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| author | MathieuCarriere <mathieu.carriere3@gmail.com> | 2021-10-19 14:37:39 +0200 |
|---|---|---|
| committer | MathieuCarriere <mathieu.carriere3@gmail.com> | 2021-10-19 14:37:39 +0200 |
| commit | 423c4be21968fd42c5470a9132d0e332c73ec2b9 (patch) | |
| tree | b9d0f0f033f4b62d7f59410737f051a75676186a /src/python/doc/differentiation_sum.inc | |
| parent | fc1c33d19c7d50d01bacb61529badbde8217ce7e (diff) | |
fix python documentation
Diffstat (limited to 'src/python/doc/differentiation_sum.inc')
| -rw-r--r-- | src/python/doc/differentiation_sum.inc | 5 |
1 files changed, 3 insertions, 2 deletions
diff --git a/src/python/doc/differentiation_sum.inc b/src/python/doc/differentiation_sum.inc index 7340d24d..3dd8e59c 100644 --- a/src/python/doc/differentiation_sum.inc +++ b/src/python/doc/differentiation_sum.inc @@ -1,4 +1,4 @@ -. list-table:: +.. list-table:: :widths: 40 30 30 :header-rows: 0 @@ -7,4 +7,5 @@ - :Requires: `TensorFlow <installation.html#tensorflow>`_ 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. +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>`_. |