Precision: [tensor(0.3924, device='cuda:0'), tensor(0.3937, device='cuda:0'), tensor(0.4336, device='cuda:0'), tensor(0.3934, device='cuda:0'), tensor(0.4148, device='cuda:0'), tensor(0.4285, device='cuda:0'), tensor(0.4054, device='cuda:0'), tensor(0.3798, device='cuda:0'), tensor(0.4226, device='cuda:0'), tensor(0.4155, device='cuda:0')]

Output distance: [tensor(19.2406, device='cuda:0'), tensor(19.2379, device='cuda:0'), tensor(19.1581, device='cuda:0'), tensor(19.2385, device='cuda:0'), tensor(19.1959, device='cuda:0'), tensor(19.1684, device='cuda:0'), tensor(19.2146, device='cuda:0'), tensor(19.2657, device='cuda:0'), tensor(19.1802, device='cuda:0'), tensor(19.1944, device='cuda:0')]

Prediction loss: [tensor(108.8682, device='cuda:0'), tensor(109.1667, device='cuda:0'), tensor(109.5417, device='cuda:0'), tensor(109.4664, device='cuda:0'), tensor(108.9145, device='cuda:0'), tensor(109.0252, device='cuda:0'), tensor(108.8024, device='cuda:0'), tensor(108.3253, device='cuda:0'), tensor(110.3332, device='cuda:0'), tensor(108.9019, device='cuda:0')]

Others: [{'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(6616, device='cuda:0'), 'num_positive_true': tensor(125872, device='cuda:0')}, {'num_positive': tensor(6616, 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=183, microseconds=361260), datetime.timedelta(seconds=182, microseconds=975846), datetime.timedelta(seconds=183, microseconds=781605), datetime.timedelta(seconds=183, microseconds=381345), datetime.timedelta(seconds=183, microseconds=89742), datetime.timedelta(seconds=183, microseconds=571893), datetime.timedelta(seconds=183, microseconds=187328), datetime.timedelta(seconds=183, microseconds=159463), datetime.timedelta(seconds=183, microseconds=114565), datetime.timedelta(seconds=183, microseconds=563189)]

Phi time: [datetime.timedelta(seconds=4, microseconds=364615), datetime.timedelta(seconds=4, microseconds=353950), datetime.timedelta(seconds=4, microseconds=400780), datetime.timedelta(seconds=4, microseconds=392084), datetime.timedelta(seconds=4, microseconds=362616), datetime.timedelta(seconds=4, microseconds=274572), datetime.timedelta(seconds=4, microseconds=350147), datetime.timedelta(seconds=4, microseconds=343899), datetime.timedelta(seconds=4, microseconds=320399), datetime.timedelta(seconds=4, microseconds=349756)]

