Merge pull request #16 from lamblin/abergeron-fix_gpuadvsub1

theano/tensor/tests/test_subtensor.py

@@ -500,9 +500,25 @@ class T_subtensor(unittest.TestCase, utt.TestOptimizationMixin):
              self.ignore_topo)]
         assert len(topo_) == 1
         self.assertTrue(isinstance(topo_[0].op, self.adv_sub1))
-        self.assertTrue(numpy.allclose(f([0]), ones[0] * 5))
+        f_0 = f([0])
+        self.assertTrue(f_0.shape == (1, 3))
+        self.assertTrue(numpy.allclose(f_0, ones[0] * 5))
+        f_00 = f([0, 0])
+        self.assertTrue(f_00.shape == (2, 3))
+        self.assertTrue(numpy.allclose(f_00, 5))
         self.assertRaises(IndexError, f, [0, 1])
 
+        # Test the gradient
+        c = t.sum()
+        gn = theano.grad(c, n)
+        g = self.function([idx], gn, op=self.adv_incsub1)
+        g_0 = g([0])
+        self.assertTrue(g_0.shape == (1, 3))
+        self.assertTrue(numpy.allclose(g_0, 1))
+        g_00 = g([0, 0])
+        self.assertTrue(g_00.shape == (1, 3))
+        self.assertTrue(numpy.allclose(g_00, 2))
+
     def test_adv_sub1_idx_broadcast(self):
         # The idx can be a broadcastable vector.
         ones = numpy.ones((4, 3), dtype=self.dtype)
@@ -518,7 +534,18 @@ class T_subtensor(unittest.TestCase, utt.TestOptimizationMixin):
              self.ignore_topo)]
         assert len(topo_) == 1
         self.assertTrue(isinstance(topo_[0].op, self.adv_sub1))
-        self.assertTrue(numpy.allclose(f([0]), ones[0] * 5))
+        f_0 = f([0])
+        self.assertTrue(f_0.shape == (1, 3))
+        self.assertTrue(numpy.allclose(f_0, 5))
+
+        # Test the gradient
+        c = t.sum()
+        gn = theano.grad(c, n)
+        g = self.function([idx], gn, op=self.adv_incsub1)
+        g_0 = g([0])
+        self.assertTrue(g_0.shape == (4, 3))
+        self.assertTrue(numpy.allclose(g_0[0], 1))
+        self.assertTrue(numpy.allclose(g_0[1:], 0))
 
     @attr('slow')
     def test_shape_i_const(self):