diff --git a/src/transformers/models/blip/processing_blip.py b/src/transformers/models/blip/processing_blip.py
index 7fc154f3483e..f600e8ce27d8 100644
--- a/src/transformers/models/blip/processing_blip.py
+++ b/src/transformers/models/blip/processing_blip.py
@@ -60,7 +60,6 @@ class BlipProcessor(ProcessorMixin):
     def __init__(self, image_processor, tokenizer, **kwargs):
         tokenizer.return_token_type_ids = False
         super().__init__(image_processor, tokenizer)
-        self.current_processor = self.image_processor
 
     def __call__(
         self,
diff --git a/src/transformers/models/blip_2/processing_blip_2.py b/src/transformers/models/blip_2/processing_blip_2.py
index abbbeb6ae0a4..40729f4f4501 100644
--- a/src/transformers/models/blip_2/processing_blip_2.py
+++ b/src/transformers/models/blip_2/processing_blip_2.py
@@ -66,7 +66,6 @@ class Blip2Processor(ProcessorMixin):
 
     def __init__(self, image_processor, tokenizer, num_query_tokens=None, **kwargs):
         tokenizer.return_token_type_ids = False
-        self.current_processor = image_processor
         if not hasattr(tokenizer, "image_token"):
             self.image_token = AddedToken("<image>", normalized=False, special=True)
             tokenizer.add_tokens([self.image_token], special_tokens=True)
diff --git a/src/transformers/models/chinese_clip/processing_chinese_clip.py b/src/transformers/models/chinese_clip/processing_chinese_clip.py
index c6fb9f9df247..0510b9b0f3c9 100644
--- a/src/transformers/models/chinese_clip/processing_chinese_clip.py
+++ b/src/transformers/models/chinese_clip/processing_chinese_clip.py
@@ -16,8 +16,6 @@
 Image/Text processor class for Chinese-CLIP
 """
 
-import warnings
-
 from ...processing_utils import ProcessorMixin
 
 
@@ -41,27 +39,7 @@ class ChineseCLIPProcessor(ProcessorMixin):
     tokenizer_class = ("BertTokenizer", "BertTokenizerFast")
 
     def __init__(self, image_processor=None, tokenizer=None, **kwargs):
-        feature_extractor = None
-        if "feature_extractor" in kwargs:
-            warnings.warn(
-                "The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"
-                " instead.",
-                FutureWarning,
-            )
-            feature_extractor = kwargs.pop("feature_extractor")
-
-        image_processor = image_processor if image_processor is not None else feature_extractor
-
         super().__init__(image_processor, tokenizer)
-        self.current_processor = self.image_processor
-
-    @property
-    def feature_extractor_class(self):
-        warnings.warn(
-            "`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.",
-            FutureWarning,
-        )
-        return self.image_processor_class
 
 
 __all__ = ["ChineseCLIPProcessor"]
diff --git a/src/transformers/models/clip/processing_clip.py b/src/transformers/models/clip/processing_clip.py
index 893346e798bb..7b856f9981ee 100644
--- a/src/transformers/models/clip/processing_clip.py
+++ b/src/transformers/models/clip/processing_clip.py
@@ -16,8 +16,6 @@
 Image/Text processor class for CLIP
 """
 
-import warnings
-
 from ...processing_utils import ProcessorMixin
 
 
@@ -40,34 +38,7 @@ class CLIPProcessor(ProcessorMixin):
     tokenizer_class = "AutoTokenizer"
 
     def __init__(self, image_processor=None, tokenizer=None, **kwargs):
-        feature_extractor = None
-        if "feature_extractor" in kwargs:
-            warnings.warn(
-                "The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"
-                " instead.",
-                FutureWarning,
-            )
-            feature_extractor = kwargs.pop("feature_extractor")
-
-        image_processor = image_processor if image_processor is not None else feature_extractor
-
         super().__init__(image_processor, tokenizer)
 
-    @property
-    def feature_extractor_class(self):
-        warnings.warn(
-            "`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.",
-            FutureWarning,
-        )
-        return self.image_processor_class
-
-    @property
-    def feature_extractor(self):
-        warnings.warn(
-            "`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.",
-            FutureWarning,
-        )
-        return self.image_processor
-
 
 __all__ = ["CLIPProcessor"]
diff --git a/src/transformers/models/clipseg/processing_clipseg.py b/src/transformers/models/clipseg/processing_clipseg.py
index e8cd47b0aa54..39e091106c71 100644
--- a/src/transformers/models/clipseg/processing_clipseg.py
+++ b/src/transformers/models/clipseg/processing_clipseg.py
@@ -16,8 +16,6 @@
 Image/Text processor class for CLIPSeg
 """
 
-import warnings
-
 from ...processing_utils import ProcessorMixin
 from ...tokenization_utils_base import BatchEncoding
 
@@ -41,17 +39,6 @@ class CLIPSegProcessor(ProcessorMixin):
     tokenizer_class = ("CLIPTokenizer", "CLIPTokenizerFast")
 
     def __init__(self, image_processor=None, tokenizer=None, **kwargs):
-        feature_extractor = None
-        if "feature_extractor" in kwargs:
-            warnings.warn(
-                "The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"
-                " instead.",
-                FutureWarning,
-            )
-            feature_extractor = kwargs.pop("feature_extractor")
-
-        image_processor = image_processor if image_processor is not None else feature_extractor
-
         super().__init__(image_processor, tokenizer)
 
     def __call__(self, text=None, images=None, visual_prompt=None, return_tensors=None, **kwargs):
@@ -124,21 +111,5 @@ def __call__(self, text=None, images=None, visual_prompt=None, return_tensors=No
         else:
             return BatchEncoding(data=dict(**image_features), tensor_type=return_tensors)
 
-    @property
-    def feature_extractor_class(self):
-        warnings.warn(
-            "`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.",
-            FutureWarning,
-        )
-        return self.image_processor_class
-
-    @property
-    def feature_extractor(self):
-        warnings.warn(
-            "`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.",
-            FutureWarning,
-        )
-        return self.image_processor
-
 
 __all__ = ["CLIPSegProcessor"]
diff --git a/src/transformers/models/donut/processing_donut.py b/src/transformers/models/donut/processing_donut.py
index a545c90539b9..65ca58bcf781 100644
--- a/src/transformers/models/donut/processing_donut.py
+++ b/src/transformers/models/donut/processing_donut.py
@@ -17,8 +17,6 @@
 """
 
 import re
-import warnings
-from contextlib import contextmanager
 from typing import Optional, Union
 
 from ...image_utils import ImageInput
@@ -55,20 +53,7 @@ class DonutProcessor(ProcessorMixin):
     tokenizer_class = "AutoTokenizer"
 
     def __init__(self, image_processor=None, tokenizer=None, **kwargs):
-        feature_extractor = None
-        if "feature_extractor" in kwargs:
-            warnings.warn(
-                "The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"
-                " instead.",
-                FutureWarning,
-            )
-            feature_extractor = kwargs.pop("feature_extractor")
-
-        image_processor = image_processor if image_processor is not None else feature_extractor
-
         super().__init__(image_processor, tokenizer)
-        self.current_processor = self.image_processor
-        self._in_target_context_manager = False
 
     def __call__(
         self,
@@ -82,9 +67,6 @@ def __call__(
         [`~DonutProcessor.as_target_processor`] this method forwards all its arguments to DonutTokenizer's
         [`~DonutTokenizer.__call__`]. Please refer to the docstring of the above two methods for more information.
         """
-        if self._in_target_context_manager:
-            return self.current_processor(images, text, **kwargs)
-
         if images is None and text is None:
             raise ValueError("You need to specify either an `images` or `text` input to process.")
 
@@ -116,22 +98,6 @@ def model_input_names(self):
 
         return list(image_processor_input_names + ["input_ids", "labels"])
 
-    @contextmanager
-    def as_target_processor(self):
-        """
-        Temporarily sets the tokenizer for processing the input. Useful for encoding the labels when fine-tuning TrOCR.
-        """
-        warnings.warn(
-            "`as_target_processor` is deprecated and will be removed in v5 of Transformers. You can process your "
-            "labels by using the argument `text` of the regular `__call__` method (either in the same call as "
-            "your images inputs, or in a separate call."
-        )
-        self._in_target_context_manager = True
-        self.current_processor = self.tokenizer
-        yield
-        self.current_processor = self.image_processor
-        self._in_target_context_manager = False
-
     def token2json(self, tokens, is_inner_value=False, added_vocab=None):
         """
         Convert a (generated) token sequence into an ordered JSON format.
@@ -190,21 +156,5 @@ def token2json(self, tokens, is_inner_value=False, added_vocab=None):
         else:
             return [] if is_inner_value else {"text_sequence": tokens}
 
-    @property
-    def feature_extractor_class(self):
-        warnings.warn(
-            "`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.",
-            FutureWarning,
-        )
-        return self.image_processor_class
-
-    @property
-    def feature_extractor(self):
-        warnings.warn(
-            "`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.",
-            FutureWarning,
-        )
-        return self.image_processor
-
 
 __all__ = ["DonutProcessor"]
diff --git a/src/transformers/models/flava/processing_flava.py b/src/transformers/models/flava/processing_flava.py
index 8e8a806e8615..272fb01d7b7a 100644
--- a/src/transformers/models/flava/processing_flava.py
+++ b/src/transformers/models/flava/processing_flava.py
@@ -16,8 +16,6 @@
 Image/Text processor class for FLAVA
 """
 
-import warnings
-
 from ...processing_utils import ProcessorMixin
 
 
@@ -38,34 +36,7 @@ class FlavaProcessor(ProcessorMixin):
     tokenizer_class = ("BertTokenizer", "BertTokenizerFast")
 
     def __init__(self, image_processor=None, tokenizer=None, **kwargs):
-        feature_extractor = None
-        if "feature_extractor" in kwargs:
-            warnings.warn(
-                "The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"
-                " instead.",
-                FutureWarning,
-            )
-            feature_extractor = kwargs.pop("feature_extractor")
-
-        image_processor = image_processor if image_processor is not None else feature_extractor
         super().__init__(image_processor, tokenizer)
-        self.current_processor = self.image_processor
-
-    @property
-    def feature_extractor_class(self):
-        warnings.warn(
-            "`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.",
-            FutureWarning,
-        )
-        return self.image_processor_class
-
-    @property
-    def feature_extractor(self):
-        warnings.warn(
-            "`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.",
-            FutureWarning,
-        )
-        return self.image_processor
 
 
 __all__ = ["FlavaProcessor"]
diff --git a/src/transformers/models/fuyu/processing_fuyu.py b/src/transformers/models/fuyu/processing_fuyu.py
index 75b2bbad926e..a715ce412313 100644
--- a/src/transformers/models/fuyu/processing_fuyu.py
+++ b/src/transformers/models/fuyu/processing_fuyu.py
@@ -531,7 +531,6 @@ def __call__(
 
         if text is not None and images is None:
             logger.warning("You are processing a text with no associated image. Make sure it is intended.")
-            self.current_processor = self.tokenizer
             text_encoding = self.tokenizer(text, **output_kwargs["text_kwargs"])
             return text_encoding
 
diff --git a/src/transformers/models/git/processing_git.py b/src/transformers/models/git/processing_git.py
index 20fae1a9f36b..2eba7c68f584 100644
--- a/src/transformers/models/git/processing_git.py
+++ b/src/transformers/models/git/processing_git.py
@@ -39,7 +39,6 @@ class GitProcessor(ProcessorMixin):
 
     def __init__(self, image_processor, tokenizer):
         super().__init__(image_processor, tokenizer)
-        self.current_processor = self.image_processor
 
 
 __all__ = ["GitProcessor"]
diff --git a/src/transformers/models/idefics/processing_idefics.py b/src/transformers/models/idefics/processing_idefics.py
index 4b5ccaffe5c8..b0ad20df386b 100644
--- a/src/transformers/models/idefics/processing_idefics.py
+++ b/src/transformers/models/idefics/processing_idefics.py
@@ -159,7 +159,6 @@ class IdeficsProcessor(ProcessorMixin):
 
     def __init__(self, image_processor, tokenizer=None, image_size=224, add_end_of_utterance_token=None, **kwargs):
         super().__init__(image_processor, tokenizer)
-        self.current_processor = self.image_processor
         self.image_token_id = (
             tokenizer.image_token_id
             if hasattr(tokenizer, "image_token")
diff --git a/src/transformers/models/layoutlmv2/processing_layoutlmv2.py b/src/transformers/models/layoutlmv2/processing_layoutlmv2.py
index 603cdf4df4e9..0a6ea0d20030 100644
--- a/src/transformers/models/layoutlmv2/processing_layoutlmv2.py
+++ b/src/transformers/models/layoutlmv2/processing_layoutlmv2.py
@@ -16,7 +16,6 @@
 Processor class for LayoutLMv2.
 """
 
-import warnings
 from typing import Optional, Union
 
 from ...processing_utils import ProcessorMixin
@@ -49,17 +48,6 @@ class LayoutLMv2Processor(ProcessorMixin):
     tokenizer_class = ("LayoutLMv2Tokenizer", "LayoutLMv2TokenizerFast")
 
     def __init__(self, image_processor=None, tokenizer=None, **kwargs):
-        feature_extractor = None
-        if "feature_extractor" in kwargs:
-            warnings.warn(
-                "The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"
-                " instead.",
-                FutureWarning,
-            )
-            feature_extractor = kwargs.pop("feature_extractor")
-
-        image_processor = image_processor if image_processor is not None else feature_extractor
-
         super().__init__(image_processor, tokenizer)
 
     def __call__(
@@ -166,21 +154,5 @@ def get_overflowing_images(self, images, overflow_to_sample_mapping):
     def model_input_names(self):
         return ["input_ids", "bbox", "token_type_ids", "attention_mask", "image"]
 
-    @property
-    def feature_extractor_class(self):
-        warnings.warn(
-            "`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.",
-            FutureWarning,
-        )
-        return self.image_processor_class
-
-    @property
-    def feature_extractor(self):
-        warnings.warn(
-            "`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.",
-            FutureWarning,
-        )
-        return self.image_processor
-
 
 __all__ = ["LayoutLMv2Processor"]
diff --git a/src/transformers/models/layoutlmv3/processing_layoutlmv3.py b/src/transformers/models/layoutlmv3/processing_layoutlmv3.py
index 1f1b6cead607..f4a2906b5985 100644
--- a/src/transformers/models/layoutlmv3/processing_layoutlmv3.py
+++ b/src/transformers/models/layoutlmv3/processing_layoutlmv3.py
@@ -16,7 +16,6 @@
 Processor class for LayoutLMv3.
 """
 
-import warnings
 from typing import Optional, Union
 
 from ...processing_utils import ProcessorMixin
@@ -49,17 +48,6 @@ class LayoutLMv3Processor(ProcessorMixin):
     tokenizer_class = ("LayoutLMv3Tokenizer", "LayoutLMv3TokenizerFast")
 
     def __init__(self, image_processor=None, tokenizer=None, **kwargs):
-        feature_extractor = None
-        if "feature_extractor" in kwargs:
-            warnings.warn(
-                "The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"
-                " instead.",
-                FutureWarning,
-            )
-            feature_extractor = kwargs.pop("feature_extractor")
-
-        image_processor = image_processor if image_processor is not None else feature_extractor
-
         super().__init__(image_processor, tokenizer)
 
     def __call__(
@@ -164,21 +152,5 @@ def get_overflowing_images(self, images, overflow_to_sample_mapping):
     def model_input_names(self):
         return ["input_ids", "bbox", "attention_mask", "pixel_values"]
 
-    @property
-    def feature_extractor_class(self):
-        warnings.warn(
-            "`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.",
-            FutureWarning,
-        )
-        return self.image_processor_class
-
-    @property
-    def feature_extractor(self):
-        warnings.warn(
-            "`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.",
-            FutureWarning,
-        )
-        return self.image_processor
-
 
 __all__ = ["LayoutLMv3Processor"]
diff --git a/src/transformers/models/layoutxlm/processing_layoutxlm.py b/src/transformers/models/layoutxlm/processing_layoutxlm.py
index e3ece89f434b..8e6ef52f6c0f 100644
--- a/src/transformers/models/layoutxlm/processing_layoutxlm.py
+++ b/src/transformers/models/layoutxlm/processing_layoutxlm.py
@@ -16,7 +16,6 @@
 Processor class for LayoutXLM.
 """
 
-import warnings
 from typing import Optional, Union
 
 from ...processing_utils import ProcessorMixin
@@ -49,16 +48,6 @@ class LayoutXLMProcessor(ProcessorMixin):
     tokenizer_class = ("LayoutXLMTokenizer", "LayoutXLMTokenizerFast")
 
     def __init__(self, image_processor=None, tokenizer=None, **kwargs):
-        if "feature_extractor" in kwargs:
-            warnings.warn(
-                "The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"
-                " instead.",
-                FutureWarning,
-            )
-            feature_extractor = kwargs.pop("feature_extractor")
-
-        image_processor = image_processor if image_processor is not None else feature_extractor
-
         super().__init__(image_processor, tokenizer)
 
     def __call__(
@@ -165,21 +154,5 @@ def get_overflowing_images(self, images, overflow_to_sample_mapping):
     def model_input_names(self):
         return ["input_ids", "bbox", "attention_mask", "image"]
 
-    @property
-    def feature_extractor_class(self):
-        warnings.warn(
-            "`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.",
-            FutureWarning,
-        )
-        return self.image_processor_class
-
-    @property
-    def feature_extractor(self):
-        warnings.warn(
-            "`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.",
-            FutureWarning,
-        )
-        return self.image_processor
-
 
 __all__ = ["LayoutXLMProcessor"]
diff --git a/src/transformers/models/mgp_str/processing_mgp_str.py b/src/transformers/models/mgp_str/processing_mgp_str.py
index 8f7d32388748..349e075c7996 100644
--- a/src/transformers/models/mgp_str/processing_mgp_str.py
+++ b/src/transformers/models/mgp_str/processing_mgp_str.py
@@ -14,8 +14,6 @@
 # limitations under the License.
 """Processor class for MGP-STR."""
 
-import warnings
-
 from transformers import AutoTokenizer
 from transformers.utils import is_torch_available
 from transformers.utils.generic import ExplicitEnum
@@ -57,17 +55,6 @@ class MgpstrProcessor(ProcessorMixin):
     char_tokenizer_class = "MgpstrTokenizer"
 
     def __init__(self, image_processor=None, tokenizer=None, **kwargs):
-        feature_extractor = None
-        if "feature_extractor" in kwargs:
-            warnings.warn(
-                "The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"
-                " instead.",
-                FutureWarning,
-            )
-            feature_extractor = kwargs.pop("feature_extractor")
-
-        image_processor = image_processor if image_processor is not None else feature_extractor
-
         self.char_tokenizer = tokenizer
         self.bpe_tokenizer = AutoTokenizer.from_pretrained("openai-community/gpt2")
         self.wp_tokenizer = AutoTokenizer.from_pretrained("google-bert/bert-base-uncased")
diff --git a/src/transformers/models/musicgen/processing_musicgen.py b/src/transformers/models/musicgen/processing_musicgen.py
index e2bcbf373d48..030013d34f98 100644
--- a/src/transformers/models/musicgen/processing_musicgen.py
+++ b/src/transformers/models/musicgen/processing_musicgen.py
@@ -44,8 +44,6 @@ class MusicgenProcessor(ProcessorMixin):
 
     def __init__(self, feature_extractor, tokenizer):
         super().__init__(feature_extractor, tokenizer)
-        self.current_processor = self.feature_extractor
-        self._in_target_context_manager = False
 
     def get_decoder_prompt_ids(self, task=None, language=None, no_timestamps=True):
         return self.tokenizer.get_decoder_prompt_ids(task=task, language=language, no_timestamps=no_timestamps)
@@ -56,10 +54,6 @@ def __call__(self, *args, **kwargs):
         argument to [`~T5Tokenizer.__call__`]. Please refer to the docstring of the above two methods for more
         information.
         """
-        # For backward compatibility
-        if self._in_target_context_manager:
-            return self.current_processor(*args, **kwargs)
-
         if len(args) > 0:
             kwargs["audio"] = args[0]
         return super().__call__(*args, **kwargs)
diff --git a/src/transformers/models/nougat/processing_nougat.py b/src/transformers/models/nougat/processing_nougat.py
index 2815dcfa7b7a..b0b6d665bd22 100644
--- a/src/transformers/models/nougat/processing_nougat.py
+++ b/src/transformers/models/nougat/processing_nougat.py
@@ -44,7 +44,6 @@ class NougatProcessor(ProcessorMixin):
 
     def __init__(self, image_processor, tokenizer):
         super().__init__(image_processor, tokenizer)
-        self.current_processor = self.image_processor
 
     def __call__(
         self,
diff --git a/src/transformers/models/owlvit/processing_owlvit.py b/src/transformers/models/owlvit/processing_owlvit.py
index e7fb401d9a76..e6715e9688b9 100644
--- a/src/transformers/models/owlvit/processing_owlvit.py
+++ b/src/transformers/models/owlvit/processing_owlvit.py
@@ -71,17 +71,6 @@ class OwlViTProcessor(ProcessorMixin):
     tokenizer_class = ("CLIPTokenizer", "CLIPTokenizerFast")
 
     def __init__(self, image_processor=None, tokenizer=None, **kwargs):
-        feature_extractor = None
-        if "feature_extractor" in kwargs:
-            warnings.warn(
-                "The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"
-                " instead.",
-                FutureWarning,
-            )
-            feature_extractor = kwargs.pop("feature_extractor")
-
-        image_processor = image_processor if image_processor is not None else feature_extractor
-
         super().__init__(image_processor, tokenizer)
 
     def __call__(
@@ -283,21 +272,5 @@ def post_process_image_guided_detection(
             outputs=outputs, threshold=threshold, nms_threshold=nms_threshold, target_sizes=target_sizes
         )
 
-    @property
-    def feature_extractor_class(self):
-        warnings.warn(
-            "`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.",
-            FutureWarning,
-        )
-        return self.image_processor_class
-
-    @property
-    def feature_extractor(self):
-        warnings.warn(
-            "`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.",
-            FutureWarning,
-        )
-        return self.image_processor
-
 
 __all__ = ["OwlViTProcessor"]
diff --git a/src/transformers/models/pix2struct/processing_pix2struct.py b/src/transformers/models/pix2struct/processing_pix2struct.py
index fba2fe93ef19..25667f09ad81 100644
--- a/src/transformers/models/pix2struct/processing_pix2struct.py
+++ b/src/transformers/models/pix2struct/processing_pix2struct.py
@@ -95,7 +95,6 @@ def __call__(
             output_kwargs["text_kwargs"]["add_special_tokens"] = (
                 add_special_tokens if add_special_tokens is not None else True
             )
-            self.current_processor = self.tokenizer
             text_encoding = self.tokenizer(text=text, **output_kwargs["text_kwargs"])
             return text_encoding
 
diff --git a/src/transformers/models/speech_to_text/processing_speech_to_text.py b/src/transformers/models/speech_to_text/processing_speech_to_text.py
index 2df5808b9f66..3cfe31c6547a 100644
--- a/src/transformers/models/speech_to_text/processing_speech_to_text.py
+++ b/src/transformers/models/speech_to_text/processing_speech_to_text.py
@@ -17,7 +17,6 @@
 """
 
 import warnings
-from contextlib import contextmanager
 
 from ...processing_utils import ProcessorMixin
 
@@ -43,8 +42,6 @@ class Speech2TextProcessor(ProcessorMixin):
 
     def __init__(self, feature_extractor, tokenizer):
         super().__init__(feature_extractor, tokenizer)
-        self.current_processor = self.feature_extractor
-        self._in_target_context_manager = False
 
     def __call__(self, *args, **kwargs):
         """
@@ -54,10 +51,6 @@ def __call__(self, *args, **kwargs):
         [`~Speech2TextTokenizer.__call__`]. Please refer to the docstring of the above two methods for more
         information.
         """
-        # For backward compatibility
-        if self._in_target_context_manager:
-            return self.current_processor(*args, **kwargs)
-
         if "raw_speech" in kwargs:
             warnings.warn("Using `raw_speech` as a keyword argument is deprecated. Use `audio` instead.")
             audio = kwargs.pop("raw_speech")
@@ -85,22 +78,5 @@ def __call__(self, *args, **kwargs):
             inputs["labels"] = encodings["input_ids"]
             return inputs
 
-    @contextmanager
-    def as_target_processor(self):
-        """
-        Temporarily sets the tokenizer for processing the input. Useful for encoding the labels when fine-tuning
-        Speech2Text.
-        """
-        warnings.warn(
-            "`as_target_processor` is deprecated and will be removed in v5 of Transformers. You can process your "
-            "labels by using the argument `text` of the regular `__call__` method (either in the same call as "
-            "your audio inputs, or in a separate call."
-        )
-        self._in_target_context_manager = True
-        self.current_processor = self.tokenizer
-        yield
-        self.current_processor = self.feature_extractor
-        self._in_target_context_manager = False
-
 
 __all__ = ["Speech2TextProcessor"]
diff --git a/src/transformers/models/trocr/processing_trocr.py b/src/transformers/models/trocr/processing_trocr.py
index 81c7db2850b3..037f708e4ee4 100644
--- a/src/transformers/models/trocr/processing_trocr.py
+++ b/src/transformers/models/trocr/processing_trocr.py
@@ -16,8 +16,6 @@
 Processor class for TrOCR.
 """
 
-import warnings
-from contextlib import contextmanager
 from typing import Optional, Union
 
 from ...image_processing_utils import BatchFeature
@@ -50,20 +48,7 @@ class TrOCRProcessor(ProcessorMixin):
     tokenizer_class = "AutoTokenizer"
 
     def __init__(self, image_processor=None, tokenizer=None, **kwargs):
-        feature_extractor = None
-        if "feature_extractor" in kwargs:
-            warnings.warn(
-                "The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"
-                " instead.",
-                FutureWarning,
-            )
-            feature_extractor = kwargs.pop("feature_extractor")
-
-        image_processor = image_processor if image_processor is not None else feature_extractor
-
         super().__init__(image_processor, tokenizer)
-        self.current_processor = self.image_processor
-        self._in_target_context_manager = False
 
     def __call__(
         self,
@@ -77,10 +62,6 @@ def __call__(
         [`~TrOCRProcessor.as_target_processor`] this method forwards all its arguments to TrOCRTokenizer's
         [`~TrOCRTokenizer.__call__`]. Please refer to the docstring of the above two methods for more information.
         """
-        # For backward compatibility
-        if self._in_target_context_manager:
-            return self.current_processor(images, **kwargs)
-
         if images is None and text is None:
             raise ValueError("You need to specify either an `images` or `text` input to process.")
 
@@ -108,37 +89,5 @@ def model_input_names(self):
         image_processor_input_names = self.image_processor.model_input_names
         return image_processor_input_names + ["labels"]
 
-    @contextmanager
-    def as_target_processor(self):
-        """
-        Temporarily sets the tokenizer for processing the input. Useful for encoding the labels when fine-tuning TrOCR.
-        """
-        warnings.warn(
-            "`as_target_processor` is deprecated and will be removed in v5 of Transformers. You can process your "
-            "labels by using the argument `text` of the regular `__call__` method (either in the same call as "
-            "your images inputs, or in a separate call."
-        )
-        self._in_target_context_manager = True
-        self.current_processor = self.tokenizer
-        yield
-        self.current_processor = self.image_processor
-        self._in_target_context_manager = False
-
-    @property
-    def feature_extractor_class(self):
-        warnings.warn(
-            "`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.",
-            FutureWarning,
-        )
-        return self.image_processor_class
-
-    @property
-    def feature_extractor(self):
-        warnings.warn(
-            "`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.",
-            FutureWarning,
-        )
-        return self.image_processor
-
 
 __all__ = ["TrOCRProcessor"]
diff --git a/src/transformers/models/vilt/processing_vilt.py b/src/transformers/models/vilt/processing_vilt.py
index 5b5126ad4a85..ceda264a5345 100644
--- a/src/transformers/models/vilt/processing_vilt.py
+++ b/src/transformers/models/vilt/processing_vilt.py
@@ -16,8 +16,6 @@
 Processor class for ViLT.
 """
 
-import warnings
-
 from ...processing_utils import ProcessingKwargs, ProcessorMixin
 
 
@@ -56,34 +54,7 @@ class ViltProcessor(ProcessorMixin):
     valid_processor_kwargs = ViltProcessorKwargs
 
     def __init__(self, image_processor=None, tokenizer=None, **kwargs):
-        feature_extractor = None
-        if "feature_extractor" in kwargs:
-            warnings.warn(
-                "The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"
-                " instead.",
-                FutureWarning,
-            )
-            feature_extractor = kwargs.pop("feature_extractor")
-
-        image_processor = image_processor if image_processor is not None else feature_extractor
         super().__init__(image_processor, tokenizer)
-        self.current_processor = self.image_processor
-
-    @property
-    def feature_extractor_class(self):
-        warnings.warn(
-            "`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.",
-            FutureWarning,
-        )
-        return self.image_processor_class
-
-    @property
-    def feature_extractor(self):
-        warnings.warn(
-            "`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.",
-            FutureWarning,
-        )
-        return self.image_processor
 
 
 __all__ = ["ViltProcessor"]
diff --git a/src/transformers/models/vision_text_dual_encoder/processing_vision_text_dual_encoder.py b/src/transformers/models/vision_text_dual_encoder/processing_vision_text_dual_encoder.py
index 7bfe3e980ef0..b98f2ac3f373 100644
--- a/src/transformers/models/vision_text_dual_encoder/processing_vision_text_dual_encoder.py
+++ b/src/transformers/models/vision_text_dual_encoder/processing_vision_text_dual_encoder.py
@@ -16,8 +16,6 @@
 Processor class for VisionTextDualEncoder
 """
 
-import warnings
-
 from ...processing_utils import ProcessingKwargs, ProcessorMixin
 
 
@@ -46,34 +44,7 @@ class VisionTextDualEncoderProcessor(ProcessorMixin):
     tokenizer_class = "AutoTokenizer"
 
     def __init__(self, image_processor=None, tokenizer=None, **kwargs):
-        feature_extractor = None
-        if "feature_extractor" in kwargs:
-            warnings.warn(
-                "The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"
-                " instead.",
-                FutureWarning,
-            )
-            feature_extractor = kwargs.pop("feature_extractor")
-
-        image_processor = image_processor if image_processor is not None else feature_extractor
         super().__init__(image_processor, tokenizer)
-        self.current_processor = self.image_processor
-
-    @property
-    def feature_extractor_class(self):
-        warnings.warn(
-            "`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.",
-            FutureWarning,
-        )
-        return self.image_processor_class
-
-    @property
-    def feature_extractor(self):
-        warnings.warn(
-            "`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.",
-            FutureWarning,
-        )
-        return self.image_processor
 
 
 __all__ = ["VisionTextDualEncoderProcessor"]
diff --git a/src/transformers/models/wav2vec2/processing_wav2vec2.py b/src/transformers/models/wav2vec2/processing_wav2vec2.py
index ee8e3abd195d..642151e24fed 100644
--- a/src/transformers/models/wav2vec2/processing_wav2vec2.py
+++ b/src/transformers/models/wav2vec2/processing_wav2vec2.py
@@ -17,7 +17,6 @@
 """
 
 import warnings
-from contextlib import contextmanager
 from typing import Optional, Union
 
 from ...processing_utils import ProcessingKwargs, ProcessorMixin, Unpack
@@ -50,8 +49,6 @@ class Wav2Vec2Processor(ProcessorMixin):
 
     def __init__(self, feature_extractor, tokenizer):
         super().__init__(feature_extractor, tokenizer)
-        self.current_processor = self.feature_extractor
-        self._in_target_context_manager = False
 
     @classmethod
     def from_pretrained(cls, pretrained_model_name_or_path, **kwargs):
@@ -104,13 +101,6 @@ def __call__(
             tokenizer_init_kwargs=self.tokenizer.init_kwargs,
             **kwargs,
         )
-        # For backward compatibility
-        if self._in_target_context_manager:
-            return self.current_processor(
-                audio,
-                **output_kwargs["audio_kwargs"],
-                **output_kwargs["text_kwargs"],
-            )
 
         if audio is not None:
             inputs = self.feature_extractor(audio, **output_kwargs["audio_kwargs"])
@@ -139,10 +129,6 @@ def pad(self, *args, **kwargs):
         Returns:
             This method returns the results of each `pad` method. If both are used, the output is a dictionary containing the results of both.
         """
-        # For backward compatibility
-        if self._in_target_context_manager:
-            return self.current_processor.pad(*args, **kwargs)
-
         input_features = kwargs.pop("input_features", None)
         labels = kwargs.pop("labels", None)
         if len(args) > 0:
@@ -168,22 +154,5 @@ def model_input_names(self):
         feature_extractor_input_names = self.feature_extractor.model_input_names
         return feature_extractor_input_names + ["labels"]
 
-    @contextmanager
-    def as_target_processor(self):
-        """
-        Temporarily sets the tokenizer for processing the input. Useful for encoding the labels when fine-tuning
-        Wav2Vec2.
-        """
-        warnings.warn(
-            "`as_target_processor` is deprecated and will be removed in v5 of Transformers. You can process your "
-            "labels by using the argument `text` of the regular `__call__` method (either in the same call as "
-            "your audio inputs, or in a separate call."
-        )
-        self._in_target_context_manager = True
-        self.current_processor = self.tokenizer
-        yield
-        self.current_processor = self.feature_extractor
-        self._in_target_context_manager = False
-
 
 __all__ = ["Wav2Vec2Processor"]
diff --git a/src/transformers/models/wav2vec2_with_lm/processing_wav2vec2_with_lm.py b/src/transformers/models/wav2vec2_with_lm/processing_wav2vec2_with_lm.py
index beb22ca86749..f5605ea6c5b5 100644
--- a/src/transformers/models/wav2vec2_with_lm/processing_wav2vec2_with_lm.py
+++ b/src/transformers/models/wav2vec2_with_lm/processing_wav2vec2_with_lm.py
@@ -19,7 +19,7 @@
 import os
 import warnings
 from collections.abc import Iterable
-from contextlib import contextmanager, nullcontext
+from contextlib import nullcontext
 from dataclasses import dataclass
 from multiprocessing import Pool, get_context, get_start_method
 from typing import TYPE_CHECKING, Optional, Union
@@ -110,8 +110,6 @@ def __init__(
             )
 
         self.decoder = decoder
-        self.current_processor = self.feature_extractor
-        self._in_target_context_manager = False
 
     def save_pretrained(self, save_directory):
         super().save_pretrained(save_directory)
@@ -227,10 +225,6 @@ def __call__(self, *args, **kwargs):
         Wav2Vec2CTCTokenizer's [`~Wav2Vec2CTCTokenizer.__call__`]. Please refer to the docstring of the above two
         methods for more information.
         """
-        # For backward compatibility
-        if self._in_target_context_manager:
-            return self.current_processor(*args, **kwargs)
-
         if "raw_speech" in kwargs:
             warnings.warn("Using `raw_speech` as a keyword argument is deprecated. Use `audio` instead.")
             audio = kwargs.pop("raw_speech")
@@ -266,10 +260,6 @@ def pad(self, *args, **kwargs):
         Wav2Vec2CTCTokenizer's [`~Wav2Vec2CTCTokenizer.pad`]. Please refer to the docstring of the above two methods
         for more information.
         """
-        # For backward compatibility
-        if self._in_target_context_manager:
-            return self.current_processor.pad(*args, **kwargs)
-
         input_features = kwargs.pop("input_features", None)
         labels = kwargs.pop("labels", None)
         if len(args) > 0:
@@ -638,22 +628,5 @@ def decode(
                 word_offsets=word_offsets[:n_best] if word_offsets is not None else None,
             )
 
-    @contextmanager
-    def as_target_processor(self):
-        """
-        Temporarily sets the processor for processing the target. Useful for encoding the labels when fine-tuning
-        Wav2Vec2.
-        """
-        warnings.warn(
-            "`as_target_processor` is deprecated and will be removed in v5 of Transformers. You can process your "
-            "labels by using the argument `text` of the regular `__call__` method (either in the same call as "
-            "your audio inputs, or in a separate call."
-        )
-        self._in_target_context_manager = True
-        self.current_processor = self.tokenizer
-        yield
-        self.current_processor = self.feature_extractor
-        self._in_target_context_manager = False
-
 
 __all__ = ["Wav2Vec2ProcessorWithLM"]
diff --git a/src/transformers/models/whisper/processing_whisper.py b/src/transformers/models/whisper/processing_whisper.py
index 26dd02d3c40a..ece78b2f10b1 100644
--- a/src/transformers/models/whisper/processing_whisper.py
+++ b/src/transformers/models/whisper/processing_whisper.py
@@ -39,8 +39,6 @@ class WhisperProcessor(ProcessorMixin):
 
     def __init__(self, feature_extractor, tokenizer):
         super().__init__(feature_extractor, tokenizer)
-        self.current_processor = self.feature_extractor
-        self._in_target_context_manager = False
 
     def get_decoder_prompt_ids(self, task=None, language=None, no_timestamps=True):
         return self.tokenizer.get_decoder_prompt_ids(task=task, language=language, no_timestamps=no_timestamps)
@@ -51,10 +49,6 @@ def __call__(self, *args, **kwargs):
         argument to [`~WhisperTokenizer.__call__`]. Please refer to the docstring of the above two methods for more
         information.
         """
-        # For backward compatibility
-        if self._in_target_context_manager:
-            return self.current_processor(*args, **kwargs)
-
         audio = kwargs.pop("audio", None)
         sampling_rate = kwargs.pop("sampling_rate", None)
         text = kwargs.pop("text", None)
diff --git a/src/transformers/models/x_clip/processing_x_clip.py b/src/transformers/models/x_clip/processing_x_clip.py
index 581dabc6d8b5..2110a783bb37 100644
--- a/src/transformers/models/x_clip/processing_x_clip.py
+++ b/src/transformers/models/x_clip/processing_x_clip.py
@@ -16,8 +16,6 @@
 Image/Text processor class for XCLIP
 """
 
-import warnings
-
 from ...processing_utils import ProcessorMixin
 
 
@@ -40,35 +38,8 @@ class XCLIPProcessor(ProcessorMixin):
     tokenizer_class = ("CLIPTokenizer", "CLIPTokenizerFast")
 
     def __init__(self, image_processor=None, tokenizer=None, **kwargs):
-        feature_extractor = None
-        if "feature_extractor" in kwargs:
-            warnings.warn(
-                "The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"
-                " instead.",
-                FutureWarning,
-            )
-            feature_extractor = kwargs.pop("feature_extractor")
-
-        image_processor = image_processor if image_processor is not None else feature_extractor
         super().__init__(image_processor, tokenizer)
         self.video_processor = self.image_processor
-        self.current_processor = self.image_processor
-
-    @property
-    def feature_extractor_class(self):
-        warnings.warn(
-            "`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.",
-            FutureWarning,
-        )
-        return self.image_processor_class
-
-    @property
-    def feature_extractor(self):
-        warnings.warn(
-            "`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.",
-            FutureWarning,
-        )
-        return self.image_processor
 
 
 __all__ = ["XCLIPProcessor"]