Precision: [tensor(0.5036, device='cuda:0'), tensor(0.4924, device='cuda:0'), tensor(0.4711, device='cuda:0'), tensor(0.4819, device='cuda:0'), tensor(0.4596, device='cuda:0'), tensor(0.4696, device='cuda:0'), tensor(0.4748, device='cuda:0'), tensor(0.4681, device='cuda:0'), tensor(0.4748, device='cuda:0'), tensor(0.4624, device='cuda:0')]

Output distance: [tensor(19.0181, device='cuda:0'), tensor(19.0405, device='cuda:0'), tensor(19.0831, device='cuda:0'), tensor(19.0617, device='cuda:0'), tensor(19.1061, device='cuda:0'), tensor(19.0862, device='cuda:0'), tensor(19.0759, device='cuda:0'), tensor(19.0892, device='cuda:0'), tensor(19.0759, device='cuda:0'), tensor(19.1007, device='cuda:0')]

Prediction loss: [tensor(109.2514, device='cuda:0'), tensor(108.5480, device='cuda:0'), tensor(108.7862, device='cuda:0'), tensor(107.7917, device='cuda:0'), tensor(106.8682, device='cuda:0'), tensor(108.2832, device='cuda:0'), tensor(107.2991, device='cuda:0'), tensor(108.4396, device='cuda:0'), tensor(109.1228, device='cuda:0'), tensor(108.3643, device='cuda:0')]

Others: [{'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}]

Compressed training loss: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]

Training loss: 0

Prediction time: [datetime.timedelta(seconds=1, microseconds=862154), datetime.timedelta(seconds=1, microseconds=865144), datetime.timedelta(seconds=1, microseconds=841244), datetime.timedelta(seconds=1, microseconds=854187), datetime.timedelta(seconds=1, microseconds=845217), datetime.timedelta(seconds=1, microseconds=854195), datetime.timedelta(seconds=1, microseconds=878088), datetime.timedelta(seconds=1, microseconds=845227), datetime.timedelta(seconds=1, microseconds=853192), datetime.timedelta(seconds=1, microseconds=851200)]

Phi time: [datetime.timedelta(seconds=4, microseconds=958046), datetime.timedelta(seconds=4, microseconds=828289), datetime.timedelta(seconds=4, microseconds=858666), datetime.timedelta(seconds=4, microseconds=880618), datetime.timedelta(seconds=4, microseconds=877720), datetime.timedelta(seconds=4, microseconds=872593), datetime.timedelta(seconds=4, microseconds=898120), datetime.timedelta(seconds=4, microseconds=950848), datetime.timedelta(seconds=4, microseconds=897117), datetime.timedelta(seconds=4, microseconds=964723)]

