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2022-05-23 20:26:04.741498
Namespace(data='mri', algorithm='ALS-RS', rank='8,4,4,1', seed=0, alpha=1.0, max_num_samples=16384, max_num_steps=5, rre_gap_tol=0.0, verbose=False)
Loading MRI tensor...
Finished.
AlgorithmConfig(input_shape=(256, 256, 14, 20), rank=(8, 4, 4, 1), l2_regularization_strength=0.0, algorithm='ALS-RS', random_seed=0, epsilon=0.1, delta=0.01, downsampling_ratio=1.0, max_num_samples=16384, max_num_steps=5, rre_gap_tol=0.0, verbose=False)
step: 0
loss: 324912849692.4593 rmse: 133.0651912886661 rre: 0.8848532306031022 time: 0.28118641199999983
loss: 248488828264.31516 rmse: 116.36823656689651 rre: 0.7738222826616479 time: 0.2785144960000001
loss: 220595682073.49335 rmse: 109.64264975784072 rre: 0.7290986614196024 time: 0.18406630199999974
loss: 131993704434.64587 rmse: 84.81206310649094 rre: 0.5639809127173651 time: 0.248948881
loss: 104225077962.75511 rmse: 75.36455399438447 rre: 0.501157127788784 time: 0.3576417909999998
rre_diff: 0.48563974501736906

step: 1
loss: 95789436944.21017 rmse: 72.25032903403445 rre: 0.4804482407364776 time: 0.2810780460000002
loss: 91344558903.95981 rmse: 70.55411692763194 rre: 0.4691688163610798 time: 0.2731639760000002
loss: 89333596428.82872 rmse: 69.77316574090031 rre: 0.4639756687480146 time: 0.1823420449999995
loss: 89333343400.08493 rmse: 69.77306692796944 rre: 0.4639750116645183 time: 0.2633921199999998
loss: 87621844796.5989 rmse: 69.1014587146635 rre: 0.45950896993348334 time: 0.35144488500000026
rre_diff: 0.04164815785530063

step: 2
loss: 87148985204.95532 rmse: 68.91475019008595 rre: 0.45826740074808175 time: 0.2791207369999995
loss: 86401979688.50894 rmse: 68.61875999861657 rre: 0.45629913335514394 time: 0.27211347000000075
loss: 86139620793.53764 rmse: 68.51450064486687 rre: 0.4556058323867045 time: 0.17935714399999902
loss: 86139618917.97447 rmse: 68.51449989896578 rre: 0.4556058274266321 time: 0.25096268899999963
loss: 86211884060.25475 rmse: 68.54323332123344 rre: 0.4557968981437264 time: 0.34936473600000006
Warning: The loss function increased!
rre_diff: 0.00371207178975691

step: 3
loss: 85800918613.8018 rmse: 68.37966799152497 rre: 0.45470922593579916 time: 0.28085106900000056
loss: 85505706000.1066 rmse: 68.2619307074848 rre: 0.4539262997990953 time: 0.27399129600000016
loss: 85379363861.22441 rmse: 68.21148058608554 rre: 0.45359081797644796 time: 0.18351487600000027
loss: 85379362745.18958 rmse: 68.21148014027295 rre: 0.4535908150118958 time: 0.25522786500000016
loss: 85591025132.95769 rmse: 68.29597870788318 rre: 0.4541527112509283 time: 0.34931598200000025
Warning: The loss function increased!
rre_diff: 0.0016441868927981051

step: 4
loss: 85212045127.89598 rmse: 68.1446104721107 rre: 0.45314614694108246 time: 0.27825447699999906
loss: 85006170173.96655 rmse: 68.06224093996441 rre: 0.4525984083032234 time: 0.2726656639999998
loss: 84937301630.4271 rmse: 68.03466472312437 rre: 0.45241503273879213 time: 0.17828294300000103
loss: 84937299383.62614 rmse: 68.03466382328209 rre: 0.4524150267550458 time: 0.24564495699999966
loss: 85296946612.98833 rmse: 68.17855014704595 rre: 0.4533718380532452 time: 0.35297525799999896
Warning: The loss function increased!
rre_diff: 0.0007808731976831074

