[Trainer] Allow passing image processor (#29896)

* Add image processor to trainer

* Replace tokenizer=image_processor everywhere

src/transformers/trainer_callback.py

@@ -189,6 +189,8 @@ class TrainerCallback:
             The model being trained.
         tokenizer ([`PreTrainedTokenizer`]):
             The tokenizer used for encoding the data.
+        image_processor ([`BaseImageProcessor`]):
+            The image processor used for encoding the images.
         optimizer (`torch.optim.Optimizer`):
             The optimizer used for the training steps.
         lr_scheduler (`torch.optim.lr_scheduler.LambdaLR`):
@@ -307,12 +309,13 @@ class TrainerCallback:
 class CallbackHandler(TrainerCallback):
     """Internal class that just calls the list of callbacks in order."""
 
-    def __init__(self, callbacks, model, tokenizer, optimizer, lr_scheduler):
+    def __init__(self, callbacks, model, tokenizer, image_processor, optimizer, lr_scheduler):
         self.callbacks = []
         for cb in callbacks:
             self.add_callback(cb)
         self.model = model
         self.tokenizer = tokenizer
+        self.image_processor = image_processor
         self.optimizer = optimizer
         self.lr_scheduler = lr_scheduler
         self.train_dataloader = None
@@ -417,6 +420,7 @@ class CallbackHandler(TrainerCallback):
                 control,
                 model=self.model,
                 tokenizer=self.tokenizer,
+                image_processor=self.image_processor,
                 optimizer=self.optimizer,
                 lr_scheduler=self.lr_scheduler,
                 train_dataloader=self.train_dataloader,