Precision: [tensor(0.3521, device='cuda:0'), tensor(0.3579, device='cuda:0'), tensor(0.3581, device='cuda:0'), tensor(0.3509, device='cuda:0'), tensor(0.3488, device='cuda:0'), tensor(0.3499, device='cuda:0'), tensor(0.3484, device='cuda:0'), tensor(0.3494, device='cuda:0'), tensor(0.3583, device='cuda:0'), tensor(0.3597, device='cuda:0')]

Output distance: [tensor(19.9126, device='cuda:0'), tensor(19.8782, device='cuda:0'), tensor(19.8770, device='cuda:0'), tensor(19.9202, device='cuda:0'), tensor(19.9329, device='cuda:0'), tensor(19.9262, device='cuda:0'), tensor(19.9350, device='cuda:0'), tensor(19.9293, device='cuda:0'), tensor(19.8758, device='cuda:0'), tensor(19.8670, device='cuda:0')]

Prediction loss: [tensor(103.6907, device='cuda:0'), tensor(103.7919, device='cuda:0'), tensor(104.5319, device='cuda:0'), tensor(102.9155, device='cuda:0'), tensor(103.4797, device='cuda:0'), tensor(104.1206, device='cuda:0'), tensor(103.1544, device='cuda:0'), tensor(104.5483, device='cuda:0'), tensor(104.3832, device='cuda:0'), tensor(104.6039, device='cuda:0')]

Others: [{'iter_num': 13, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 13, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 13, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 15, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 15, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 13, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 13, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 13, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 15, 'num_positive': tensor(19848, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'iter_num': 15, '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=3, microseconds=2315), datetime.timedelta(seconds=3, microseconds=9234), datetime.timedelta(seconds=3, microseconds=34129), datetime.timedelta(seconds=3, microseconds=116781), datetime.timedelta(seconds=3, microseconds=121765), datetime.timedelta(seconds=3, microseconds=9235), datetime.timedelta(seconds=3, microseconds=11229), datetime.timedelta(seconds=3, microseconds=18203), datetime.timedelta(seconds=3, microseconds=217352), datetime.timedelta(seconds=3, microseconds=212373)]

Phi time: [datetime.timedelta(seconds=5, microseconds=14582), datetime.timedelta(seconds=4, microseconds=999086), datetime.timedelta(seconds=5, microseconds=947), datetime.timedelta(seconds=4, microseconds=983924), datetime.timedelta(seconds=5, microseconds=62411), datetime.timedelta(seconds=5, microseconds=14035), datetime.timedelta(seconds=5, microseconds=36347), datetime.timedelta(seconds=5, microseconds=15742), datetime.timedelta(seconds=5, microseconds=15179), datetime.timedelta(seconds=5, microseconds=85454)]

