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-rw-r--r--src/python/gudhi/wasserstein/wasserstein.py1
1 files changed, 0 insertions, 1 deletions
diff --git a/src/python/gudhi/wasserstein/wasserstein.py b/src/python/gudhi/wasserstein/wasserstein.py
index 5b61d176..42c8dc2d 100644
--- a/src/python/gudhi/wasserstein/wasserstein.py
+++ b/src/python/gudhi/wasserstein/wasserstein.py
@@ -167,7 +167,6 @@ def wasserstein_distance(X, Y, matching=False, order=2., internal_p=2., enable_a
dists.append(_perstot_autodiff(Y_orig[diag2], order, internal_p))
dists = [dist.reshape(1) for dist in dists]
return ep.concatenate(dists).norms.lp(order).raw
- # Should just compute the L^order norm manually?
# We can also concatenate the 3 vectors to compute just one norm.
# Comptuation of the otcost using the ot.emd2 library.