Implement shape merging in identity elimination pass

src/onnx_ir/passes/common/identity_elimination.py

@@ -15,6 +15,29 @@
 logger = logging.getLogger(__name__)
 
 
+def _merge_shapes(shape1: ir.Shape | None, shape2: ir.Shape | None) -> ir.Shape | None:
+    def merge_dims(dim1, dim2):
+        if dim1 == dim2:
+            return dim1
+        if not isinstance(dim1, ir.SymbolicDim):
+            return dim1  # Prefer int value over symbolic dim
+        if not isinstance(dim2, ir.SymbolicDim):
+            return dim2
+        if dim1.value is None:
+            return dim2
+        return dim1
+
+    if shape1 is None:
+        return shape2
+    if shape2 is None:
+        return shape1
+    if len(shape1) != len(shape2):
+        raise ValueError(
+            f"Shapes must have the same rank, got {len(shape1)} and {len(shape2)}."
+        )
+    return ir.Shape([merge_dims(dim1, dim2) for dim1, dim2 in zip(shape1, shape2)])
+
+
 class IdentityEliminationPass(ir.passes.InPlacePass):
     """Pass for eliminating redundant Identity nodes.
 
@@ -75,6 +98,11 @@ def _try_eliminate_identity_node(self, node: ir.Node) -> bool:
         if output_is_graph_output and input_is_graph_input:
             return False
 
+        # Copy over shape/type if the output has more complete information
+        input_value.shape = _merge_shapes(input_value.shape, output_value.shape)
+        if input_value.type is None:
+            input_value.type = output_value.type
+
         # Case 1 & 2 (merged): Eliminate the identity node
         # Replace all uses of output with input
         ir.convenience.replace_all_uses_with(output_value, input_value)