Precision: [tensor(0.3437, device='cuda:0'), tensor(0.3371, device='cuda:0'), tensor(0.3319, device='cuda:0'), tensor(0.3396, device='cuda:0'), tensor(0.3367, device='cuda:0'), tensor(0.3349, device='cuda:0'), tensor(0.3322, device='cuda:0'), tensor(0.3336, device='cuda:0'), tensor(0.3369, device='cuda:0'), tensor(0.3414, device='cuda:0')]

Output distance: [tensor(6.2436, device='cuda:0'), tensor(6.2835, device='cuda:0'), tensor(6.3145, device='cuda:0'), tensor(6.2683, device='cuda:0'), tensor(6.2856, device='cuda:0'), tensor(6.2967, device='cuda:0'), tensor(6.3129, device='cuda:0'), tensor(6.3045, device='cuda:0'), tensor(6.2846, device='cuda:0'), tensor(6.2578, device='cuda:0')]

Prediction loss: [tensor(19331226., device='cuda:0'), tensor(16988368., device='cuda:0'), tensor(18784406., device='cuda:0'), tensor(18649600., device='cuda:0'), tensor(20333382., device='cuda:0'), tensor(13375762., device='cuda:0'), tensor(19718238., device='cuda:0'), tensor(17689002., device='cuda:0'), tensor(19286060., device='cuda:0'), tensor(17398136., device='cuda:0')]

Others: [{'iter_num': 21, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 23, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 19, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 27, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 21, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 25, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 21, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 41, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 21, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 23, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, 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=155102), datetime.timedelta(seconds=1, microseconds=160083), datetime.timedelta(seconds=1, microseconds=120251), datetime.timedelta(seconds=1, microseconds=173026), datetime.timedelta(seconds=1, microseconds=124234), datetime.timedelta(seconds=1, microseconds=167052), datetime.timedelta(seconds=1, microseconds=136183), datetime.timedelta(seconds=1, microseconds=230781), datetime.timedelta(seconds=1, microseconds=153112), datetime.timedelta(seconds=1, microseconds=254681)]

Phi time: [datetime.timedelta(microseconds=198158), datetime.timedelta(microseconds=204137), datetime.timedelta(microseconds=205130), datetime.timedelta(microseconds=209114), datetime.timedelta(microseconds=208120), datetime.timedelta(microseconds=198160), datetime.timedelta(microseconds=205130), datetime.timedelta(microseconds=193181), datetime.timedelta(microseconds=194178), datetime.timedelta(microseconds=209114)]

