1 files changed, 0 insertions, 106 deletions
diff --git a/test/test_gpu.py b/test/test_gpu.py
deleted file mode 100644
index 8e62a74..0000000
--- a/test/test_gpu.py
+++ /dev/null
@@ -1,106 +0,0 @@
-"""Tests for module gpu for gpu acceleration """
-
-# Author: Remi Flamary <remi.flamary@unice.fr>
-#
-# License: MIT License
-
-import numpy as np
-import ot
-import pytest
-
-try:  # test if cudamat installed
-    import ot.gpu
-    nogpu = False
-except ImportError:
-    nogpu = True
-
-
-@pytest.mark.skipif(nogpu, reason="No GPU available")
-def test_gpu_old_doctests():
-    a = [.5, .5]
-    b = [.5, .5]
-    M = [[0., 1.], [1., 0.]]
-    G = ot.sinkhorn(a, b, M, 1)
-    np.testing.assert_allclose(G, np.array([[0.36552929, 0.13447071],
-                                            [0.13447071, 0.36552929]]))
-
-
-@pytest.mark.skipif(nogpu, reason="No GPU available")
-def test_gpu_dist():
-
-    rng = np.random.RandomState(0)
-
-    for n_samples in [50, 100, 500, 1000]:
-        print(n_samples)
-        a = rng.rand(n_samples // 4, 100)
-        b = rng.rand(n_samples, 100)
-
-        M = ot.dist(a.copy(), b.copy())
-        M2 = ot.gpu.dist(a.copy(), b.copy())
-
-        np.testing.assert_allclose(M, M2, rtol=1e-10)
-
-        M2 = ot.gpu.dist(a.copy(), b.copy(), metric='euclidean', to_numpy=False)
-
-        # check raise not implemented wrong metric
-        with pytest.raises(NotImplementedError):
-            M2 = ot.gpu.dist(a.copy(), b.copy(), metric='cityblock', to_numpy=False)
-
-
-@pytest.mark.skipif(nogpu, reason="No GPU available")
-def test_gpu_sinkhorn():
-
-    rng = np.random.RandomState(0)
-
-    for n_samples in [50, 100, 500, 1000]:
-        a = rng.rand(n_samples // 4, 100)
-        b = rng.rand(n_samples, 100)
-
-        wa = ot.unif(n_samples // 4)
-        wb = ot.unif(n_samples)
-
-        wb2 = np.random.rand(n_samples, 20)
-        wb2 /= wb2.sum(0, keepdims=True)
-
-        M = ot.dist(a.copy(), b.copy())
-        M2 = ot.gpu.dist(a.copy(), b.copy(), to_numpy=False)
-
-        reg = 1
-
-        G = ot.sinkhorn(wa, wb, M, reg)
-        G1 = ot.gpu.sinkhorn(wa, wb, M, reg)
-
-        np.testing.assert_allclose(G1, G, rtol=1e-10)
-
-        # run all on gpu
-        ot.gpu.sinkhorn(wa, wb, M2, reg, to_numpy=False, log=True)
-
-        # run sinkhorn for multiple targets
-        ot.gpu.sinkhorn(wa, wb2, M2, reg, to_numpy=False, log=True)
-
-
-@pytest.mark.skipif(nogpu, reason="No GPU available")
-def test_gpu_sinkhorn_lpl1():
-
-    rng = np.random.RandomState(0)
-
-    for n_samples in [50, 100, 500]:
-        print(n_samples)
-        a = rng.rand(n_samples // 4, 100)
-        labels_a = np.random.randint(10, size=(n_samples // 4))
-        b = rng.rand(n_samples, 100)
-
-        wa = ot.unif(n_samples // 4)
-        wb = ot.unif(n_samples)
-
-        M = ot.dist(a.copy(), b.copy())
-        M2 = ot.gpu.dist(a.copy(), b.copy(), to_numpy=False)
-
-        reg = 1
-
-        G = ot.da.sinkhorn_lpl1_mm(wa, labels_a, wb, M, reg)
-        G1 = ot.gpu.da.sinkhorn_lpl1_mm(wa, labels_a, wb, M, reg)
-
-        np.testing.assert_allclose(G1, G, rtol=1e-10)
-
-        ot.gpu.da.sinkhorn_lpl1_mm(wa, labels_a, wb, M2, reg, to_numpy=False, log=True)