Fixed architecture-dependent bug, due to Numpy flaw

theano/tensor/basic.py

@@ -1300,7 +1300,9 @@ class MaxAndArgmax(Op):
         return Apply(self, inputs, outputs)
     def perform(self, node, (x, axis), (max, max_idx)):
         max[0] = numpy.asarray(numpy.max(x, axis))
-        max_idx[0] = numpy.asarray(numpy.argmax(x, axis), dtype='int32')
+        # Note: using 'view' is important until Numpy's ticket 870 is resolved.
+        max_idx[0] = numpy.asarray(numpy.argmax(x, axis), dtype='int32').view(
+            numpy.int32)
     def grad(self, (x, axis), (g_max, g_max_idx)):
         # @warning: This only works if axis is 0, else the max is
         # broadcasted wrong in the call to eq.