diff --git a/src/server/package/src/model_explorer/pytorch_exported_program_adater_impl.py b/src/server/package/src/model_explorer/pytorch_exported_program_adater_impl.py
index 571851dc..67534f40 100644
--- a/src/server/package/src/model_explorer/pytorch_exported_program_adater_impl.py
+++ b/src/server/package/src/model_explorer/pytorch_exported_program_adater_impl.py
@@ -15,13 +15,16 @@
 
 import json
 import types
-from typing import Dict
 
 import torch
 import torch.fx
 from torch.fx import _pytree as fx_pytree
 
-from .graph_builder import Graph, GraphNode, IncomingEdge, KeyValue, MetadataItem
+from .graph_builder import Graph
+from .graph_builder import GraphNode
+from .graph_builder import IncomingEdge
+from .graph_builder import KeyValue
+from .graph_builder import MetadataItem
 from .types import ModelExplorerGraphs
 
 
@@ -32,7 +35,9 @@ def __init__(self, ep: torch.export.ExportedProgram):
     self.gm = self.ep.graph_module
     self.inputs_map = self.get_inputs_map()
 
-  def _graph_module_flat_inputs(self, ep: torch.export.ExportedProgram, args, kwargs):
+  def legacy_graph_module_flat_inputs(
+      self, ep: torch.export.ExportedProgram, args, kwargs
+  ):
     """Transform args, kwargs of __call__ to args for graph_module.
 
     self.graph_module takes stuff from state dict as inputs.
@@ -61,8 +66,7 @@ def _graph_module_flat_inputs(self, ep: torch.export.ExportedProgram, args, kwar
     param_buffer_keys = (
         ep.graph_signature.parameters + ep.graph_signature.buffers
     )
-    param_buffer_values = tuple(
-        ep.state_dict[key] for key in param_buffer_keys)
+    param_buffer_values = tuple(ep.state_dict[key] for key in param_buffer_keys)
 
     if hasattr(ep.graph_signature, 'lifted_tensor_constants'):
       ordered_tensor_constants = tuple(
@@ -83,9 +87,14 @@ def get_inputs_map(self):
       )
       return inputs_map
 
-    input_tensors = self._graph_module_flat_inputs(
-        self.ep, *self.ep.example_inputs
-    )
+    input_tensors = None
+    if hasattr(self.ep, '_graph_module_flat_inputs'):
+      input_tensors = self.ep._graph_module_flat_inputs(*self.ep.example_inputs)
+    else:
+      # Backward compatibility with torch 2.2.x
+      input_tensors = self.legacy_graph_module_flat_inputs(
+          self.ep, *self.ep.example_inputs
+      )
     for input_spec, tensor in zip(
         self.ep.graph_signature.input_specs, input_tensors
     ):
@@ -176,15 +185,14 @@ def add_outputs_metadata(self, fx_node: torch.fx.node.Node, node: GraphNode):
     if out_vals is None:
       return
 
-    if isinstance(out_vals, tuple):
+    if isinstance(out_vals, (tuple, list)):
       for idx, val in enumerate(out_vals):
         metadata = MetadataItem(id=str(idx), attrs=[])
         if val is None:
           continue
         dtype = str(val.dtype)
         shape = json.dumps(val.shape)
-        metadata.attrs.append(
-            KeyValue(key='tensor_shape', value=dtype + shape))
+        metadata.attrs.append(KeyValue(key='tensor_shape', value=dtype + shape))
         node.outputsMetadata.append(metadata)
     else:
       dtype = str(out_vals.dtype)