Don't generate too much warning (and also fix a failure in travis tests)

theano/tensor/opt.py

@@ -3487,21 +3487,6 @@ def local_reduce_join(node):
         if T.extract_constant(join.inputs[0]) != 0:
             return
 
-        if len(node.op.axis) != 1 or 0 not in node.op.axis:
-            if theano.config.warn.reduce_join:
-                _logger.warn((
-                    'Your current code is fine, but Theano versions '
-                    'prior to 0.7 (or this development version Sept 2014) '
-                    'might have given an incorrect result. '
-                    'To disable this warning, set the Theano flag '
-                    'warn.reduce_join to False.'))
-            return
-        try:
-            join_axis = get_scalar_constant_value(join.inputs[0])
-            if join_axis != node.op.axis[0]:
-                return
-        except NotScalarConstantError:
-            return
         if isinstance(node.op.scalar_op, (scalar.Maximum, scalar.Minimum)):
             #Support only 2 inputs for now
             if len(join.inputs) != 3:
@@ -3522,9 +3507,31 @@ def local_reduce_join(node):
                 return
             new_inp.append(inp.inputs[0])
         ret = Elemwise(node.op.scalar_op)(*new_inp)
-        if ret.dtype == node.outputs[0].dtype:
+
+        if ret.dtype != node.outputs[0].dtype:
+            # The reduction do something about the dtype.
+            return
+
+        # I put this warning late to don't add extra warning.
+        if len(node.op.axis) != 1 or 0 not in node.op.axis:
+            if theano.config.warn.reduce_join:
+                _logger.warn((
+                    'Your current code is fine, but Theano versions '
+                    'prior to 0.7 (or this development version Sept 2014) '
+                    'might have given an incorrect result. '
+                    'To disable this warning, set the Theano flag '
+                    'warn.reduce_join to False.'))
+            return
+
+        # We add the new check late to don't add extra warning.
+        try:
+            join_axis = get_scalar_constant_value(join.inputs[0])
+            if join_axis != node.op.axis[0]:
+                return
+        except NotScalarConstantError:
+            return
+
         return [ret]
-        #else the reduction do something about the dtype.
 
 
 @register_canonicalize