fix issues

Author: xadupre

onnx_diagnostic/ext_test_case.py

@@ -910,7 +910,7 @@ def assertEqualAny(
         elif hasattr(expected, "shape"):
             self.assertEqual(type(expected), type(value), msg=msg)
             self.assertEqualArray(expected, value, msg=msg, atol=atol, rtol=rtol)
-        elif expected.__class__.__name__ in ("Dim", "_Dim"):
+        elif expected.__class__.__name__ in ("Dim", "_Dim", "_DimHintType"):
             self.assertEqual(type(expected), type(value), msg=msg)
             self.assertEqual(expected.__name__, value.__name__, msg=msg)
         else:

onnx_diagnostic/helpers/helper.py

@@ -409,7 +409,7 @@ def string_type(
             f"dtype={obj.dtype}, shape={obj.shape})"
         )
 
-    if obj.__class__.__name__ == "_DimHint":
+    if obj.__class__.__name__ in ("_DimHint", "_DimHintType"):
         return str(obj)
 
     if isinstance(obj, torch.nn.Module):

onnx_diagnostic/torch_models/test_helper.py

@@ -226,6 +226,7 @@ def validate_model(
     """
     assert not trained, f"trained={trained} not supported yet"
     summary = version_summary()
+    folder_name = None
     if dump_folder:
         folder_name = _make_folder_name(
             model_id, exporter, optimization, dtype=dtype, device=device
@@ -237,12 +238,12 @@ def validate_model(
         summary["dump_folder_name"] = folder_name
         if verbose:
             print(f"[validate_model] dump into {folder_name!r}")
-    else:
-        folder_name = None
+
     if verbose:
         print(f"[validate_model] validate model id {model_id!r}")
         print("[validate_model] get dummy inputs...")
         summary["model_id"] = model_id
+
     begin = time.perf_counter()
     if quiet:
         try:
@@ -344,7 +345,10 @@ def validate_model(
         )
         if patch:
             if verbose:
-                print("[validate_model] applies patches before exporting")
+                print(
+                    f"[validate_model] applies patches before exporting "
+                    f"stop_if_static={stop_if_static}"
+                )
             with bypass_export_some_errors(  # type: ignore
                 patch_transformers=True,
                 stop_if_static=stop_if_static,
@@ -527,6 +531,7 @@ def call_torch_export_export(
         "export-strict",
         "export-nostrict",
     }, f"Unexpected value for exporter={exporter!r}"
+    assert not optimization, f"No optimization is implemented for exporter={exporter!r}"
     assert "model" in data, f"model is missing from data: {sorted(data)}"
     assert "inputs_export" in data, f"inputs_export is missing from data: {sorted(data)}"
     summary: Dict[str, Union[str, int, float]] = {}