta(microseconds=240980), datetime.timedelta(microseconds=236001), datetime.timedelta(microseconds=243967), datetime.timedelta(microseconds=234009)]
