Precision: [tensor(0.2609, device='cuda:0'), tensor(0.2598, device='cuda:0'), tensor(0.2715, device='cuda:0'), tensor(0.2697, device='cuda:0'), tensor(0.2770, device='cuda:0'), tensor(0.2716, device='cuda:0'), tensor(0.2752, device='cuda:0'), tensor(0.2657, device='cuda:0'), tensor(0.2558, device='cuda:0'), tensor(0.2651, device='cuda:0')]

Output distance: [tensor(21.4160, device='cuda:0'), tensor(21.4271, device='cuda:0'), tensor(21.3108, device='cuda:0'), tensor(21.3286, device='cuda:0'), tensor(21.2554, device='cuda:0'), tensor(21.3089, device='cuda:0'), tensor(21.2739, device='cuda:0'), tensor(21.3685, device='cuda:0'), tensor(21.4671, device='cuda:0'), tensor(21.3742, device='cuda:0')]

Prediction loss: [tensor(100.2323, device='cuda:0'), tensor(100.3680, device='cuda:0'), tensor(100.0964, device='cuda:0'), tensor(100.2439, device='cuda:0'), tensor(100.9449, device='cuda:0'), tensor(101.2982, device='cuda:0'), tensor(101.5158, device='cuda:0'), tensor(101.1591, device='cuda:0'), tensor(99.7126, device='cuda:0'), tensor(100.1889, device='cuda:0')]

Others: [{'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, 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=903925), datetime.timedelta(seconds=1, microseconds=917815), datetime.timedelta(seconds=1, microseconds=912887), datetime.timedelta(seconds=1, microseconds=899942), datetime.timedelta(seconds=1, microseconds=909879), datetime.timedelta(seconds=1, microseconds=901930), datetime.timedelta(seconds=1, microseconds=901934), datetime.timedelta(seconds=1, microseconds=912885), datetime.timedelta(seconds=1, microseconds=961680), datetime.timedelta(seconds=1, microseconds=901933)]

Phi time: [datetime.timedelta(seconds=5, microseconds=126869), datetime.timedelta(seconds=5, microseconds=62874), datetime.timedelta(seconds=5, microseconds=67285), datetime.timedelta(seconds=5, microseconds=83462), datetime.timedelta(seconds=5, microseconds=83173), datetime.timedelta(seconds=5, microseconds=89364), datetime.timedelta(seconds=5, microseconds=81958), datetime.timedelta(seconds=5, microseconds=85848), datetime.timedelta(seconds=5, microseconds=75165), datetime.timedelta(seconds=5, microseconds=104045)]

