up

Author: metascroy

exir/backend/test/test_backends.py

@@ -1446,6 +1446,85 @@ def inputs(self):
                 torch.allclose(model_outputs[0], ref_output, atol=1e-03, rtol=1e-03)
             )
 
+    def test_arrange_graph_outputs_reorders_mutations_before_user_outputs(self):
+        """
+        Directly test that arrange_graph_outputs correctly reorders a
+        submodule's output tuple so that BUFFER_MUTATION outputs come before
+        USER_OUTPUT outputs, and that getitem indices in the parent graph are
+        remapped accordingly.
+        """
+        from executorch.exir.lowered_backend_module import arrange_graph_outputs
+        from torch.export.exported_program import OutputKind, OutputSpec, TensorArgument
+
+        # Build a submodule graph with 3 outputs in order:
+        #   [user_out_0, buffer_mut_1, user_out_2]
+        # The expected reordering is:
+        #   [buffer_mut_1, user_out_0, user_out_2]
+        sub_graph = torch.fx.Graph()
+        x = sub_graph.placeholder("x")
+        buf = sub_graph.placeholder("buf")
+        add_node = sub_graph.call_function(torch.ops.aten.add.Tensor, (x, x))
+        mul_node = sub_graph.call_function(torch.ops.aten.mul.Tensor, (buf, x))
+        sub_node = sub_graph.call_function(torch.ops.aten.sub.Tensor, (x, x))
+        # Output order: user, mutation, user
+        sub_graph.output((add_node, mul_node, sub_node))
+        sub_gm = torch.fx.GraphModule({}, sub_graph)
+
+        output_specs = [
+            OutputSpec(
+                kind=OutputKind.USER_OUTPUT,
+                arg=TensorArgument(name="add"),
+                target=None,
+            ),
+            OutputSpec(
+                kind=OutputKind.BUFFER_MUTATION,
+                arg=TensorArgument(name="mul"),
+                target="buf",
+            ),
+            OutputSpec(
+                kind=OutputKind.USER_OUTPUT,
+                arg=TensorArgument(name="sub"),
+                target=None,
+            ),
+        ]
+
+        # Build a parent graph with a call_module node and getitem users
+        parent_graph = torch.fx.Graph()
+        px = parent_graph.placeholder("x")
+        call_mod = parent_graph.call_module("sub_mod", (px,))
+        gi0 = parent_graph.call_function(operator.getitem, (call_mod, 0))
+        gi1 = parent_graph.call_function(operator.getitem, (call_mod, 1))
+        gi2 = parent_graph.call_function(operator.getitem, (call_mod, 2))
+        parent_graph.output((gi0, gi1, gi2))
+
+        # Run arrange_graph_outputs
+        arrange_graph_outputs(sub_gm, output_specs, call_mod)
+
+        # Verify output_specs are reordered: mutation first
+        self.assertEqual(output_specs[0].kind, OutputKind.BUFFER_MUTATION)
+        self.assertEqual(output_specs[1].kind, OutputKind.USER_OUTPUT)
+        self.assertEqual(output_specs[2].kind, OutputKind.USER_OUTPUT)
+        self.assertEqual(output_specs[0].target, "buf")
+
+        # Verify the submodule graph output tuple is reordered
+        output_node = None
+        for node in sub_gm.graph.nodes:
+            if node.op == "output":
+                output_node = node
+                break
+        reordered = list(output_node.args[0])
+        self.assertIs(reordered[0], mul_node)  # buffer mutation first
+        self.assertIs(reordered[1], add_node)  # then user outputs
+        self.assertIs(reordered[2], sub_node)
+
+        # Verify getitem indices were remapped:
+        #   old 0 (user) -> new 1
+        #   old 1 (mutation) -> new 0
+        #   old 2 (user) -> new 2 (unchanged)
+        self.assertEqual(gi0.args[1], 1)
+        self.assertEqual(gi1.args[1], 0)
+        self.assertEqual(gi2.args[1], 2)
+
     def test_prohibited_nested_backends(self):
         class MyBackend(BackendDetails):
             @staticmethod

exir/lowered_backend_module.py

@@ -449,6 +449,97 @@ def arrange_graph_placeholders(
     return gm
 
 
+def arrange_graph_outputs(
+    gm: torch.fx.GraphModule,
+    output_specs: List[OutputSpec],
+    call_module_node: torch.fx.Node,
+) -> torch.fx.GraphModule:
+    """
+    Reorders the output tuple of the graph so that buffer mutation outputs come
+    before user outputs, matching the ordering that ExportedProgram's verifier
+    expects: [buffer_mutations..., user_outputs...].
+
+    The partitioner may produce a submodule whose output tuple has buffer
+    mutations and user outputs interleaved in arbitrary order.  The verifier
+    determines which outputs are mutations by position (first N outputs where
+    N = number of mutation specs), so a misordered tuple causes a
+    SpecViolationError.
+
+    This function builds a permutation from the output_specs (which
+    _get_new_signature already classified correctly) and rewrites the graph's
+    output node to match.  It also remaps getitem indices on the parent
+    graph's call_module_node so the parent continues to extract the correct
+    outputs.
+
+    Args:
+        gm: The graph module whose output ordering may need adjustment.
+        output_specs: The output specs built by _get_new_signature, with
+            correct kind annotations but potentially mismatched ordering
+            relative to the graph's output tuple.
+        call_module_node: The call_module node in the parent graph whose
+            getitem users need index remapping.
+
+    Returns:
+        The graph module with reordered outputs (modified in-place).
+    """
+    # Find the output node
+    output_node = None
+    for node in gm.graph.nodes:
+        if node.op == "output":
+            output_node = node
+            break
+
+    if output_node is None or not output_node.args[0]:
+        return gm
+
+    old_outputs = list(output_node.args[0])
+
+    if len(old_outputs) != len(output_specs):
+        raise RuntimeError(
+            f"Mismatch between graph outputs ({len(old_outputs)}) and "
+            f"output_specs ({len(output_specs)}). This indicates a bug in "
+            "_get_new_signature."
+        )
+
+    # Separate indices by kind: mutations first, then user outputs
+    mutation_indices = []
+    user_output_indices = []
+    for i, spec in enumerate(output_specs):
+        if spec.kind in (OutputKind.BUFFER_MUTATION, OutputKind.USER_INPUT_MUTATION):
+            mutation_indices.append(i)
+        else:
+            user_output_indices.append(i)
+
+    new_order = mutation_indices + user_output_indices
+
+    # Check if already in correct order
+    if new_order == list(range(len(old_outputs))):
+        return gm
+
+    # Build reverse mapping: old_index -> new_index
+    old_to_new = {old_idx: new_idx for new_idx, old_idx in enumerate(new_order)}
+
+    # Reorder the output tuple in the submodule graph
+    new_outputs = [old_outputs[i] for i in new_order]
+    output_node.args = (tuple(new_outputs),)
+
+    # Reorder the output_specs to match (in-place)
+    reordered_specs = [output_specs[i] for i in new_order]
+    output_specs.clear()
+    output_specs.extend(reordered_specs)
+
+    # Remap getitem indices in the parent graph
+    for user in list(call_module_node.users.keys()):
+        if user.op == "call_function" and user.target == operator.getitem:
+            old_idx = user.args[1]
+            if isinstance(old_idx, int) and old_idx in old_to_new:
+                user.args = (user.args[0], old_to_new[old_idx])
+
+    gm.graph.lint()
+
+    return gm
+
+
 # TODO Don't regenerate new signature manually.
 def _get_new_signature(  # noqa: C901
     original_program: ExportedProgram,
@@ -706,8 +797,6 @@ def create_exported_program_from_submodule(
     # Arrange the submodule's placeholders in order
     submodule = arrange_graph_placeholders(submodule, owning_program, tag)
 
-    # TODO: we probably need to arrange the outputs wrt buffer mutations.
-
     # Get updated graph signature
     (
         subgraph_signature,
@@ -719,6 +808,11 @@ def create_exported_program_from_submodule(
         owning_program, submodule, call_module_node, tag, is_submodule
     )
 
+    # Reorder outputs: buffer mutations first, then user outputs.
+    # The verifier expects this ordering but _get_new_signature produces
+    # output_specs in graph order which may interleave the two kinds.
+    arrange_graph_outputs(submodule, subgraph_signature.output_specs, call_module_node)
+
     in_spec = pytree.tree_flatten((tuple(subgraph_signature.user_inputs), {}))[1]
     out_spec = pytree.tree_flatten(subgraph_signature.user_outputs)[1]