Add a dedicated type for address properties

There are a few properties which are sized based on "#address-cells" and
"#size-cells". "reg" is of course the most common, but there's a growing
number in /chosen. As these properties need special parsing to decode,
give them a dedicated type.

Signed-off-by: Rob Herring <robh@kernel.org>

dtschema/dtb.py

@@ -28,7 +28,8 @@
     'uint32': u32,
     'int64': s64,
     'uint64': u64,
-    'phandle': u32
+    'phandle': u32,
+    'address': u32
 }
 
 
@@ -451,15 +452,15 @@ def fixup_interrupts(dt, icells):
                     i += cells
 
 
-def fixup_addresses(dt, ac, sc):
+def fixup_addresses(validator, dt, ac, sc):
     for k, v in dt.items():
         if isinstance(v, dict):
             if '#address-cells' in dt:
                 ac = _get_cells_size(dt,'#address-cells')
             if '#size-cells' in dt:
                 sc = _get_cells_size(dt, '#size-cells')
-            fixup_addresses(v, ac, sc)
-        elif k == 'reg':
+            fixup_addresses(validator, v, ac, sc)
+        elif 'address' in validator.property_get_type(k):
             i = 0
             dt[k] = []
             val = v[0]
@@ -486,7 +487,7 @@ def fdt_unflatten(validator, dtb):
     #print(phandle_loc)
     fixup_gpios(dt)
     fixup_interrupts(dt, 1)
-    fixup_addresses(dt, 2, 1)
+    fixup_addresses(validator, dt, 2, 1)
     fixup_phandles(validator, dt)
 
 #    pprint.pprint(dt, compact=True)

dtschema/schemas/reg.yaml

@@ -30,7 +30,7 @@ properties:
       - $ref: types.yaml#/definitions/uint32-matrix
 
   reg:
-    $ref: types.yaml#/definitions/uint32-matrix
+    $ref: types.yaml#/definitions/address
 
   reg-io-width:
     $ref: types.yaml#/definitions/uint32

dtschema/schemas/types.yaml

@@ -349,3 +349,9 @@ definitions:
               const: 0
       additionalItems:
         $ref: "#/definitions/cell"
+
+  address:
+    $ref: "#/definitions/uint32-matrix"
+    items:
+      minItems: 1
+      maxItems: 5 # At most 3 address cells and 2 size cells

dtschema/validator.py

@@ -33,7 +33,7 @@ def _merge_dim(dim1, dim2):
     return tuple(d)
 
 
-type_re = re.compile('(flag|u?int(8|16|32|64)(-(array|matrix))?|string(-array)?|phandle(-array)?)')
+type_re = re.compile('(address|flag|u?int(8|16|32|64)(-(array|matrix))?|string(-array)?|phandle(-array)?)')
 
 
 def _extract_prop_type(props, schema, propname, subschema, is_pattern):