robust_pca sample

[chkone]

Hello,

I just execute this sample:
https://jeankossaifi.github.io/tensorly/rpca.html

Step by step with same data, but during the execution of that:
low_rank_part, sparse_part = robust_pca(X, n_iter_max=20)
I got:
AssertionError Traceback (most recent call last)
in ()
----> 1 low_rank_part, sparse_part = robust_pca(X, n_iter_max=20)

C:\ProgramData\Anaconda3\lib\site-packages\tensorly\decomposition\robust_decomposition.py in robust_pca(X, mask, tol, reg_E, reg_J, mu_init, mu_max, learning_rate, n_iter_max, random_state, verbose)
76
77 # Initialise the decompositions
---> 78 D = T.zeros_like(X) # low rank part
79 E = T.zeros_like(X) # sparse part
80 L_x = T.zeros_like(X) # Lagrangian variables for the (X - D - E - L_x/mu) term

C:\ProgramData\Anaconda3\lib\site-packages\mxnet\ndarray\register.py in zeros_like(data, out, name, **kwargs)

AssertionError: Argument data must have NDArray type, but got [[[ 6.79022540e+00 1.77902254e+01 2.17902254e+01 ..., 3.79022540e+00
0.00000000e+00 -2.20977460e+00]
[ 5.79022540e+00 1.67902254e+01 1.57902254e+01 ..., 6.79022540e+00
-5.20977460e+00 -1.02097746e+01]
[ 5.79022540e+00 1.37902254e+01 2.27902254e+01 ..., 4.79022540e+00
-4.20977460e+00 -1.72097746e+01]
...,
[ -5.32097746e+01 -4.42097746e+01 -4.12097746e+01 ..., -3.12097746e+01
-3.72097746e+01 -3.92097746e+01]
[ -5.32097746e+01 -5.32097746e+01 -5.32097746e+01 ..., 2.55000000e+02
-5.02097746e+01 -5.92097746e+01]
[ -6.12097746e+01 -5.92097746e+01 0.00000000e+00 ..., -4.92097746e
...

Thanks

Cheers

[JeanKossaifi]

It seems you are using TensorLy with the MXNet backend but feeding the algorithm NumPy arrays: try to set the backend to numpy (import tensorly as tl; tl.set_backend('numpy')), this should solve your issue.

[chkone]

Thanks that fix the issue

[JeanKossaifi]

Glad to hear!