Update tests of local_subtensor_merge

theano/tensor/tests/test_basic.py

@@ -2508,23 +2508,6 @@ class T_subtensor(unittest.TestCase):
             assert numpy.all(t_out == v_out)
             assert numpy.all(t_out.shape == v_out.shape)
 
-    def test_merge_subtensor(self):
-        # Bug reported by Razvan
-        data = numpy.asarray(numpy.arange(8),
-                             dtype = theano.config.floatX)
-        x = theano.tensor.vector()
-        y1 = x[2:][::-1]
-        y2 = x[:-2][::-1]
-        length = theano.tensor.minimum(y1.shape[0], y2.shape[0])
-        y1 = y1[:length]
-        y2 = y2[:length]
-        t = theano.shared(numpy.int64(0))
-        fun = theano.function([x], [y1[t], y2[t]])
-        val0, val1 = fun(data)
-        assert val0 == data[2:][::-1][0]
-        assert val1 == data[:-2][::-1][0]
-
-
     def grad_list_(self, idxs, data):
         n = self.shared(data)
 

theano/tensor/tests/test_opt.py

@@ -1742,7 +1742,8 @@ class test_local_subtensor_merge(unittest.TestCase):
 
 
     def test_scalar5(self):
-        # var[int1:][:int2]
+        # General case with two real slices
+        # var[b1:e1:s1][b2:e2:s2]
         x = tensor.matrix('x')
         b1 = tensor.iscalar('b1')
         e1 = tensor.iscalar('e1')
@@ -1777,6 +1778,59 @@ class test_local_subtensor_merge(unittest.TestCase):
                                 for s2 in s2r:
                                     f(x_val, b1,e1,s1,b2,e2,s2)
 
+    def test_const4(self):
+        # Bug reported by Razvan
+        data = numpy.asarray(numpy.arange(8),
+                             dtype = theano.config.floatX)
+        x = theano.tensor.vector('x')
+        y = x[7:1:-1]
+        t = theano.shared(numpy.int64(0))
+
+        fun = theano.function([x], y[t])
+        val = fun(data)
+        assert val == data[7:1:-1][0]
+
+    def test_scalar6(self):
+        # General case with one slice and one index
+        # var[b:e:s][i]
+        x = tensor.matrix('x')
+        b = tensor.iscalar('b')
+        e = tensor.iscalar('e')
+        s = tensor.iscalar('s')
+        i = tensor.iscalar('i')
+        f = function([x,b,e,s,i], x[b:e:s][i], mode=mode_opt)
+        #theano.printing.debugprint(f, print_type=True)
+
+        topo=f.maker.env.toposort()
+        #print [t for t in topo if isinstance(t.op, tensor.Subtensor)]
+        assert len([t for t in topo if isinstance(t.op, tensor.Subtensor)]) == 1
+        #print topo[-1].op
+        assert isinstance(topo[-1].op, theano.compile.function_module.DeepCopyOp)
+
+        b_r = self.rng.permutation(range(-8,8))[:2]
+        e_r = self.rng.permutation(range(-8,8))[:2]
+        i_r = self.rng.permutation(range(-8,8))[:2]
+
+        s_r = self.rng.permutation([-7,-6,-5,-4,-3,-2,-1,1,2,3,4,5,6,7])[:2]
+
+        for x_s in self.x_shapes:
+            x_val = self.rng.uniform(size=x_s).astype(config.floatX)
+            for b_v in b_r:
+                for e_v in e_r:
+                    for s_v in s_r:
+                        for i_v in i_r:
+                            # The index could be out of bounds
+                            # In that case, an Exception should be raised,
+                            # otherwise, we let DebugMode check f
+                            try:
+                                x_val[b_v:e_v:s_v][i_v]
+                            except IndexError:
+                                self.assertRaises(IndexError,
+                                        f, x_val, b_v, e_v, s_v, i_v)
+                            else:
+                                # Executed if the "try" clause did not
+                                # raise an exception
+                                f(x_val, b_v, e_v, s_v, i_v)
 
 class Test_alloc_zero(unittest.TestCase):
     def setUp(self):