[MRG] Sliced and 1D Wasserstein distances : backend versions (#256)

* add numpy and torch backends

* stat sets on functions

* proper import

* install recent torch on windows

* install recent torch on windows

* now testing all functions in backedn

* add jax backedn

* clenaup windowds

* proper convert for jax backedn

* pep8

* try again windows tests

* test jax conversion

* try proper widows tests

* emd fuction ses backedn

* better test partial OT

* proper tests to_numpy and teplate Backend

* pep8

* pep8 x2

* feaking sinkhorn works with torch

* sinkhorn2 compatible

* working ot.emd2

* important detach

* it should work

* jax autodiff emd

* pep8

* no tast same for jax

* new independat tests per backedn

* freaking pep8

* add tests for gradients

* deprecate ot.gpu

* worging dist function

* working dist

* dist done in backedn

* not in

* remove indexing

* change accuacy for jax

* first pull backend

* projection simplex

* projection simplex

* projection simplex

* projection simplex no ci

* projection simplex no ci

* projection simplex no ci

* pep8

* add backedn discusion to quickstart guide

* projection simplex no ci

* projection simplex no ci

* projection simplex no ci

* pep8 + better doc

* proper links

* corect doctest

* big debug documentation

* doctest again

* doctest again bis

* doctest again ter (last one or i kill myself)

* backend test + doc proj simplex

* correction test_utils

* correction test_utils

* correction cumsum

* correction flip

* correction flip v2

* more debug

* more debug

* more debug + pep8

* pep8

* argh

* proj_simplex

* backedn works for sort

* proj simplex

* jax sucks

* update doc

* Update test/test_utils.py

Co-authored-by: Alexandre Gramfort <alexandre.gramfort@m4x.org>

* Update docs/source/quickstart.rst

Co-authored-by: Alexandre Gramfort <alexandre.gramfort@m4x.org>

* Update docs/source/quickstart.rst

Co-authored-by: Alexandre Gramfort <alexandre.gramfort@m4x.org>

* Update docs/source/quickstart.rst

Co-authored-by: Alexandre Gramfort <alexandre.gramfort@m4x.org>

* Update docs/source/readme.rst

Co-authored-by: Alexandre Gramfort <alexandre.gramfort@m4x.org>

* Update test/test_utils.py

Co-authored-by: Alexandre Gramfort <alexandre.gramfort@m4x.org>

* Update ot/utils.py

Co-authored-by: Alexandre Gramfort <alexandre.gramfort@m4x.org>

* Update docs/source/readme.rst

Co-authored-by: Alexandre Gramfort <alexandre.gramfort@m4x.org>

* Update ot/lp/__init__.py

Co-authored-by: Alexandre Gramfort <alexandre.gramfort@m4x.org>

* begin comment alex

* comment alex part 2

* optimize test gromov

* proj_simplex on vectors

* add awesome gradient decsnt example on the weights

* pep98 of course

* proof read example by alex

* pep8 again

* encoding oos in translation

* correct legend

* new backend functions for sliced

* small indent pb

* Optimized backendversion of sliced W

* error in sliced W

* after master merge

* error sliced

* error sliced

* pep8

* test_sliced pep8

* doctest + precision for sliced

* doctest

* type win test_backend gather

* type win test_backend gather

* Update sliced.py

change argument of padding pad_width

* Update backend.py

update redefinition

* Update backend.py

pep8

* Update backend.py

pep 8 again....

* pep8

* build docs

* emd2_1D example

* refectoring emd_1d and variants

* remove unused previous wasserstein_1d

* pep8

* upate example

* move stuff

* tesys should work + implemù random backend

* test random generayor functions

* correction

* better random generation

* update sliced

* update sliced

* proper tests sliced

* max sliced

* chae file nam

* add stuff

* example sliced flow and barycenter

* correct typo + update readme

* exemple sliced flow done

* pep8

* solver1d works

* pep8

Co-authored-by: Rémi Flamary <remi.flamary@gmail.com>
Co-authored-by: Alexandre Gramfort <alexandre.gramfort@m4x.org>

1 files changed, 36 insertions, 0 deletions

diff --git a/test/test_backend.py b/test/test_backend.py
index 0f11ace..1832b91 100644
--- a/test/test_backend.py
+++ b/test/test_backend.py
@@ -208,6 +208,11 @@ def test_empty_backend():
     with pytest.raises(NotImplementedError):
         nx.reshape(M, (5, 3, 2))
     with pytest.raises(NotImplementedError):
+        nx.seed(42)
+    with pytest.raises(NotImplementedError):
+        nx.rand()
+    with pytest.raises(NotImplementedError):
+        nx.randn()
         nx.coo_matrix(M, M, M)
     with pytest.raises(NotImplementedError):
         nx.issparse(M)
@@ -248,6 +253,7 @@ def test_func_backends(nx):
 
         Mb = nx.from_numpy(M)
         vb = nx.from_numpy(v)
+
         val = nx.from_numpy(val)
 
         sp_rowb = nx.from_numpy(sp_row)
@@ -255,6 +261,7 @@ def test_func_backends(nx):
         sp_datab = nx.from_numpy(sp_data)
 
         A = nx.set_gradients(val, v, v)
+
         lst_b.append(nx.to_numpy(A))
         lst_name.append('set_gradients')
 
@@ -505,6 +512,35 @@ def test_func_backends(nx):
         assert np.allclose(a1, a2, atol=1e-7)
 
 
+def test_random_backends(nx):
+
+    tmp_u = nx.rand()
+
+    assert tmp_u < 1
+
+    tmp_n = nx.randn()
+
+    nx.seed(0)
+    M1 = nx.to_numpy(nx.rand(5, 2))
+    nx.seed(0)
+    M2 = nx.to_numpy(nx.rand(5, 2, type_as=tmp_n))
+
+    assert np.all(M1 >= 0)
+    assert np.all(M1 < 1)
+    assert M1.shape == (5, 2)
+    assert np.allclose(M1, M2)
+
+    nx.seed(0)
+    M1 = nx.to_numpy(nx.randn(5, 2))
+    nx.seed(0)
+    M2 = nx.to_numpy(nx.randn(5, 2, type_as=tmp_u))
+
+    nx.seed(42)
+    v1 = nx.randn()
+    v2 = nx.randn()
+    assert v1 != v2
+
+
 def test_gradients_backends():
 
     rnd = np.random.RandomState(0)