fix: resolve emitter getitem, alloc spec, and view_copy spec errors

- _emitter.py: handle single _AbstractValue from delegate in getitem
  (fixes '_AbstractValue' object is not subscriptable)
- memory_planning.py: skip memory.alloc nodes in ensure_graph_node_specs
  (fixes 'Out-var allocation node already has a spec assigned')
- replace_view_copy_with_view_pass.py: derive base_spec from meta["val"]
  when meta["spec"] is missing (fixes KeyError: 'spec' for xnnpack tests)

Fixes test_mobilenet_v3, test_resnet18, test_mobilenet_v3_xnnpack,
test_resnet18_xnnpack, test_to_out_variant_multiple_out,
test_emit_lowered_backend_module, test_emit_nested_lowered_backend_module.

Co-authored-by: Cursor <cursoragent@cursor.com>

Author: NefAI

exir/emit/_emitter.py

@@ -1747,9 +1747,12 @@ def call_function(  # pyre-fixme[14]
         # Default to none and let delegates and ops override.
         if target == operator.getitem:
             assert len(args) == 2
-            head = typing.cast(Mapping[int, _EmitterValue], args[0])
+            head = args[0]
             index = typing.cast(int, args[1])
-            return head[index]
+            # Delegate may return a single _AbstractValue (single output) or tuple/list.
+            if index == 0 and isinstance(head, _AbstractValue):
+                return head
+            return typing.cast(Mapping[int, _EmitterValue], head)[index]
 
         elif target == memory.alloc:
             assert len(args) == 1

exir/memory_planning.py

@@ -759,12 +759,15 @@ def ensure_graph_node_specs(graph_module: torch.fx.GraphModule) -> None:
     """
     Set meta["spec"] from meta["val"] for nodes that are missing spec (e.g. output
     or out-var nodes in delegated graphs that were built after SpecPropPass).
+    Skip memory.alloc nodes; their spec is set by MemoryPlanningPass._set_alloc_node_spec.
     """
     for node in graph_module.graph.nodes:
         if "spec" in node.meta:
             continue
         if "val" not in node.meta:
             continue
+        if node.op == "call_function" and node.target is memory.alloc:
+            continue
         val = node.meta["val"]
 
         def to_spec(x: Any) -> Any:

exir/passes/replace_view_copy_with_view_pass.py

@@ -282,12 +282,23 @@ def call(self, graph_module: torch.fx.GraphModule) -> PassResult:
 
                     # Create spec for the node.
                     # _ViewSpec gives a view into its base spec for non-size
-                    # related information.
+                    # related information. Use base.meta["spec"] if present,
+                    # else derive from base.meta["val"] (e.g. after delegation).
+                    base_spec = base.meta.get("spec")
+                    if base_spec is None and "val" in base.meta:
+                        val = base.meta["val"]
+                        if isinstance(val, torch.Tensor):
+                            base_spec = TensorSpec.from_tensor(val)
+                    if base_spec is None:
+                        raise KeyError(
+                            f"replace_view_copy_with_view: base node {base} has no "
+                            "'spec' and no tensor 'val' to derive one"
+                        )
 
                     # the shape is not the same as node.args[1] because node.args[1]
                     # can have an inferred sizes (-1).
                     shape = node.meta["val"].shape
-                    node.meta["spec"] = _ViewSpec(base.meta["spec"], shape)
+                    node.meta["spec"] = _ViewSpec(base_spec, shape)
 
                     n_replaced += 1