Arm backend: Update output reorder workaround (#15981)

Updates _annotate_external_ids() to only assign ids to actual outputs in
current order instead of traversing all producers.

This makes the mapping more robust to structured (tuple/namedtuple)
outputs and avoids interference from lifted constants or shared
producers.


cc @freddan80 @per @zingo @oscarandersson8218 @digantdesai

Co-authored-by: Zingo Andersen <zingo.andersen@arm.com>

Author: mansnils

backends/arm/tosa/backend.py

@@ -17,9 +17,8 @@
 
 import logging
 import tempfile
-from collections import deque
 from itertools import count
-from typing import cast, Dict, final, List, Set
+from typing import cast, Dict, final, List
 
 import tosa_serializer as ts
 from executorch.backends.arm.common.arm_compile_spec import ArmCompileSpec
@@ -43,35 +42,36 @@
 
 
 def _annotate_external_ids(ep_graph: Graph) -> Dict[str, int]:
-    """Assign deterministic output IDs to nodes reachable from graph outputs.
+    """Assign deterministic output IDs to leaf outputs.
+
+    Flattens the output structure and assigns the external ID
+    based on the leaf position in the exported output tuple/list.
 
     Args:
         ep_graph (Graph): FX graph produced by export preprocessing.
 
     Returns:
-        dict[str, int]: Mapping from node name to external output index.
-
+        dict[str, int]: Mapping from *leaf output node name* to external output index.
     """
     node2external_id = {}
 
-    def bfs_mark(start_nodes: List[Node], idx: int, seen: Set[Node]):
-        """Walk producer graph from ``start_nodes`` and record external IDs."""
-        q = deque(start_nodes)
-        while q:
-            n = q.popleft()
-            if n in seen:
-                continue
-            seen.add(n)
-            node2external_id[n.name] = idx
-            # Walk backwards so we touch every producer
-            q.extend(n.all_input_nodes)
+    def _collect_leaves(arg, nodes):
+        # Collect only FX Nodes that are actual outputs
+        # (ignore ints/None/etc inside structured outputs).
+        if isinstance(arg, Node):
+            nodes.append(arg)
+        elif isinstance(arg, (list, tuple)):
+            for a in arg:
+                _collect_leaves(a, nodes)
 
     out = ep_graph.output_node()
-    # First argument of output node is tuple of outputs
-    output_list = cast(tuple, out.args[0])
-    seen: Set[Node] = set()
-    for idx, val in enumerate(output_list):
-        bfs_mark([val], idx, seen)
+    out_leaves: list[Node] = []
+    # First argument of output is the structured container (tuple/list) of outputs
+    _collect_leaves(out.args[0], out_leaves)
+
+    # Map each output leaf's name to its position
+    node2external_id = {leaf.name: idx for idx, leaf in enumerate(out_leaves)}
+
     return node2external_id