fix in elemwise_cgen

theano/tensor/elemwise.py

@@ -690,6 +690,9 @@ class CAReduce(Op):
         return input_dtype
 
     def make_node(self, input):
+        for axis in self.axis:
+            if axis >= input.type.ndim:
+                raise TypeError('Not enough dimensions on %s to reduce on axis %s' % (input, axis))
         input = as_tensor_variable(input)
         axis = self.axis
         if axis is None:

theano/tensor/elemwise_cgen.py

@@ -29,7 +29,7 @@ def make_checks(loop_orders, dtypes, sub):
         var = "%%(lv%i)s" % i
         nonx = [x for x in loop_order if x != 'x']
         if nonx:
-            min_nd = max(nonx)
+            min_nd = max(nonx) + 1
             init += """
             if (%(var)s->nd < %(min_nd)s) {
                 PyErr_SetString(PyExc_ValueError, "Not enough dimensions on input.");

theano/tensor/opt.py

@@ -496,13 +496,8 @@ class Canonizer(gof.LocalOptimizer):
         denum = []
         parent = input.owner
 
-
-        # We get the (num, denum) pairs for each input (input2) *to* input that has the same
-        # type as this one.
-        pairs = [self.get_num_denum(input2)
-                if (getattr(input2.type, 'dtype', None) == input.type.dtype) 
-                else ([input2], [])
-                for input2 in parent.inputs ]
+        # We get the (num, denum) pairs for each input
+        pairs = [self.get_num_denum(input2) if input2.type.dtype == input.type.dtype else ([input2], []) for input2 in parent.inputs]
 
         if parent.op == self.main:
             # If we have main(x, y), numx, denumx, numy and denumy