refactor

_unittests/ut_torch_models/test_validate_whole_models1.py

@@ -122,6 +122,7 @@ def test_g_validate_model_onnx_dynamo_os_ort(self):
     @hide_stdout()
     @ignore_warnings(FutureWarning)
     @requires_experimental()
+    @requires_transformers("4.52")  # empty_cache None does not work
     def test_i_validate_model_custom(self):
         mid = "arnir0/Tiny-LLM"
         summary, data = validate_model(
@@ -150,6 +151,7 @@ def test_i_validate_model_custom(self):
     @requires_torch("2.7")
     @hide_stdout()
     @ignore_warnings(FutureWarning)
+    @requires_transformers("4.52")  # empty_cache None does not work
     @requires_experimental()
     def test_j_validate_model_custom_torch(self):
         mid = "arnir0/Tiny-LLM"

onnx_diagnostic/helpers/helper.py

@@ -1016,6 +1016,8 @@ def max_diff(
 
     You may use :func:`string_diff` to display the discrepancies in one string.
     """
+    if verbose >= 10:
+        print(f"[max_diff] {type(expected)} ? {type(got)}")
     if expected is None and got is None:
         return dict(abs=0, rel=0, sum=0, n=0, dnan=0)
 
@@ -1061,8 +1063,8 @@ def max_diff(
     if expected.__class__.__name__ == "CausalLMOutputWithPast":
         if verbose >= 6:
             print(
-                f"[max_diff] CausalLMOutputWithPast: {string_type(expected)} "
-                f"? {string_type(got)}"
+                f"[max_diff] CausalLMOutputWithPast: {string_type(expected, with_shape=True)} "
+                f"? {string_type(got, with_shape=True)}"
             )
         if got.__class__.__name__ == "CausalLMOutputWithPast":
             return max_diff(