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2022-05-17 19:44:25.456719
Namespace(data='hyperspectral', algorithm='ALS-DJSSW19', rank='16,16,4', seed=0, alpha=1.0, max_num_samples=1028, max_num_steps=5, rre_gap_tol=0.0, verbose=False)
Loading hyperspectral tensor...
Finished.
AlgorithmConfig(input_shape=(1024, 1344, 33), rank=(16, 16, 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=1028, max_num_steps=5, rre_gap_tol=0.0, verbose=False)
step: 0
loss: 8111.067767425508 rmse: 0.013363875848109249 rre: 0.4226535158391079 time: 0.7732356239999998
loss: 6103.957767196702 rmse: 0.011593089199816243 rre: 0.3666496131383897 time: 0.4251200150000001
loss: 2038.683225340252 rmse: 0.0066998995599634875 rre: 0.21189482280233096 time: 1.2073112759999995
loss: 262211.0435430199 rmse: 0.07598343218897373 rre: 2.403095114411426 time: 6.516391722
Warning: The loss function increased!
rre_diff: 2242.1586745553172

step: 1
loss: 9541.268889812485 rmse: 0.014494274601262382 rre: 0.458404147822711 time: 0.7703865010000008
loss: 2138.369489030973 rmse: 0.00686174843523644 rre: 0.21701354711152132 time: 0.42365036200000006
loss: 1918.8193542954798 rmse: 0.006499956684974689 rre: 0.20557131605612375 time: 1.1953496359999995
loss: 328572.1636431101 rmse: 0.08505675328691194 rre: 2.690053112672335 time: 6.523857111000002
Warning: The loss function increased!
rre_diff: -0.28695799826090873

step: 2
loss: 12205.787202593552 rmse: 0.016393674750116504 rre: 0.5184756540251649 time: 0.7653244000000008
loss: 1970.7594294728228 rmse: 0.006587342187529909 rre: 0.2083350195137218 time: 0.4175687620000019
loss: 1833.1496216497599 rmse: 0.006353197760548603 rre: 0.20092983508949028 time: 1.196930008999999
loss: 448033.1313033568 rmse: 0.09932269215475212 rre: 3.1412357851072565 time: 6.471887754999997
Warning: The loss function increased!
rre_diff: -0.4511826724349217

step: 3
loss: 15916.120867892587 rmse: 0.018720266699625038 rre: 0.5920577703632085 time: 0.7614387619999974
loss: 3625.5453703041794 rmse: 0.008934702360207918 rre: 0.2825739634547809 time: 0.4154041649999982
loss: 207750.52945470414 rmse: 0.06763390871692275 rre: 2.1390283503114893 time: 1.1908006729999983
Warning: The loss function increased!
loss: 35887.15315075867 rmse: 0.028110134358489317 rre: 0.8890270496643489 time: 6.365078109999999
rre_diff: 2.252208735442908

step: 4
loss: 22262610.298473127 rmse: 0.7001344691756791 rre: 22.142849748122654 time: 0.7628792349999998
Warning: The loss function increased!
loss: 5071.251786363774 rmse: 0.010566982890303642 rre: 0.33419739311858515 time: 0.4143800419999977
loss: 63366.80295498037 rmse: 0.037352899168202586 rre: 1.1813439708404758 time: 1.1955282479999951
Warning: The loss function increased!
loss: 7566.809263215187 rmse: 0.01290772816953705 rre: 0.40822713068845085 time: 6.370810732999999
rre_diff: 0.480799918975898

