Precision: [tensor(0.6918, device='cuda:0'), tensor(0.7007, device='cuda:0'), tensor(0.6934, device='cuda:0'), tensor(0.6926, device='cuda:0'), tensor(0.6968, device='cuda:0'), tensor(0.6957, device='cuda:0'), tensor(0.6947, device='cuda:0'), tensor(0.6955, device='cuda:0'), tensor(0.6934, device='cuda:0'), tensor(0.6970, device='cuda:0')]

Output distance: [tensor(4.9226, device='cuda:0'), tensor(4.9047, device='cuda:0'), tensor(4.9194, device='cuda:0'), tensor(4.9210, device='cuda:0'), tensor(4.9126, device='cuda:0'), tensor(4.9147, device='cuda:0'), tensor(4.9168, device='cuda:0'), tensor(4.9152, device='cuda:0'), tensor(4.9194, device='cuda:0'), tensor(4.9121, device='cuda:0')]

Prediction loss: [tensor(18072812., device='cuda:0'), tensor(18338320., device='cuda:0'), tensor(18910388., device='cuda:0'), tensor(17696576., device='cuda:0'), tensor(17978296., device='cuda:0'), tensor(19205730., device='cuda:0'), tensor(19257776., device='cuda:0'), tensor(18342374., device='cuda:0'), tensor(17901192., device='cuda:0'), tensor(18750966., device='cuda:0')]

Others: [{'iter_num': 5, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 30, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 30, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 30, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 5, 'num_positive': tensor(3809, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}]

Compressed training loss: [tensor(40813.2148, device='cuda:0'), tensor(40874.9961, device='cuda:0'), tensor(40807.4766, device='cuda:0'), tensor(40969.1133, device='cuda:0'), tensor(40776.8633, device='cuda:0'), tensor(40891.9922, device='cuda:0'), tensor(40742.1562, device='cuda:0'), tensor(40762.2578, device='cuda:0'), tensor(40812.8203, device='cuda:0'), tensor(40874.6328, device='cuda:0')]

Training loss: 0

Prediction time: [datetime.timedelta(seconds=1, microseconds=104), datetime.timedelta(seconds=1, microseconds=229321), datetime.timedelta(microseconds=996467), datetime.timedelta(seconds=1, microseconds=2442), datetime.timedelta(microseconds=986801), datetime.timedelta(seconds=1, microseconds=180333), datetime.timedelta(seconds=1, microseconds=4471), datetime.timedelta(seconds=1, microseconds=202306), datetime.timedelta(seconds=1, microseconds=6505), datetime.timedelta(microseconds=999983)]

Phi time: [datetime.timedelta(microseconds=287368), datetime.timedelta(microseconds=299974), datetime.timedelta(microseconds=308481), datetime.timedelta(microseconds=297555), datetime.timedelta(microseconds=299990), datetime.timedelta(microseconds=298547), datetime.timedelta(microseconds=298608), datetime.timedelta(microseconds=288645), datetime.timedelta(microseconds=287768), datetime.timedelta(microseconds=287443)]

