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| author | MathieuCarriere <mathieu.carriere3@gmail.com> | 2021-11-17 00:18:33 +0100 |
|---|---|---|
| committer | MathieuCarriere <mathieu.carriere3@gmail.com> | 2021-11-17 00:18:33 +0100 |
| commit | 7b83812e37986c9adf9cccaeab360f1d4ffa846f (patch) | |
| tree | 9bb8926680b6eddf00279a2c22a9f86634552be3 /src/python/doc/cubical_complex_tflow_itf_ref.rst | |
| parent | 7e71aff27074874acdfd3530826b3f10709e346c (diff) | |
fix doc
Diffstat (limited to 'src/python/doc/cubical_complex_tflow_itf_ref.rst')
| -rw-r--r-- | src/python/doc/cubical_complex_tflow_itf_ref.rst | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/src/python/doc/cubical_complex_tflow_itf_ref.rst b/src/python/doc/cubical_complex_tflow_itf_ref.rst index 92727a75..692191ba 100644 --- a/src/python/doc/cubical_complex_tflow_itf_ref.rst +++ b/src/python/doc/cubical_complex_tflow_itf_ref.rst @@ -16,7 +16,7 @@ Example of gradient computed from cubical persistence import tensorflow as tf X = tf.Variable([[0.,2.,2.],[2.,2.,2.],[2.,2.,1.]], dtype=tf.float32, trainable=True) - cl = CubicalLayer(dimension=0) + cl = CubicalLayer(dimensions=[0]) with tf.GradientTape() as tape: dgm = cl.call(X) |