Add ImageProcessorFast to BiT processor (#37180)

* Add ImageProcessorFast to BiT processor

* propose a fast processor and add tests

* all tests pass except one

* run make

* remove useless print

* use same test as clip

* apply make

* Update src/transformers/models/bit/image_processing_bit_fast.py

Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>

* Update setup.py

Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>

* Update src/transformers/models/bit/image_processing_bit_fast.py

Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>

* apply review comment

---------

Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>

docs/source/en/model_doc/bit.md

@@ -58,6 +58,11 @@ If you're interested in submitting a resource to be included here, please feel f
 [[autodoc]] BitImageProcessor
     - preprocess
 
+## BitImageProcessorFast
+
+[[autodoc]] BitImageProcessorFast
+    - preprocess
+
 ## BitModel
 
 [[autodoc]] BitModel

docs/source/ja/model_doc/bit.md

@@ -54,6 +54,11 @@ BiT を始めるのに役立つ公式 Hugging Face およびコミュニティ (
 [[autodoc]] BitImageProcessor
     - preprocess
 
+## BitImageProcessorFast
+
+[[autodoc]] BitImageProcessorFast
+    - preprocess
+
 ## BitModel
 
 [[autodoc]] BitModel

src/transformers/models/auto/image_processing_auto.py

@@ -59,7 +59,7 @@ else:
             ("align", ("EfficientNetImageProcessor",)),
             ("aria", ("AriaImageProcessor",)),
             ("beit", ("BeitImageProcessor",)),
-            ("bit", ("BitImageProcessor",)),
+            ("bit", ("BitImageProcessor", "BitImageProcessorFast")),
             ("blip", ("BlipImageProcessor", "BlipImageProcessorFast")),
             ("blip-2", ("BlipImageProcessor", "BlipImageProcessorFast")),
             ("bridgetower", ("BridgeTowerImageProcessor",)),
@@ -79,13 +79,13 @@ else:
             ("deta", ("DetaImageProcessor",)),
             ("detr", ("DetrImageProcessor", "DetrImageProcessorFast")),
             ("dinat", ("ViTImageProcessor", "ViTImageProcessorFast")),
-            ("dinov2", ("BitImageProcessor",)),
+            ("dinov2", ("BitImageProcessor", "BitImageProcessorFast")),
             ("donut-swin", ("DonutImageProcessor", "DonutImageProcessorFast")),
             ("dpt", ("DPTImageProcessor",)),
             ("efficientformer", ("EfficientFormerImageProcessor",)),
             ("efficientnet", ("EfficientNetImageProcessor",)),
             ("flava", ("FlavaImageProcessor", "FlavaImageProcessorFast")),
-            ("focalnet", ("BitImageProcessor",)),
+            ("focalnet", ("BitImageProcessor", "BitImageProcessorFast")),
             ("fuyu", ("FuyuImageProcessor",)),
             ("gemma3", ("Gemma3ImageProcessor", "Gemma3ImageProcessorFast")),
             ("git", ("CLIPImageProcessor", "CLIPImageProcessorFast")),
@@ -93,7 +93,7 @@ else:
             ("got_ocr2", ("GotOcr2ImageProcessor", "GotOcr2ImageProcessorFast")),
             ("grounding-dino", ("GroundingDinoImageProcessor",)),
             ("groupvit", ("CLIPImageProcessor", "CLIPImageProcessorFast")),
-            ("hiera", ("BitImageProcessor",)),
+            ("hiera", ("BitImageProcessor", "BitImageProcessorFast")),
             ("idefics", ("IdeficsImageProcessor",)),
             ("idefics2", ("Idefics2ImageProcessor",)),
             ("idefics3", ("Idefics3ImageProcessor",)),

src/transformers/models/bit/__init__.py

@@ -20,6 +20,7 @@ from ...utils.import_utils import define_import_structure
 if TYPE_CHECKING:
     from .configuration_bit import *
     from .image_processing_bit import *
+    from .image_processing_bit_fast import *
     from .modeling_bit import *
 else:
     import sys

src/transformers/models/bit/image_processing_bit_fast.py

@@ -0,0 +1,44 @@
+# coding=utf-8
+# Copyright 2025 The HuggingFace Inc. team. All rights reserved.
+#
+# 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.
+"""Fast Image processor class for BiT."""
+
+from ...image_processing_utils_fast import (
+    BASE_IMAGE_PROCESSOR_FAST_DOCSTRING,
+    BaseImageProcessorFast,
+)
+from ...image_utils import OPENAI_CLIP_MEAN, OPENAI_CLIP_STD, PILImageResampling
+from ...utils import add_start_docstrings
+
+
+@add_start_docstrings(
+    "Constructs a fast Bit image processor.",
+    BASE_IMAGE_PROCESSOR_FAST_DOCSTRING,
+)
+class BitImageProcessorFast(BaseImageProcessorFast):
+    resample = PILImageResampling.BICUBIC
+    image_mean = OPENAI_CLIP_MEAN
+    image_std = OPENAI_CLIP_STD
+    size = {"shortest_edge": 224}
+    default_to_square = False
+    crop_size = {"height": 224, "width": 224}
+    rescale_factor = 1 / 255
+    do_resize = True
+    do_center_crop = True
+    do_rescale = True
+    do_normalize = True
+    do_convert_rgb = True
+
+
+__all__ = ["BitImageProcessorFast"]

tests/models/bit/test_image_processing_bit.py

@@ -0,0 +1,128 @@
+# coding=utf-8
+# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
+#
+# 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 unittest
+
+from transformers.testing_utils import require_torch, require_vision
+from transformers.utils import is_torchvision_available, is_vision_available
+
+from ...test_image_processing_common import ImageProcessingTestMixin, prepare_image_inputs
+
+
+if is_vision_available():
+    from transformers import BitImageProcessor
+
+    if is_torchvision_available():
+        from transformers import BitImageProcessorFast
+
+
+class BitImageProcessingTester:
+    def __init__(
+        self,
+        parent,
+        batch_size=7,
+        num_channels=3,
+        image_size=18,
+        min_resolution=30,
+        max_resolution=400,
+        do_resize=True,
+        size=None,
+        do_center_crop=True,
+        crop_size=None,
+        do_normalize=True,
+        image_mean=[0.48145466, 0.4578275, 0.40821073],
+        image_std=[0.26862954, 0.26130258, 0.27577711],
+        do_convert_rgb=True,
+    ):
+        super().__init__()
+        size = size if size is not None else {"shortest_edge": 20}
+        crop_size = crop_size if crop_size is not None else {"height": 18, "width": 18}
+        self.parent = parent
+        self.batch_size = batch_size
+        self.num_channels = num_channels
+        self.image_size = image_size
+        self.min_resolution = min_resolution
+        self.max_resolution = max_resolution
+        self.do_resize = do_resize
+        self.size = size
+        self.do_center_crop = do_center_crop
+        self.crop_size = crop_size
+        self.do_normalize = do_normalize
+        self.image_mean = image_mean
+        self.image_std = image_std
+        self.do_convert_rgb = do_convert_rgb
+
+    def prepare_image_processor_dict(self):
+        return {
+            "do_resize": self.do_resize,
+            "size": self.size,
+            "do_center_crop": self.do_center_crop,
+            "crop_size": self.crop_size,
+            "do_normalize": self.do_normalize,
+            "image_mean": self.image_mean,
+            "image_std": self.image_std,
+            "do_convert_rgb": self.do_convert_rgb,
+        }
+
+    def expected_output_image_shape(self, images):
+        return self.num_channels, self.crop_size["height"], self.crop_size["width"]
+
+    def prepare_image_inputs(self, equal_resolution=False, numpify=False, torchify=False):
+        return prepare_image_inputs(
+            batch_size=self.batch_size,
+            num_channels=self.num_channels,
+            min_resolution=self.min_resolution,
+            max_resolution=self.max_resolution,
+            equal_resolution=equal_resolution,
+            numpify=numpify,
+            torchify=torchify,
+        )
+
+
+@require_torch
+@require_vision
+class BitImageProcessingTest(ImageProcessingTestMixin, unittest.TestCase):
+    image_processing_class = BitImageProcessor if is_vision_available() else None
+    fast_image_processing_class = BitImageProcessorFast if is_torchvision_available() else None
+
+    def setUp(self):
+        super().setUp()
+        self.image_processor_tester = BitImageProcessingTester(self)
+
+    @property
+    def image_processor_dict(self):
+        return self.image_processor_tester.prepare_image_processor_dict()
+
+    def test_image_processor_properties(self):
+        for image_processing_class in self.image_processor_list:
+            image_processing = image_processing_class(**self.image_processor_dict)
+            self.assertTrue(hasattr(image_processing, "do_resize"))
+            self.assertTrue(hasattr(image_processing, "size"))
+            self.assertTrue(hasattr(image_processing, "do_center_crop"))
+            self.assertTrue(hasattr(image_processing, "center_crop"))
+            self.assertTrue(hasattr(image_processing, "do_normalize"))
+            self.assertTrue(hasattr(image_processing, "image_mean"))
+            self.assertTrue(hasattr(image_processing, "image_std"))
+            self.assertTrue(hasattr(image_processing, "do_convert_rgb"))
+
+    def test_image_processor_from_dict_with_kwargs(self):
+        for image_processing_class in self.image_processor_list:
+            image_processor = image_processing_class.from_dict(self.image_processor_dict)
+            self.assertEqual(image_processor.size, {"shortest_edge": 20})
+            self.assertEqual(image_processor.crop_size, {"height": 18, "width": 18})
+
+            image_processor = image_processing_class.from_dict(self.image_processor_dict, size=42, crop_size=84)
+            self.assertEqual(image_processor.size, {"shortest_edge": 42})
+            self.assertEqual(image_processor.crop_size, {"height": 84, "width": 84})