diff --git a/CHANGELOGS.rst b/CHANGELOGS.rst
index b6d36fa3..26ab8af8 100644
--- a/CHANGELOGS.rst
+++ b/CHANGELOGS.rst
@@ -4,6 +4,9 @@ Change Logs
 0.4.3
 +++++
 
+* :pr:`75`: renames bypass_export_some_patches into torch_export_patches, keeps the old name
+* :pr:`74`: increases the list of class/architectures
+
 0.4.2
 +++++
 
diff --git a/README.rst b/README.rst
index cf240828..e89ded82 100644
--- a/README.rst
+++ b/README.rst
@@ -30,13 +30,13 @@ it helps exporting **pytorch models into ONNX**, mostly designed for LLMs using
 
 .. code-block:: python
 
-  with bypass_export_some_errors(patch_transformers=True) as f:
+  with torch_export_patches(patch_transformers=True) as f:
       ep = torch.export.export(model, args, kwargs=kwargs, dynamic_shapes=dynamic_shapes)
       # ...
 
 It also implements tools to investigate, validate exported models (ExportedProgramm, ONNXProgram, ...).
 See `documentation of onnx-diagnostic <https://sdpython.github.io/doc/onnx-diagnostic/dev/>`_ and
-`bypass_export_some_errors <https://sdpython.github.io/doc/onnx-diagnostic/dev/api/torch_export_patches/index.html#onnx_diagnostic.torch_export_patches.bypass_export_some_errors>`_.
+`torch_export_patches <https://sdpython.github.io/doc/onnx-diagnostic/dev/api/torch_export_patches/index.html#onnx_diagnostic.torch_export_patches.torch_export_patches>`_.
 
 Getting started
 +++++++++++++++
diff --git a/_doc/api/torch_export_patches/index.rst b/_doc/api/torch_export_patches/index.rst
index a536d9dc..b35e8c62 100644
--- a/_doc/api/torch_export_patches/index.rst
+++ b/_doc/api/torch_export_patches/index.rst
@@ -13,6 +13,6 @@ onnx_diagnostic.torch_export_patches
     :members:
     :no-undoc-members:
 
-.. autofunction:: onnx_diagnostic.torch_export_patches.bypass_export_some_errors
+.. autofunction:: onnx_diagnostic.torch_export_patches.torch_export_patches
 
 .. autofunction:: onnx_diagnostic.torch_export_patches.register_additional_serialization_functions
diff --git a/_doc/examples/plot_export_hub_codellama.py b/_doc/examples/plot_export_hub_codellama.py
index 533ad0dd..bf932afc 100644
--- a/_doc/examples/plot_export_hub_codellama.py
+++ b/_doc/examples/plot_export_hub_codellama.py
@@ -29,7 +29,7 @@
     get_pretrained_config,
     task_from_id,
 )
-from onnx_diagnostic.torch_export_patches import bypass_export_some_errors
+from onnx_diagnostic.torch_export_patches import torch_export_patches
 from onnx_diagnostic.torch_export_patches.patch_inputs import use_dyn_not_str
 
 model_id = "codellama/CodeLlama-7b-Python-hf"
@@ -90,9 +90,9 @@
 #
 # The model uses :class:`transformers.cache_utils.DynamicCache`.
 # It still requires patches to be exportable (control flow).
-# See :func:`onnx_diagnostic.torch_export_patches.bypass_export_some_errors`
+# See :func:`onnx_diagnostic.torch_export_patches.torch_export_patches`
 
-with bypass_export_some_errors(patch_transformers=True) as f:
+with torch_export_patches(patch_transformers=True) as f:
     ep = torch.export.export(
         model,
         (),
diff --git a/_doc/examples/plot_export_locate_issue.py b/_doc/examples/plot_export_locate_issue.py
index 3cfbdad1..3c1006aa 100644
--- a/_doc/examples/plot_export_locate_issue.py
+++ b/_doc/examples/plot_export_locate_issue.py
@@ -26,7 +26,7 @@
 import traceback
 import torch
 from onnx_diagnostic import doc
-from onnx_diagnostic.torch_export_patches import bypass_export_some_errors
+from onnx_diagnostic.torch_export_patches import torch_export_patches
 
 
 class ModelWithIssue(torch.nn.Module):
@@ -80,12 +80,12 @@ def forward(self, x: torch.Tensor, ys: list[torch.Tensor]):
 # Stop when a dynamic dimension turns static
 # ==========================================
 #
-# We use :func:`bypass_export_some_errors
-# <onnx_diagnostic.torch_export_patches.bypass_export_some_errors>`
+# We use :func:`torch_export_patches
+# <onnx_diagnostic.torch_export_patches.torch_export_patches>`
 # to replace torch implementation by a new one raising the exception
 # mentioned in previous section.
 
-with bypass_export_some_errors(stop_if_static=1, verbose=1):
+with torch_export_patches(stop_if_static=1, verbose=1):
     try:
         torch.export.export(model, inputs, dynamic_shapes=dyn_shapes)
     except (AssertionError, torch._dynamo.exc.TorchRuntimeError) as e:
diff --git a/_doc/examples/plot_export_tiny_llm_patched.py b/_doc/examples/plot_export_tiny_llm_patched.py
index f1576baf..60a20d15 100644
--- a/_doc/examples/plot_export_tiny_llm_patched.py
+++ b/_doc/examples/plot_export_tiny_llm_patched.py
@@ -69,7 +69,7 @@
 from onnx_diagnostic import doc
 from onnx_diagnostic.helpers.cache_helper import is_cache_dynamic_registered
 from onnx_diagnostic.helpers import string_type
-from onnx_diagnostic.torch_export_patches import bypass_export_some_errors
+from onnx_diagnostic.torch_export_patches import torch_export_patches
 from onnx_diagnostic.torch_models.llms import get_tiny_llm
 
 
@@ -101,10 +101,10 @@
 
 # %%
 # If they are not registered, function
-# func:`onnx_diagnostic.torch_export_patches.bypass_export_some_errors`
+# func:`onnx_diagnostic.torch_export_patches.torch_export_patches`
 # should take care of it. Then we export.
 
-with bypass_export_some_errors(patch_transformers=True, verbose=10) as modificator:
+with torch_export_patches(patch_transformers=True, verbose=10) as modificator:
     assert is_cache_dynamic_registered()  # it must be true here
     ep = torch.export.export(
         untrained_model,
@@ -126,7 +126,7 @@
 
 cloned_inputs = copy.deepcopy(inputs)
 
-with bypass_export_some_errors(patch_transformers=True, verbose=10) as modificator:
+with torch_export_patches(patch_transformers=True, verbose=10) as modificator:
     ep = torch.export.export(
         model,
         (),
diff --git a/_doc/examples/plot_export_tiny_phi2.py b/_doc/examples/plot_export_tiny_phi2.py
index ddcf1480..b91bdcb4 100644
--- a/_doc/examples/plot_export_tiny_phi2.py
+++ b/_doc/examples/plot_export_tiny_phi2.py
@@ -26,7 +26,7 @@
 from onnx_diagnostic.helpers import max_diff, string_diff, string_type
 from onnx_diagnostic.helpers.cache_helper import is_cache_dynamic_registered
 from onnx_diagnostic.helpers.rt_helper import make_feeds
-from onnx_diagnostic.torch_export_patches import bypass_export_some_errors
+from onnx_diagnostic.torch_export_patches import torch_export_patches
 from onnx_diagnostic.torch_export_patches.patch_inputs import use_dyn_not_str
 from onnx_diagnostic.torch_models.hghub import (
     get_untrained_model_with_inputs,
@@ -76,7 +76,7 @@
 # ++++++
 
 
-with bypass_export_some_errors(patch_transformers=True) as modificator:
+with torch_export_patches(patch_transformers=True) as modificator:
 
     # Unnecessary steps but useful in case of an error
     # We check the cache is registered.
@@ -110,7 +110,7 @@
 # applies :meth:`torch.export.ExportedProgram.run_decompositions`
 # may export local pieces of the model again.
 
-with bypass_export_some_errors(patch_transformers=True):
+with torch_export_patches(patch_transformers=True):
     epo = torch.onnx.export(
         ep, (), kwargs=copy.deepcopy(inputs), dynamic_shapes=dynamic_shapes, dynamo=True
     )
diff --git a/_doc/examples/plot_export_with_dynamic_cache.py b/_doc/examples/plot_export_with_dynamic_cache.py
index ed7d9ae7..5dfa9c3f 100644
--- a/_doc/examples/plot_export_with_dynamic_cache.py
+++ b/_doc/examples/plot_export_with_dynamic_cache.py
@@ -30,7 +30,7 @@
     make_dynamic_cache,
 )
 from onnx_diagnostic.export import ModelInputs
-from onnx_diagnostic.torch_export_patches import bypass_export_some_errors
+from onnx_diagnostic.torch_export_patches import torch_export_patches
 
 
 class Model(torch.nn.Module):
@@ -99,14 +99,14 @@ def forward(self, cache, z):
 # And finally the export.
 # The export is simple if ``transformers>=4.50``, otherwise,
 # transformers needs to be patched.
-# :func:`onnx_diagnostic.torch_export_patches.bypass_export_some_errors`
+# :func:`onnx_diagnostic.torch_export_patches.torch_export_patches`
 # registers functions to serialize ``DynamicCache``. This one is modified to make
 # the shape inference implemented in :epkg:`torch` happy.
 
 if has_transformers("4.50"):
     ep = torch.export.export(model, inputs[0], dynamic_shapes=ds[0], strict=False)
 else:
-    with bypass_export_some_errors(patch_transformers=True) as modificator:
+    with torch_export_patches(patch_transformers=True) as modificator:
         ep = torch.export.export(
             model, modificator(inputs[0]), dynamic_shapes=ds[0], strict=False
         )
diff --git a/_doc/index.rst b/_doc/index.rst
index 917df6b1..6d4792dd 100644
--- a/_doc/index.rst
+++ b/_doc/index.rst
@@ -24,12 +24,12 @@ Sources available at `github/onnx-diagnostic <https://github.com/sdpython/onnx-d
 
 .. code-block:: python
 
-  with bypass_export_some_errors(patch_transformers=True) as f:
+  with torch_export_patches(patch_transformers=True) as f:
       ep = torch.export.export(model, args, kwargs=kwargs, dynamic_shapes=dynamic_shapes)
       # ...
 
 It also implements tools to investigate, validate exported models (ExportedProgramm, ONNXProgram, ...).
-:func:`onnx_diagnostic.torch_export_patches.bypass_export_some_errors`.
+:func:`onnx_diagnostic.torch_export_patches.torch_export_patches`.
 
 .. toctree::
     :maxdepth: 1
diff --git a/_doc/recipes/plot_dynamic_shapes_python_int.py b/_doc/recipes/plot_dynamic_shapes_python_int.py
index 054f9a86..2685776f 100644
--- a/_doc/recipes/plot_dynamic_shapes_python_int.py
+++ b/_doc/recipes/plot_dynamic_shapes_python_int.py
@@ -14,7 +14,7 @@
 import math
 import torch
 from onnx_diagnostic import doc
-from onnx_diagnostic.torch_export_patches import bypass_export_some_errors
+from onnx_diagnostic.torch_export_patches import torch_export_patches
 
 
 class Model(torch.nn.Module):
@@ -73,12 +73,12 @@ def forward(self, x):
 # Find the error
 # ++++++++++++++
 #
-# Function :func:`onnx_diagnostic.torch_export_patches.bypass_export_some_errors`
+# Function :func:`onnx_diagnostic.torch_export_patches.torch_export_patches`
 # has a parameter ``stop_if_static`` which patches torch to raise exception
 # when something like that is happening.
 
 
-with bypass_export_some_errors(stop_if_static=True):
+with torch_export_patches(stop_if_static=True):
     ep = torch.export.export(model, (x,), dynamic_shapes=({0: DYN, 1: DYN},))
     print(ep)
 
diff --git a/_unittests/ut_export/test_dynamic_shapes.py b/_unittests/ut_export/test_dynamic_shapes.py
index a4a13de4..5782087b 100644
--- a/_unittests/ut_export/test_dynamic_shapes.py
+++ b/_unittests/ut_export/test_dynamic_shapes.py
@@ -5,7 +5,7 @@
 from onnx_diagnostic.helpers import string_type
 from onnx_diagnostic.helpers.cache_helper import make_dynamic_cache
 from onnx_diagnostic.export import ModelInputs, CoupleInputsDynamicShapes
-from onnx_diagnostic.torch_export_patches import bypass_export_some_errors
+from onnx_diagnostic.torch_export_patches import torch_export_patches
 
 
 class TestDynamicShapes(ExtTestCase):
@@ -571,7 +571,7 @@ def test_couple_input_ds_cache(self):
 
         kwargs = {"A": T3x4, "B": (T3x1, cache)}
         Cls = CoupleInputsDynamicShapes
-        with bypass_export_some_errors(patch_transformers=True):
+        with torch_export_patches(patch_transformers=True):
             self.assertEqual(
                 None,
                 Cls(
@@ -749,7 +749,7 @@ def test_couple_input_ds_change_dynamic_dimensions_dynamic_cache(self):
             {"A": make_dynamic_cache([(torch.ones((2, 2, 2, 2)), torch.ones((2, 2, 2, 2)))])},
             {"A": [[{0: "batch", 2: "last"}], [{0: "batch", 2: "last"}]]},
         )
-        with bypass_export_some_errors(patch_transformers=True):
+        with torch_export_patches(patch_transformers=True):
             new_inputs = inst.change_dynamic_dimensions()
         self.assertIsInstance(new_inputs["A"], transformers.cache_utils.DynamicCache)
         self.assertEqual((3, 2, 3, 2), new_inputs["A"].key_cache[0].shape)
diff --git a/_unittests/ut_export/test_serialization.py b/_unittests/ut_export/test_serialization.py
index e568a91f..2be71f2c 100644
--- a/_unittests/ut_export/test_serialization.py
+++ b/_unittests/ut_export/test_serialization.py
@@ -7,7 +7,7 @@
     flatten_unflatten_for_dynamic_shapes,
 )
 from onnx_diagnostic.export import ModelInputs
-from onnx_diagnostic.torch_export_patches import bypass_export_some_errors
+from onnx_diagnostic.torch_export_patches import torch_export_patches
 
 
 class TestSerialization(ExtTestCase):
@@ -49,7 +49,7 @@ def forward(self, cache):
                 return cache.key_cache[0]
 
         cache = self._get_cache()
-        with bypass_export_some_errors(patch_transformers=True):
+        with torch_export_patches(patch_transformers=True):
             flat_unflat = flatten_unflatten_for_dynamic_shapes(cache)
             s = string_type(flat_unflat, with_shape=True)
             self.assertEqual("#2[#2[T1s2x4x1x7,T1s2x4x1x7],#2[T1s2x4x1x7,T1s2x4x1x7]]", s)
diff --git a/_unittests/ut_helpers/test_cache_helper.py b/_unittests/ut_helpers/test_cache_helper.py
index 28db5f4c..0dfe45e3 100644
--- a/_unittests/ut_helpers/test_cache_helper.py
+++ b/_unittests/ut_helpers/test_cache_helper.py
@@ -14,7 +14,7 @@
 from onnx_diagnostic.torch_export_patches.patch_inputs import (
     convert_dynamic_axes_into_dynamic_shapes,
 )
-from onnx_diagnostic.torch_export_patches import bypass_export_some_errors
+from onnx_diagnostic.torch_export_patches import torch_export_patches
 
 
 class TestCacheHelpers(ExtTestCase):
@@ -67,14 +67,14 @@ def test_replace_by(self):
         )
         self.assertEqual(dynamic_shapes, nds)
 
-        with bypass_export_some_errors(patch_transformers=True):
+        with torch_export_patches(patch_transformers=True):
             cpl = CoupleInputsDynamicShapes(tuple(), kwargs, dynamic_shapes)
             res = cpl.replace_string_by()
         dsc = res["past_key_values"]
         self.assertEqual([[{0: batch, 2: DYN}], [{0: batch, 2: DYN}]], dsc)
 
     def test_unflatten_flatten_dynamic_cache(self):
-        with bypass_export_some_errors(patch_transformers=True):
+        with torch_export_patches(patch_transformers=True):
             c1 = make_dynamic_cache([(torch.rand((4, 4, 4)), torch.rand((4, 4, 4)))])
             self.assertIsInstance(c1, transformers.cache_utils.DynamicCache)
             unflat = flatten_unflatten_for_dynamic_shapes(c1)
@@ -87,7 +87,7 @@ def test_unflatten_flatten_dynamic_cache(self):
             )
 
     def test_unflatten_flatten_encoder_decoder_cache(self):
-        with bypass_export_some_errors(patch_transformers=True):
+        with torch_export_patches(patch_transformers=True):
             c2 = make_encoder_decoder_cache(
                 make_dynamic_cache(
                     [
diff --git a/_unittests/ut_helpers/test_ort_session_tinyllm.py b/_unittests/ut_helpers/test_ort_session_tinyllm.py
index febe05fe..28e475a5 100644
--- a/_unittests/ut_helpers/test_ort_session_tinyllm.py
+++ b/_unittests/ut_helpers/test_ort_session_tinyllm.py
@@ -12,7 +12,7 @@
     InferenceSessionForNumpy,
     InferenceSessionForTorch,
 )
-from onnx_diagnostic.torch_export_patches import bypass_export_some_errors
+from onnx_diagnostic.torch_export_patches import torch_export_patches
 from onnx_diagnostic.torch_models.llms import get_tiny_llm
 from onnx_diagnostic.reference import ExtendedReferenceEvaluator
 from onnx_diagnostic.helpers.onnx_helper import np_dtype_to_tensor_dtype
@@ -77,7 +77,7 @@ def test_check_allruntimes_on_tiny_llm(self):
         model, inputs, ds = data["model"], data["inputs"], data["dynamic_shapes"]
         expected = model(**copy.deepcopy(inputs))
 
-        with bypass_export_some_errors(patch_transformers=True):
+        with torch_export_patches(patch_transformers=True):
             ep = torch.onnx.export(
                 model, (), kwargs=copy.deepcopy(inputs), dynamic_shapes=ds, dynamo=True
             )
diff --git a/_unittests/ut_tasks/test_tasks.py b/_unittests/ut_tasks/test_tasks.py
index 2b1368db..95135667 100644
--- a/_unittests/ut_tasks/test_tasks.py
+++ b/_unittests/ut_tasks/test_tasks.py
@@ -2,7 +2,7 @@
 import torch
 from onnx_diagnostic.ext_test_case import ExtTestCase, hide_stdout, has_transformers
 from onnx_diagnostic.torch_models.hghub.model_inputs import get_untrained_model_with_inputs
-from onnx_diagnostic.torch_export_patches import bypass_export_some_errors
+from onnx_diagnostic.torch_export_patches import torch_export_patches
 from onnx_diagnostic.torch_export_patches.patch_inputs import use_dyn_not_str
 
 
@@ -17,7 +17,7 @@ def test_text2text_generation(self):
         raise unittest.SkipTest(f"not working for {mid!r}")
         model(**inputs)
         model(**data["inputs2"])
-        with bypass_export_some_errors(patch_transformers=True, verbose=10):
+        with torch_export_patches(patch_transformers=True, verbose=10):
             torch.export.export(
                 model, (), kwargs=inputs, dynamic_shapes=use_dyn_not_str(ds), strict=False
             )
@@ -31,7 +31,7 @@ def test_text_generation(self):
         model, inputs, ds = data["model"], data["inputs"], data["dynamic_shapes"]
         model(**inputs)
         model(**data["inputs2"])
-        with bypass_export_some_errors(patch_transformers=True, verbose=10):
+        with torch_export_patches(patch_transformers=True, verbose=10):
             torch.export.export(
                 model, (), kwargs=inputs, dynamic_shapes=use_dyn_not_str(ds), strict=False
             )
@@ -85,7 +85,7 @@ def test_automatic_speech_recognition(self):
             "#1[T1r3]",
             self.string_type(torch.utils._pytree.tree_flatten(inputs["encoder_outputs"])[0]),
         )
-        with bypass_export_some_errors(patch_transformers=True, verbose=10):
+        with torch_export_patches(patch_transformers=True, verbose=10):
             flat = torch.utils._pytree.tree_flatten(inputs["past_key_values"])[0]
             self.assertIsInstance(flat, list)
             self.assertIsInstance(flat[0], torch.Tensor)
@@ -96,7 +96,7 @@ def test_automatic_speech_recognition(self):
             torch.export.export(
                 model, (), kwargs=inputs, dynamic_shapes=use_dyn_not_str(ds), strict=False
             )
-        with bypass_export_some_errors(patch_transformers=True, verbose=10):
+        with torch_export_patches(patch_transformers=True, verbose=10):
             flat = torch.utils._pytree.tree_flatten(inputs["past_key_values"])[0]
             self.assertIsInstance(flat, list)
             self.assertIsInstance(flat[0], torch.Tensor)
@@ -117,7 +117,7 @@ def test_fill_mask(self):
         model, inputs, ds = data["model"], data["inputs"], data["dynamic_shapes"]
         model(**inputs)
         model(**data["inputs2"])
-        with bypass_export_some_errors(patch_transformers=True, verbose=10):
+        with torch_export_patches(patch_transformers=True, verbose=10):
             torch.export.export(
                 model, (), kwargs=inputs, dynamic_shapes=use_dyn_not_str(ds), strict=False
             )
@@ -131,7 +131,7 @@ def test_feature_extraction(self):
         model, inputs, ds = data["model"], data["inputs"], data["dynamic_shapes"]
         model(**inputs)
         model(**data["inputs2"])
-        with bypass_export_some_errors(patch_transformers=True, verbose=10):
+        with torch_export_patches(patch_transformers=True, verbose=10):
             torch.export.export(
                 model, (), kwargs=inputs, dynamic_shapes=use_dyn_not_str(ds), strict=False
             )
@@ -145,7 +145,7 @@ def test_text_classification(self):
         model, inputs, ds = data["model"], data["inputs"], data["dynamic_shapes"]
         model(**inputs)
         model(**data["inputs2"])
-        with bypass_export_some_errors(patch_transformers=True, verbose=10):
+        with torch_export_patches(patch_transformers=True, verbose=10):
             torch.export.export(
                 model, (), kwargs=inputs, dynamic_shapes=use_dyn_not_str(ds), strict=False
             )
@@ -159,7 +159,7 @@ def test_sentence_similary(self):
         model, inputs, ds = data["model"], data["inputs"], data["dynamic_shapes"]
         model(**inputs)
         model(**data["inputs2"])
-        with bypass_export_some_errors(patch_transformers=True, verbose=10):
+        with torch_export_patches(patch_transformers=True, verbose=10):
             torch.export.export(
                 model, (), kwargs=inputs, dynamic_shapes=use_dyn_not_str(ds), strict=False
             )
@@ -175,7 +175,7 @@ def test_falcon_mamba_dev(self):
         self.assertIn((data["size"], data["n_weights"]), [(138640384, 34660096)])
         if not has_transformers("4.55"):
             raise unittest.SkipTest("The model has control flow.")
-        with bypass_export_some_errors(patch_transformers=True, verbose=10, stop_if_static=1):
+        with torch_export_patches(patch_transformers=True, verbose=10, stop_if_static=1):
             torch.export.export(
                 model, (), kwargs=inputs, dynamic_shapes=use_dyn_not_str(ds), strict=False
             )
diff --git a/_unittests/ut_tasks/test_tasks_image_classification.py b/_unittests/ut_tasks/test_tasks_image_classification.py
index bfb87332..2b723ee5 100644
--- a/_unittests/ut_tasks/test_tasks_image_classification.py
+++ b/_unittests/ut_tasks/test_tasks_image_classification.py
@@ -2,7 +2,7 @@
 import torch
 from onnx_diagnostic.ext_test_case import ExtTestCase, hide_stdout, has_transformers
 from onnx_diagnostic.torch_models.hghub.model_inputs import get_untrained_model_with_inputs
-from onnx_diagnostic.torch_export_patches import bypass_export_some_errors
+from onnx_diagnostic.torch_export_patches import torch_export_patches
 from onnx_diagnostic.torch_export_patches.patch_inputs import use_dyn_not_str
 
 
@@ -18,7 +18,7 @@ def test_image_classification(self):
         model(**data["inputs2"])
         if not has_transformers("4.51.999"):
             raise unittest.SkipTest("Requires transformers>=4.52")
-        with bypass_export_some_errors(patch_transformers=True, verbose=10):
+        with torch_export_patches(patch_transformers=True, verbose=10):
             torch.export.export(
                 model, (), kwargs=inputs, dynamic_shapes=use_dyn_not_str(ds), strict=False
             )
diff --git a/_unittests/ut_tasks/test_tasks_image_text_to_text.py b/_unittests/ut_tasks/test_tasks_image_text_to_text.py
index a99db3f4..731371ef 100644
--- a/_unittests/ut_tasks/test_tasks_image_text_to_text.py
+++ b/_unittests/ut_tasks/test_tasks_image_text_to_text.py
@@ -2,7 +2,7 @@
 import torch
 from onnx_diagnostic.ext_test_case import ExtTestCase, hide_stdout, has_transformers, has_torch
 from onnx_diagnostic.torch_models.hghub.model_inputs import get_untrained_model_with_inputs
-from onnx_diagnostic.torch_export_patches import bypass_export_some_errors
+from onnx_diagnostic.torch_export_patches import torch_export_patches
 from onnx_diagnostic.torch_export_patches.patch_inputs import use_dyn_not_str
 
 
@@ -20,7 +20,7 @@ def test_image_text_to_text(self):
             raise unittest.SkipTest("The model has control flow.")
         if not has_torch("2.7.99"):
             raise unittest.SkipTest("sym_max does not work with dynamic dimension")
-        with bypass_export_some_errors(patch_transformers=True, verbose=10):
+        with torch_export_patches(patch_transformers=True, verbose=10):
             torch.export.export(
                 model, (), kwargs=inputs, dynamic_shapes=use_dyn_not_str(ds), strict=False
             )
diff --git a/_unittests/ut_tasks/test_tasks_zero_shot_image_classification.py b/_unittests/ut_tasks/test_tasks_zero_shot_image_classification.py
index b441646a..bbfb34ab 100644
--- a/_unittests/ut_tasks/test_tasks_zero_shot_image_classification.py
+++ b/_unittests/ut_tasks/test_tasks_zero_shot_image_classification.py
@@ -2,7 +2,7 @@
 import torch
 from onnx_diagnostic.ext_test_case import ExtTestCase, hide_stdout, requires_torch
 from onnx_diagnostic.torch_models.hghub.model_inputs import get_untrained_model_with_inputs
-from onnx_diagnostic.torch_export_patches import bypass_export_some_errors
+from onnx_diagnostic.torch_export_patches import torch_export_patches
 from onnx_diagnostic.torch_export_patches.patch_inputs import use_dyn_not_str
 
 
@@ -17,7 +17,7 @@ def test_zero_shot_image_classification(self):
         model, inputs, ds = data["model"], data["inputs"], data["dynamic_shapes"]
         model(**inputs)
         model(**data["inputs2"])
-        with bypass_export_some_errors(patch_transformers=True, verbose=10):
+        with torch_export_patches(patch_transformers=True, verbose=10):
             torch.export.export(
                 model, (), kwargs=inputs, dynamic_shapes=use_dyn_not_str(ds), strict=False
             )
diff --git a/_unittests/ut_torch_export_patches/test_dynamic_class.py b/_unittests/ut_torch_export_patches/test_dynamic_class.py
index 32831134..1cdb19eb 100644
--- a/_unittests/ut_torch_export_patches/test_dynamic_class.py
+++ b/_unittests/ut_torch_export_patches/test_dynamic_class.py
@@ -13,7 +13,7 @@
 from onnx_diagnostic.helpers import string_type
 from onnx_diagnostic.helpers.cache_helper import make_dynamic_cache
 from onnx_diagnostic.torch_export_patches.onnx_export_errors import (
-    bypass_export_some_errors,
+    torch_export_patches,
 )
 from onnx_diagnostic.torch_models.hghub.model_inputs import get_untrained_model_with_inputs
 
@@ -56,7 +56,7 @@ def forward(self, x, cache):
             DYN = torch.export.Dim.DYNAMIC
 
             # patching
-            with bypass_export_some_errors(patch_transformers=True):
+            with torch_export_patches(patch_transformers=True):
                 got = model(*inputs)
                 self.assertEqualArray(expected, got)
                 ep = torch.export.export(
@@ -260,7 +260,7 @@ def forward(self, x, dc):
             self.assertEqualArray(expected, got)
             return
 
-        with bypass_export_some_errors(patch_transformers=True):
+        with torch_export_patches(patch_transformers=True):
             ep = torch.export.export(model, (), kwargs=inputs)
 
             args, _spec = torch.utils._pytree.tree_flatten(inputs)
@@ -292,7 +292,7 @@ def test_phi2_export_module(self):
             str_inputs, string_type(inputs_copied, with_shape=True, with_min_max=True)
         )
 
-        with bypass_export_some_errors(patch_transformers=True):
+        with torch_export_patches(patch_transformers=True):
             ep = torch.export.export(
                 model,
                 (),
@@ -330,7 +330,7 @@ def test_phi2_export_interpreter(self):
             str_inputs, string_type(inputs_copied, with_shape=True, with_min_max=True)
         )
 
-        with bypass_export_some_errors(patch_transformers=True):
+        with torch_export_patches(patch_transformers=True):
             ep = torch.export.export(
                 model,
                 (),
diff --git a/_unittests/ut_torch_export_patches/test_onnx_export_errors.py b/_unittests/ut_torch_export_patches/test_onnx_export_errors.py
index 699ccdd7..b9adbc7d 100644
--- a/_unittests/ut_torch_export_patches/test_onnx_export_errors.py
+++ b/_unittests/ut_torch_export_patches/test_onnx_export_errors.py
@@ -10,7 +10,7 @@
 )
 from onnx_diagnostic.helpers import string_type
 from onnx_diagnostic.torch_export_patches.onnx_export_errors import (
-    bypass_export_some_errors,
+    torch_export_patches,
 )
 
 
@@ -34,7 +34,7 @@ def __init__(self):
 
         cache = MambaCache(_config(), max_batch_size=1, device="cpu")
 
-        with bypass_export_some_errors(verbose=1):
+        with torch_export_patches(verbose=1):
             values, spec = py_pytree.tree_flatten(cache)
             cache2 = py_pytree.tree_unflatten(values, spec)
             self.assertEqual(cache.max_batch_size, cache2.max_batch_size)
@@ -78,7 +78,7 @@ def forward(self, x: torch.Tensor, cache: MambaCache):
         model = Model()
         model(x, cache)
 
-        with bypass_export_some_errors(verbose=1):
+        with torch_export_patches(verbose=1):
             cache = MambaCache(_config(), max_batch_size=1, device="cpu")
             torch.export.export(Model(), (x, cache))
 
@@ -113,7 +113,7 @@ def forward(self, x: torch.Tensor, cache: MambaCache):
         model(x, cache)
         DYN = torch.export.Dim.DYNAMIC
 
-        with bypass_export_some_errors():
+        with torch_export_patches():
             cache = MambaCache(_config(), max_batch_size=2, device="cpu")
             torch.export.export(
                 Model(),
diff --git a/_unittests/ut_torch_export_patches/test_patch_base_class.py b/_unittests/ut_torch_export_patches/test_patch_base_class.py
index 7dc4c708..6e10e91f 100644
--- a/_unittests/ut_torch_export_patches/test_patch_base_class.py
+++ b/_unittests/ut_torch_export_patches/test_patch_base_class.py
@@ -1,7 +1,10 @@
 import unittest
 import torch
 from onnx_diagnostic.ext_test_case import ExtTestCase, hide_stdout
-from onnx_diagnostic.torch_export_patches import bypass_export_some_errors
+from onnx_diagnostic.torch_export_patches import (
+    torch_export_patches,
+    bypass_export_some_errors,
+)
 
 
 class TestPatchBaseClass(ExtTestCase):
@@ -73,6 +76,28 @@ def m1(self, x):
         model = Model()
         x = torch.arange(4)
         self.assertEqualArray(x * x, model(x))
+        with torch_export_patches(custom_patches=[patched_Model], verbose=10):
+            self.assertEqualArray(x**3, model(x))
+
+    @hide_stdout()
+    def test_bypass_export_some_errors(self):
+        class Model2(torch.nn.Module):
+            def m2(self, x):
+                return x * x
+
+            def forward(self, x):
+                return self.m2(x)
+
+        class patched_Model:
+            _PATCHED_CLASS_ = Model2
+            _PATCHES_ = ["m2"]
+
+            def m2(self, x):
+                return x**3
+
+        model = Model2()
+        x = torch.arange(4)
+        self.assertEqualArray(x * x, model(x))
         with bypass_export_some_errors(custom_patches=[patched_Model], verbose=10):
             self.assertEqualArray(x**3, model(x))
 
diff --git a/_unittests/ut_torch_export_patches/test_patch_serialization.py b/_unittests/ut_torch_export_patches/test_patch_serialization.py
index 619bd76d..1e0bcb12 100644
--- a/_unittests/ut_torch_export_patches/test_patch_serialization.py
+++ b/_unittests/ut_torch_export_patches/test_patch_serialization.py
@@ -9,7 +9,7 @@
     flatten_unflatten_for_dynamic_shapes,
 )
 from onnx_diagnostic.torch_export_patches.onnx_export_errors import (
-    bypass_export_some_errors,
+    torch_export_patches,
 )
 from onnx_diagnostic.helpers.torch_test_helper import torch_deepcopy
 
@@ -21,7 +21,7 @@ def test_encoder_decoder_cache_flatten(self):
             make_dynamic_cache([(torch.rand((4, 4, 4)), torch.rand((4, 4, 4)))]),
             make_dynamic_cache([(torch.rand((5, 5, 5)), torch.rand((5, 5, 5)))]),
         )
-        with bypass_export_some_errors():
+        with torch_export_patches():
             flat, _spec = torch.utils._pytree.tree_flatten(cache)
             self.assertEqual(
                 "#4[T1s4x4x4,T1s4x4x4,T1s5x5x5,T1s5x5x5]",
@@ -39,7 +39,7 @@ def test_encoder_decoder_cache_deepcopy(self):
             make_dynamic_cache([(torch.rand((4, 4, 4)), torch.rand((4, 4, 4)))]),
             make_dynamic_cache([(torch.rand((5, 5, 5)), torch.rand((5, 5, 5)))]),
         )
-        with bypass_export_some_errors():
+        with torch_export_patches():
             cache2 = torch_deepcopy([cache])
             self.assertEqualAny([cache], cache2)
 
@@ -65,13 +65,13 @@ def forward(self, cache):
             [[{0: DYN}, {0: DYN}, {0: DYN}], [{0: DYN}, {0: DYN}, {0: DYN}]],
         ]
 
-        with bypass_export_some_errors(patch_transformers=True):
+        with torch_export_patches(patch_transformers=True):
             torch.export.export(model, (cache,), dynamic_shapes=(ds,))
 
     @ignore_warnings(UserWarning)
     def test_dynamic_cache_flatten(self):
         cache = make_dynamic_cache([(torch.rand((4, 4, 4)), torch.rand((4, 4, 4)))])
-        with bypass_export_some_errors():
+        with torch_export_patches():
             flat, _spec = torch.utils._pytree.tree_flatten(cache)
             self.assertEqual(
                 "#2[T1s4x4x4,T1s4x4x4]",
@@ -97,13 +97,13 @@ def forward(self, cache):
         DYN = torch.export.Dim.DYNAMIC
         ds = [[{0: DYN}, {0: DYN}, {0: DYN}], [{0: DYN}, {0: DYN}, {0: DYN}]]
 
-        with bypass_export_some_errors():
+        with torch_export_patches():
             torch.export.export(model, (cache,), dynamic_shapes=(ds,))
 
     @ignore_warnings(UserWarning)
     def test_dynamic_cache_deepcopy(self):
         cache = make_dynamic_cache([(torch.rand((4, 4, 4)), torch.rand((4, 4, 4)))])
-        with bypass_export_some_errors():
+        with torch_export_patches():
             cache2 = torch_deepcopy([cache])
             self.assertEqualAny([cache], cache2)
 
@@ -111,7 +111,7 @@ def test_dynamic_cache_deepcopy(self):
     def test_base_model_output_deepcopy(self):
         bo = BaseModelOutput(last_hidden_state=torch.rand((4, 4, 4)))
         self.assertEqual(bo.__class__.__name__, "BaseModelOutput")
-        with bypass_export_some_errors():
+        with torch_export_patches():
             bo2 = torch_deepcopy([bo])
             self.assertIsInstance(bo2, list)
             self.assertEqual(bo2[0].__class__.__name__, "BaseModelOutput")
@@ -120,7 +120,7 @@ def test_base_model_output_deepcopy(self):
     @ignore_warnings(UserWarning)
     def test_base_model_output_string_type(self):
         bo = BaseModelOutput(last_hidden_state=torch.rand((4, 4, 4)))
-        with bypass_export_some_errors():
+        with torch_export_patches():
             self.assertEqual(
                 "BaseModelOutput(last_hidden_state:T1s4x4x4)",
                 self.string_type(bo, with_shape=True),
@@ -129,7 +129,7 @@ def test_base_model_output_string_type(self):
     @ignore_warnings(UserWarning)
     def test_base_model_output_flatten(self):
         bo = BaseModelOutput(last_hidden_state=torch.rand((4, 4, 4)))
-        with bypass_export_some_errors():
+        with torch_export_patches():
             flat, _spec = torch.utils._pytree.tree_flatten(bo)
             self.assertEqual(
                 "#1[T1s4x4x4]",
@@ -153,13 +153,13 @@ def forward(self, cache):
         DYN = torch.export.Dim.DYNAMIC
         ds = [{0: DYN}]
 
-        with bypass_export_some_errors():
+        with torch_export_patches():
             torch.export.export(model, (bo,), dynamic_shapes=(ds,))
 
     @ignore_warnings(UserWarning)
     def test_base_model_output_unflatten_flatten(self):
         bo = BaseModelOutput(last_hidden_state=torch.rand((4, 4, 4)))
-        with bypass_export_some_errors(patch_transformers=True):
+        with torch_export_patches(patch_transformers=True):
             flat, _spec = torch.utils._pytree.tree_flatten(bo)
             unflat = flatten_unflatten_for_dynamic_shapes(bo, use_dict=True)
             self.assertIsInstance(unflat, dict)
@@ -170,7 +170,7 @@ def test_base_sliding_window_cache_unflatten_flatten(self):
         cache = make_sliding_window_cache(
             [(torch.rand((4, 4, 4, 4)), torch.rand((4, 4, 4, 4)))]
         )
-        with bypass_export_some_errors():
+        with torch_export_patches():
             cache2 = torch_deepcopy([cache])
             self.assertEqualAny([cache], cache2)
 
@@ -192,7 +192,7 @@ def forward(self, cache):
         DYN = torch.export.Dim.DYNAMIC
         ds = [[{0: DYN}, {0: DYN}], [{0: DYN}, {0: DYN}]]
 
-        with bypass_export_some_errors(patch_transformers=True):
+        with torch_export_patches(patch_transformers=True):
             torch.export.export(model, (cache,), dynamic_shapes=(ds,))
 
     @ignore_warnings(UserWarning)
@@ -200,7 +200,7 @@ def test_sliding_window_cache_flatten(self):
         cache = make_sliding_window_cache(
             [(torch.rand((4, 4, 4, 4)), torch.rand((4, 4, 4, 4)))]
         )
-        with bypass_export_some_errors():
+        with torch_export_patches():
             flat, _spec = torch.utils._pytree.tree_flatten(cache)
             self.assertEqual(
                 "#2[T1s4x4x4x4,T1s4x4x4x4]",
diff --git a/_unittests/ut_torch_models/test_hghub_model.py b/_unittests/ut_torch_models/test_hghub_model.py
index 6083812f..7b2b49e1 100644
--- a/_unittests/ut_torch_models/test_hghub_model.py
+++ b/_unittests/ut_torch_models/test_hghub_model.py
@@ -10,7 +10,7 @@
 from onnx_diagnostic.torch_models.hghub.model_inputs import get_untrained_model_with_inputs
 from onnx_diagnostic.torch_models.hghub.hub_api import get_pretrained_config
 from onnx_diagnostic.torch_models.hghub.hub_data import load_models_testing
-from onnx_diagnostic.torch_export_patches import bypass_export_some_errors
+from onnx_diagnostic.torch_export_patches import torch_export_patches
 
 
 class TestHuggingFaceHubModel(ExtTestCase):
@@ -91,7 +91,7 @@ def test_get_untrained_model_with_inputs_clip_vit(self):
         mid = "openai/clip-vit-base-patch16"
         data = get_untrained_model_with_inputs(mid, verbose=1)
         model, inputs = data["model"], data["inputs"]
-        with bypass_export_some_errors(patch_transformers=True):
+        with torch_export_patches(patch_transformers=True):
             model(**inputs)
         # different expected value for different version of transformers
         self.assertIn((data["size"], data["n_weights"]), [(188872708, 47218177)])
diff --git a/_unittests/ut_torch_models/test_tiny_llms_bypassed.py b/_unittests/ut_torch_models/test_tiny_llms_bypassed.py
index 4ec3e943..35b3c224 100644
--- a/_unittests/ut_torch_models/test_tiny_llms_bypassed.py
+++ b/_unittests/ut_torch_models/test_tiny_llms_bypassed.py
@@ -6,7 +6,7 @@
 from onnx_diagnostic.torch_models.llms import get_tiny_llm
 from onnx_diagnostic.torch_models.llms import get_phi2
 from onnx_diagnostic.helpers import string_type
-from onnx_diagnostic.torch_export_patches import bypass_export_some_errors
+from onnx_diagnostic.torch_export_patches import torch_export_patches
 from onnx_diagnostic.torch_export_patches.patches.patch_transformers import (
     patched_DynamicCache,
 )
@@ -22,7 +22,7 @@ def test_export_tiny_llm_2_bypassed(self):
             {"attention_mask", "past_key_values", "input_ids", "position_ids"}, set(inputs)
         )
 
-        with bypass_export_some_errors(
+        with torch_export_patches(
             patch_torch=False, patch_transformers=True, catch_constraints=False, verbose=10
         ) as modificator:
 
@@ -61,11 +61,11 @@ def test_export_phi2_2_bypassed(self):
         self.assertEqual(
             {"attention_mask", "past_key_values", "input_ids", "position_ids"}, set(inputs)
         )
-        with bypass_export_some_errors(patch_transformers=True) as modificator:
+        with torch_export_patches(patch_transformers=True) as modificator:
             inputs = modificator(inputs)
             ep = torch.export.export(model, (), kwargs=inputs, dynamic_shapes=ds, strict=False)
             assert ep
-        with bypass_export_some_errors(patch_transformers=True) as modificator:
+        with torch_export_patches(patch_transformers=True) as modificator:
             inputs = modificator(inputs)
             ep = torch.export.export(model, (), kwargs=inputs, dynamic_shapes=ds, strict=False)
             assert ep
diff --git a/_unittests/ut_torch_models/test_tiny_llms_onnx.py b/_unittests/ut_torch_models/test_tiny_llms_onnx.py
index eda2d3de..48c13f06 100644
--- a/_unittests/ut_torch_models/test_tiny_llms_onnx.py
+++ b/_unittests/ut_torch_models/test_tiny_llms_onnx.py
@@ -10,7 +10,7 @@
     requires_transformers,
 )
 from onnx_diagnostic.torch_models.llms import get_tiny_llm
-from onnx_diagnostic.torch_export_patches import bypass_export_some_errors
+from onnx_diagnostic.torch_export_patches import torch_export_patches
 
 try:
     from experimental_experiment.torch_interpreter import to_onnx, ExportOptions
@@ -58,7 +58,7 @@ def test_onnx_export_tiny_llm_xdbg(self):
         self.assertEqual(
             {"attention_mask", "past_key_values", "input_ids", "position_ids"}, set(inputs)
         )
-        with bypass_export_some_errors(patch_transformers=True):
+        with torch_export_patches(patch_transformers=True):
             onx = to_onnx(
                 model, (), kwargs=inputs, dynamic_shapes=data["dynamic_shapes"], verbose=1
             )
@@ -74,7 +74,7 @@ def test_bypass_onnx_export_tiny_llm_official_nopositionids(self):
         del inputs["position_ids"]
         del ds["position_ids"]
         self.assertEqual({"attention_mask", "past_key_values", "input_ids"}, set(inputs))
-        with bypass_export_some_errors(patch_transformers=True, verbose=1) as modificator:
+        with torch_export_patches(patch_transformers=True, verbose=1) as modificator:
             new_inputs = modificator(copy.deepcopy(inputs))
             ep = torch.onnx.export(
                 model,
@@ -101,7 +101,7 @@ def test_bypass_onnx_export_tiny_llm_official_full(self):
         self.assertEqual(
             {"attention_mask", "past_key_values", "input_ids", "position_ids"}, set(inputs)
         )
-        with bypass_export_some_errors(patch_transformers=True, verbose=1) as modificator:
+        with torch_export_patches(patch_transformers=True, verbose=1) as modificator:
             new_inputs = modificator(copy.deepcopy(inputs))
             ep = torch.onnx.export(
                 model,
@@ -134,7 +134,7 @@ def test_bypass_onnx_export_tiny_llm_xdbg(self):
         self.assertEqual(
             {"attention_mask", "past_key_values", "input_ids", "position_ids"}, set(inputs)
         )
-        with bypass_export_some_errors(patch_transformers=True, verbose=2) as modificator:
+        with torch_export_patches(patch_transformers=True, verbose=2) as modificator:
             new_inputs = modificator(inputs)
             onx = to_onnx(
                 model,
diff --git a/onnx_diagnostic/torch_export_patches/__init__.py b/onnx_diagnostic/torch_export_patches/__init__.py
index ff978ee3..0b241ba0 100644
--- a/onnx_diagnostic/torch_export_patches/__init__.py
+++ b/onnx_diagnostic/torch_export_patches/__init__.py
@@ -1,4 +1,8 @@
 from .onnx_export_errors import (
-    bypass_export_some_errors,
+    torch_export_patches,
     register_additional_serialization_functions,
 )
+
+
+# bypass_export_some_errors is the first name given to the patches.
+bypass_export_some_errors = torch_export_patches  # type: ignore
diff --git a/onnx_diagnostic/torch_export_patches/onnx_export_errors.py b/onnx_diagnostic/torch_export_patches/onnx_export_errors.py
index 54b3e875..27cbfe14 100644
--- a/onnx_diagnostic/torch_export_patches/onnx_export_errors.py
+++ b/onnx_diagnostic/torch_export_patches/onnx_export_errors.py
@@ -93,7 +93,7 @@ def register_additional_serialization_functions(
 
 
 @contextlib.contextmanager
-def bypass_export_some_errors(
+def torch_export_patches(
     patch_sympy: bool = True,
     patch_torch: bool = True,
     patch_transformers: bool = False,
@@ -145,13 +145,13 @@ def bypass_export_some_errors(
 
     ::
 
-        with bypass_export_some_errors(patch_transformers=True) as modificator:
+        with torch_export_patches(patch_transformers=True) as modificator:
             inputs = modificator(inputs)
             onx = to_onnx(..., inputs, ...)
 
     ::
 
-        with bypass_export_some_errors(patch_transformers=True) as modificator:
+        with torch_export_patches(patch_transformers=True) as modificator:
             inputs = modificator(inputs)
             onx = torch.onnx.export(..., inputs, ...)
 
@@ -159,7 +159,7 @@ def bypass_export_some_errors(
 
     ::
 
-        with bypass_export_some_errors(patch_transformers=True) as modificator:
+        with torch_export_patches(patch_transformers=True) as modificator:
             inputs = modificator(inputs)
             ep = torch.export.export(..., inputs, ...)
 
@@ -190,7 +190,7 @@ def bypass_export_some_errors(
 
         if verbose:
             print(
-                "[bypass_export_some_errors] replace torch.jit.isinstance, "
+                "[torch_export_patches] replace torch.jit.isinstance, "
                 "torch._dynamo.mark_static_address"
             )
 
@@ -210,8 +210,8 @@ def bypass_export_some_errors(
             f_sympy_name = getattr(sympy.core.numbers.IntegerConstant, "name", None)
 
             if verbose:
-                print(f"[bypass_export_some_errors] sympy.__version__={sympy.__version__!r}")
-                print("[bypass_export_some_errors] patch sympy")
+                print(f"[torch_export_patches] sympy.__version__={sympy.__version__!r}")
+                print("[torch_export_patches] patch sympy")
 
             sympy.core.numbers.IntegerConstant.name = lambda self: f"IntCst{str(self)}"
 
@@ -228,9 +228,9 @@ def bypass_export_some_errors(
             )
 
             if verbose:
-                print(f"[bypass_export_some_errors] torch.__version__={torch.__version__!r}")
-                print(f"[bypass_export_some_errors] stop_if_static={stop_if_static!r}")
-                print("[bypass_export_some_errors] patch pytorch")
+                print(f"[torch_export_patches] torch.__version__={torch.__version__!r}")
+                print(f"[torch_export_patches] stop_if_static={stop_if_static!r}")
+                print("[torch_export_patches] patch pytorch")
 
             # torch.jit.isinstance
             f_jit_isinstance = torch.jit.isinstance
@@ -252,7 +252,7 @@ def bypass_export_some_errors(
         # torch._export.non_strict_utils.produce_guards_and_solve_constraints
         if catch_constraints:
             if verbose:
-                print("[bypass_export_some_errors] modifies shape constraints")
+                print("[torch_export_patches] modifies shape constraints")
             f_produce_guards_and_solve_constraints = (
                 torch._export.non_strict_utils.produce_guards_and_solve_constraints
             )
@@ -277,22 +277,20 @@ def bypass_export_some_errors(
             ShapeEnv._log_guard_remember = ShapeEnv._log_guard
 
             if verbose:
-                print(
-                    "[bypass_export_some_errors] assert when a dynamic dimension turns static"
-                )
-                print("[bypass_export_some_errors] replaces ShapeEnv._set_replacement")
+                print("[torch_export_patches] assert when a dynamic dimension turns static")
+                print("[torch_export_patches] replaces ShapeEnv._set_replacement")
 
             f_shape_env__set_replacement = ShapeEnv._set_replacement
             ShapeEnv._set_replacement = patched_ShapeEnv._set_replacement
 
             if verbose:
-                print("[bypass_export_some_errors] replaces ShapeEnv._log_guard")
+                print("[torch_export_patches] replaces ShapeEnv._log_guard")
             f_shape_env__log_guard = ShapeEnv._log_guard
             ShapeEnv._log_guard = patched_ShapeEnv._log_guard
 
             if stop_if_static > 1:
                 if verbose:
-                    print("[bypass_export_some_errors] replaces ShapeEnv._check_frozen")
+                    print("[torch_export_patches] replaces ShapeEnv._check_frozen")
                 f_shape_env__check_frozen = ShapeEnv._check_frozen
                 ShapeEnv._check_frozen = patched_ShapeEnv._check_frozen
 
@@ -305,7 +303,7 @@ def bypass_export_some_errors(
                 import transformers
 
                 print(
-                    f"[bypass_export_some_errors] transformers.__version__="
+                    f"[torch_export_patches] transformers.__version__="
                     f"{transformers.__version__!r}"
                 )
             revert_patches_info = patch_module_or_classes(
@@ -314,7 +312,7 @@ def bypass_export_some_errors(
 
         if custom_patches:
             if verbose:
-                print("[bypass_export_some_errors] applies custom patches")
+                print("[torch_export_patches] applies custom patches")
             revert_custom_patches_info = patch_module_or_classes(
                 custom_patches, verbose=verbose
             )
@@ -326,7 +324,7 @@ def bypass_export_some_errors(
         fct_callable = replacement_before_exporting if patch_transformers else (lambda x: x)
 
         if verbose:
-            print("[bypass_export_some_errors] done patching")
+            print("[torch_export_patches] done patching")
 
         try:
             yield fct_callable
@@ -336,7 +334,7 @@ def bypass_export_some_errors(
             #######
 
             if verbose:
-                print("[bypass_export_some_errors] remove patches")
+                print("[torch_export_patches] remove patches")
 
             if patch_sympy:
                 # tracked by https://github.com/pytorch/pytorch/issues/143494
@@ -346,7 +344,7 @@ def bypass_export_some_errors(
                     delattr(sympy.core.numbers.IntegerConstant, "name")
 
                 if verbose:
-                    print("[bypass_export_some_errors] restored sympy functions")
+                    print("[torch_export_patches] restored sympy functions")
 
             #######
             # torch
@@ -362,22 +360,22 @@ def bypass_export_some_errors(
                 torch._meta_registrations._broadcast_shapes = f__broadcast_shapes
 
                 if verbose:
-                    print("[bypass_export_some_errors] restored pytorch functions")
+                    print("[torch_export_patches] restored pytorch functions")
 
             if stop_if_static:
                 if verbose:
-                    print("[bypass_export_some_errors] restored ShapeEnv._set_replacement")
+                    print("[torch_export_patches] restored ShapeEnv._set_replacement")
 
                 ShapeEnv._set_replacement = f_shape_env__set_replacement
 
                 if verbose:
-                    print("[bypass_export_some_errors] restored ShapeEnv._log_guard")
+                    print("[torch_export_patches] restored ShapeEnv._log_guard")
 
                 ShapeEnv._log_guard = f_shape_env__log_guard
 
                 if stop_if_static > 1:
                     if verbose:
-                        print("[bypass_export_some_errors] restored ShapeEnv._check_frozen")
+                        print("[torch_export_patches] restored ShapeEnv._check_frozen")
                     ShapeEnv._check_frozen = f_shape_env__check_frozen
 
             if catch_constraints:
@@ -389,11 +387,11 @@ def bypass_export_some_errors(
                     f__check_input_constraints_for_graph
                 )
                 if verbose:
-                    print("[bypass_export_some_errors] restored shape constraints")
+                    print("[torch_export_patches] restored shape constraints")
 
             if custom_patches:
                 if verbose:
-                    print("[bypass_export_some_errors] unpatch custom patches")
+                    print("[torch_export_patches] unpatch custom patches")
                 unpatch_module_or_classes(
                     custom_patches, revert_custom_patches_info, verbose=verbose
                 )
@@ -404,7 +402,7 @@ def bypass_export_some_errors(
 
             if patch_transformers:
                 if verbose:
-                    print("[bypass_export_some_errors] unpatch transformers")
+                    print("[torch_export_patches] unpatch transformers")
                 unpatch_module_or_classes(
                     patch_transformers_list, revert_patches_info, verbose=verbose
                 )
diff --git a/onnx_diagnostic/torch_models/test_helper.py b/onnx_diagnostic/torch_models/test_helper.py
index a39266c2..aa93ece7 100644
--- a/onnx_diagnostic/torch_models/test_helper.py
+++ b/onnx_diagnostic/torch_models/test_helper.py
@@ -12,7 +12,7 @@
 from ..helpers.torch_test_helper import to_any, torch_deepcopy
 from ..helpers.cache_helper import flatten_unflatten_for_dynamic_shapes
 from ..tasks import random_input_kwargs
-from ..torch_export_patches import bypass_export_some_errors
+from ..torch_export_patches import torch_export_patches
 from ..torch_export_patches.patch_inputs import use_dyn_not_str
 from .hghub import get_untrained_model_with_inputs
 
@@ -242,9 +242,9 @@ def validate_model(
         depend on the the exporter
     :param quiet: if quiet, catches exception if any issue
     :param patch: applies patches (``patch_transformers=True``) before exporting,
-        see :func:`onnx_diagnostic.torch_export_patches.bypass_export_some_errors`
+        see :func:`onnx_diagnostic.torch_export_patches.torch_export_patches`
     :param stop_if_static: stops if a dynamic dimension becomes static,
-        see :func:`onnx_diagnostic.torch_export_patches.bypass_export_some_errors`
+        see :func:`onnx_diagnostic.torch_export_patches.torch_export_patches`
     :param dump_folder: dumps everything in a subfolder of this one
     :param drop_inputs: drops this list of inputs (given their names)
     :param ortfusiontype: runs ort fusion, the parameters defines the fusion type,
@@ -417,7 +417,7 @@ def validate_model(
                     f"[validate_model] applies patches before exporting "
                     f"stop_if_static={stop_if_static}"
                 )
-            with bypass_export_some_errors(  # type: ignore
+            with torch_export_patches(  # type: ignore
                 patch_transformers=True,
                 stop_if_static=stop_if_static,
                 verbose=max(0, verbose - 1),