add

Author: xadupre

_unittests/ut_torch_onnx/test_sbs.py

@@ -432,13 +432,13 @@ def forward(self, x):
             ],
             sorted(df.columns),
         )
-        self.assertEqual(len(results), 12)
+        self.assertEqual(len(results), 8)
         self.assertEqual(
+            [None, None, None, None, None, 0, 0, 0],
             [r.err_dev for r in results],
-            [None, None, None, None, None, None, None, None, None, 0, 0, 0],
         )
         self.assertEqual(
-            [-1.0, -1.0, -1.0, -1.0, -10.0, -10.0, -10.0, -10.0, -1.0, 0.0, 1.0, 2.0],
+            [-10.0, -10.0, -10.0, -10.0, -1.0, 0.0, 1.0, 2.0],
             df["onnx_id_node"].fillna(-10).tolist(),
         )
         self.clean_dump()
@@ -466,7 +466,7 @@ def forward(self, x):
                 use_tensor=True,
             ),
         )
-        self.assertEqual(len(results), 5)
+        self.assertEqual(len(results), 2)
 
 
 if __name__ == "__main__":

onnx_diagnostic/_command_lines_parser.py

@@ -1250,6 +1250,10 @@ def _size(name):
         import transformers.modeling_outputs  # noqa: F401
     print(f"-- load ep {args.ep!r}")
     begin = time.perf_counter()
+    # We need to load the plugs.
+    from .torch_export_patches.patches.patch_transformers import PLUGS_Qwen25
+
+    assert len(PLUGS_Qwen25) == 1, "Missing PLUGS for Qwen2.5"
     ep = torch.export.load(args.ep)
     print(f"-- done in {time.perf_counter() - begin:1.1f}s")
 

onnx_diagnostic/torch_onnx/sbs.py

@@ -498,7 +498,7 @@ def _loop_cmp(
     torch_results: Dict[str, Any] = {}
     last_position = 0
     torch_output_names = None
-    torch_input_names = []
+    torch_input_names: List[str] = []
     name_to_ep_node = {}
     torch_names_to_onnx_names = {}
     for i, node in enumerate(ep_graph_nodes):