Precision: [tensor(0.5952, device='cuda:0'), tensor(0.5941, device='cuda:0'), tensor(0.6004, device='cuda:0'), tensor(0.5957, device='cuda:0'), tensor(0.6009, device='cuda:0'), tensor(0.6059, device='cuda:0'), tensor(0.6101, device='cuda:0'), tensor(0.6067, device='cuda:0'), tensor(0.5936, device='cuda:0'), tensor(0.6012, device='cuda:0')]

Output distance: [tensor(5.1158, device='cuda:0'), tensor(5.1179, device='cuda:0'), tensor(5.1053, device='cuda:0'), tensor(5.1147, device='cuda:0'), tensor(5.1042, device='cuda:0'), tensor(5.0943, device='cuda:0'), tensor(5.0858, device='cuda:0'), tensor(5.0927, device='cuda:0'), tensor(5.1189, device='cuda:0'), tensor(5.1037, device='cuda:0')]

Prediction loss: [tensor(17188072., device='cuda:0'), tensor(19722126., device='cuda:0'), tensor(16699780., device='cuda:0'), tensor(18145036., device='cuda:0'), tensor(21842464., device='cuda:0'), tensor(18307520., device='cuda:0'), tensor(19640126., device='cuda:0'), tensor(19637754., device='cuda:0'), tensor(18615374., device='cuda:0'), tensor(20419376., device='cuda:0')]

Others: [{'iter_num': 7, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 13, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(3809, 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=31624), datetime.timedelta(seconds=1, microseconds=17683), datetime.timedelta(seconds=1, microseconds=32621), datetime.timedelta(seconds=1, microseconds=29635), datetime.timedelta(seconds=1, microseconds=38599), datetime.timedelta(seconds=1, microseconds=45565), datetime.timedelta(seconds=1, microseconds=13700), datetime.timedelta(seconds=1, microseconds=31626), datetime.timedelta(seconds=1, microseconds=32626), datetime.timedelta(seconds=1, microseconds=29635)]

Phi time: [datetime.timedelta(microseconds=240978), datetime.timedelta(microseconds=242971), datetime.timedelta(microseconds=236995), datetime.timedelta(microseconds=255915), datetime.timedelta(microseconds=235003), datetime.timedelta(microseconds=252928), datetime.timedelta(microseconds=268860), datetime.timedelta(microseconds=237991), datetime.timedelta(microseconds=262887), datetime.timedelta(microseconds=254921)]

