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| author | Rémi Flamary <remi.flamary@gmail.com> | 2022-12-15 09:28:01 +0100 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2022-12-15 09:28:01 +0100 |
| commit | 0411ea22a96f9c22af30156b45c16ef39ffb520d (patch) | |
| tree | 7c131ad804d5b16a8c362c2fe296350a770400df /test/test_backend.py | |
| parent | 8490196dcc982c492b7565e1ec4de5f75f006acf (diff) | |
[MRG] New API for OT solver (with pre-computed ground cost matrix) (#388)
* new API for OT solver
* use itertools for product of parameters
* add tests for result class
* add tests for result class
* add tests for result class last time?
* add sinkhorn
* make partial OT bckend compatible
* add TV as unbalanced flavor
* better tests
* make smoth backend compatible and add l2 tregularizatio to solve
* add reularizedd unbalanced
* add test for more complex attibutes
* add test for more complex attibutes
* add generic unbalaned solver and implement it for ot.solve
* add entropy to possible regularization
* star of documentation for ot.solv
* weird new pep8
* documenttaion for function ot.solve done
* pep8
* Update ot/solvers.py
Co-authored-by: Alexandre Gramfort <alexandre.gramfort@m4x.org>
* update release file
* Apply suggestions from code review
Co-authored-by: Alexandre Gramfort <alexandre.gramfort@m4x.org>
* add test NotImplemented
* pep8
* pep8gcmp pep8!
* compute kl in backend
* debug tensorflow kl backend
Co-authored-by: Alexandre Gramfort <alexandre.gramfort@m4x.org>
Diffstat (limited to 'test/test_backend.py')
| -rw-r--r-- | test/test_backend.py | 6 |
1 files changed, 6 insertions, 0 deletions
diff --git a/test/test_backend.py b/test/test_backend.py index 311c075..3628f61 100644 --- a/test/test_backend.py +++ b/test/test_backend.py @@ -275,6 +275,8 @@ def test_empty_backend(): with pytest.raises(NotImplementedError): nx.sqrtm(M) with pytest.raises(NotImplementedError): + nx.kl_div(M, M) + with pytest.raises(NotImplementedError): nx.isfinite(M) with pytest.raises(NotImplementedError): nx.array_equal(M, M) @@ -592,6 +594,10 @@ def test_func_backends(nx): lst_b.append(nx.to_numpy(A)) lst_name.append("matrix square root") + A = nx.kl_div(nx.abs(Mb), nx.abs(Mb) + 1) + lst_b.append(nx.to_numpy(A)) + lst_name.append("Kullback-Leibler divergence") + A = nx.concatenate([vb, nx.from_numpy(np.array([np.inf, np.nan]))], axis=0) A = nx.isfinite(A) lst_b.append(nx.to_numpy(A)) |