crash fix for the Mean Op (not used by default) with the axis was a scalar.

theano/tensor/basic.py

@@ -3207,6 +3207,7 @@ def prod(input, axis=None, dtype=None, keepdims=False):
 class Mean(elemwise.CAReduce):
     def __init__(self, axis=None):
         elemwise.CAReduce.__init__(self, scal.add, axis)
+        assert self.axis is None or len(self.axis) == 1
 
     def __str__(self):
         if self.axis is not None:
@@ -3221,7 +3222,7 @@ class Mean(elemwise.CAReduce):
     def perform(self, node, inp, out):
         input, = inp
         output, = out
-        output[0] = numpy.mean(input, axis=self.axis)
+        output[0] = numpy.mean(input, axis=self.axis[0])
 
     def c_code(self, node, name, inames, onames, sub):
         if self.axis is not None:

theano/tensor/tests/test_basic.py

@@ -6422,14 +6422,14 @@ class TestInferShape(utt.InferShapeTester):
         #
         # to be resolved as desired/appropriate
 
-        """
         adtens3_val = rand(3, 4, 5)
         aiscal_val = 2
-
+        self._compile_and_check([adtens3],
+                                [Mean(None)(adtens3)],
+                                [adtens3_val], Mean)
         self._compile_and_check([adtens3],
                                 [Mean(aiscal_val)(adtens3)],
                                 [adtens3_val], Mean)
-        """
 
         # IncSubtensor
         # Note: Is testing only for the 4-tensor below sufficient?