Precision: [tensor(0.0323, device='cuda:0'), tensor(0.0351, device='cuda:0'), tensor(0.0422, device='cuda:0'), tensor(0.0237, device='cuda:0'), tensor(0.0282, device='cuda:0'), tensor(0.0302, device='cuda:0'), tensor(0.0296, device='cuda:0'), tensor(0.0312, device='cuda:0'), tensor(0.0355, device='cuda:0'), tensor(0.0318, device='cuda:0')]

Output distance: [tensor(21.8316, device='cuda:0'), tensor(21.8147, device='cuda:0'), tensor(21.7721, device='cuda:0'), tensor(21.8830, device='cuda:0'), tensor(21.8561, device='cuda:0'), tensor(21.8440, device='cuda:0'), tensor(21.8479, device='cuda:0'), tensor(21.8383, device='cuda:0'), tensor(21.8123, device='cuda:0'), tensor(21.8343, device='cuda:0')]

Prediction loss: [tensor(114.1118, device='cuda:0'), tensor(111.4270, device='cuda:0'), tensor(114.9948, device='cuda:0'), tensor(117.2458, device='cuda:0'), tensor(113.7065, device='cuda:0'), tensor(112.9530, device='cuda:0'), tensor(114.9883, device='cuda:0'), tensor(115.1073, device='cuda:0'), tensor(113.3674, device='cuda:0'), tensor(115.5053, device='cuda:0')]

Others: [{'iter_num': 60, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(19848, 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=5, microseconds=499724), datetime.timedelta(seconds=5, microseconds=516601), datetime.timedelta(seconds=5, microseconds=533531), datetime.timedelta(seconds=5, microseconds=528552), datetime.timedelta(seconds=5, microseconds=517594), datetime.timedelta(seconds=5, microseconds=520530), datetime.timedelta(seconds=5, microseconds=520583), datetime.timedelta(seconds=5, microseconds=506644), datetime.timedelta(seconds=5, microseconds=524523), datetime.timedelta(seconds=5, microseconds=475776)]

Phi time: [datetime.timedelta(seconds=4, microseconds=289308), datetime.timedelta(seconds=4, microseconds=363222), datetime.timedelta(seconds=4, microseconds=343095), datetime.timedelta(seconds=4, microseconds=339052), datetime.timedelta(seconds=4, microseconds=354666), datetime.timedelta(seconds=4, microseconds=350386), datetime.timedelta(seconds=4, microseconds=350001), datetime.timedelta(seconds=4, microseconds=352257), datetime.timedelta(seconds=4, microseconds=367805), datetime.timedelta(seconds=4, microseconds=367560)]

