Precision: [tensor(0.5521, device='cuda:0'), tensor(0.5510, device='cuda:0'), tensor(0.5509, device='cuda:0'), tensor(0.5492, device='cuda:0'), tensor(0.5484, device='cuda:0'), tensor(0.5499, device='cuda:0'), tensor(0.5507, device='cuda:0'), tensor(0.5471, device='cuda:0'), tensor(0.5505, device='cuda:0'), tensor(0.5496, device='cuda:0')]
Output distance: [tensor(4.9934, device='cuda:0'), tensor(5.0003, device='cuda:0'), tensor(5.0008, device='cuda:0'), tensor(5.0108, device='cuda:0'), tensor(5.0160, device='cuda:0'), tensor(5.0066, device='cuda:0'), tensor(5.0018, device='cuda:0'), tensor(5.0234, device='cuda:0'), tensor(5.0034, device='cuda:0'), tensor(5.0087, device='cuda:0')]
Prediction loss: [tensor(18660430., device='cuda:0'), tensor(17503474., device='cuda:0'), tensor(18278714., device='cuda:0'), tensor(17913834., device='cuda:0'), tensor(19118344., device='cuda:0'), tensor(18750222., device='cuda:0'), tensor(18406990., device='cuda:0'), tensor(17981014., device='cuda:0'), tensor(18712310., device='cuda:0'), tensor(19681294., 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': 9, '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': 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')}]
Compressed training loss: [tensor(40853.2031, device='cuda:0'), tensor(40748.1055, device='cuda:0'), tensor(40855.2266, device='cuda:0'), tensor(40864.9023, device='cuda:0'), tensor(40826.3672, device='cuda:0'), tensor(40823.7227, device='cuda:0'), tensor(40813.4766, device='cuda:0'), tensor(40855.3125, device='cuda:0'), tensor(40973.2500, device='cuda:0'), tensor(40843.5547, device='cuda:0')]
Training loss: 0
Prediction time: [datetime.timedelta(microseconds=127457), datetime.timedelta(microseconds=129448), datetime.timedelta(microseconds=138410), datetime.timedelta(microseconds=132435), datetime.timedelta(microseconds=140394), datetime.timedelta(microseconds=143389), datetime.timedelta(microseconds=125465), datetime.timedelta(microseconds=127456), datetime.timedelta(microseconds=140402), datetime.timedelta(microseconds=129448)]
Phi time: [datetime.timedelta(microseconds=355492), datetime.timedelta(microseconds=243071), datetime.timedelta(microseconds=236002), datetime.timedelta(microseconds=243969), datetime.timedelta(microseconds=236998), datetime.timedelta(microseconds=258905), datetime.timedelta(microseconds=238990), datetime.timedelta(microseconds=237994), datetime.timedelta(microseconds=234011), datetime.timedelta(microseconds=236997)]
