Preserve overridable initializer defaults in rewrite rules

onnxscript/rewriter/_ir_utils.py

@@ -52,6 +52,9 @@ def visit(node: ir.Node, depth):
 
 
 def get_const_value(value: ir.Value) -> ir.TensorProtocol | None:
+    """Return a runtime constant, excluding overridable graph-input defaults."""
+    if value.is_graph_input():
+        return None
     node = value.producer()
     if node is not None:
         optimizer.basic_constant_propagation([node])
@@ -61,11 +64,8 @@ def get_const_value(value: ir.Value) -> ir.TensorProtocol | None:
 def get_numpy_value(val: ir.Value | None) -> np.ndarray | None:
     """Convenience wrapper to get (optional) numpy value from an optional IR Value.
 
-    This is intended for use in optimizations/rewriting. Note that this does not
-    yet handle the distinction between inputs with default values (values that are
-    both graph inputs and graph initializers), which should not be treated as a
-    constant, and true constant values. The caller should make the distinction, as
-    a value does not contain enough information to determine this. (TODO)
+    This is intended for use in optimizations/rewriting. Graph inputs with
+    initializer defaults are not constants, since callers can override them.
     """
     if val is None:
         return None

onnxscript/rewriter/_matcher.py

@@ -15,6 +15,7 @@
 import onnx_ir as ir
 
 import onnxscript.rewriter._basics as _basics
+import onnxscript.rewriter._ir_utils as _ir_utils
 import onnxscript.rewriter._pattern_ir as _pattern_ir
 
 
@@ -81,7 +82,7 @@ def _match_constant(self, pattern_constant: _pattern_ir.Constant, value: ir.Valu
         if subgraph replacement happens. But subsequent DCE will remove the constant
         node if it is not used elsewhere.
         """
-        constant_value = value.const_value
+        constant_value = _ir_utils.get_const_value(value)
         if constant_value is None:
             return self.fail(
                 f"Value {value.name} is not a constant, expecting {pattern_constant.value}.",