Precision: [tensor(0.8249, device='cuda:0'), tensor(0.8272, device='cuda:0'), tensor(0.8250, device='cuda:0'), tensor(0.8252, device='cuda:0'), tensor(0.8243, device='cuda:0'), tensor(0.8254, device='cuda:0'), tensor(0.8253, device='cuda:0'), tensor(0.8262, device='cuda:0'), tensor(0.8253, device='cuda:0'), tensor(0.8247, device='cuda:0')]

Output distance: [tensor(13592.6982, device='cuda:0'), tensor(13453.1533, device='cuda:0'), tensor(13592.9834, device='cuda:0'), tensor(13578.7676, device='cuda:0'), tensor(13645.0078, device='cuda:0'), tensor(13579.9639, device='cuda:0'), tensor(13574.4375, device='cuda:0'), tensor(13512.8701, device='cuda:0'), tensor(13559.9639, device='cuda:0'), tensor(13617.2090, device='cuda:0')]

Prediction loss: [tensor(10664.6484, device='cuda:0'), tensor(10575.9854, device='cuda:0'), tensor(10613.3711, device='cuda:0'), tensor(10604.3467, device='cuda:0'), tensor(10661.0908, device='cuda:0'), tensor(10556.3682, device='cuda:0'), tensor(10753.6973, device='cuda:0'), tensor(10686.9443, device='cuda:0'), tensor(10555.4502, device='cuda:0'), tensor(10608.3184, device='cuda:0')]

Others: [{'iter_num': 11, 'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(18000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}]

Compressed training loss: [tensor(1.9330e+08, device='cuda:0'), tensor(1.9187e+08, device='cuda:0'), tensor(1.9260e+08, device='cuda:0'), tensor(1.9242e+08, device='cuda:0'), tensor(1.9331e+08, device='cuda:0'), tensor(1.9149e+08, device='cuda:0'), tensor(1.9480e+08, device='cuda:0'), tensor(1.9378e+08, device='cuda:0'), tensor(1.9154e+08, device='cuda:0'), tensor(1.9235e+08, device='cuda:0')]

Training loss: 192271840.0

Prediction time: [datetime.timedelta(seconds=1, microseconds=149167), datetime.timedelta(seconds=1, microseconds=180037), datetime.timedelta(seconds=1, microseconds=158129), datetime.timedelta(seconds=1, microseconds=162112), datetime.timedelta(seconds=1, microseconds=167091), datetime.timedelta(seconds=1, microseconds=10751), datetime.timedelta(seconds=1, microseconds=168087), datetime.timedelta(seconds=1, microseconds=169084), datetime.timedelta(seconds=1, microseconds=167093), datetime.timedelta(seconds=1, microseconds=13735)]

Phi time: [datetime.timedelta(seconds=1, microseconds=918663), datetime.timedelta(seconds=1, microseconds=289612), datetime.timedelta(seconds=1, microseconds=301899), datetime.timedelta(seconds=1, microseconds=299834), datetime.timedelta(seconds=1, microseconds=304208), datetime.timedelta(seconds=1, microseconds=304753), datetime.timedelta(seconds=1, microseconds=317233), datetime.timedelta(seconds=1, microseconds=303178), datetime.timedelta(seconds=1, microseconds=300655), datetime.timedelta(seconds=1, microseconds=301511)]

