Precision: [tensor(0.6855, device='cuda:0'), tensor(0.6847, device='cuda:0'), tensor(0.6868, device='cuda:0'), tensor(0.6873, device='cuda:0'), tensor(0.6878, device='cuda:0'), tensor(0.6889, device='cuda:0'), tensor(0.6836, device='cuda:0'), tensor(0.6907, device='cuda:0'), tensor(0.6934, device='cuda:0'), tensor(0.6957, device='cuda:0')]
Output distance: [tensor(359230.3438, device='cuda:0'), tensor(379300.9062, device='cuda:0'), tensor(432648.8438, device='cuda:0'), tensor(420093.6250, device='cuda:0'), tensor(515829.3750, device='cuda:0'), tensor(398067.6562, device='cuda:0'), tensor(371899.9062, device='cuda:0'), tensor(524193.6562, device='cuda:0'), tensor(349164.1875, device='cuda:0'), tensor(422929.3125, device='cuda:0')]
Prediction loss: [tensor(18171544., device='cuda:0'), tensor(18014148., device='cuda:0'), tensor(17524156., device='cuda:0'), tensor(17556808., device='cuda:0'), tensor(17657792., device='cuda:0'), tensor(18034016., device='cuda:0'), tensor(18941454., device='cuda:0'), tensor(18696572., device='cuda:0'), tensor(17539286., device='cuda:0'), tensor(16139315., device='cuda:0')]
Others: [{'iter_num': 5, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}]
Compressed training loss: [tensor(40852.7930, device='cuda:0'), tensor(40878.4219, device='cuda:0'), tensor(40928.2422, device='cuda:0'), tensor(40804.5469, device='cuda:0'), tensor(40774.9688, device='cuda:0'), tensor(40716.5430, device='cuda:0'), tensor(40717.9531, device='cuda:0'), tensor(40734.0078, device='cuda:0'), tensor(40988.0234, device='cuda:0'), tensor(40788.3633, device='cuda:0')]
Training loss: 0
Prediction time: [datetime.timedelta(microseconds=88622), datetime.timedelta(microseconds=100571), datetime.timedelta(microseconds=85635), datetime.timedelta(microseconds=86630), datetime.timedelta(microseconds=90603), datetime.timedelta(microseconds=89618), datetime.timedelta(microseconds=100572), datetime.timedelta(microseconds=98580), datetime.timedelta(microseconds=86631), datetime.timedelta(microseconds=89618)]
Phi time: [datetime.timedelta(microseconds=239984), datetime.timedelta(microseconds=245959), datetime.timedelta(microseconds=236997), datetime.timedelta(microseconds=239984), datetime.timedelta(microseconds=247950), datetime.timedelta(microseconds=238989), datetime.timedelta(microseconds=241976), datetime.timedelta(microseconds=238988), datetime.timedelta(microseconds=238988), datetime.timedelta(microseconds=249943)]
