Precision: [tensor(0.3082, device='cuda:0'), tensor(0.3142, device='cuda:0'), tensor(0.3001, device='cuda:0'), tensor(0.2976, device='cuda:0'), tensor(0.3062, device='cuda:0'), tensor(0.3187, device='cuda:0'), tensor(0.3157, device='cuda:0'), tensor(0.3180, device='cuda:0'), tensor(0.3175, device='cuda:0'), tensor(0.3054, device='cuda:0')]

Output distance: [tensor(20.1759, device='cuda:0'), tensor(20.1400, device='cuda:0'), tensor(20.2246, device='cuda:0'), tensor(20.2400, device='cuda:0'), tensor(20.1883, device='cuda:0'), tensor(20.1134, device='cuda:0'), tensor(20.1309, device='cuda:0'), tensor(20.1176, device='cuda:0'), tensor(20.1206, device='cuda:0'), tensor(20.1929, device='cuda:0')]

Prediction loss: [tensor(102.9521, device='cuda:0'), tensor(104.3174, device='cuda:0'), tensor(103.7281, device='cuda:0'), tensor(103.9772, device='cuda:0'), tensor(104.0980, device='cuda:0'), tensor(103.9364, device='cuda:0'), tensor(102.6384, device='cuda:0'), tensor(104.0122, device='cuda:0'), tensor(104.6468, device='cuda:0'), tensor(101.8206, device='cuda:0')]

Others: [{'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': 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': 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': 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': 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')}]

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

Training loss: 0

Prediction time: [datetime.timedelta(seconds=2, microseconds=416584), datetime.timedelta(seconds=2, microseconds=426013), datetime.timedelta(seconds=2, microseconds=451420), datetime.timedelta(seconds=2, microseconds=428747), datetime.timedelta(seconds=2, microseconds=454573), datetime.timedelta(seconds=2, microseconds=450047), datetime.timedelta(seconds=2, microseconds=460479), datetime.timedelta(seconds=2, microseconds=426909), datetime.timedelta(seconds=2, microseconds=433693), datetime.timedelta(seconds=2, microseconds=449938)]

Phi time: [datetime.timedelta(seconds=4, microseconds=378969), datetime.timedelta(seconds=4, microseconds=421100), datetime.timedelta(seconds=4, microseconds=429326), datetime.timedelta(seconds=4, microseconds=363300), datetime.timedelta(seconds=4, microseconds=431058), datetime.timedelta(seconds=4, microseconds=422742), datetime.timedelta(seconds=4, microseconds=362464), datetime.timedelta(seconds=4, microseconds=407184), datetime.timedelta(seconds=4, microseconds=416437), datetime.timedelta(seconds=4, microseconds=393593)]

