Make MaxAndArgmax work when axis==None

theano/tensor/basic.py

@@ -1879,13 +1879,17 @@ class MaxAndArgmax(Op):
         elif isinstance(axis,(tuple,list)):
             assert len(axis)==1,"MaxAndArgmax don't support multiple axis. the max fct support it."
         #we make the axis all positive to make the infer_shape work with negative axis
-        if x.type.ndim>0:
+        if x.type.ndim>0 and axis is not None:
             for id,a in enumerate(axis):
                 if not isinstance(a, TensorVariable) and a<0:
                     if -a>x.type.ndim:
                         raise ValueError('axis out of range')
                     axis[id]=x.type.ndim+a
-        axis = _as_tensor_variable(axis)
+        if axis is None:
+            axis = _as_tensor_variable(range(x.type.ndim))
+        else:
+            axis = _as_tensor_variable(axis)
+
         inputs = [x, axis]
         #TODO: figure things out if axis is a constant
         broadcastable = [False] * (x.type.ndim - 1)
@@ -1895,6 +1899,8 @@ class MaxAndArgmax(Op):
     def perform(self, node, inp, outs):
         x, axis = inp
         max, max_idx = outs
+        if len(axis) == 0 or python_all(axis == range(x.ndim)):
+            axis = None
         max[0] = numpy.asarray(numpy.max(x, axis))
         max_idx[0] = theano._asarray(numpy.argmax(x, axis), dtype='int32')