Precision: [tensor(0.6241, device='cuda:0'), tensor(0.6319, device='cuda:0'), tensor(0.6264, device='cuda:0'), tensor(0.6329, device='cuda:0'), tensor(0.6306, device='cuda:0'), tensor(0.6362, device='cuda:0'), tensor(0.6235, device='cuda:0'), tensor(0.6312, device='cuda:0'), tensor(0.6278, device='cuda:0'), tensor(0.6311, device='cuda:0')]
Output distance: [tensor(4.9373, device='cuda:0'), tensor(4.9142, device='cuda:0'), tensor(4.9325, device='cuda:0'), tensor(4.9107, device='cuda:0'), tensor(4.9189, device='cuda:0'), tensor(4.9039, device='cuda:0'), tensor(4.9386, device='cuda:0'), tensor(4.9189, device='cuda:0'), tensor(4.9281, device='cuda:0'), tensor(4.9149, device='cuda:0')]
Prediction loss: [tensor(17813784., device='cuda:0'), tensor(18899540., device='cuda:0'), tensor(18818972., device='cuda:0'), tensor(19704666., device='cuda:0'), tensor(17297220., device='cuda:0'), tensor(19705688., device='cuda:0'), tensor(17381136., device='cuda:0'), tensor(18507940., device='cuda:0'), tensor(18068196., device='cuda:0'), tensor(18068548., device='cuda:0')]
Others: [{'iter_num': 7, 'num_positive': tensor(5659, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(5659, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(5631, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(5664, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(5647, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(5624, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(5666, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(5623, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(5632, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(5682, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}]
Compressed training loss: [tensor(40967.9375, device='cuda:0'), tensor(40882.4180, device='cuda:0'), tensor(40923.2656, device='cuda:0'), tensor(40699.4844, device='cuda:0'), tensor(40746.3984, device='cuda:0'), tensor(40850.4062, device='cuda:0'), tensor(40949.9961, device='cuda:0'), tensor(40976.7539, device='cuda:0'), tensor(40822.0469, device='cuda:0'), tensor(40747.1406, device='cuda:0')]
Training loss: 0
Prediction time: [datetime.timedelta(seconds=1, microseconds=59506), datetime.timedelta(seconds=1, microseconds=55523), datetime.timedelta(seconds=1, microseconds=84401), datetime.timedelta(seconds=1, microseconds=86392), datetime.timedelta(seconds=1, microseconds=87388), datetime.timedelta(seconds=1, microseconds=31625), datetime.timedelta(seconds=1, microseconds=60502), datetime.timedelta(seconds=1, microseconds=50545), datetime.timedelta(seconds=1, microseconds=59506), datetime.timedelta(seconds=1, microseconds=56518)]
Phi time: [datetime.timedelta(microseconds=237992), datetime.timedelta(microseconds=243966), datetime.timedelta(microseconds=253924), datetime.timedelta(microseconds=234008), datetime.timedelta(microseconds=256910), datetime.timedelta(microseconds=253923), datetime.timedelta(microseconds=253924), datetime.timedelta(microseconds=254919), datetime.timedelta(microseconds=239982), datetime.timedelta(microseconds=236000)]
