fixed tensor.basic.max and documented its reasoning

theano/tensor/basic.py

@@ -2674,16 +2674,22 @@ def max(x, axis=None, keepdims=False):
     :note: we return an error as numpy when we reduce a dim with a shape of 0
     """
 
-    if isinstance(axis, (list, tuple)) and len(axis) > 1:
+    # We have a choice of implementing this call with the
+    # CAReduce op or the MaxAndArgmax op.
+
+    # MaxAndArgmax supports grad and Rop, so we prefer to use that.
+    # CAReduce is faster, but optimizations will replace MaxAndArgmax[0]
+    # with CAReduce at compile time, so at this stage the important
+    # thing is supporting all user interface features, not speed.
+    # Some cases can be implemented only with CAReduce.
+
+    # We thus prefer to use MaxAndArgmax, if possible. It does not
+    # support all axis arguments, so we may need to fall back to CAReduce.
+
+    try:
+        out = max_and_argmax(x, axis)[0]
+    except:
         out = CAReduce(scal.maximum, axis)(x)
-    else:
-        try:
-            const = get_scalar_constant_value(axis)
-            assert const.dtype in discrete_dtypes
-            const = int(const)
-            out = CAReduce(scal.maximum, [const])(x)
-        except NotScalarConstantError:
-            out = max_and_argmax(x, axis)[0]
 
     if keepdims:
         out = makeKeepDims(x, out, axis)