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2022-05-17 21:31:46.379348
Namespace(data='hyperspectral', algorithm='ALS-DJSSW19', rank='1,1,1', seed=0, alpha=1.0, max_num_samples=1024, max_num_steps=5, rre_gap_tol=0.0, verbose=False)
Loading hyperspectral tensor...
Finished.
AlgorithmConfig(input_shape=(1024, 1344, 33), rank=(1, 1, 1), 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: 22265.42658570579 rmse: 0.02214159626631701 rre: 0.7002626793762806 time: 0.5459696879999996
loss: 14386.673551575152 rmse: 0.017798098745460147 rre: 0.5628927637100607 time: 0.21292389199999917
loss: 3343.23831870397 rmse: 0.008579798439154842 rre: 0.2713495707918252 time: 0.5329694399999996
loss: 3347.569143309797 rmse: 0.008585353767995945 rre: 0.27152526677202 time: 0.5065493750000005
Warning: The loss function increased!
rre_diff: 4.0184954323061834

step: 1
loss: 3337.1583000046608 rmse: 0.008571993271148154 rre: 0.27110272012236114 time: 0.5446409350000003
loss: 3336.5998159796786 rmse: 0.008571275966006488 rre: 0.27108003422318777 time: 0.21397379499999936
loss: 3336.583546089885 rmse: 0.008571255068402183 rre: 0.2710793733037036 time: 0.5311001280000003
loss: 3338.4374530512355 rmse: 0.008573635962293786 rre: 0.27115467280405536 time: 0.5046223120000004
Warning: The loss function increased!
rre_diff: 0.0003705939679646275

step: 2
loss: 3336.581271339866 rmse: 0.008571252146631203 rre: 0.2710792808981177 time: 0.543954351
loss: 3336.581236310783 rmse: 0.008571252101638577 rre: 0.2710792794751554 time: 0.212926877000001
loss: 3336.581234576026 rmse: 0.008571252099410393 rre: 0.2710792794046856 time: 0.5260329549999998
loss: 3337.910905640552 rmse: 0.008572959807071397 rre: 0.2711332883355641 time: 0.4970236089999993
Warning: The loss function increased!
rre_diff: 2.1384468491258968e-05

step: 3
loss: 3336.581234153549 rmse: 0.008571252098867747 rre: 0.27107927938752363 time: 0.5364423820000006
loss: 3336.581234141426 rmse: 0.008571252098852176 rre: 0.2710792793870312 time: 0.20514216999999846
loss: 3336.5812341417677 rmse: 0.008571252098852615 rre: 0.271079279387045 time: 0.5223204489999986
Warning: The loss function increased!
loss: 3346.9015640430375 rmse: 0.00858449767067598 rre: 0.2714981913527108 time: 0.4975859670000027
Warning: The loss function increased!
rre_diff: -0.0003649030171467005

step: 4
loss: 3336.5812341419296 rmse: 0.008571252098852823 rre: 0.2710792793870516 time: 0.5371798139999981
loss: 3336.581234141422 rmse: 0.008571252098852171 rre: 0.271079279387031 time: 0.20460786599999992
loss: 3336.581234143317 rmse: 0.008571252098854605 rre: 0.27107927938710796 time: 0.5216772640000009
Warning: The loss function increased!
loss: 3339.043822097724 rmse: 0.008574414552800667 rre: 0.2711792969489421 time: 0.4974204919999998
Warning: The loss function increased!
rre_diff: 0.00031889440376869915

