Precision: [tensor(0.3211, device='cuda:0'), tensor(0.3166, device='cuda:0'), tensor(0.3148, device='cuda:0'), tensor(0.3293, device='cuda:0'), tensor(0.3270, device='cuda:0'), tensor(0.3215, device='cuda:0'), tensor(0.3184, device='cuda:0'), tensor(0.3137, device='cuda:0'), tensor(0.3102, device='cuda:0'), tensor(0.3196, device='cuda:0')]

Output distance: [tensor(6.3796, device='cuda:0'), tensor(6.4064, device='cuda:0'), tensor(6.4174, device='cuda:0'), tensor(6.3303, device='cuda:0'), tensor(6.3439, device='cuda:0'), tensor(6.3770, device='cuda:0'), tensor(6.3959, device='cuda:0'), tensor(6.4237, device='cuda:0'), tensor(6.4447, device='cuda:0'), tensor(6.3886, device='cuda:0')]

Prediction loss: [tensor(14587201., device='cuda:0'), tensor(17033202., device='cuda:0'), tensor(15712946., device='cuda:0'), tensor(19212740., device='cuda:0'), tensor(18908606., device='cuda:0'), tensor(19600486., device='cuda:0'), tensor(18691546., device='cuda:0'), tensor(19559726., device='cuda:0'), tensor(19788020., device='cuda:0'), tensor(18290226., device='cuda:0')]

Others: [{'iter_num': 60, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 60, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}]

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

Training loss: 0

Prediction time: [datetime.timedelta(seconds=1, microseconds=469796), datetime.timedelta(seconds=1, microseconds=376250), datetime.timedelta(seconds=1, microseconds=401049), datetime.timedelta(seconds=1, microseconds=361269), datetime.timedelta(seconds=1, microseconds=351307), datetime.timedelta(seconds=1, microseconds=388155), datetime.timedelta(seconds=1, microseconds=354299), datetime.timedelta(seconds=1, microseconds=350311), datetime.timedelta(seconds=1, microseconds=355238), datetime.timedelta(seconds=1, microseconds=359271)]

Phi time: [datetime.timedelta(microseconds=256963), datetime.timedelta(microseconds=234011), datetime.timedelta(microseconds=232971), datetime.timedelta(microseconds=242988), datetime.timedelta(microseconds=253932), datetime.timedelta(microseconds=229970), datetime.timedelta(microseconds=229034), datetime.timedelta(microseconds=252882), datetime.timedelta(microseconds=231027), datetime.timedelta(microseconds=237053)]

