Auto processor (#14465)

* Add AutoProcessor class

* Init and tests

* Add doc

* Fix init

* Update src/transformers/models/auto/processing_auto.py

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Reverts to tokenizer or feature extractor when available

* Adapt test

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

tests/test_processor_auto.py

@@ -0,0 +1,56 @@
+# coding=utf-8
+# Copyright 2021 the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# 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 transformers import AutoProcessor, BeitFeatureExtractor, BertTokenizerFast, Wav2Vec2Config, Wav2Vec2Processor
+from transformers.testing_utils import require_torch
+
+
+SAMPLE_PROCESSOR_CONFIG_DIR = os.path.join(os.path.dirname(os.path.abspath(__file__)), "fixtures")
+SAMPLE_PROCESSOR_CONFIG = os.path.join(
+    os.path.dirname(os.path.abspath(__file__)), "fixtures/dummy_feature_extractor_config.json"
+)
+SAMPLE_CONFIG = os.path.join(os.path.dirname(os.path.abspath(__file__)), "fixtures/dummy-config.json")
+
+
+class AutoFeatureExtractorTest(unittest.TestCase):
+    def test_processor_from_model_shortcut(self):
+        processor = AutoProcessor.from_pretrained("facebook/wav2vec2-base-960h")
+        self.assertIsInstance(processor, Wav2Vec2Processor)
+
+    def test_processor_from_local_directory_from_config(self):
+        with tempfile.TemporaryDirectory() as tmpdirname:
+            model_config = Wav2Vec2Config()
+            processor = AutoProcessor.from_pretrained("facebook/wav2vec2-base-960h")
+
+            # save in new folder
+            model_config.save_pretrained(tmpdirname)
+            processor.save_pretrained(tmpdirname)
+
+            processor = AutoProcessor.from_pretrained(tmpdirname)
+
+        self.assertIsInstance(processor, Wav2Vec2Processor)
+
+    def test_auto_processor_reverts_to_tokenizer(self):
+        processor = AutoProcessor.from_pretrained("bert-base-cased")
+        self.assertIsInstance(processor, BertTokenizerFast)
+
+    @require_torch
+    def test_auto_processor_reverts_to_feature_extractor(self):
+        processor = AutoProcessor.from_pretrained("microsoft/beit-base-patch16-224")
+        self.assertIsInstance(processor, BeitFeatureExtractor)