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| -rw-r--r-- | src/python/doc/differentiation_sum.inc | 3 |
1 files changed, 2 insertions, 1 deletions
diff --git a/src/python/doc/differentiation_sum.inc b/src/python/doc/differentiation_sum.inc index 3dd8e59c..3aec33df 100644 --- a/src/python/doc/differentiation_sum.inc +++ b/src/python/doc/differentiation_sum.inc @@ -8,4 +8,5 @@ We provide TensorFlow 2 models that can handle automatic differentiation for the computation of persistence diagrams from complexes available in the Gudhi library. This includes simplex trees, cubical complexes and Vietoris-Rips complexes. Detailed example on how to use these layers in practice are available -in the following `notebook <https://github.com/GUDHI/TDA-tutorial/blob/master/Tuto-GUDHI-optimization.ipynb>`_. +in the following `notebook <https://github.com/GUDHI/TDA-tutorial/blob/master/Tuto-GUDHI-optimization.ipynb>`_. Note that even if TensorFlow GPU is enabled, all +internal computations using Gudhi will be done on CPU. |