[ASR] Add official ASR CTC example to examples/pytorch/speech-recognition (#13620)

* up

* rename

* add asr example

* add auto feature extractor

* some more fixes

* correct layerdrop

* correct for multi-gpu dist

* clean up

* refactor

* refactor

* more fixes

* more fixes

* clean-up

* finish

* up

* Apply suggestions from code review

* fix isort

* update

* up

* add note

* apply surajs suggestions

* Apply suggestions from code review

Co-authored-by: Suraj Patil <surajp815@gmail.com>

* isort

* small change

* Apply suggestions from code review

Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

* Apply suggestions from code review

Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

* add hubert

* Update examples/pytorch/speech-recognition/run_speech_recognition_ctc.py

Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

examples/pytorch/test_examples.py

@@ -39,6 +39,7 @@ SRC_DIRS = [
         "summarization",
         "translation",
         "image-classification",
+        "speech-recognition",
     ]
 ]
 sys.path.extend(SRC_DIRS)
@@ -52,6 +53,7 @@ if SRC_DIRS is not None:
     import run_mlm
     import run_ner
     import run_qa as run_squad
+    import run_speech_recognition_ctc
     import run_summarization
     import run_swag
     import run_translation
@@ -374,3 +376,37 @@ class ExamplesTests(TestCasePlus):
             run_image_classification.main()
             result = get_results(tmp_dir)
             self.assertGreaterEqual(result["eval_accuracy"], 0.8)
+
+    def test_run_speech_recognition_ctc(self):
+        stream_handler = logging.StreamHandler(sys.stdout)
+        logger.addHandler(stream_handler)
+
+        tmp_dir = self.get_auto_remove_tmp_dir()
+        testargs = f"""
+            run_speech_recognition_ctc.py
+            --output_dir {tmp_dir}
+            --model_name_or_path hf-internal-testing/tiny-random-wav2vec2
+            --dataset_name patrickvonplaten/librispeech_asr_dummy
+            --dataset_config_name clean
+            --train_split_name validation
+            --eval_split_name validation
+            --audio_column_name file
+            --do_train
+            --do_eval
+            --learning_rate 1e-4
+            --per_device_train_batch_size 2
+            --per_device_eval_batch_size 1
+            --remove_unused_columns False
+            --overwrite_output_dir True
+            --preprocessing_num_workers 16
+            --max_steps 10
+            --seed 42
+        """.split()
+
+        if is_cuda_and_apex_available():
+            testargs.append("--fp16")
+
+        with patch.object(sys, "argv", testargs):
+            run_speech_recognition_ctc.main()
+            result = get_results(tmp_dir)
+            self.assertLess(result["eval_loss"], result["train_loss"])