Updated and fixed the MapDimShuffle tranformation. (#1531)

The reordering of the dimension was quite strange, it is now much more
cleaner. Furthermore, the `tile_sizes` parameter of the map range was
ignored, i.e. not changed. Furthermore, the parameters are now correclty
copied. Before it was just assigned, thus if later the parameter list of
the map was again changed this effect would propagate to _all_ maps that
where treated.

dace/transformation/dataflow/map_dim_shuffle.py

@@ -27,18 +27,19 @@ def expressions(cls):
         return [sdutil.node_path_graph(cls.map_entry)]
 
     def can_be_applied(self, graph, expr_index, sdfg, permissive=False):
+        map_entry: nodes.MapEntry = self.map_entry
+        if self.parameters is None:
+            return False
+        if len(self.parameters) != len(map_entry.map.params):
+            return False
+        if set(self.parameters) != set(map_entry.map.params):
+            return False
         return True
 
     def apply(self, graph: SDFGState, sdfg: SDFG):
-        map_entry = self.map_entry
-        if self.parameters is None:
-            return
-
-        if set(self.parameters) != set(map_entry.map.params):
-            return
+        map_entry: nodes.MapEntry = self.map_entry
+        new_map_order: list[int] = [map_entry.map.params.index(param) for param in self.parameters]
 
-        map_entry.range.ranges = [
-            r for list_param in self.parameters for map_param, r in zip(map_entry.map.params, map_entry.range.ranges)
-            if list_param == map_param
-        ]
-        map_entry.map.params = self.parameters
+        map_entry.range.ranges = [map_entry.range.ranges[new_pos] for new_pos in new_map_order]
+        map_entry.range.tile_sizes = [map_entry.range.tile_sizes[new_pos] for new_pos in new_map_order]
+        map_entry.map.params = [map_entry.map.params[new_pos] for new_pos in new_map_order]

tests/transformations/map_dim_shuffle_test.py

@@ -36,6 +36,9 @@ def test_map_dim_shuffle():
     sdfg(A=A, B=B)
     assert np.allclose(B, expected)
 
+    assert sdfg.apply_transformations_repeated(MapDimShuffle, options={"parameters": ["k", "i"]}) == 0
+    assert sdfg.apply_transformations_repeated(MapDimShuffle, options={"parameters": ["k", "i", "l"]}) == 0
+
 
 if __name__ == '__main__':
     test_map_dim_shuffle()