Precision: [tensor(0.5536, device='cuda:0'), tensor(0.5591, device='cuda:0'), tensor(0.5575, device='cuda:0'), tensor(0.5588, device='cuda:0'), tensor(0.5564, device='cuda:0'), tensor(0.5579, device='cuda:0'), tensor(0.5559, device='cuda:0'), tensor(0.5519, device='cuda:0'), tensor(0.5555, device='cuda:0'), tensor(0.5546, device='cuda:0')]

Output distance: [tensor(4.9845, device='cuda:0'), tensor(4.9514, device='cuda:0'), tensor(4.9614, device='cuda:0'), tensor(4.9535, device='cuda:0'), tensor(4.9677, device='cuda:0'), tensor(4.9588, device='cuda:0'), tensor(4.9709, device='cuda:0'), tensor(4.9950, device='cuda:0'), tensor(4.9730, device='cuda:0'), tensor(4.9787, device='cuda:0')]

Prediction loss: [tensor(19745466., device='cuda:0'), tensor(18065074., device='cuda:0'), tensor(17639314., device='cuda:0'), tensor(20118134., device='cuda:0'), tensor(17745382., device='cuda:0'), tensor(17220990., device='cuda:0'), tensor(17881026., device='cuda:0'), tensor(18203996., device='cuda:0'), tensor(19086154., device='cuda:0'), tensor(19284556., device='cuda:0')]

Others: [{'iter_num': 30, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 30, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 9, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 30, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 30, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 11, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}, {'iter_num': 7, 'num_positive': tensor(11427, device='cuda:0'), 'num_positive_true': tensor(20211, device='cuda:0')}]

Compressed training loss: [tensor(40877.7539, device='cuda:0'), tensor(40773.8125, device='cuda:0'), tensor(40808.8281, device='cuda:0'), tensor(40779.0938, device='cuda:0'), tensor(40855.4180, device='cuda:0'), tensor(40875.9648, device='cuda:0'), tensor(40885.1641, device='cuda:0'), tensor(40858.2344, device='cuda:0'), tensor(40899.7773, device='cuda:0'), tensor(40826.3672, device='cuda:0')]

Training loss: 0

Prediction time: [datetime.timedelta(seconds=1, microseconds=209992), datetime.timedelta(seconds=1, microseconds=213302), datetime.timedelta(seconds=1, microseconds=30326), datetime.timedelta(seconds=1, microseconds=68964), datetime.timedelta(seconds=1, microseconds=234225), datetime.timedelta(seconds=1, microseconds=60537), datetime.timedelta(seconds=1, microseconds=213688), datetime.timedelta(seconds=1, microseconds=64434), datetime.timedelta(seconds=1, microseconds=84869), datetime.timedelta(seconds=1, microseconds=41932)]

Phi time: [datetime.timedelta(microseconds=229754), datetime.timedelta(microseconds=233282), datetime.timedelta(microseconds=246482), datetime.timedelta(microseconds=214496), datetime.timedelta(microseconds=242806), datetime.timedelta(microseconds=241677), datetime.timedelta(microseconds=240857), datetime.timedelta(microseconds=242473), datetime.timedelta(microseconds=226119), datetime.timedelta(microseconds=250654)]

