test for weird strides, small fixes

_test_elemwise.py

@@ -120,6 +120,16 @@ class _test_Broadcast(unittest.TestCase):
         f(xv, yv)
         assert (xv == yv).all()
 
+    def test_weird_strides(self):
+        x = modes.build(Tensor('float64', [0, 0, 0, 0, 0], name = 'x'))
+        y = modes.build(Tensor('float64', [0, 0, 0, 0, 0], name = 'y'))
+        e = Broadcast(Add, (x, y)).out
+        f = gof.CLinker(env([x, y], [e])).make_function(inplace = False)
+        xv = numpy.random.rand(2, 2, 2, 2, 2)
+        yv = numpy.random.rand(2, 2, 2, 2, 2).transpose(4, 0, 3, 1, 2)
+        zv = xv + yv
+        assert (f(xv, yv) == zv).all()
+
 
 class _test_CAReduce(unittest.TestCase):
 

elemwise.py

@@ -397,9 +397,6 @@ class CAReduce(Op):
         if dimensions_to_reduce is None:
             dimensions_to_reduce = range(len(inputs[0].broadcastable))
 
-        self.nin = 1
-        self.nout = 1
-
         self.inputs = inputs
         self.outputs = [Tensor(dtype = inputs[0].dtype,
                                broadcastable = [x for i, x in enumerate(inputs[0].broadcastable) if i not in dimensions_to_reduce])]

tensor.py

@@ -153,7 +153,7 @@ class _Op(BaseTensorOp):
         return self.c_impl(self.inputs, self.outputs) % sub
 
     def c_impl(self, inputs, outputs):
-        raise AbstractFunctionError()
+        raise AbstractFunctionError("No c_impl for %s" % self.__class__.__name__)
 
 class _Unary:
     nin = 1