diff --git a/graph_net/torch/dim_gen_passes/non_batch_call_function_arange_pass.py b/graph_net/torch/dim_gen_passes/non_batch_call_function_arange_pass.py
index 9c55aa518..dfd81479b 100644
--- a/graph_net/torch/dim_gen_passes/non_batch_call_function_arange_pass.py
+++ b/graph_net/torch/dim_gen_passes/non_batch_call_function_arange_pass.py
@@ -69,6 +69,24 @@ def get_new_node_arg(i, arg, len_args):
 
             return size_node
 
+        # def create_new_node(node):
+        #     if not (self._node_need_rewrite(node) and last_node_axis is not None):
+        #         # Copy other nodes to the new graph
+        #         new_node = new_graph.node_copy(node, lambda x: val_map[x])
+        #         try_reset_last_node_axis(node=node, new_node=new_node)
+        #         return new_node
+
+        #     new_node_args = tuple(
+        #         get_new_node_arg(i, arg, len(node.args))
+        #         for i, arg in enumerate(node.args)
+        #     )
+
+        #     new_node = new_graph.call_function(
+        #         self.node_target(), args=new_node_args, kwargs=node.kwargs
+        #     )
+
+        #     return new_node
+
         def create_new_node(node):
             if not (self._node_need_rewrite(node) and last_node_axis is not None):
                 # Copy other nodes to the new graph
@@ -85,8 +103,22 @@ def create_new_node(node):
                 self.node_target(), args=new_node_args, kwargs=node.kwargs
             )
 
+            static_limit = _get_static_limit(node)
+            if static_limit != float("inf"):
+                max_val = int(static_limit - 1)
+                new_node = new_graph.call_function(
+                    torch.clamp, args=(new_node, 0, max_val)
+                )
             return new_node
 
+        def _get_static_limit(node):
+            static_limit = float("inf")
+            for user in node.users:
+                if user.op == "call_function" and ("embedding" in str(user.target)):
+                    indexed_dim_size = user.args[1].meta["tensor_meta"].shape[0]
+                    static_limit = min(static_limit, indexed_dim_size)
+            return static_limit
+
         for node in traced_module.graph.nodes:
             val_map[node] = create_new_node(node)