Clarify the doc of enable_autodiff

1 files changed, 4 insertions, 1 deletions

diff --git a/src/python/gudhi/wasserstein/wasserstein.py b/src/python/gudhi/wasserstein/wasserstein.py
index 3d1caeb3..0d164eda 100644
--- a/src/python/gudhi/wasserstein/wasserstein.py
+++ b/src/python/gudhi/wasserstein/wasserstein.py
@@ -100,7 +100,10 @@ def wasserstein_distance(X, Y, matching=False, order=2., internal_p=2., enable_a
     :param internal_p: Ground metric on the (upper-half) plane (i.e. norm L^p in R^2);
                        Default value is 2 (Euclidean norm).
     :param enable_autodiff: If X and Y are torch.tensor, tensorflow.Tensor or jax.numpy.ndarray, make the computation
-        transparent to automatic differentiation.
+        transparent to automatic differentiation. This requires the package EagerPy.
+
+        .. note:: This considers the function defined on the coordinates of the off-diagonal points of X and Y
+            and lets the various frameworks compute its gradient. It never pulls new points from the diagonal.
     :type enable_autodiff: bool
     :returns: the Wasserstein distance of order q (1 <= q < infinity) between persistence diagrams with
               respect to the internal_p-norm as ground metric.