Precision: [tensor(0.9993, device='cuda:0'), tensor(0.9997, device='cuda:0'), tensor(0.9993, device='cuda:0'), tensor(0.9998, device='cuda:0'), tensor(0.9998, device='cuda:0'), tensor(0.9997, device='cuda:0'), tensor(0.9993, device='cuda:0'), tensor(0.9997, device='cuda:0'), tensor(0.9992, device='cuda:0'), tensor(0.9998, device='cuda:0')]

Output distance: [tensor(147290.7188, device='cuda:0'), tensor(142541.1719, device='cuda:0'), tensor(141489.3438, device='cuda:0'), tensor(140840.6875, device='cuda:0'), tensor(138382.0156, device='cuda:0'), tensor(139544.6875, device='cuda:0'), tensor(141431.9688, device='cuda:0'), tensor(138780.4375, device='cuda:0'), tensor(146556.8125, device='cuda:0'), tensor(138370.8281, device='cuda:0')]

Prediction loss: [tensor(143922.3125, device='cuda:0'), tensor(147168.9688, device='cuda:0'), tensor(127028.0391, device='cuda:0'), tensor(120353.8125, device='cuda:0'), tensor(125457.0469, device='cuda:0'), tensor(146047.7656, device='cuda:0'), tensor(146923.9219, device='cuda:0'), tensor(136792.5469, device='cuda:0'), tensor(154266.7344, device='cuda:0'), tensor(125186.2500, device='cuda:0')]

Others: [{'num_positive': tensor(5993, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(5990, device='cuda:0'), 'num_positive_true': tensor(18000, device='cuda:0')}, {'num_positive': tensor(5990, 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(5995, 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(5990, 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')}]

Compressed training loss: [tensor(1.9532e+08, device='cuda:0'), tensor(2.0322e+08, device='cuda:0'), tensor(1.8636e+08, device='cuda:0'), tensor(1.8288e+08, device='cuda:0'), tensor(1.8646e+08, device='cuda:0'), tensor(2.0128e+08, device='cuda:0'), tensor(2.0131e+08, device='cuda:0'), tensor(1.9556e+08, device='cuda:0'), tensor(2.0296e+08, device='cuda:0'), tensor(1.8736e+08, device='cuda:0')]

Training loss: 191462752.0

Prediction time: [datetime.timedelta(seconds=42, microseconds=402538), datetime.timedelta(seconds=42, microseconds=517599), datetime.timedelta(seconds=42, microseconds=548793), datetime.timedelta(seconds=41, microseconds=569621), datetime.timedelta(seconds=42, microseconds=414904), datetime.timedelta(seconds=42, microseconds=457958), datetime.timedelta(seconds=42, microseconds=250946), datetime.timedelta(seconds=42, microseconds=444685), datetime.timedelta(seconds=42, microseconds=453209), datetime.timedelta(seconds=42, microseconds=182284)]

Phi time: [datetime.timedelta(seconds=1, microseconds=97727), datetime.timedelta(microseconds=569161), datetime.timedelta(microseconds=553138), datetime.timedelta(microseconds=548002), datetime.timedelta(microseconds=555733), datetime.timedelta(microseconds=553895), datetime.timedelta(microseconds=555988), datetime.timedelta(microseconds=549108), datetime.timedelta(microseconds=556963), datetime.timedelta(microseconds=552435)]

