diff --git a/backends/vulkan/op_registry.py b/backends/vulkan/op_registry.py
index b7f8f3de955..a6cc59e26f0 100644
--- a/backends/vulkan/op_registry.py
+++ b/backends/vulkan/op_registry.py
@@ -397,14 +397,17 @@ def check_reduce_node(node: torch.fx.Node) -> bool:
                 # If we can't get memory layout information, we'll assume the dims aren't packed
                 pass
 
-        keepdim = node.args[2]
-        if isinstance(keepdim, bool) and not keepdim:
+        def try_find_keepdim_arg(node: torch.fx.Node) -> bool:
+            for arg in node.args:
+                if isinstance(arg, bool):
+                    return arg
+
+            # Assume false by default
             return False
 
-        if len(node.args) > 2:
-            keepdim = node.args[2]
-            if isinstance(keepdim, bool) and not keepdim:
-                return False
+        keepdim = try_find_keepdim_arg(node)
+        if isinstance(keepdim, bool) and not keepdim:
+            return False
 
         return True
 
diff --git a/backends/vulkan/partitioner/vulkan_partitioner.py b/backends/vulkan/partitioner/vulkan_partitioner.py
index 1b5ff0a44e4..04a1a500b64 100644
--- a/backends/vulkan/partitioner/vulkan_partitioner.py
+++ b/backends/vulkan/partitioner/vulkan_partitioner.py
@@ -204,7 +204,7 @@ def is_in_local_scalar_dense_chain(self, node: torch.fx.Node) -> Tuple[bool, boo
     def log_skip(self, node: torch.fx.Node, reason: str) -> None:
         if node.op == "call_function":
             logger.info(
-                f"[Vulkan Partitioner] Due to [{reason}], skipping {node.format_node()}"
+                f"[Vulkan Partitioner] Due to [{reason}], skipping {utils.node_io_str(node)}"
             )
 
     def is_node_supported(
diff --git a/backends/vulkan/utils.py b/backends/vulkan/utils.py
index 1765f0b5e1c..bc03860ed3f 100644
--- a/backends/vulkan/utils.py
+++ b/backends/vulkan/utils.py
@@ -1059,6 +1059,8 @@ def get_node_val_str(node: torch.fx.Node) -> str:
         assert isinstance(node.meta["val"], (list, tuple))
         return f"[{', '.join(get_tensor_val_str(t) for t in node.meta['val'])}]"
     else:
+        if "val" not in node.meta:
+            return str(node)
         return str(node.meta["val"])