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2022-05-23 20:24:39.846051
Namespace(data='mri', algorithm='ALS-RS', rank='4,4,2,2', 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=(4, 4, 2, 2), 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: 304305934606.07587 rmse: 128.77638518295734 rre: 0.856333646320282 time: 0.278641543
loss: 211573984852.2396 rmse: 107.37721901869553 rre: 0.7140340627155616 time: 0.27179160999999974
loss: 181373275777.43057 rmse: 99.41860555719606 rre: 0.6611110949256451 time: 0.19840432800000007
loss: 140767683062.17545 rmse: 87.58555781680377 rre: 0.5824240211720549 time: 0.20204181000000032
loss: 130102049958.70148 rmse: 84.20213216079387 rre: 0.5599250107754811 time: 0.28848945099999934
rre_diff: 0.43291516358937365

step: 1
loss: 116468826111.34721 rmse: 79.66835834503556 rre: 0.5297764469862132 time: 0.27451189400000064
loss: 111733800291.8107 rmse: 78.03210167718156 rre: 0.5188957126286787 time: 0.2667959980000001
loss: 111299783873.20021 rmse: 77.88040109275158 rre: 0.5178869382759177 time: 0.1947972440000001
loss: 110476495821.05719 rmse: 77.59182454397579 rre: 0.5159679699192224 time: 0.197604546
loss: 109647718738.468 rmse: 77.30023589445183 rre: 0.5140289717782379 time: 0.28684643600000026
rre_diff: 0.04589603899724315

step: 2
loss: 109221281698.31279 rmse: 77.149773135729 rre: 0.5130284286846462 time: 0.27419547700000013
loss: 108706786707.46017 rmse: 76.96784876147298 rre: 0.5118186730098004 time: 0.2666540579999994
loss: 108673653417.47092 rmse: 76.9561181580688 rre: 0.5117406671675618 time: 0.19486524399999894
loss: 108529443860.95607 rmse: 76.90504095833205 rre: 0.5114010154167206 time: 0.20571573099999974
loss: 108765769687.78616 rmse: 76.98872683911925 rre: 0.5119575074733831 time: 0.28501885299999863
Warning: The loss function increased!
rre_diff: 0.002071464304854831

step: 3
loss: 108546123107.9382 rmse: 76.91095027126654 rre: 0.5114403110025165 time: 0.2748742460000013
loss: 108455985578.1333 rmse: 76.87900991869995 rre: 0.511227914928972 time: 0.27077848200000076
loss: 108451896263.19666 rmse: 76.87756054988277 rre: 0.5112182769562776 time: 0.19368209599999986
loss: 108324782796.13057 rmse: 76.83249430991526 rre: 0.5109185967195441 time: 0.19358872000000105
loss: 108652238819.847 rmse: 76.94853552213647 rre: 0.511690244364752 time: 0.28730777799999885
Warning: The loss function increased!
rre_diff: 0.0002672631086311217

step: 4
loss: 108458270822.05472 rmse: 76.87981986184744 rre: 0.5112333008665243 time: 0.2746037430000001
loss: 108386274187.91307 rmse: 76.85429849265924 rre: 0.5110635895712045 time: 0.2703929580000004
loss: 108385838331.1828 rmse: 76.85414396434292 rre: 0.5110625619930783 time: 0.19370027100000087
loss: 108342656326.77373 rmse: 76.83883270849567 rre: 0.5109607456272066 time: 0.1995565629999998
loss: 108718792331.45334 rmse: 76.97209882519094 rre: 0.5118469349660243 time: 0.2973248159999997
Warning: The loss function increased!
rre_diff: -0.0001566906012723246

