Add test demonstrating problem with current version of subtensor(alloc) opt.

theano/gof/tests/test_compute_test_value.py

@@ -276,3 +276,29 @@ class TestComputeTestValue(unittest.TestCase):
 
         finally:
             theano.config.compute_test_value = orig_compute_test_value
+
+    def test_no_perform(self):
+        pass
+
+    def test_no_c_code(self):
+        orig_compute_test_value = theano.config.compute_test_value
+        try:
+            theano.config.compute_test_value = 'raise'
+            # int_div has no C code for the moment
+            # If that changes, use another op with no C code here
+            i = T.iscalar('i')
+            j = T.iscalar('j')
+            i.tag.test_value = 3
+            j.tag.test_value = 2
+
+            o = i // j
+
+            # Check that the c_code function is not implemented
+            self.assertRaises(NotImplementedError, o.owner.op.c_code,
+                    o.owner, 'o', ('x', 'y'), 'z', {'fail': ''})
+
+            assert hasattr(o.tag, 'test_value')
+            assert o.tag.test_value == 1
+
+        finally:
+            theano.config.compute_test_value = orig_compute_test_value

theano/tensor/tests/test_opt.py

@@ -1581,8 +1581,9 @@ class test_local_subtensor_merge(unittest.TestCase):
                                 for s2 in s2r:
                                     f(x_val, b1,e1,s1,b2,e2,s2)
 
+class Test_alloc_zero(unittest.TestCase):
 
-def test_setsubtensor_allocs0():
+    def test_setsubtensor_allocs0(self):
         x = tensor.matrix()
         y = tensor.matrix()
         x0 = tensor.zeros_like(x)
@@ -1592,7 +1593,7 @@ def test_setsubtensor_allocs0():
         assert numpy.all( [ not isinstance(x.op, tensor.IncSubtensor) for x in
                            f.maker.env.toposort() ])
 
-def test_setsubtensor_allocs1():
+    def test_setsubtensor_allocs1(self):
         y = tensor.matrix()
         x0 = tensor.constant(numpy.asarray(numpy.zeros_like((4,4)), dtype=config.floatX))
         y0 = tensor.zeros_like(y)
@@ -1601,7 +1602,7 @@ def test_setsubtensor_allocs1():
         assert numpy.all( [ not isinstance(x.op, tensor.IncSubtensor) for x in
                            f.maker.env.toposort() ])
 
-def test_setsubtensor_allocs2():
+    def test_setsubtensor_allocs2(self):
         x = tensor.matrix()
         y0 = tensor.constant(numpy.asarray(numpy.zeros_like((4,4)), dtype=config.floatX))
         x0 = tensor.zeros_like(x)
@@ -1610,7 +1611,7 @@ def test_setsubtensor_allocs2():
         assert numpy.all( [ not isinstance(x.op, tensor.IncSubtensor) for x in
                            f.maker.env.toposort() ])
 
-def test_incsubtensor_allocs0():
+    def test_incsubtensor_allocs0(self):
         x = tensor.matrix()
         y = tensor.matrix()
         y0 = tensor.zeros_like(y)
@@ -1619,7 +1620,7 @@ def test_incsubtensor_allocs0():
         assert numpy.all( [ not isinstance(x.op, tensor.IncSubtensor) for x in
                            f.maker.env.toposort() ])
 
-def test_incsubtensor_allocs1():
+    def test_incsubtensor_allocs1(self):
         x = tensor.matrix()
         y0 = tensor.constant(numpy.asarray(numpy.zeros_like((4,4)), dtype=config.floatX))
         z  = tensor.inc_subtensor(x[:4], y0)
@@ -1628,7 +1629,7 @@ def test_incsubtensor_allocs1():
                            f.maker.env.toposort() ])
 
 
-def test_dot_allocs_0():
+    def test_dot_allocs_0(self):
         v1 = tensor.vector('v1')
         v2 = tensor.vector('v2')
         m1 = tensor.matrix('m1')
@@ -1652,6 +1653,27 @@ def test_dot_allocs_0():
                                       f.maker.env.toposort() ])
 
 
+def test_local_subtensor_alloc0():
+    x = tensor.matrix('x')
+    y = tensor.vector('y')
+
+    # The rows of yx are copies of x
+    yx = tensor.alloc(y, x.shape[0], x.shape[1])
+
+    # Slice of each row
+    z_mat = yx[:,3:]
+    assert z_mat.ndim == 2
+
+    # Only one column
+    z_vec = yx[:,3]
+    assert z_vec.ndim == 1
+
+    f = theano.function([x, y], z_mat)
+    g = theano.function([x, y], z_vec)
+
+    # DebugMode should detect if something goes wrong.
+    f(numpy.zeros((3,5)), numpy.arange(5))
+    g(numpy.zeros((3,5)), numpy.arange(5))
 
 
 def test_local_fill_useless():