Precision: [tensor(0.3139, device='cuda:0'), tensor(0.2989, device='cuda:0'), tensor(0.3032, device='cuda:0'), tensor(0.2980, device='cuda:0'), tensor(0.3091, device='cuda:0'), tensor(0.3069, device='cuda:0'), tensor(0.3043, device='cuda:0'), tensor(0.3056, device='cuda:0'), tensor(0.3084, device='cuda:0'), tensor(0.3024, device='cuda:0')]

Output distance: [tensor(6.4227, device='cuda:0'), tensor(6.5130, device='cuda:0'), tensor(6.4867, device='cuda:0'), tensor(6.5182, device='cuda:0'), tensor(6.4516, device='cuda:0'), tensor(6.4647, device='cuda:0'), tensor(6.4804, device='cuda:0'), tensor(6.4726, device='cuda:0'), tensor(6.4558, device='cuda:0'), tensor(6.4920, device='cuda:0')]

Prediction loss: [tensor(13560435., device='cuda:0'), tensor(18626770., device='cuda:0'), tensor(23357738., device='cuda:0'), tensor(19526426., device='cuda:0'), tensor(18984476., device='cuda:0'), tensor(14497494., device='cuda:0'), tensor(15539289., device='cuda:0'), tensor(13661453., device='cuda:0'), tensor(18918924., device='cuda:0'), tensor(20905680., device='cuda:0')]

Others: [{'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}]

Compressed training loss: [tensor(40714.5938, device='cuda:0'), tensor(40776.4297, device='cuda:0'), tensor(40695.2109, device='cuda:0'), tensor(40690.4414, device='cuda:0'), tensor(41182.8047, device='cuda:0'), tensor(40618.8477, device='cuda:0'), tensor(41040.5977, device='cuda:0'), tensor(40694.8047, device='cuda:0'), tensor(40900.6875, device='cuda:0'), tensor(40375.6953, device='cuda:0')]

Training loss: 0

Prediction time: [datetime.timedelta(seconds=14, microseconds=377778), datetime.timedelta(seconds=21, microseconds=795571), datetime.timedelta(seconds=14, microseconds=373033), datetime.timedelta(seconds=12, microseconds=762281), datetime.timedelta(seconds=13, microseconds=770860), datetime.timedelta(seconds=12, microseconds=959211), datetime.timedelta(seconds=15, microseconds=777853), datetime.timedelta(seconds=16, microseconds=543170), datetime.timedelta(seconds=15, microseconds=803482), datetime.timedelta(seconds=15, microseconds=989645)]

Phi time: [datetime.timedelta(microseconds=201152), datetime.timedelta(microseconds=213103), datetime.timedelta(microseconds=222064), datetime.timedelta(microseconds=215094), datetime.timedelta(microseconds=209121), datetime.timedelta(microseconds=216091), datetime.timedelta(microseconds=210116), datetime.timedelta(microseconds=208124), datetime.timedelta(microseconds=214101), datetime.timedelta(microseconds=210116)]

