putting advance_indexing as part of the TestAdvancedSubtensor class

theano/tensor/tests/test_subtensor.py

@@ -1265,6 +1265,27 @@ class TestAdvancedSubtensor(unittest.TestCase):
                   [5, 6, 7],
                   [.5, .3 + 2.1, .15 + 2.1]]), aval
 
+    def test_advanced_indexing(self):
+        # tests advanced indexing in Theano for 2D and 3D tensors
+        rng = numpy.random.RandomState(utt.seed_rng())
+        a = rng.uniform(size=(3,3))
+        b = theano.shared(a)
+        i = tensor.iscalar()
+        j = tensor.iscalar()
+        z = b[[i, j], :]
+        f1 = theano.function([i,j],z)
+        cmd = f1(0,1) == a[[0,1],:]
+        self.assertTrue(numpy.all(cmp))
+
+        aa = rng.uniform(size=(4,2,3))
+        bb = theano.shared(aa)
+        k = tensor.iscalar()
+        z = bb[[i, j, k],:, i:k]
+        f2 = theano.function([i,j,k],z)
+        cmd = f2(0,1,2) == aa[[0,1,2],:, 0:2]
+        self.assertTrue(numpy.all(cmp))
+
+
 
 class TestInferShape(utt.InferShapeTester):
     def test_infer_shape(self):
@@ -1429,24 +1450,3 @@ class TestInferShape(utt.InferShapeTester):
         self._compile_and_check([admat, advec],
                     [set_subtensor(admat[aivec_val, bivec_val], advec)],
                     [admat_val, advec_val], AdvancedIncSubtensor)
-
-
-def test_advanced_indexing():
-    # tests advanced indexing in Theano for 2D and 3D tensors
-    rng = numpy.random.RandomState(utt.seed_rng())
-    a = rng.uniform(size=(3,3))
-    b = theano.shared(a)
-    i = T.iscalar()
-    j = T.iscalar()
-    z = b[[i, j], :]
-    f1 = theano.function([i,j],z)
-    cmd = f1(0,1) == a[[0,1],:]
-    numpy.all(cmp)
-
-    aa = rng.uniform(size=(4,2,3))
-    bb = theano.shared(aa)
-    k = T.iscalar()
-    z = bb[[i, j, k],:, i:k]
-    f2 = theano.function([i,j,k],z)
-    cmd = f2(0,1,2) == aa[[0,1,2],:, 0:2]
-    numpy.all(cmp)