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1 change: 1 addition & 0 deletions RELEASES.md
Original file line number Diff line number Diff line change
Expand Up @@ -15,6 +15,7 @@

#### Closed issues

- Remove a leftover debug `print` from `ot.utils.projection_sparse_simplex` with `axis=1`, and make the `ot.datasets.make_gauss_hd` docstring a raw string so importing `ot` no longer emits a `SyntaxWarning` (PR #860)
- Fix `ot.dist` ignoring the weights `w` for `metric="cityblock"`, which returned the unweighted distance although the weights are documented for this metric (PR #859)
- Fix swapped arguments to `div_to_product` in `ot.gromov.fused_unbalanced_across_spaces_cost`: with `reg_type="independent"` (UCOOT) the entropic terms used the plan marginals as the reference measures and vice versa (PR #855, Issue #854)
- Fix device placement in `ot.batch.bregman_projection_batch` so `ot.solve_batch(..., method="sinkhorn")` no longer crashes on GPU when the torch default device is CPU (PR #851)
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2 changes: 1 addition & 1 deletion ot/datasets.py
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Expand Up @@ -186,7 +186,7 @@ def get_data_classif(dataset, n, nz=0.5, theta=0, random_state=None, **kwargs):
def make_gauss_hd(
ns, nt, p=100, dim=5, m_diff=3.0, a=(10.0, 15.0), b=(3.0, 3.0), sub_the_same=False
):
"""Generation of source and target domains from Gaussian HD distributions
r"""Generation of source and target domains from Gaussian HD distributions

Parameters
----------
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1 change: 0 additions & 1 deletion ot/utils.py
Original file line number Diff line number Diff line change
Expand Up @@ -201,7 +201,6 @@ def projection_sparse_simplex(V, max_nz, z=1, axis=None, nx=None):

row_indices = nx.arange(V.shape[0])
row_indices = row_indices.reshape(-1, 1)
print(row_indices.shape)
# Extract the top max_nz values for each row
# and then project to simplex.
U = V[row_indices, max_nz_indices]
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