Enable transformers v4.47 support

setup.py

@@ -51,7 +51,7 @@
         "datasets>=1.2.1",
         "evaluate",
         "protobuf>=3.20.1",
-        "transformers>=4.36,<4.47.0",
+        "transformers>=4.36,<4.48.0",
     ],
     "onnxruntime-gpu": [
         "onnx",
@@ -60,19 +60,19 @@
         "evaluate",
         "protobuf>=3.20.1",
         "accelerate",  # ORTTrainer requires it.
-        "transformers>=4.36,<4.47.0",
+        "transformers>=4.36,<4.48.0",
     ],
     "exporters": [
         "onnx",
         "onnxruntime",
         "timm",
-        "transformers>=4.36,<4.47.0",
+        "transformers>=4.36,<4.48.0",
     ],
     "exporters-gpu": [
         "onnx",
         "onnxruntime-gpu",
         "timm",
-        "transformers>=4.36,<4.47.0",
+        "transformers>=4.36,<4.48.0",
     ],
     "exporters-tf": [
         "tensorflow>=2.4,<=2.12.1",

tests/onnx/test_onnx_export_custom_module.py

@@ -22,7 +22,7 @@
 
 if is_torch_available():
     import torch
-    from transformers.models.deberta import modeling_deberta
+    from transformers.models.sew_d import modeling_sew_d
 
     from optimum.utils import check_if_torch_greater
 
@@ -36,7 +36,7 @@ def test_training(self):
         """Tests export of StableDropout in training mode."""
         devnull = open(os.devnull, "wb")
         # drop_prob must be > 0 for the test to be meaningful
-        sd = modeling_deberta.StableDropout(0.1)
+        sd = modeling_sew_d.StableDropout(0.1)
         # Avoid warnings in training mode
         do_constant_folding = False
         # Dropout is a no-op in inference mode

tests/test_configuration_utils.py

@@ -12,13 +12,12 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-import os
 import tempfile
 import unittest
 
 from huggingface_hub import HfFolder, delete_repo
 from requests.exceptions import HTTPError
-from transformers.testing_utils import TOKEN, USER, is_staging_test
+from transformers.testing_utils import TOKEN, TemporaryHubRepo, is_staging_test
 
 from optimum.configuration_utils import BaseConfig
 
@@ -69,28 +68,21 @@ def tearDownClass(cls):
 
     def test_push_to_hub(self):
         config = FakeConfig(attribute=15)
-        with tempfile.TemporaryDirectory() as tmp_dir:
-            config.save_pretrained(
-                os.path.join(tmp_dir, "optimum-test-base-config"), push_to_hub=True, token=self._token
-            )
 
-            new_config = FakeConfig.from_pretrained(f"{USER}/optimum-test-base-config")
+        with TemporaryHubRepo(token=self._token) as tmp_repo:
+            config.push_to_hub(tmp_repo.repo_id, token=self._token)
+
+            new_config = FakeConfig.from_pretrained(tmp_repo.repo_id)
             for k, v in config.to_dict().items():
                 if k != "optimum_version" and k != "transformers_version":
                     self.assertEqual(v, getattr(new_config, k))
 
     def test_push_to_hub_in_organization(self):
         config = FakeConfig(attribute=15)
 
-        with tempfile.TemporaryDirectory() as tmp_dir:
-            config.save_pretrained(
-                os.path.join(tmp_dir, "optimum-test-base-config-org"),
-                push_to_hub=True,
-                token=self._token,
-                organization="valid_org",
-            )
-
-            new_config = FakeConfig.from_pretrained("valid_org/optimum-test-base-config-org")
+        with TemporaryHubRepo(namespace="valid_org", token=self._token) as tmp_repo:
+            config.push_to_hub(tmp_repo.repo_id, token=self._token)
+            new_config = FakeConfig.from_pretrained(tmp_repo.repo_id)
             for k, v in config.to_dict().items():
                 if k != "optimum_version" and k != "transformers_version":
                     self.assertEqual(v, getattr(new_config, k))