Precision: [tensor(0.3247, device='cuda:0'), tensor(0.3106, device='cuda:0'), tensor(0.3222, device='cuda:0'), tensor(0.3199, device='cuda:0'), tensor(0.3246, device='cuda:0'), tensor(0.3223, device='cuda:0'), tensor(0.3134, device='cuda:0'), tensor(0.3189, device='cuda:0'), tensor(0.3193, device='cuda:0'), tensor(0.3159, device='cuda:0')]

Output distance: [tensor(20.7784, device='cuda:0'), tensor(20.9193, device='cuda:0'), tensor(20.8035, device='cuda:0'), tensor(20.8262, device='cuda:0'), tensor(20.7796, device='cuda:0'), tensor(20.8023, device='cuda:0'), tensor(20.8915, device='cuda:0'), tensor(20.8368, device='cuda:0'), tensor(20.8319, device='cuda:0'), tensor(20.8664, device='cuda:0')]

Prediction loss: [tensor(101.2877, device='cuda:0'), tensor(100.3888, device='cuda:0'), tensor(101.7312, device='cuda:0'), tensor(101.3920, device='cuda:0'), tensor(102.6811, device='cuda:0'), tensor(101.7743, device='cuda:0'), tensor(100.4705, device='cuda:0'), tensor(101.3631, device='cuda:0'), tensor(101.5473, device='cuda:0'), tensor(101.3584, device='cuda:0')]

Others: [{'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(33080, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}]

Compressed training loss: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]

Training loss: 0

Prediction time: [datetime.timedelta(seconds=1, microseconds=958695), datetime.timedelta(seconds=1, microseconds=950726), datetime.timedelta(seconds=1, microseconds=939770), datetime.timedelta(seconds=1, microseconds=968648), datetime.timedelta(seconds=1, microseconds=944803), datetime.timedelta(seconds=2, microseconds=24413), datetime.timedelta(seconds=1, microseconds=936786), datetime.timedelta(seconds=1, microseconds=940773), datetime.timedelta(seconds=1, microseconds=938775), datetime.timedelta(seconds=1, microseconds=924836)]

Phi time: [datetime.timedelta(seconds=5, microseconds=357190), datetime.timedelta(seconds=5, microseconds=276140), datetime.timedelta(seconds=5, microseconds=302505), datetime.timedelta(seconds=5, microseconds=304195), datetime.timedelta(seconds=5, microseconds=291553), datetime.timedelta(seconds=5, microseconds=322571), datetime.timedelta(seconds=5, microseconds=357590), datetime.timedelta(seconds=5, microseconds=305200), datetime.timedelta(seconds=5, microseconds=290716), datetime.timedelta(seconds=5, microseconds=305179)]

