Precision: [tensor(0.6411, device='cuda:0'), tensor(0.6587, device='cuda:0'), tensor(0.6506, device='cuda:0'), tensor(0.6453, device='cuda:0'), tensor(0.6453, device='cuda:0'), tensor(0.6532, device='cuda:0'), tensor(0.6437, device='cuda:0'), tensor(0.6482, device='cuda:0'), tensor(0.6456, device='cuda:0'), tensor(0.6487, device='cuda:0')]

Output distance: [tensor(5.0239, device='cuda:0'), tensor(4.9887, device='cuda:0'), tensor(5.0050, device='cuda:0'), tensor(5.0155, device='cuda:0'), tensor(5.0155, device='cuda:0'), tensor(4.9997, device='cuda:0'), tensor(5.0186, device='cuda:0'), tensor(5.0097, device='cuda:0'), tensor(5.0150, device='cuda:0'), tensor(5.0087, device='cuda:0')]

Prediction loss: [tensor(18285538., device='cuda:0'), tensor(19815344., device='cuda:0'), tensor(19514450., device='cuda:0'), tensor(16909238., device='cuda:0'), tensor(16789526., device='cuda:0'), tensor(19655126., device='cuda:0'), tensor(18509868., device='cuda:0'), tensor(18102196., device='cuda:0'), tensor(17957096., device='cuda:0'), tensor(17736176., device='cuda:0')]

Others: [{'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}]

Compressed training loss: [tensor(40599.1445, device='cuda:0'), tensor(40826.3320, device='cuda:0'), tensor(40930.1211, device='cuda:0'), tensor(40819.7383, device='cuda:0'), tensor(40528.4922, device='cuda:0'), tensor(40858.8047, device='cuda:0'), tensor(40901.4531, device='cuda:0'), tensor(40686.0703, device='cuda:0'), tensor(41002.8945, device='cuda:0'), tensor(40734.8086, device='cuda:0')]

Training loss: 0

Prediction time: [datetime.timedelta(seconds=24, microseconds=778349), datetime.timedelta(seconds=25, microseconds=303493), datetime.timedelta(seconds=25, microseconds=330066), datetime.timedelta(seconds=25, microseconds=184030), datetime.timedelta(seconds=25, microseconds=295274), datetime.timedelta(seconds=25, microseconds=277145), datetime.timedelta(seconds=25, microseconds=316460), datetime.timedelta(seconds=23, microseconds=245759), datetime.timedelta(seconds=25, microseconds=199817), datetime.timedelta(seconds=25, microseconds=308880)]

Phi time: [datetime.timedelta(microseconds=187470), datetime.timedelta(microseconds=345417), datetime.timedelta(microseconds=345253), datetime.timedelta(microseconds=349117), datetime.timedelta(microseconds=331764), datetime.timedelta(microseconds=339402), datetime.timedelta(microseconds=388265), datetime.timedelta(microseconds=399944), datetime.timedelta(microseconds=268516), datetime.timedelta(microseconds=258957)]

