Precision: [tensor(0.5692, device='cuda:0'), tensor(0.5638, device='cuda:0'), tensor(0.5750, device='cuda:0'), tensor(0.5633, device='cuda:0'), tensor(0.5780, device='cuda:0'), tensor(0.5807, device='cuda:0'), tensor(0.5821, device='cuda:0'), tensor(0.5736, device='cuda:0'), tensor(0.5757, device='cuda:0'), tensor(0.5685, device='cuda:0')]

Output distance: [tensor(18.8869, device='cuda:0'), tensor(18.8978, device='cuda:0'), tensor(18.8755, device='cuda:0'), tensor(18.8987, device='cuda:0'), tensor(18.8694, device='cuda:0'), tensor(18.8640, device='cuda:0'), tensor(18.8612, device='cuda:0'), tensor(18.8782, device='cuda:0'), tensor(18.8739, device='cuda:0'), tensor(18.8885, device='cuda:0')]

Prediction loss: [tensor(108.8753, device='cuda:0'), tensor(109.1021, device='cuda:0'), tensor(108.9730, device='cuda:0'), tensor(109.1334, device='cuda:0'), tensor(108.8052, device='cuda:0'), tensor(109.0998, device='cuda:0'), tensor(109.3389, device='cuda:0'), tensor(109.0739, device='cuda:0'), tensor(109.4946, device='cuda:0'), tensor(108.7724, 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=819360), datetime.timedelta(seconds=1, microseconds=808403), datetime.timedelta(seconds=1, microseconds=816317), datetime.timedelta(seconds=1, microseconds=823342), datetime.timedelta(seconds=1, microseconds=825335), datetime.timedelta(seconds=1, microseconds=804422), datetime.timedelta(seconds=1, microseconds=816369), datetime.timedelta(seconds=1, microseconds=826330), datetime.timedelta(seconds=1, microseconds=821351), datetime.timedelta(seconds=1, microseconds=807411)]

Phi time: [datetime.timedelta(seconds=6, microseconds=87279), datetime.timedelta(seconds=5, microseconds=977458), datetime.timedelta(seconds=6, microseconds=102533), datetime.timedelta(seconds=6, microseconds=14621), datetime.timedelta(seconds=6, microseconds=82838), datetime.timedelta(seconds=6, microseconds=104269), datetime.timedelta(seconds=6, microseconds=76819), datetime.timedelta(seconds=6, microseconds=104359), datetime.timedelta(seconds=6, microseconds=16102), datetime.timedelta(seconds=6, microseconds=139610)]

