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2022-05-18 09:10:24.420076
Namespace(data='mri', algorithm='ALS-DJSSW19', rank='8,8,4,4', seed=0, alpha=1.0, max_num_samples=1024, max_num_steps=5, rre_gap_tol=0.0, verbose=False)
Loading MRI tensor...
Finished.
AlgorithmConfig(input_shape=(256, 256, 14, 20), rank=(8, 8, 4, 4), l2_regularization_strength=0.0, algorithm='ALS-DJSSW19', random_seed=0, epsilon=0.1, delta=0.01, downsampling_ratio=1.0, max_num_samples=1024, max_num_steps=5, rre_gap_tol=0.0, verbose=False)
step: 0
loss: 291963897710.7579 rmse: 126.13789972307775 rre: 0.8387883186469536 time: 0.3213100080000002
loss: 183829586573.04907 rmse: 100.0895471380635 rre: 0.6655727037027188 time: 0.306155446
loss: 148492165331.18906 rmse: 89.95654959523692 rre: 0.598190576757044 time: 0.26839148600000007
loss: 125200817677.30743 rmse: 82.60086620504299 rre: 0.5492769566880136 time: 0.2801048470000005
loss: 68916592609830.69 rmse: 1937.9515598579605 rre: 12.886936710387436 time: 6.466591569
Warning: The loss function increased!
rre_diff: -11.965711281308366

step: 1
loss: 378091299797.7586 rmse: 143.54212161766873 rre: 0.9545224322826793 time: 0.3170987220000008
loss: 187253404509.0447 rmse: 101.01732879346034 rre: 0.6717422405073611 time: 0.3069127990000009
loss: 167911950986.35306 rmse: 95.65811594971214 rre: 0.6361046950880419 time: 0.25809940700000134
loss: 153294820012.9009 rmse: 91.39969761888787 rre: 0.6077871825906149 time: 0.28076294700000126
loss: 233770900254416.2 rmse: 3569.2440455792716 rre: 23.734660386804787 time: 6.413685949000001
Warning: The loss function increased!
rre_diff: -10.84772367641735

step: 2
loss: 390543745416.2491 rmse: 145.8867544044407 rre: 0.9701137065735828 time: 0.32409035699999933
loss: 223900307433.1396 rmse: 110.46084571582007 rre: 0.7345394782829237 time: 0.3019925230000027
loss: 171391047090.73468 rmse: 96.64404191890621 rre: 0.6426608783432429 time: 0.2528355979999972
loss: 155973586530.7155 rmse: 92.1948258579503 rre: 0.6130746043743619 time: 0.2656803329999988
loss: 1029872456238.642 rmse: 236.9041892759919 rre: 1.5753589289141554 time: 6.111554842
Warning: The loss function increased!
rre_diff: 22.15930145789063

step: 3
loss: 2765688041583.512 rmse: 388.2242100679228 rre: 2.581602620115111 time: 0.30971332100000026
Warning: The loss function increased!
loss: 2540738990828.878 rmse: 372.1011782716735 rre: 2.4743881289783682 time: 0.3025835459999975
loss: 2619462178806.9277 rmse: 377.8218629933366 rre: 2.5124293800989874 time: 0.2526405490000023
Warning: The loss function increased!
loss: 190516416855.92484 rmse: 101.89367388445167 rre: 0.677569735867922 time: 0.27289087500000164
loss: 258441163333.66907 rmse: 118.67571656131386 rre: 0.7891664993409963 time: 5.990743025999997
Warning: The loss function increased!
rre_diff: 0.7861924295731592

step: 4
loss: 434109660118.1353 rmse: 153.80864425986545 rre: 1.0227924707430038 time: 0.3119372130000002
Warning: The loss function increased!
loss: 7031151821637.435 rmse: 619.0051422379827 rre: 4.1162432831963685 time: 0.3033158849999964
Warning: The loss function increased!
loss: 178715462344.44995 rmse: 98.68748549481705 rre: 0.656249312945778 time: 0.2511629000000042
loss: 168854445864.34912 rmse: 95.92620623072398 rre: 0.6378874344276788 time: 0.26591598499999947
loss: 191429708192.22226 rmse: 102.13760916390214 rre: 0.6791918499459123 time: 6.0582494489999945
Warning: The loss function increased!
rre_diff: 0.10997464939508395

