Precision: [tensor(0.7354, device='cuda:0'), tensor(0.7383, device='cuda:0'), tensor(0.7290, device='cuda:0'), tensor(0.7435, device='cuda:0'), tensor(0.7356, device='cuda:0'), tensor(0.7354, device='cuda:0'), tensor(0.7443, device='cuda:0'), tensor(0.7325, device='cuda:0'), tensor(0.7269, device='cuda:0'), tensor(0.7388, device='cuda:0')]
Output distance: [tensor(5.0323, device='cuda:0'), tensor(5.0326, device='cuda:0'), tensor(5.0407, device='cuda:0'), tensor(5.0255, device='cuda:0'), tensor(5.0362, device='cuda:0'), tensor(5.0339, device='cuda:0'), tensor(5.0268, device='cuda:0'), tensor(5.0423, device='cuda:0'), tensor(5.0449, device='cuda:0'), tensor(5.0362, device='cuda:0')]
Prediction loss: [tensor(20241226., device='cuda:0'), tensor(19575400., device='cuda:0'), tensor(19128282., device='cuda:0'), tensor(18927166., device='cuda:0'), tensor(19047218., device='cuda:0'), tensor(18259518., device='cuda:0'), tensor(18761382., device='cuda:0'), tensor(19753844., device='cuda:0'), tensor(18357180., device='cuda:0'), tensor(19217476., device='cuda:0')]
Others: [{'iter_num': 7, 'num_positive': tensor(2215, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(2186, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(2207, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(2195, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(2182, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(2203, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(2178, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(2161, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(2193, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(2152, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}]
Compressed training loss: [tensor(40897.8984, device='cuda:0'), tensor(40834.0898, device='cuda:0'), tensor(40905.0391, device='cuda:0'), tensor(41023.3711, device='cuda:0'), tensor(40733.8672, device='cuda:0'), tensor(40927.9766, device='cuda:0'), tensor(40910.6680, device='cuda:0'), tensor(40785.2539, device='cuda:0'), tensor(40829.7969, device='cuda:0'), tensor(40657.1758, device='cuda:0')]
Training loss: 0
Prediction time: [datetime.timedelta(microseconds=982837), datetime.timedelta(microseconds=982882), datetime.timedelta(microseconds=972875), datetime.timedelta(microseconds=968889), datetime.timedelta(microseconds=977849), datetime.timedelta(microseconds=979897), datetime.timedelta(seconds=1, microseconds=4746), datetime.timedelta(microseconds=964905), datetime.timedelta(microseconds=998818), datetime.timedelta(microseconds=972920)]
Phi time: [datetime.timedelta(microseconds=237042), datetime.timedelta(microseconds=233014), datetime.timedelta(microseconds=246952), datetime.timedelta(microseconds=255912), datetime.timedelta(microseconds=228024), datetime.timedelta(microseconds=241042), datetime.timedelta(microseconds=225038), datetime.timedelta(microseconds=233956), datetime.timedelta(microseconds=244908), datetime.timedelta(microseconds=223995)]
