Precision: [tensor(0.7304, device='cuda:0'), tensor(0.7393, device='cuda:0'), tensor(0.7357, device='cuda:0'), tensor(0.7314, device='cuda:0'), tensor(0.7383, device='cuda:0'), tensor(0.7300, device='cuda:0'), tensor(0.7354, device='cuda:0'), tensor(0.7293, device='cuda:0'), tensor(0.7377, device='cuda:0'), tensor(0.7379, device='cuda:0')]
Output distance: [tensor(5.0168, device='cuda:0'), tensor(5.0053, device='cuda:0'), tensor(5.0108, device='cuda:0'), tensor(5.0152, device='cuda:0'), tensor(5.0079, device='cuda:0'), tensor(5.0181, device='cuda:0'), tensor(5.0100, device='cuda:0'), tensor(5.0192, device='cuda:0'), tensor(5.0050, device='cuda:0'), tensor(5.0087, device='cuda:0')]
Prediction loss: [tensor(19407076., device='cuda:0'), tensor(17723536., device='cuda:0'), tensor(18720446., device='cuda:0'), tensor(18474582., device='cuda:0'), tensor(19200500., device='cuda:0'), tensor(19218368., device='cuda:0'), tensor(18941626., device='cuda:0'), tensor(19048902., device='cuda:0'), tensor(18055420., device='cuda:0'), tensor(20676520., device='cuda:0')]
Others: [{'iter_num': 7, 'num_positive': tensor(2392, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(2394, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(2387, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(2394, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(2384, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(2385, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(2396, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(2383, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(2413, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(2381, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}]
Compressed training loss: [tensor(40924.0859, device='cuda:0'), tensor(40839.6875, device='cuda:0'), tensor(40764.3047, device='cuda:0'), tensor(40743.3516, device='cuda:0'), tensor(40927.3164, device='cuda:0'), tensor(40858.8594, device='cuda:0'), tensor(40741.9453, device='cuda:0'), tensor(40826.7188, device='cuda:0'), tensor(40789.4883, device='cuda:0'), tensor(40923.6992, device='cuda:0')]
Training loss: 0
Prediction time: [datetime.timedelta(seconds=1, microseconds=34613), datetime.timedelta(seconds=1, microseconds=40586), datetime.timedelta(seconds=1, microseconds=19676), datetime.timedelta(seconds=1, microseconds=28637), datetime.timedelta(seconds=1, microseconds=16689), datetime.timedelta(seconds=1, microseconds=25649), datetime.timedelta(seconds=1, microseconds=10713), datetime.timedelta(seconds=1, microseconds=57514), datetime.timedelta(seconds=1, microseconds=39591), datetime.timedelta(seconds=1, microseconds=53532)]
Phi time: [datetime.timedelta(microseconds=236995), datetime.timedelta(microseconds=246952), datetime.timedelta(microseconds=252927), datetime.timedelta(microseconds=254919), datetime.timedelta(microseconds=244961), datetime.timedelta(microseconds=254920), datetime.timedelta(microseconds=235003), datetime.timedelta(microseconds=235004), datetime.timedelta(microseconds=257906), datetime.timedelta(microseconds=256910)]
