Precision: [tensor(0.4488, device='cuda:0'), tensor(0.4701, device='cuda:0'), tensor(0.4536, device='cuda:0'), tensor(0.4716, device='cuda:0'), tensor(0.4329, device='cuda:0'), tensor(0.4731, device='cuda:0'), tensor(0.4519, device='cuda:0'), tensor(0.4557, device='cuda:0'), tensor(0.4395, device='cuda:0'), tensor(0.4537, device='cuda:0')]

Output distance: [tensor(19.1279, device='cuda:0'), tensor(19.0852, device='cuda:0'), tensor(19.1182, device='cuda:0'), tensor(19.0822, device='cuda:0'), tensor(19.1596, device='cuda:0'), tensor(19.0792, device='cuda:0'), tensor(19.1215, device='cuda:0'), tensor(19.1140, device='cuda:0'), tensor(19.1463, device='cuda:0'), tensor(19.1179, device='cuda:0')]

Prediction loss: [tensor(109.1891, device='cuda:0'), tensor(109.8091, device='cuda:0'), tensor(108.3841, device='cuda:0'), tensor(108.6935, device='cuda:0'), tensor(109.7670, device='cuda:0'), tensor(109.3823, device='cuda:0'), tensor(108.8538, device='cuda:0'), tensor(109.2729, device='cuda:0'), tensor(109.2552, device='cuda:0'), tensor(109.1913, 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=227, microseconds=583009), datetime.timedelta(seconds=226, microseconds=556754), datetime.timedelta(seconds=244, microseconds=506369), datetime.timedelta(seconds=226, microseconds=748548), datetime.timedelta(seconds=226, microseconds=721094), datetime.timedelta(seconds=227, microseconds=86522), datetime.timedelta(seconds=226, microseconds=317427), datetime.timedelta(seconds=226, microseconds=494428), datetime.timedelta(seconds=227, microseconds=644891), datetime.timedelta(seconds=240, microseconds=706347)]

Phi time: [datetime.timedelta(seconds=4, microseconds=469600), datetime.timedelta(seconds=4, microseconds=430589), datetime.timedelta(seconds=4, microseconds=436523), datetime.timedelta(seconds=4, microseconds=442865), datetime.timedelta(seconds=4, microseconds=399881), datetime.timedelta(seconds=4, microseconds=465171), datetime.timedelta(seconds=4, microseconds=432174), datetime.timedelta(seconds=4, microseconds=461277), datetime.timedelta(seconds=4, microseconds=413314), datetime.timedelta(seconds=4, microseconds=400904)]

