Make the MaxAndArgmax op work with theano constant.

theano/tensor/basic.py

@@ -2183,6 +2183,11 @@ class MaxAndArgmax(Op):
 
     def make_node(self, x, axis=None):
         x = _as_tensor_variable(x)
+        if isinstance(axis, Variable):
+            if not isinstance(axis, Constant):
+                raise TypeError("MaxAndArgmax need a constant axis")
+            axis = [axis.data]
+
         if isinstance(axis, int):
             axis = [axis]
         elif isinstance(axis, (tuple, list)):
@@ -2192,6 +2197,7 @@ class MaxAndArgmax(Op):
                 assert axis == range(x.type.ndim), (
                     "MaxAndArgmax does not support multiple"
                     " axes. the max fct supports it.")
+
         # we make the axis all positive to make the infer_shape work
         # with negative axis
         if x.type.ndim > 0 and axis is not None:

theano/tensor/tests/test_basic.py

@@ -1790,7 +1790,8 @@ class T_max_and_argmax(unittest.TestCase):
         data = rand(2, 3)
         n = as_tensor_variable(data)
         for (axis, np_axis)  in [(-1, -1), (0, 0), (1, 1), (None, None),
-                                 ([0, 1], None), ([1, 0], None)]:
+                                 ([0, 1], None), ([1, 0], None),
+                                 (constant(0), 0)]:
             v, i = eval_outputs(max_and_argmax(n, axis))
             assert i.dtype == 'int64'
             self.assertTrue(numpy.all(v == numpy.max(data, np_axis)))