1 files changed, 106 insertions, 0 deletions
diff --git a/test/test_gpu.py b/test/test_gpu.py
new file mode 100644
index 0000000..8e62a74
--- /dev/null
+++ b/test/test_gpu.py
@@ -0,0 +1,106 @@
+"""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)