Add push to hub to feature extractor (#15632)

* Add push to hub to feature extractor

* Quality

* Clean up

tests/test_feature_extraction_common.py

@@ -23,7 +23,7 @@ from pathlib import Path
 
 from huggingface_hub import Repository, delete_repo, login
 from requests.exceptions import HTTPError
-from transformers import AutoFeatureExtractor
+from transformers import AutoFeatureExtractor, Wav2Vec2FeatureExtractor
 from transformers.file_utils import is_torch_available, is_vision_available
 from transformers.testing_utils import PASS, USER, is_staging_test
 
@@ -40,7 +40,6 @@ if is_torch_available():
 if is_vision_available():
     from PIL import Image
 
-
 SAMPLE_FEATURE_EXTRACTION_CONFIG_DIR = os.path.join(os.path.dirname(os.path.abspath(__file__)), "fixtures")
 
 
@@ -124,11 +123,47 @@ class ConfigPushToHubTester(unittest.TestCase):
 
     @classmethod
     def tearDownClass(cls):
+        try:
+            delete_repo(token=cls._token, name="test-feature-extractor")
+        except HTTPError:
+            pass
+
+        try:
+            delete_repo(token=cls._token, name="test-feature-extractor-org", organization="valid_org")
+        except HTTPError:
+            pass
+
         try:
             delete_repo(token=cls._token, name="test-dynamic-feature-extractor")
         except HTTPError:
             pass
 
+    def test_push_to_hub(self):
+        feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained(SAMPLE_FEATURE_EXTRACTION_CONFIG_DIR)
+        with tempfile.TemporaryDirectory() as tmp_dir:
+            feature_extractor.save_pretrained(
+                os.path.join(tmp_dir, "test-feature-extractor"), push_to_hub=True, use_auth_token=self._token
+            )
+
+            new_feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained(f"{USER}/test-feature-extractor")
+            for k, v in feature_extractor.__dict__.items():
+                self.assertEqual(v, getattr(new_feature_extractor, k))
+
+    def test_push_to_hub_in_organization(self):
+        feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained(SAMPLE_FEATURE_EXTRACTION_CONFIG_DIR)
+
+        with tempfile.TemporaryDirectory() as tmp_dir:
+            feature_extractor.save_pretrained(
+                os.path.join(tmp_dir, "test-feature-extractor-org"),
+                push_to_hub=True,
+                use_auth_token=self._token,
+                organization="valid_org",
+            )
+
+            new_feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained("valid_org/test-feature-extractor-org")
+            for k, v in feature_extractor.__dict__.items():
+                self.assertEqual(v, getattr(new_feature_extractor, k))
+
     def test_push_to_hub_dynamic_feature_extractor(self):
         CustomFeatureExtractor.register_for_auto_class()
         feature_extractor = CustomFeatureExtractor.from_pretrained(SAMPLE_FEATURE_EXTRACTION_CONFIG_DIR)