Precision: [tensor(1., device='cuda:0'), tensor(1., device='cuda:0'), tensor(1., device='cuda:0'), tensor(1., device='cuda:0'), tensor(1., device='cuda:0'), tensor(1., device='cuda:0'), tensor(1., device='cuda:0'), tensor(1., device='cuda:0'), tensor(1., device='cuda:0'), tensor(1., device='cuda:0')]

Output distance: [tensor(38267.6328, device='cuda:0'), tensor(37878.3711, device='cuda:0'), tensor(38052.8594, device='cuda:0'), tensor(38656.2305, device='cuda:0'), tensor(38120.9336, device='cuda:0'), tensor(38236.7852, device='cuda:0'), tensor(38018.8945, device='cuda:0'), tensor(40272.5820, device='cuda:0'), tensor(38706.6602, device='cuda:0'), tensor(38187.9805, device='cuda:0')]

Prediction loss: [tensor(38804.5234, device='cuda:0'), tensor(37782.7422, device='cuda:0'), tensor(36809.6367, device='cuda:0'), tensor(39480.6445, device='cuda:0'), tensor(39238.2461, device='cuda:0'), tensor(39290.5664, device='cuda:0'), tensor(37466.7852, device='cuda:0'), tensor(41268.6523, device='cuda:0'), tensor(37867.3828, device='cuda:0'), tensor(37729.1562, device='cuda:0')]

Others: [{'iter_num': 30, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 17, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 30, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 19, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 23, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 15, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 30, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 25, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'iter_num': 19, 'num_positive': tensor(6000, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}]

Compressed training loss: [tensor(3654835.7500, device='cuda:0'), tensor(3546535.5000, device='cuda:0'), tensor(3518228.7500, device='cuda:0'), tensor(3636029.7500, device='cuda:0'), tensor(3623135.7500, device='cuda:0'), tensor(3619216., device='cuda:0'), tensor(3592947.5000, device='cuda:0'), tensor(3628516.2500, device='cuda:0'), tensor(3514330., device='cuda:0'), tensor(3587012.2500, device='cuda:0')]

Training loss: 3607749.75

Prediction time: [datetime.timedelta(seconds=1, microseconds=869077), datetime.timedelta(microseconds=708971), datetime.timedelta(seconds=1, microseconds=193939), datetime.timedelta(seconds=1, microseconds=888988), datetime.timedelta(seconds=1, microseconds=306462), datetime.timedelta(seconds=1, microseconds=521546), datetime.timedelta(seconds=1, microseconds=87390), datetime.timedelta(seconds=1, microseconds=884074), datetime.timedelta(seconds=1, microseconds=634020), datetime.timedelta(seconds=1, microseconds=303472)]

Phi time: [datetime.timedelta(seconds=1, microseconds=504684), datetime.timedelta(microseconds=982792), datetime.timedelta(microseconds=942686), datetime.timedelta(microseconds=953789), datetime.timedelta(microseconds=946443), datetime.timedelta(microseconds=952265), datetime.timedelta(microseconds=946304), datetime.timedelta(microseconds=935809), datetime.timedelta(microseconds=940910), datetime.timedelta(microseconds=938806)]

