Precision: [tensor(0.3989, device='cuda:0'), tensor(0.4036, device='cuda:0'), tensor(0.3928, device='cuda:0'), tensor(0.4002, device='cuda:0'), tensor(0.4053, device='cuda:0'), tensor(0.3927, device='cuda:0'), tensor(0.4012, device='cuda:0'), tensor(0.3982, device='cuda:0'), tensor(0.3848, device='cuda:0'), tensor(0.3957, device='cuda:0')]

Output distance: [tensor(19.6321, device='cuda:0'), tensor(19.6037, device='cuda:0'), tensor(19.6684, device='cuda:0'), tensor(19.6239, device='cuda:0'), tensor(19.5937, device='cuda:0'), tensor(19.6690, device='cuda:0'), tensor(19.6182, device='cuda:0'), tensor(19.6363, device='cuda:0'), tensor(19.7164, device='cuda:0'), tensor(19.6515, device='cuda:0')]

Prediction loss: [tensor(103.6657, device='cuda:0'), tensor(105.0171, device='cuda:0'), tensor(105.3355, device='cuda:0'), tensor(104.9870, device='cuda:0'), tensor(105.2015, device='cuda:0'), tensor(103.9801, device='cuda:0'), tensor(104.1127, device='cuda:0'), tensor(104.3337, device='cuda:0'), tensor(103.8719, device='cuda:0'), tensor(104.2966, device='cuda:0')]

Others: [{'iter_num': 9, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}]

Compressed training loss: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]

Training loss: 0

Prediction time: [datetime.timedelta(seconds=2, microseconds=523434), datetime.timedelta(seconds=2, microseconds=671170), datetime.timedelta(seconds=2, microseconds=519696), datetime.timedelta(seconds=2, microseconds=439831), datetime.timedelta(seconds=2, microseconds=531724), datetime.timedelta(seconds=2, microseconds=547087), datetime.timedelta(seconds=2, microseconds=695936), datetime.timedelta(seconds=2, microseconds=449930), datetime.timedelta(seconds=2, microseconds=549940), datetime.timedelta(seconds=2, microseconds=421199)]

Phi time: [datetime.timedelta(seconds=4, microseconds=624710), datetime.timedelta(seconds=4, microseconds=695198), datetime.timedelta(seconds=4, microseconds=640726), datetime.timedelta(seconds=4, microseconds=603663), datetime.timedelta(seconds=4, microseconds=636745), datetime.timedelta(seconds=4, microseconds=598483), datetime.timedelta(seconds=4, microseconds=621849), datetime.timedelta(seconds=4, microseconds=609408), datetime.timedelta(seconds=4, microseconds=655275), datetime.timedelta(seconds=4, microseconds=626709)]

