Precision: [tensor(0.5062, device='cuda:0'), tensor(0.5385, device='cuda:0'), tensor(0.5215, device='cuda:0'), tensor(0.5160, device='cuda:0'), tensor(0.5265, device='cuda:0'), tensor(0.5006, device='cuda:0'), tensor(0.5331, device='cuda:0'), tensor(0.5047, device='cuda:0'), tensor(0.5313, device='cuda:0'), tensor(0.5088, device='cuda:0')]

Output distance: [tensor(19.0130, device='cuda:0'), tensor(18.9483, device='cuda:0'), tensor(18.9825, device='cuda:0'), tensor(18.9933, device='cuda:0'), tensor(18.9725, device='cuda:0'), tensor(19.0242, device='cuda:0'), tensor(18.9592, device='cuda:0'), tensor(19.0160, device='cuda:0'), tensor(18.9628, device='cuda:0'), tensor(19.0079, device='cuda:0')]

Prediction loss: [tensor(109.1755, device='cuda:0'), tensor(109.0128, device='cuda:0'), tensor(108.6242, device='cuda:0'), tensor(108.1572, device='cuda:0'), tensor(108.6974, device='cuda:0'), tensor(107.7567, device='cuda:0'), tensor(108.9123, device='cuda:0'), tensor(108.2888, device='cuda:0'), tensor(109.3584, device='cuda:0'), tensor(108.2843, 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=649915), datetime.timedelta(seconds=1, microseconds=645855), datetime.timedelta(seconds=1, microseconds=675670), datetime.timedelta(seconds=1, microseconds=681125), datetime.timedelta(seconds=1, microseconds=656489), datetime.timedelta(seconds=1, microseconds=636311), datetime.timedelta(seconds=1, microseconds=662636), datetime.timedelta(seconds=1, microseconds=649977), datetime.timedelta(seconds=1, microseconds=676005), datetime.timedelta(seconds=1, microseconds=639783)]

Phi time: [datetime.timedelta(seconds=4, microseconds=681318), datetime.timedelta(seconds=4, microseconds=527010), datetime.timedelta(seconds=4, microseconds=567851), datetime.timedelta(seconds=4, microseconds=580781), datetime.timedelta(seconds=4, microseconds=559314), datetime.timedelta(seconds=4, microseconds=610988), datetime.timedelta(seconds=4, microseconds=554511), datetime.timedelta(seconds=4, microseconds=596993), datetime.timedelta(seconds=4, microseconds=583107), datetime.timedelta(seconds=4, microseconds=563669)]

