Precision: [tensor(0.2792, device='cuda:0'), tensor(0.2934, device='cuda:0'), tensor(0.2498, device='cuda:0'), tensor(0.3061, device='cuda:0'), tensor(0.2204, device='cuda:0'), tensor(0.2771, device='cuda:0'), tensor(0.2681, device='cuda:0'), tensor(0.2595, device='cuda:0'), tensor(0.2901, device='cuda:0'), tensor(0.2372, device='cuda:0')]

Output distance: [tensor(19.4671, device='cuda:0'), tensor(19.4386, device='cuda:0'), tensor(19.5257, device='cuda:0'), tensor(19.4132, device='cuda:0'), tensor(19.5846, device='cuda:0'), tensor(19.4713, device='cuda:0'), tensor(19.4891, device='cuda:0'), tensor(19.5063, device='cuda:0'), tensor(19.4453, device='cuda:0'), tensor(19.5511, device='cuda:0')]

Prediction loss: [tensor(107.3784, device='cuda:0'), tensor(108.6889, device='cuda:0'), tensor(107.4183, device='cuda:0'), tensor(108.0539, device='cuda:0'), tensor(106.9724, device='cuda:0'), tensor(107.7289, device='cuda:0'), tensor(107.3680, device='cuda:0'), tensor(109.3425, device='cuda:0'), tensor(107.9470, device='cuda:0'), tensor(105.8121, 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=669910), datetime.timedelta(seconds=1, microseconds=679875), datetime.timedelta(seconds=1, microseconds=707760), datetime.timedelta(seconds=1, microseconds=674008), datetime.timedelta(seconds=1, microseconds=705766), datetime.timedelta(seconds=1, microseconds=708751), datetime.timedelta(seconds=1, microseconds=690830), datetime.timedelta(seconds=1, microseconds=710794), datetime.timedelta(seconds=1, microseconds=711740), datetime.timedelta(seconds=1, microseconds=764517)]

Phi time: [datetime.timedelta(seconds=4, microseconds=351000), datetime.timedelta(seconds=4, microseconds=281442), datetime.timedelta(seconds=4, microseconds=293512), datetime.timedelta(seconds=4, microseconds=262221), datetime.timedelta(seconds=4, microseconds=329603), datetime.timedelta(seconds=4, microseconds=313329), datetime.timedelta(seconds=4, microseconds=265224), datetime.timedelta(seconds=4, microseconds=276563), datetime.timedelta(seconds=4, microseconds=251562), datetime.timedelta(seconds=4, microseconds=312708)]

