Precision: [tensor(0.6288, device='cuda:0'), tensor(0.6276, device='cuda:0'), tensor(0.6282, device='cuda:0'), tensor(0.6317, device='cuda:0'), tensor(0.6269, device='cuda:0'), tensor(0.6282, device='cuda:0'), tensor(0.6287, device='cuda:0'), tensor(0.6269, device='cuda:0'), tensor(0.6331, device='cuda:0'), tensor(0.6288, device='cuda:0')]
Output distance: [tensor(4.9233, device='cuda:0'), tensor(4.9268, device='cuda:0'), tensor(4.9241, device='cuda:0'), tensor(4.9168, device='cuda:0'), tensor(4.9331, device='cuda:0'), tensor(4.9249, device='cuda:0'), tensor(4.9239, device='cuda:0'), tensor(4.9291, device='cuda:0'), tensor(4.9118, device='cuda:0'), tensor(4.9244, device='cuda:0')]
Prediction loss: [tensor(17518650., device='cuda:0'), tensor(18426412., device='cuda:0'), tensor(18893636., device='cuda:0'), tensor(17100780., device='cuda:0'), tensor(18055554., device='cuda:0'), tensor(17729348., device='cuda:0'), tensor(19086476., device='cuda:0'), tensor(18247104., device='cuda:0'), tensor(18836562., device='cuda:0'), tensor(17537962., device='cuda:0')]
Others: [{'iter_num': 7, 'num_positive': tensor(5658, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(5663, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(5675, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(5631, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(5597, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(5664, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(5658, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(5656, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(5642, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(5646, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}]
Compressed training loss: [tensor(40766.0586, device='cuda:0'), tensor(40869.2891, device='cuda:0'), tensor(40845.4375, device='cuda:0'), tensor(40893.5781, device='cuda:0'), tensor(40739.3242, device='cuda:0'), tensor(40806.9766, device='cuda:0'), tensor(40797.5352, device='cuda:0'), tensor(41004.2656, device='cuda:0'), tensor(40831.8633, device='cuda:0'), tensor(40741.9453, device='cuda:0')]
Training loss: 0
Prediction time: [datetime.timedelta(seconds=1, microseconds=28685), datetime.timedelta(seconds=1, microseconds=8764), datetime.timedelta(seconds=1, microseconds=32675), datetime.timedelta(seconds=1, microseconds=800), datetime.timedelta(microseconds=988857), datetime.timedelta(seconds=1, microseconds=12758), datetime.timedelta(seconds=1, microseconds=56622), datetime.timedelta(seconds=1, microseconds=16687), datetime.timedelta(seconds=1, microseconds=137230), datetime.timedelta(microseconds=982888)]
Phi time: [datetime.timedelta(microseconds=230038), datetime.timedelta(microseconds=253946), datetime.timedelta(microseconds=251945), datetime.timedelta(microseconds=239989), datetime.timedelta(microseconds=250947), datetime.timedelta(microseconds=231029), datetime.timedelta(microseconds=226004), datetime.timedelta(microseconds=229033), datetime.timedelta(microseconds=227098), datetime.timedelta(microseconds=231025)]
