Precision: [tensor(0.4335, device='cuda:0'), tensor(0.4388, device='cuda:0'), tensor(0.4334, device='cuda:0'), tensor(0.4356, device='cuda:0'), tensor(0.4323, device='cuda:0'), tensor(0.4222, device='cuda:0'), tensor(0.4290, device='cuda:0'), tensor(0.4365, device='cuda:0'), tensor(0.4277, device='cuda:0'), tensor(0.4398, device='cuda:0')]

Output distance: [tensor(19.4241, device='cuda:0'), tensor(19.3927, device='cuda:0'), tensor(19.4247, device='cuda:0'), tensor(19.4120, device='cuda:0'), tensor(19.4314, device='cuda:0'), tensor(19.4924, device='cuda:0'), tensor(19.4513, device='cuda:0'), tensor(19.4066, device='cuda:0'), tensor(19.4592, device='cuda:0'), tensor(19.3866, device='cuda:0')]

Prediction loss: [tensor(104.4351, device='cuda:0'), tensor(104.7483, device='cuda:0'), tensor(105.0761, device='cuda:0'), tensor(104.2636, device='cuda:0'), tensor(105.0281, device='cuda:0'), tensor(104.0727, device='cuda:0'), tensor(104.1584, device='cuda:0'), tensor(105.3649, device='cuda:0'), tensor(104.4870, device='cuda:0'), tensor(104.7722, device='cuda:0')]

Others: [{'iter_num': 11, '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': 11, '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': 13, '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': 13, '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': 15, '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')}]

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

Training loss: 0

Prediction time: [datetime.timedelta(seconds=2, microseconds=888745), datetime.timedelta(seconds=2, microseconds=933564), datetime.timedelta(seconds=2, microseconds=919615), datetime.timedelta(seconds=2, microseconds=918568), datetime.timedelta(seconds=3, microseconds=74962), datetime.timedelta(seconds=2, microseconds=905675), datetime.timedelta(seconds=3, microseconds=43092), datetime.timedelta(seconds=2, microseconds=918619), datetime.timedelta(seconds=3, microseconds=181506), datetime.timedelta(seconds=2, microseconds=927606)]

Phi time: [datetime.timedelta(seconds=5, microseconds=156504), datetime.timedelta(seconds=5, microseconds=142436), datetime.timedelta(seconds=5, microseconds=114704), datetime.timedelta(seconds=5, microseconds=170922), datetime.timedelta(seconds=5, microseconds=145567), datetime.timedelta(seconds=5, microseconds=69079), datetime.timedelta(seconds=5, microseconds=169446), datetime.timedelta(seconds=5, microseconds=132010), datetime.timedelta(seconds=5, microseconds=114666), datetime.timedelta(seconds=5, microseconds=119960)]

