Precision: [tensor(0.9083, device='cuda:0'), tensor(0.9077, device='cuda:0'), tensor(0.9107, device='cuda:0'), tensor(0.9117, device='cuda:0'), tensor(0.9103, device='cuda:0'), tensor(0.9127, device='cuda:0'), tensor(0.9136, device='cuda:0'), tensor(0.9076, device='cuda:0'), tensor(0.9119, device='cuda:0'), tensor(0.9130, device='cuda:0')]

Output distance: [tensor(598.3158, device='cuda:0'), tensor(581.2533, device='cuda:0'), tensor(563.4316, device='cuda:0'), tensor(560.9727, device='cuda:0'), tensor(556.1940, device='cuda:0'), tensor(553.7224, device='cuda:0'), tensor(535.0980, device='cuda:0'), tensor(587.1593, device='cuda:0'), tensor(563.2719, device='cuda:0'), tensor(559.2657, device='cuda:0')]

Prediction loss: [tensor(656.0807, device='cuda:0'), tensor(614.9120, device='cuda:0'), tensor(625.5261, device='cuda:0'), tensor(626.7864, device='cuda:0'), tensor(631.1313, device='cuda:0'), tensor(574.0379, device='cuda:0'), tensor(661.5840, device='cuda:0'), tensor(634.2985, device='cuda:0'), tensor(586.1852, device='cuda:0'), tensor(582.2615, device='cuda:0')]

Others: [{'num_positive': tensor(16553, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16525, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16566, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16589, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16546, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16591, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16626, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16533, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16614, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(16562, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}]

Compressed training loss: [tensor(9496100., device='cuda:0'), tensor(8766591., device='cuda:0'), tensor(8963627., device='cuda:0'), tensor(9060084., device='cuda:0'), tensor(9018197., device='cuda:0'), tensor(8322901., device='cuda:0'), tensor(9287161., device='cuda:0'), tensor(9031302., device='cuda:0'), tensor(8425572., device='cuda:0'), tensor(8417291., device='cuda:0')]

Training loss: 8902065.0

Prediction time: [datetime.timedelta(seconds=47, microseconds=926117), datetime.timedelta(seconds=47, microseconds=735150), datetime.timedelta(seconds=50, microseconds=79488), datetime.timedelta(seconds=51, microseconds=906685), datetime.timedelta(seconds=51, microseconds=376909), datetime.timedelta(seconds=51, microseconds=844625), datetime.timedelta(seconds=51, microseconds=570401), datetime.timedelta(seconds=51, microseconds=439918), datetime.timedelta(seconds=50, microseconds=827822), datetime.timedelta(seconds=49, microseconds=756674)]

Phi time: [datetime.timedelta(seconds=1, microseconds=238323), datetime.timedelta(microseconds=627964), datetime.timedelta(microseconds=657213), datetime.timedelta(microseconds=641279), datetime.timedelta(microseconds=637488), datetime.timedelta(microseconds=629140), datetime.timedelta(microseconds=632156), datetime.timedelta(microseconds=644080), datetime.timedelta(microseconds=649067), datetime.timedelta(microseconds=645328)]

