Precision: [tensor(0.6002, device='cuda:0'), tensor(0.6020, device='cuda:0'), tensor(0.6062, device='cuda:0'), tensor(0.6020, device='cuda:0'), tensor(0.5970, device='cuda:0'), tensor(0.6036, device='cuda:0'), tensor(0.6049, device='cuda:0'), tensor(0.5983, device='cuda:0'), tensor(0.6117, device='cuda:0'), tensor(0.6020, device='cuda:0')]

Output distance: [tensor(5.1058, device='cuda:0'), tensor(5.1021, device='cuda:0'), tensor(5.0937, device='cuda:0'), tensor(5.1021, device='cuda:0'), tensor(5.1121, device='cuda:0'), tensor(5.0990, device='cuda:0'), tensor(5.0964, device='cuda:0'), tensor(5.1095, device='cuda:0'), tensor(5.0827, device='cuda:0'), tensor(5.1021, device='cuda:0')]

Prediction loss: [tensor(17171366., device='cuda:0'), tensor(18020104., device='cuda:0'), tensor(17436712., device='cuda:0'), tensor(20405262., device='cuda:0'), tensor(21665742., device='cuda:0'), tensor(17258154., device='cuda:0'), tensor(22042972., device='cuda:0'), tensor(14929270., device='cuda:0'), tensor(19103244., device='cuda:0'), tensor(19976612., device='cuda:0')]

Others: [{'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': 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': 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: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]

Training loss: 0

Prediction time: [datetime.timedelta(seconds=1, microseconds=32622), datetime.timedelta(seconds=1, microseconds=15695), datetime.timedelta(seconds=1, microseconds=32620), datetime.timedelta(seconds=1, microseconds=17686), datetime.timedelta(seconds=1, microseconds=19675), datetime.timedelta(seconds=1, microseconds=31627), datetime.timedelta(seconds=1, microseconds=24654), datetime.timedelta(seconds=1, microseconds=11709), datetime.timedelta(microseconds=997769), datetime.timedelta(seconds=1, microseconds=22665)]

Phi time: [datetime.timedelta(microseconds=249939), datetime.timedelta(microseconds=242971), datetime.timedelta(microseconds=236997), datetime.timedelta(microseconds=253923), datetime.timedelta(microseconds=238988), datetime.timedelta(microseconds=251934), datetime.timedelta(microseconds=248945), datetime.timedelta(microseconds=242970), datetime.timedelta(microseconds=241976), datetime.timedelta(microseconds=243968)]

