Precision: [tensor(0.6235, device='cuda:0'), tensor(0.6282, device='cuda:0'), tensor(0.6247, device='cuda:0'), tensor(0.6199, device='cuda:0'), tensor(0.6293, device='cuda:0'), tensor(0.6232, device='cuda:0'), tensor(0.6260, device='cuda:0'), tensor(0.6284, device='cuda:0'), tensor(0.6275, device='cuda:0'), tensor(0.6290, device='cuda:0')]
Output distance: [tensor(4.9724, device='cuda:0'), tensor(4.9583, device='cuda:0'), tensor(4.9693, device='cuda:0'), tensor(4.9816, device='cuda:0'), tensor(4.9546, device='cuda:0'), tensor(4.9661, device='cuda:0'), tensor(4.9585, device='cuda:0'), tensor(4.9575, device='cuda:0'), tensor(4.9585, device='cuda:0'), tensor(4.9580, device='cuda:0')]
Prediction loss: [tensor(17287360., device='cuda:0'), tensor(18155576., device='cuda:0'), tensor(19082200., device='cuda:0'), tensor(17827952., device='cuda:0'), tensor(18074042., device='cuda:0'), tensor(16743915., device='cuda:0'), tensor(18929636., device='cuda:0'), tensor(19533304., device='cuda:0'), tensor(18089234., device='cuda:0'), tensor(18151760., device='cuda:0')]
Others: [{'iter_num': 7, 'num_positive': tensor(5145, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(5167, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(5143, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(5156, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(5179, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(5257, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(5254, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(5172, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(5192, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(5138, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}]
Compressed training loss: [tensor(40848.3789, device='cuda:0'), tensor(40998.2617, device='cuda:0'), tensor(40813.8594, device='cuda:0'), tensor(40788.8164, device='cuda:0'), tensor(40718.8984, device='cuda:0'), tensor(41034.6562, device='cuda:0'), tensor(40871.7891, device='cuda:0'), tensor(40822.9844, device='cuda:0'), tensor(40951.2109, device='cuda:0'), tensor(40808.8750, device='cuda:0')]
Training loss: 0
Prediction time: [datetime.timedelta(seconds=1, microseconds=46609), datetime.timedelta(seconds=1, microseconds=38648), datetime.timedelta(seconds=1, microseconds=12757), datetime.timedelta(seconds=1, microseconds=4840), datetime.timedelta(seconds=1, microseconds=19708), datetime.timedelta(seconds=1, microseconds=33667), datetime.timedelta(microseconds=994827), datetime.timedelta(seconds=1, microseconds=5790), datetime.timedelta(seconds=1, microseconds=13754), datetime.timedelta(seconds=1, microseconds=20721)]
Phi time: [datetime.timedelta(microseconds=228049), datetime.timedelta(microseconds=252937), datetime.timedelta(microseconds=242978), datetime.timedelta(microseconds=244924), datetime.timedelta(microseconds=234016), datetime.timedelta(microseconds=243975), datetime.timedelta(microseconds=250949), datetime.timedelta(microseconds=227044), datetime.timedelta(microseconds=237027), datetime.timedelta(microseconds=227067)]
