dupates

Author: xadupre

_unittests/ut_export/test_shape_helper.py

@@ -25,6 +25,7 @@ def test_all_dynamic_shape_from_cache(self):
         ds = all_dynamic_shape_from_inputs(cache)
         self.assertEqual([[{0: "d_0_0", 1: "d_0_1"}], [{0: "d_1_0", 1: "d_1_1"}]], ds)
 
+    @requires_transformers("4.52")
     @requires_torch("2.7.99")
     def test_all_dynamic_shape_all_transformers_cache(self):
         caches = [

onnx_diagnostic/export/shape_helper.py

@@ -9,6 +9,7 @@ def all_dynamic_shape_from_inputs(inputs: Any, dim_prefix: Any = "d") -> Any:
     All dimensions are considered as dynamic.
     ``dim_prefix`` can be a string (the function uses it as a prefix),
     or ``torch.export.Dim.AUTO`` or ``torch.export.Dim.DYNAMIC``.
+    For caches, ``transformers>=4.52```is better.
 
     .. runpython::
         :showcode:

onnx_diagnostic/torch_models/validate.py

@@ -1124,7 +1124,7 @@ def _mk(key):
         )
         if runtime == "onnxruntime"
         else (
-            lambda model, providers, _cls_=TorchOnnxEvaluator: _cls_(
+            lambda model, providers, _cls_=TorchOnnxEvaluator: _cls_(  # type: ignore[misc]
                 model, providers=providers, verbose=max(verbose - 1, 0)
             )
         )