Precision: [tensor(0.9998, device='cuda:0'), tensor(0.9998, device='cuda:0'), tensor(0.9998, device='cuda:0'), tensor(0.9997, device='cuda:0'), tensor(0.9998, device='cuda:0'), tensor(0.9997, device='cuda:0'), tensor(0.9997, device='cuda:0'), tensor(0.9997, device='cuda:0'), tensor(0.9998, device='cuda:0'), tensor(0.9998, device='cuda:0')]

Output distance: [tensor(23339.0938, device='cuda:0'), tensor(23417.7988, device='cuda:0'), tensor(23460.0391, device='cuda:0'), tensor(23368.3965, device='cuda:0'), tensor(23397.4238, device='cuda:0'), tensor(23441.1738, device='cuda:0'), tensor(23345.7969, device='cuda:0'), tensor(23353.3945, device='cuda:0'), tensor(23385.8594, device='cuda:0'), tensor(23384.0684, device='cuda:0')]

Prediction loss: [tensor(24286.8828, device='cuda:0'), tensor(23095.4082, device='cuda:0'), tensor(23305.8262, device='cuda:0'), tensor(23461.6211, device='cuda:0'), tensor(23156.8262, device='cuda:0'), tensor(24455.6074, device='cuda:0'), tensor(24207.5781, device='cuda:0'), tensor(23386.6641, device='cuda:0'), tensor(23907.9844, device='cuda:0'), tensor(22639.6777, device='cuda:0')]

Others: [{'num_positive': tensor(5994, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(5993, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(5992, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(5993, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(5994, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(5994, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(5993, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(5994, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(5994, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(5993, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}]

Compressed training loss: [tensor(9066186., device='cuda:0'), tensor(8716182., device='cuda:0'), tensor(8910463., device='cuda:0'), tensor(8835589., device='cuda:0'), tensor(8770744., device='cuda:0'), tensor(8951810., device='cuda:0'), tensor(8933107., device='cuda:0'), tensor(8825139., device='cuda:0'), tensor(8958338., device='cuda:0'), tensor(8776506., device='cuda:0')]

Training loss: 8828905.0

Prediction time: [datetime.timedelta(seconds=271, microseconds=92513), datetime.timedelta(seconds=276, microseconds=568615), datetime.timedelta(seconds=281, microseconds=989045), datetime.timedelta(seconds=280, microseconds=953593), datetime.timedelta(seconds=277, microseconds=177041), datetime.timedelta(seconds=275, microseconds=667844), datetime.timedelta(seconds=274, microseconds=313437), datetime.timedelta(seconds=272, microseconds=709644), datetime.timedelta(seconds=273, microseconds=640027), datetime.timedelta(seconds=274, microseconds=232335)]

Phi time: [datetime.timedelta(seconds=1, microseconds=509861), datetime.timedelta(microseconds=912188), datetime.timedelta(microseconds=949426), datetime.timedelta(microseconds=918313), datetime.timedelta(microseconds=935682), datetime.timedelta(microseconds=871602), datetime.timedelta(microseconds=842646), datetime.timedelta(microseconds=842983), datetime.timedelta(microseconds=846437), datetime.timedelta(microseconds=843241)]

