Trainer - deprecate tokenizer for processing_class (#32385)

* Trainer - deprecate tokenizer for processing_class

* Extend chage across Seq2Seq trainer and docs

* Add tests

* Update to FutureWarning and add deprecation version

examples/pytorch/speech-recognition/run_speech_recognition_ctc.py

@@ -751,7 +751,7 @@ def main():
         compute_metrics=compute_metrics,
         train_dataset=vectorized_datasets["train"] if training_args.do_train else None,
         eval_dataset=vectorized_datasets["eval"] if training_args.do_eval else None,
-        tokenizer=processor,
+        processing_class=processor,
         preprocess_logits_for_metrics=preprocess_logits_for_metrics,
     )
 

examples/pytorch/speech-recognition/run_speech_recognition_ctc_adapter.py

@@ -747,7 +747,7 @@ def main():
         compute_metrics=compute_metrics,
         train_dataset=vectorized_datasets["train"] if training_args.do_train else None,
         eval_dataset=vectorized_datasets["eval"] if training_args.do_eval else None,
-        tokenizer=processor,
+        processing_class=processor,
     )
 
     # 8. Finally, we can start training

examples/pytorch/speech-recognition/run_speech_recognition_seq2seq.py

@@ -569,7 +569,7 @@ def main():
         args=training_args,
         train_dataset=vectorized_datasets["train"] if training_args.do_train else None,
         eval_dataset=vectorized_datasets["eval"] if training_args.do_eval else None,
-        tokenizer=feature_extractor,
+        processing_class=feature_extractor,
         data_collator=data_collator,
         compute_metrics=compute_metrics if training_args.predict_with_generate else None,
     )