Precision: [tensor(0.5495, device='cuda:0'), tensor(0.5476, device='cuda:0'), tensor(0.5504, device='cuda:0'), tensor(0.5547, device='cuda:0'), tensor(0.5494, device='cuda:0'), tensor(0.5510, device='cuda:0'), tensor(0.5506, device='cuda:0'), tensor(0.5514, device='cuda:0'), tensor(0.5491, device='cuda:0'), tensor(0.5510, device='cuda:0')]
Output distance: [tensor(5.0092, device='cuda:0'), tensor(5.0207, device='cuda:0'), tensor(5.0039, device='cuda:0'), tensor(4.9782, device='cuda:0'), tensor(5.0097, device='cuda:0'), tensor(5.0003, device='cuda:0'), tensor(5.0024, device='cuda:0'), tensor(4.9976, device='cuda:0'), tensor(5.0118, device='cuda:0'), tensor(5.0003, device='cuda:0')]
Prediction loss: [tensor(17151572., device='cuda:0'), tensor(18805636., device='cuda:0'), tensor(17985714., device='cuda:0'), tensor(19029898., device='cuda:0'), tensor(18712914., device='cuda:0'), tensor(18318096., device='cuda:0'), tensor(17824462., device='cuda:0'), tensor(18032388., device='cuda:0'), tensor(19235704., device='cuda:0'), tensor(18087126., device='cuda:0')]
Others: [{'iter_num': 7, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}]
Compressed training loss: [tensor(40793.0352, device='cuda:0'), tensor(40858.7344, device='cuda:0'), tensor(40868.2305, device='cuda:0'), tensor(40790.8633, device='cuda:0'), tensor(40851.9609, device='cuda:0'), tensor(40797.9883, device='cuda:0'), tensor(40750.6875, device='cuda:0'), tensor(40879.5273, device='cuda:0'), tensor(40690.7539, device='cuda:0'), tensor(40767.2383, device='cuda:0')]
Training loss: 0
Prediction time: [datetime.timedelta(seconds=1, microseconds=78426), datetime.timedelta(seconds=1, microseconds=92368), datetime.timedelta(seconds=1, microseconds=102325), datetime.timedelta(seconds=1, microseconds=86393), datetime.timedelta(seconds=1, microseconds=83405), datetime.timedelta(seconds=1, microseconds=72452), datetime.timedelta(seconds=1, microseconds=84401), datetime.timedelta(seconds=1, microseconds=79421), datetime.timedelta(seconds=1, microseconds=80418), datetime.timedelta(seconds=1, microseconds=86393)]
Phi time: [datetime.timedelta(microseconds=235004), datetime.timedelta(microseconds=243965), datetime.timedelta(microseconds=232016), datetime.timedelta(microseconds=235999), datetime.timedelta(microseconds=232016), datetime.timedelta(microseconds=232016), datetime.timedelta(microseconds=232016), datetime.timedelta(microseconds=232016), datetime.timedelta(microseconds=253924), datetime.timedelta(microseconds=236995)]
