Precision: [tensor(0.5107, device='cuda:0'), tensor(0.5120, device='cuda:0'), tensor(0.5161, device='cuda:0'), tensor(0.5115, device='cuda:0'), tensor(0.5121, device='cuda:0'), tensor(0.5098, device='cuda:0'), tensor(0.5092, device='cuda:0'), tensor(0.5091, device='cuda:0'), tensor(0.5082, device='cuda:0'), tensor(0.5118, device='cuda:0')]

Output distance: [tensor(5.2418, device='cuda:0'), tensor(5.2339, device='cuda:0'), tensor(5.2092, device='cuda:0'), tensor(5.2371, device='cuda:0'), tensor(5.2334, device='cuda:0'), tensor(5.2476, device='cuda:0'), tensor(5.2507, device='cuda:0'), tensor(5.2512, device='cuda:0'), tensor(5.2570, device='cuda:0'), tensor(5.2355, device='cuda:0')]

Prediction loss: [tensor(19450876., device='cuda:0'), tensor(20758918., device='cuda:0'), tensor(19300690., device='cuda:0'), tensor(19099172., device='cuda:0'), tensor(16333030., device='cuda:0'), tensor(18540394., device='cuda:0'), tensor(18200764., device='cuda:0'), tensor(19764946., device='cuda:0'), tensor(19281416., device='cuda:0'), tensor(19398476., device='cuda:0')]

Others: [{'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}]

Compressed training loss: [tensor(40487.3828, device='cuda:0'), tensor(40903.8789, device='cuda:0'), tensor(40751.8945, device='cuda:0'), tensor(40714.9570, device='cuda:0'), tensor(41058.4727, device='cuda:0'), tensor(40809.8086, device='cuda:0'), tensor(41355.9023, device='cuda:0'), tensor(40798.7188, device='cuda:0'), tensor(41095.0234, device='cuda:0'), tensor(40747.2734, device='cuda:0')]

Training loss: 0

Prediction time: [datetime.timedelta(seconds=39, microseconds=605561), datetime.timedelta(seconds=40, microseconds=691097), datetime.timedelta(seconds=39, microseconds=247172), datetime.timedelta(seconds=40, microseconds=879696), datetime.timedelta(seconds=41, microseconds=116107), datetime.timedelta(seconds=41, microseconds=229432), datetime.timedelta(seconds=40, microseconds=875694), datetime.timedelta(seconds=41, microseconds=25801), datetime.timedelta(seconds=41, microseconds=48020), datetime.timedelta(seconds=40, microseconds=951774)]

Phi time: [datetime.timedelta(microseconds=194666), datetime.timedelta(microseconds=348184), datetime.timedelta(microseconds=357604), datetime.timedelta(microseconds=276156), datetime.timedelta(microseconds=368643), datetime.timedelta(microseconds=370108), datetime.timedelta(microseconds=280901), datetime.timedelta(microseconds=381636), datetime.timedelta(microseconds=257627), datetime.timedelta(microseconds=428346)]

