Precision: [tensor(0.6004, device='cuda:0'), tensor(0.6046, device='cuda:0'), tensor(0.5939, device='cuda:0'), tensor(0.5988, device='cuda:0'), tensor(0.6012, device='cuda:0'), tensor(0.5973, device='cuda:0'), tensor(0.5986, device='cuda:0'), tensor(0.5988, device='cuda:0'), tensor(0.6015, device='cuda:0'), tensor(0.5952, device='cuda:0')]

Output distance: [tensor(5.1053, device='cuda:0'), tensor(5.0969, device='cuda:0'), tensor(5.1184, device='cuda:0'), tensor(5.1084, device='cuda:0'), tensor(5.1037, device='cuda:0'), tensor(5.1116, device='cuda:0'), tensor(5.1090, device='cuda:0'), tensor(5.1084, device='cuda:0'), tensor(5.1032, device='cuda:0'), tensor(5.1158, device='cuda:0')]

Prediction loss: [tensor(18409888., device='cuda:0'), tensor(21004876., device='cuda:0'), tensor(19051888., device='cuda:0'), tensor(18126784., device='cuda:0'), tensor(18240370., device='cuda:0'), tensor(19308236., device='cuda:0'), tensor(17567494., device='cuda:0'), tensor(17628530., device='cuda:0'), tensor(17176284., device='cuda:0'), tensor(19759170., 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(40892.0156, device='cuda:0'), tensor(40985.6133, device='cuda:0'), tensor(41023.7656, device='cuda:0'), tensor(40684.6758, device='cuda:0'), tensor(40736.1562, device='cuda:0'), tensor(41141.4531, device='cuda:0'), tensor(41119.6484, device='cuda:0'), tensor(40469.1406, device='cuda:0'), tensor(40884.1602, device='cuda:0'), tensor(40732.5547, device='cuda:0')]

Training loss: 0

Prediction time: [datetime.timedelta(seconds=1, microseconds=54529), datetime.timedelta(seconds=1, microseconds=47556), datetime.timedelta(seconds=1, microseconds=14696), datetime.timedelta(seconds=1, microseconds=29633), datetime.timedelta(seconds=1, microseconds=18679), datetime.timedelta(seconds=1, microseconds=31624), datetime.timedelta(seconds=1, microseconds=14696), datetime.timedelta(seconds=1, microseconds=14696), datetime.timedelta(seconds=1, microseconds=30630), datetime.timedelta(seconds=1, microseconds=47557)]

Phi time: [datetime.timedelta(microseconds=252927), datetime.timedelta(microseconds=224051), datetime.timedelta(microseconds=214093), datetime.timedelta(microseconds=213097), datetime.timedelta(microseconds=213097), datetime.timedelta(microseconds=214092), datetime.timedelta(microseconds=216084), datetime.timedelta(microseconds=213096), datetime.timedelta(microseconds=209113), datetime.timedelta(microseconds=219070)]

