Skip some export tests on torch 2.7 (#38677)

* skip

* fix

* better check

* Update import_utils.py

---------

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
Co-authored-by: Cyril Vallez <cyril.vallez@gmail.com>

src/transformers/utils/import_utils.py

@@ -393,6 +393,13 @@ def get_torch_version():
     return _torch_version
 
 
+def get_torch_major_and_minor_version() -> str:
+    if _torch_version == "N/A":
+        return "N/A"
+    parsed_version = version.parse(_torch_version)
+    return str(parsed_version.major) + "." + str(parsed_version.minor)
+
+
 def is_torch_sdpa_available():
     if not is_torch_available():
         return False

tests/models/depth_anything/test_modeling_depth_anything.py

@@ -19,6 +19,7 @@ from transformers import DepthAnythingConfig, Dinov2Config
 from transformers.file_utils import is_torch_available, is_vision_available
 from transformers.pytorch_utils import is_torch_greater_or_equal_than_2_4
 from transformers.testing_utils import require_torch, require_vision, slow, torch_device
+from transformers.utils.import_utils import get_torch_major_and_minor_version
 
 from ...test_configuration_common import ConfigTester
 from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor
@@ -146,6 +147,7 @@ class DepthAnythingModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.Tes
     test_resize_embeddings = False
     test_head_masking = False
     test_torch_exportable = True
+    test_torch_exportable_strictly = not get_torch_major_and_minor_version() == "2.7"
 
     def setUp(self):
         self.model_tester = DepthAnythingModelTester(self)
@@ -285,8 +287,11 @@ class DepthAnythingModelIntegrationTest(unittest.TestCase):
         torch.testing.assert_close(predicted_depth[0, :3, :3], expected_slice, rtol=1e-4, atol=1e-4)
 
     def test_export(self):
-        for strict in [True, False]:
+        for strict in [False, True]:
             with self.subTest(strict=strict):
+                if strict and get_torch_major_and_minor_version() == "2.7":
+                    self.skipTest(reason="`strict=True` is currently failing with torch 2.7.")
+
                 if not is_torch_greater_or_equal_than_2_4:
                     self.skipTest(reason="This test requires torch >= 2.4 to run.")
                 model = (

tests/models/dpt/test_modeling_dpt_auto_backbone.py

@@ -18,6 +18,7 @@ import unittest
 from transformers import Dinov2Config, DPTConfig
 from transformers.file_utils import is_torch_available, is_vision_available
 from transformers.testing_utils import require_torch, require_vision, slow, torch_device
+from transformers.utils.import_utils import get_torch_major_and_minor_version
 
 from ...test_configuration_common import ConfigTester
 from ...test_modeling_common import ModelTesterMixin, _config_zero_init, floats_tensor, ids_tensor
@@ -140,6 +141,7 @@ class DPTModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
     test_resize_embeddings = False
     test_head_masking = False
     test_torch_exportable = True
+    test_torch_exportable_strictly = not get_torch_major_and_minor_version() == "2.7"
 
     def setUp(self):
         self.model_tester = DPTModelTester(self)

tests/models/prompt_depth_anything/test_modeling_prompt_depth_anything.py

@@ -21,6 +21,7 @@ from transformers import Dinov2Config, PromptDepthAnythingConfig
 from transformers.file_utils import is_torch_available, is_vision_available
 from transformers.pytorch_utils import is_torch_greater_or_equal_than_2_4
 from transformers.testing_utils import require_torch, require_vision, slow, torch_device
+from transformers.utils.import_utils import get_torch_major_and_minor_version
 
 from ...test_configuration_common import ConfigTester
 from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor
@@ -284,7 +285,10 @@ class PromptDepthAnythingModelIntegrationTest(unittest.TestCase):
         self.assertTrue(torch.allclose(predicted_depth[0, :3, :3], expected_slice, atol=1e-3))
 
     def test_export(self):
-        for strict in [True, False]:
+        for strict in [False, True]:
+            if strict and get_torch_major_and_minor_version() == "2.7":
+                self.skipTest(reason="`strict=True` is currently failing with torch 2.7.")
+
             with self.subTest(strict=strict):
                 if not is_torch_greater_or_equal_than_2_4:
                     self.skipTest(reason="This test requires torch >= 2.4 to run.")

tests/models/upernet/test_modeling_upernet.py

@@ -27,6 +27,7 @@ from transformers.testing_utils import (
     torch_device,
 )
 from transformers.utils import is_torch_available, is_vision_available
+from transformers.utils.import_utils import get_torch_major_and_minor_version
 
 from ...test_configuration_common import ConfigTester
 from ...test_modeling_common import ModelTesterMixin, _config_zero_init, floats_tensor, ids_tensor
@@ -157,6 +158,7 @@ class UperNetModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase)
     test_torchscript = False
     has_attentions = False
     test_torch_exportable = True
+    test_torch_exportable_strictly = not get_torch_major_and_minor_version() == "2.7"
 
     def setUp(self):
         self.model_tester = UperNetModelTester(self)

tests/models/vitmatte/test_modeling_vitmatte.py

@@ -25,6 +25,7 @@ from transformers.testing_utils import (
     torch_device,
 )
 from transformers.utils import is_torch_available, is_vision_available
+from transformers.utils.import_utils import get_torch_major_and_minor_version
 
 from ...test_configuration_common import ConfigTester
 from ...test_modeling_common import ModelTesterMixin, floats_tensor
@@ -143,6 +144,7 @@ class VitMatteModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase
     test_resize_embeddings = False
     test_head_masking = False
     test_torch_exportable = True
+    test_torch_exportable_strictly = not get_torch_major_and_minor_version() == "2.7"
 
     def setUp(self):
         self.model_tester = VitMatteModelTester(self)

tests/models/vitpose/test_modeling_vitpose.py

@@ -21,6 +21,7 @@ import requests
 from transformers import VitPoseBackboneConfig, VitPoseConfig
 from transformers.testing_utils import require_torch, require_vision, slow, torch_device
 from transformers.utils import cached_property, is_torch_available, is_vision_available
+from transformers.utils.import_utils import get_torch_major_and_minor_version
 
 from ...test_configuration_common import ConfigTester
 from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor
@@ -154,6 +155,7 @@ class VitPoseModelTest(ModelTesterMixin, unittest.TestCase):
     test_resize_embeddings = False
     test_head_masking = False
     test_torch_exportable = True
+    test_torch_exportable_strictly = not get_torch_major_and_minor_version() == "2.7"
 
     def setUp(self):
         self.model_tester = VitPoseModelTester(self)

tests/models/zoedepth/test_modeling_zoedepth.py

@@ -20,6 +20,7 @@ import numpy as np
 from transformers import Dinov2Config, ZoeDepthConfig
 from transformers.file_utils import is_torch_available, is_vision_available
 from transformers.testing_utils import require_torch, require_vision, slow, torch_device
+from transformers.utils.import_utils import get_torch_major_and_minor_version
 
 from ...test_configuration_common import ConfigTester
 from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor
@@ -146,7 +147,8 @@ class ZoeDepthModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase
     test_pruning = False
     test_resize_embeddings = False
     test_head_masking = False
-    test_torch_exportable = True
+    # `strict=True/False` are both failing with torch 2.7, see #38677
+    test_torch_exportable = not get_torch_major_and_minor_version() == "2.7"
 
     def setUp(self):
         self.model_tester = ZoeDepthModelTester(self)

tests/test_modeling_common.py

@@ -4569,10 +4569,7 @@ class ModelTesterMixin:
 
                 # Export model
                 exported_model = torch.export.export(
-                    model,
+                    model, args=(), kwargs=inputs_dict, strict=getattr(self, "test_torch_exportable_strictly", True)
-                    args=(),
-                    kwargs=inputs_dict,
-                    strict=True,
                 )
 
                 # Run exported model and eager model