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diff --git a/dev/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip b/dev/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip
diff --git a/dev/_downloads/31ebe5f65fa406fbccca74ea8deb8a69/plot_IL2.zip b/dev/_downloads/31ebe5f65fa406fbccca74ea8deb8a69/plot_IL2.zip
diff --git a/dev/_downloads/3ca037908294af324764e4c88851b187/plot_covid.zip b/dev/_downloads/3ca037908294af324764e4c88851b187/plot_covid.zip
diff --git a/dev/_downloads/43729c3dc12e8eff64285b0fa0df2e01/plot_nn_tucker.zip b/dev/_downloads/43729c3dc12e8eff64285b0fa0df2e01/plot_nn_tucker.zip
diff --git a/dev/_downloads/6f1e7a639e0699d6164445b55e6c116d/auto_examples_jupyter.zip b/dev/_downloads/6f1e7a639e0699d6164445b55e6c116d/auto_examples_jupyter.zip
diff --git a/dev/_downloads/9176c20d1989efc7fe9ef15ff8b9ac98/plot_image_compression.zip b/dev/_downloads/9176c20d1989efc7fe9ef15ff8b9ac98/plot_image_compression.zip
diff --git a/dev/_downloads/b099986e302d05c170b2103cc56235d8/plot_parafac2.zip b/dev/_downloads/b099986e302d05c170b2103cc56235d8/plot_parafac2.zip
diff --git a/dev/_downloads/b8fdcea423023234b51dd9091c942145/plot_guide_for_constrained_cp.zip b/dev/_downloads/b8fdcea423023234b51dd9091c942145/plot_guide_for_constrained_cp.zip
diff --git a/dev/_downloads/b9cbdb6e86868da417502cdb389f58d1/plot_cp_line_search.zip b/dev/_downloads/b9cbdb6e86868da417502cdb389f58d1/plot_cp_line_search.zip
diff --git a/dev/_downloads/bcb72d6051bfbba3dbbe23efd1e3601f/plot_permute_factors.zip b/dev/_downloads/bcb72d6051bfbba3dbbe23efd1e3601f/plot_permute_factors.zip
diff --git a/dev/_downloads/c180f3d1630c24fd07b3388b592a8845/plot_parafac2_compression.zip b/dev/_downloads/c180f3d1630c24fd07b3388b592a8845/plot_parafac2_compression.zip
diff --git a/dev/_downloads/c83bd9c72b1132d0ca7a4c03a7979d57/plot_tucker_regression.zip b/dev/_downloads/c83bd9c72b1132d0ca7a4c03a7979d57/plot_tucker_regression.zip
diff --git a/dev/_downloads/cad167cb142025226f5b9454cd0abb41/plot_nn_cp_hals.zip b/dev/_downloads/cad167cb142025226f5b9454cd0abb41/plot_nn_cp_hals.zip
diff --git a/dev/_downloads/e2b69b698c4b4f8baba0fd4e55bfc00c/plot_tensor.zip b/dev/_downloads/e2b69b698c4b4f8baba0fd4e55bfc00c/plot_tensor.zip
diff --git a/dev/_downloads/f0754cb6f49432e87378932ce6ee13bb/plot_cp_regression.zip b/dev/_downloads/f0754cb6f49432e87378932ce6ee13bb/plot_cp_regression.zip
diff --git a/dev/_images/sphx_glr_plot_cp_line_search_001.png b/dev/_images/sphx_glr_plot_cp_line_search_001.png
diff --git a/dev/_images/sphx_glr_plot_cp_line_search_thumb.png b/dev/_images/sphx_glr_plot_cp_line_search_thumb.png
diff --git a/dev/_images/sphx_glr_plot_guide_for_constrained_cp_001.png b/dev/_images/sphx_glr_plot_guide_for_constrained_cp_001.png
diff --git a/dev/_images/sphx_glr_plot_guide_for_constrained_cp_002.png b/dev/_images/sphx_glr_plot_guide_for_constrained_cp_002.png
diff --git a/dev/_images/sphx_glr_plot_guide_for_constrained_cp_003.png b/dev/_images/sphx_glr_plot_guide_for_constrained_cp_003.png
diff --git a/dev/_images/sphx_glr_plot_guide_for_constrained_cp_004.png b/dev/_images/sphx_glr_plot_guide_for_constrained_cp_004.png
diff --git a/dev/_images/sphx_glr_plot_guide_for_constrained_cp_005.png b/dev/_images/sphx_glr_plot_guide_for_constrained_cp_005.png
diff --git a/dev/_images/sphx_glr_plot_guide_for_constrained_cp_006.png b/dev/_images/sphx_glr_plot_guide_for_constrained_cp_006.png
diff --git a/dev/_images/sphx_glr_plot_guide_for_constrained_cp_thumb.png b/dev/_images/sphx_glr_plot_guide_for_constrained_cp_thumb.png
diff --git a/dev/_images/sphx_glr_plot_image_compression_001.png b/dev/_images/sphx_glr_plot_image_compression_001.png
diff --git a/dev/_images/sphx_glr_plot_image_compression_thumb.png b/dev/_images/sphx_glr_plot_image_compression_thumb.png
diff --git a/dev/_images/sphx_glr_plot_nn_cp_hals_001.png b/dev/_images/sphx_glr_plot_nn_cp_hals_001.png
diff --git a/dev/_images/sphx_glr_plot_nn_cp_hals_thumb.png b/dev/_images/sphx_glr_plot_nn_cp_hals_thumb.png
diff --git a/dev/_images/sphx_glr_plot_nn_tucker_001.png b/dev/_images/sphx_glr_plot_nn_tucker_001.png
diff --git a/dev/_images/sphx_glr_plot_nn_tucker_thumb.png b/dev/_images/sphx_glr_plot_nn_tucker_thumb.png
diff --git a/dev/_images/sphx_glr_plot_permute_factors_001.png b/dev/_images/sphx_glr_plot_permute_factors_001.png
diff --git a/dev/_images/sphx_glr_plot_permute_factors_thumb.png b/dev/_images/sphx_glr_plot_permute_factors_thumb.png
diff --git a/dev/_modules/tensorly/contrib/decomposition/_tt_cross.html b/dev/_modules/tensorly/contrib/decomposition/_tt_cross.html
@@ -577,7 +577,7 @@ <h1>Source code for tensorly.contrib.decomposition._tt_cross</h1><div class="hig
     <span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">r</span><span class="p">)</span> <span class="o">=</span> <span class="n">tl</span><span class="o">.</span><span class="n">shape</span><span class="p">(</span><span class="n">A</span><span class="p">)</span>
 
     <span class="c1"># The index of row of the submatrix</span>
-    <span class="n">row_idx</span> <span class="o">=</span> <span class="n">tl</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="n">r</span><span class="p">)</span>
+    <span class="n">row_idx</span> <span class="o">=</span> <span class="n">tl</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="n">r</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">tl</span><span class="o">.</span><span class="n">int64</span><span class="p">)</span>
 
     <span class="c1"># Rest of rows / unselected rows</span>
     <span class="n">rest_of_rows</span> <span class="o">=</span> <span class="n">tl</span><span class="o">.</span><span class="n">tensor</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="n">n</span><span class="p">)),</span> <span class="n">dtype</span><span class="o">=</span><span class="n">tl</span><span class="o">.</span><span class="n">int64</span><span class="p">)</span>
@@ -623,8 +623,8 @@ <h1>Source code for tensorly.contrib.decomposition._tt_cross</h1><div class="hig
         <span class="n">A_new</span> <span class="o">=</span> <span class="n">A_new</span><span class="p">[</span><span class="n">mask</span><span class="p">,</span> <span class="p">:]</span>
 
         <span class="c1"># update the row_idx and rest_of_rows</span>
-        <span class="n">row_idx</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">rest_of_rows</span><span class="p">[</span><span class="n">max_row_idx</span><span class="p">]</span>
-        <span class="n">rest_of_rows</span> <span class="o">=</span> <span class="n">rest_of_rows</span><span class="p">[</span><span class="n">mask</span><span class="p">]</span>
+        <span class="n">row_idx</span> <span class="o">=</span> <span class="n">tl</span><span class="o">.</span><span class="n">index_update</span><span class="p">(</span><span class="n">row_idx</span><span class="p">,</span> <span class="n">i</span><span class="p">,</span> <span class="n">rest_of_rows</span><span class="p">[</span><span class="n">max_row_idx</span><span class="p">])</span>
+        <span class="n">rest_of_rows</span> <span class="o">=</span> <span class="n">rest_of_rows</span><span class="p">[</span><span class="n">tl</span><span class="o">.</span><span class="n">tensor</span><span class="p">(</span><span class="n">mask</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">tl</span><span class="o">.</span><span class="n">int64</span><span class="p">)]</span>
         <span class="n">i</span> <span class="o">=</span> <span class="n">i</span> <span class="o">+</span> <span class="mi">1</span>
 
     <span class="n">row_idx</span> <span class="o">=</span> <span class="n">tl</span><span class="o">.</span><span class="n">tensor</span><span class="p">(</span><span class="n">row_idx</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">tl</span><span class="o">.</span><span class="n">int64</span><span class="p">)</span>

diff --git a/dev/_sources/auto_examples/applications/plot_IL2.rst.txt b/dev/_sources/auto_examples/applications/plot_IL2.rst.txt
@@ -254,7 +254,7 @@ affect IL-2 signaling in immune cells.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 1.393 seconds)
+   **Total running time of the script:** (0 minutes 1.399 seconds)
 
 
 .. _sphx_glr_download_auto_examples_applications_plot_IL2.py:

diff --git a/dev/_sources/auto_examples/applications/plot_covid.rst.txt b/dev/_sources/auto_examples/applications/plot_covid.rst.txt
@@ -217,7 +217,7 @@ how each component looks like on weights.
     /home/runner/work/tensorly/tensorly/examples/applications/plot_covid.py:116: MatplotlibDeprecationWarning: Unable to determine Axes to steal space for Colorbar. Using gca(), but will raise in the future. Either provide the *cax* argument to use as the Axes for the Colorbar, provide the *ax* argument to steal space from it, or add *mappable* to an Axes.
       fig2.colorbar(ScalarMappable(norm=plt.Normalize(-1, 1), cmap="PiYG"))
 
-    <matplotlib.colorbar.Colorbar object at 0x7f9dcd9f5130>
+    <matplotlib.colorbar.Colorbar object at 0x7f33cc101910>
 
 
 
@@ -244,7 +244,7 @@ References
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 3.422 seconds)
+   **Total running time of the script:** (0 minutes 3.434 seconds)
 
 
 .. _sphx_glr_download_auto_examples_applications_plot_covid.py:

diff --git a/dev/_sources/auto_examples/applications/plot_image_compression.rst.txt b/dev/_sources/auto_examples/applications/plot_image_compression.rst.txt
@@ -116,7 +116,7 @@ Example on how to use :func:`tensorly.decomposition.parafac` and :func:`tensorly
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 1.426 seconds)
+   **Total running time of the script:** (0 minutes 1.499 seconds)
 
 
 .. _sphx_glr_download_auto_examples_applications_plot_image_compression.py:

diff --git a/dev/_sources/auto_examples/applications/sg_execution_times.rst.txt b/dev/_sources/auto_examples/applications/sg_execution_times.rst.txt
@@ -6,7 +6,7 @@
 
 Computation times
 =================
-**00:06.241** total execution time for 3 files **from auto_examples/applications**:
+**00:06.332** total execution time for 3 files **from auto_examples/applications**:
 
 .. container::
 
@@ -33,11 +33,11 @@ Computation times
      - Time
      - Mem (MB)
    * - :ref:`sphx_glr_auto_examples_applications_plot_covid.py` (``plot_covid.py``)
-     - 00:03.422
+     - 00:03.434
      - 0.0
    * - :ref:`sphx_glr_auto_examples_applications_plot_image_compression.py` (``plot_image_compression.py``)
-     - 00:01.426
+     - 00:01.499
      - 0.0
    * - :ref:`sphx_glr_auto_examples_applications_plot_IL2.py` (``plot_IL2.py``)
-     - 00:01.393
+     - 00:01.399
      - 0.0
diff --git a/dev/_sources/auto_examples/decomposition/plot_cp_line_search.rst.txt b/dev/_sources/auto_examples/decomposition/plot_cp_line_search.rst.txt
@@ -90,7 +90,7 @@ Example on how to use :func:`tensorly.decomposition.parafac` with line search to
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 3.723 seconds)
+   **Total running time of the script:** (0 minutes 3.731 seconds)
 
 
 .. _sphx_glr_download_auto_examples_decomposition_plot_cp_line_search.py:

diff --git a/dev/_sources/auto_examples/decomposition/plot_guide_for_constrained_cp.rst.txt b/dev/_sources/auto_examples/decomposition/plot_guide_for_constrained_cp.rst.txt
@@ -240,21 +240,21 @@ a python dictionary:
  .. code-block:: none
 
     1. factor
-     [[6.24 0.   1.43]
-     [4.65 0.55 0.75]
-     [4.63 0.81 0.64]
-     [3.69 1.12 0.  ]
-     [2.81 1.25 0.04]
-     [3.49 1.2  0.32]]
+     [[4.69 0.15 0.35]
+     [5.04 1.09 0.78]
+     [3.93 0.   1.09]
+     [5.07 1.23 0.64]
+     [4.56 0.92 0.49]
+     [4.19 1.11 0.26]]
     2. factor
-     [[ 0.29  0.31  0.08]
-     [-0.13  1.12  1.27]
-     [ 0.03  0.96  0.74]
-     [ 0.45  0.33 -0.68]
-     [ 0.25  0.58  0.16]
-     [ 0.46  0.21 -0.79]
-     [ 0.2   0.57  0.48]
-     [ 0.57 -0.05 -0.81]]
+     [[ 0.39 -0.52  0.34]
+     [ 0.39 -0.05 -0.07]
+     [ 0.5  -0.56 -0.73]
+     [ 0.18  0.52  0.7 ]
+     [ 0.55 -0.94 -0.55]
+     [ 0.36 -0.12  0.16]
+     [ 0.38 -0.13 -0.57]
+     [ 0.35 -0.13 -0.39]]
 
 
 
@@ -366,31 +366,31 @@ only `True` depending on the selected constraint.
  .. code-block:: none
 
     1. factor
-     [[ 21.58  -7.11   1.82]
-     [ 21.16   4.54  -3.44]
-     [ 22.64  -4.74   6.71]
-     [ 24.6   42.22 -12.9 ]
-     [ 19.67  -2.45  30.43]
-     [ 23.2   16.83   1.59]]
+     [[ 28.38  -6.73   0.89]
+     [ 21.49 -27.94  33.16]
+     [ 20.63  -8.25  11.36]
+     [ 25.01   7.64  -1.4 ]
+     [ 23.62  15.2   -7.26]
+     [ 18.14  22.78   0.8 ]]
     2. factor
-     [[0.37 0.49 0.16]
-     [0.37 0.94 1.21]
-     [0.39 0.97 0.  ]
-     [0.38 0.   0.56]
-     [0.4  0.35 0.49]
-     [0.35 0.47 0.  ]
-     [0.41 0.5  0.15]
-     [0.38 0.17 0.41]]
+     [[0.38 0.   0.18]
+     [0.37 1.11 1.07]
+     [0.39 0.   0.03]
+     [0.32 1.37 0.92]
+     [0.41 0.   0.  ]
+     [0.39 0.08 0.33]
+     [0.33 0.63 0.17]
+     [0.31 0.   0.39]]
     3. factor
-     [[ 0.06  0.01  0.01]
-     [ 0.06 -0.01 -0.01]
-     [ 0.06  0.01  0.01]
-     [ 0.07 -0.01  0.01]
-     [ 0.06  0.01  0.  ]
-     [ 0.06 -0.01 -0.  ]
+     [[ 0.05  0.01 -0.  ]
+     [ 0.06 -0.01  0.01]
+     [ 0.06  0.01  0.02]
+     [ 0.05  0.02  0.04]
      [ 0.06 -0.    0.01]
-     [ 0.06 -0.01 -0.01]
-     [ 0.06 -0.   -0.01]
+     [ 0.06  0.01  0.01]
+     [ 0.06  0.02  0.03]
+     [ 0.06  0.    0.01]
+     [ 0.06  0.    0.01]
      [ 0.06 -0.01 -0.01]]
 
 
@@ -417,7 +417,7 @@ IEEE Transactions on Signal Processing 64.19 (2016): 5052-5065.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 3.195 seconds)
+   **Total running time of the script:** (0 minutes 3.228 seconds)
 
 
 .. _sphx_glr_download_auto_examples_decomposition_plot_guide_for_constrained_cp.py:

diff --git a/dev/_sources/auto_examples/decomposition/plot_nn_cp_hals.rst.txt b/dev/_sources/auto_examples/decomposition/plot_nn_cp_hals.rst.txt
@@ -161,11 +161,11 @@ the case but the approximation is quite coarse.
  .. code-block:: none
 
     reconstructed tensor
-     [[[8233.64 8330.33]
-      [8431.29 8470.38]]
+     [[[8335.02 8150.92]
+      [8284.42 8128.53]]
 
-     [[9223.58 9249.81]
-      [9091.29 9092.84]]] 
+     [[9157.75 9086.59]
+      [9097.12 9042.34]]] 
 
     input data tensor
      [[[8210. 8211.]
@@ -224,11 +224,11 @@ Again, we can look at the reconstructed tensor entries.
  .. code-block:: none
 
     reconstructed tensor
-     [[[8200.37 8223.83]
-      [8201.24 8236.49]]
+     [[[8193.22 8237.54]
+      [8213.46 8244.62]]
 
-     [[9002.38 9021.92]
-      [9003.35 9036.18]]] 
+     [[8994.86 9034.82]
+      [9015.12 9043.21]]] 
 
     input data tensor
      [[[8210. 8211.]
@@ -296,8 +296,8 @@ First comparison option is processing time for each algorithm:
  .. code-block:: none
 
     0.04 seconds
-    0.04 seconds
-    82.35 seconds
+    0.08 seconds
+    167.46 seconds
 
 
 
@@ -331,9 +331,9 @@ In Tensorly, we provide a function to calculate Root Mean Square Error (RMSE):
 
  .. code-block:: none
 
-    212.3102
-    36.43909
-    2.1115885
+    221.49815
+    42.319496
+    1.9318805
 
 
 
@@ -397,7 +397,7 @@ Neural computation, 24(4), 1085-1105. (Link)
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (1 minutes 22.514 seconds)
+   **Total running time of the script:** (2 minutes 47.659 seconds)
 
 
 .. _sphx_glr_download_auto_examples_decomposition_plot_nn_cp_hals.py:

diff --git a/dev/_sources/auto_examples/decomposition/plot_nn_tucker.rst.txt b/dev/_sources/auto_examples/decomposition/plot_nn_tucker.rst.txt
@@ -214,7 +214,7 @@ processing time:
 
     time for tensorly nntucker: 0.09
     time for HALS with fista: 1.26
-    time for HALS with as: 0.26
+    time for HALS with as: 0.24
 
 
 
@@ -246,9 +246,9 @@ to compute Root Mean Square Error (RMSE):
 
  .. code-block:: none
 
-    RMSE tensorly nntucker: 286.626873838224
-    RMSE for hals with fista: 283.31942375720564
-    RMSE for hals with as: 283.1474616656402
+    RMSE tensorly nntucker: 287.04419956566784
+    RMSE for hals with fista: 282.90682029246904
+    RMSE for hals with as: 283.8874055186602
 
 
 
@@ -312,7 +312,7 @@ Neural computation, 24(4), 1085-1105.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 1.683 seconds)
+   **Total running time of the script:** (0 minutes 1.668 seconds)
 
 
 .. _sphx_glr_download_auto_examples_decomposition_plot_nn_tucker.py:

diff --git a/dev/_sources/auto_examples/decomposition/plot_parafac2.rst.txt b/dev/_sources/auto_examples/decomposition/plot_parafac2.rst.txt
@@ -374,7 +374,7 @@ Visualize the components
  .. code-block:: none
 
 
-    <matplotlib.legend.Legend object at 0x7f9dcfeed130>
+    <matplotlib.legend.Legend object at 0x7f33cc708950>
 
 
 
@@ -436,7 +436,7 @@ A direct fitting algorithm for the PARAFAC2 model.*
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 10.768 seconds)
+   **Total running time of the script:** (0 minutes 10.803 seconds)
 
 
 .. _sphx_glr_download_auto_examples_decomposition_plot_parafac2.py:

diff --git a/dev/_sources/auto_examples/decomposition/plot_parafac2_compression.rst.txt b/dev/_sources/auto_examples/decomposition/plot_parafac2_compression.rst.txt
@@ -159,7 +159,7 @@ with the lowest reconstruction error.
  .. code-block:: none
 
     Fitting PARAFAC2 model without compression...
-    It took 48.7s to fit a PARAFAC2 model a tensor of shape (10, 10000, 15) without compression
+    It took 48.6s to fit a PARAFAC2 model a tensor of shape (10, 10000, 15) without compression
 
 
 
@@ -218,8 +218,8 @@ we just need to perform the compression once for the whole grid search as well.
  .. code-block:: none
 
     Fitting PARAFAC2 model with SVD compression...
-    It took 19.4s to fit a PARAFAC2 model a tensor of shape (10, 10000, 15) with lossless SVD compression
-    The compression took 0.0s and the fitting took 19.4s
+    It took 19.5s to fit a PARAFAC2 model a tensor of shape (10, 10000, 15) with lossless SVD compression
+    The compression took 0.0s and the fitting took 19.5s
 
 
 
@@ -280,8 +280,8 @@ removing the parts of the data matrices that have a very low "signal strength".
  .. code-block:: none
 
     Fitting PARAFAC2 model with lossy SVD compression...
-    It took 19.3s to fit a PARAFAC2 model a tensor of shape (10, 10000, 15) with lossy SVD compression
-    Of which the compression took 0.0s and the fitting took 19.2s
+    It took 19.4s to fit a PARAFAC2 model a tensor of shape (10, 10000, 15) with lossy SVD compression
+    Of which the compression took 0.0s and the fitting took 19.3s
 
 
 
@@ -359,7 +359,7 @@ Again, we start by fitting without compression as a baseline.
  .. code-block:: none
 
     Fitting PARAFAC2 model without compression...
-    It took 114.3s to fit a PARAFAC2 model a tensor of shape (10, 2000, 2000) without compression
+    It took 115.5s to fit a PARAFAC2 model a tensor of shape (10, 2000, 2000) without compression
 
 
 
@@ -413,8 +413,8 @@ Next, we fit with lossless compression.
  .. code-block:: none
 
     Fitting PARAFAC2 model with SVD compression...
-    It took 109.4s to fit a PARAFAC2 model a tensor of shape (10, 2000, 2000) with lossless SVD compression
-    Of which the compression took 0.0s and the fitting took 109.4s
+    It took 110.3s to fit a PARAFAC2 model a tensor of shape (10, 2000, 2000) with lossless SVD compression
+    Of which the compression took 0.0s and the fitting took 110.3s
 
 
 
@@ -475,8 +475,8 @@ Finally, we fit with lossy SVD compression.
  .. code-block:: none
 
     Fitting PARAFAC2 model with lossy SVD compression...
-    It took 27.7s to fit a PARAFAC2 model a tensor of shape (10, 2000, 2000) with lossy SVD compression
-    Of which the compression took 12.9s and the fitting took 14.8s
+    It took 27.5s to fit a PARAFAC2 model a tensor of shape (10, 2000, 2000) with lossy SVD compression
+    Of which the compression took 13.0s and the fitting took 14.5s
 
 
 
@@ -492,7 +492,7 @@ PARAFAC2.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (5 minutes 39.859 seconds)
+   **Total running time of the script:** (5 minutes 41.861 seconds)
 
 
 .. _sphx_glr_download_auto_examples_decomposition_plot_parafac2_compression.py: