





import json
import sys
import tempfile
import unittest
from pathlib import Path

import transformers
from transformers import (
    CONFIG_MAPPING,
    IMAGE_PROCESSOR_MAPPING,
    AutoConfig,
    AutoImageProcessor,
    CLIPConfig,
    CLIPImageProcessor,
)
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER


sys.path.append(str(Path(__file__).parent.parent.parent.parent / """utils"""))

from test_module.custom_configuration import CustomConfig  # noqa E402
from test_module.custom_image_processing import CustomImageProcessor  # noqa E402







class   __lowerCAmelCase			(					unittest.TestCase  ):





   def 	_snake_case ( self      )				->  Optional[Any]:
      """simple docstring"""





      a__	:						Tuple      		=  0





   def 	_snake_case ( self      )				->  Dict:
      """simple docstring"""





      a__	:						Tuple      		=  AutoImageProcessor.from_pretrained("openai/clip-vit-base-patch32"      )
      self.assertIsInstance(snake_case					,			snake_case      )





   def 	_snake_case ( self      )				->  List[str]:
      """simple docstring"""





      with tempfile.TemporaryDirectory() as tmpdirname:
         a__	:						Tuple      		=  Path(snake_case      ) / "preprocessor_config.json"
         a__	:						Tuple      		=  Path(snake_case      ) / "config.json"
         json.dump(
             {"image_processor_type": "CLIPImageProcessor", "processor_class": "CLIPProcessor"}					,			open(snake_case					,			"w"      )					,			)
         json.dump({"model_type": "clip"}					,			open(snake_case					,			"w"      )      )

         a__	:						Optional[Any]      		=  AutoImageProcessor.from_pretrained(snake_case      )
         self.assertIsInstance(snake_case					,			snake_case      )





   def 	_snake_case ( self      )				->  str:
      """simple docstring"""





      with tempfile.TemporaryDirectory() as tmpdirname:
         a__	:						str      		=  Path(snake_case      ) / "preprocessor_config.json"
         a__	:						List[Any]      		=  Path(snake_case      ) / "config.json"
         json.dump(
             {"feature_extractor_type": "CLIPFeatureExtractor", "processor_class": "CLIPProcessor"}					,			open(snake_case					,			"w"      )					,			)
         json.dump({"model_type": "clip"}					,			open(snake_case					,			"w"      )      )

         a__	:						Tuple      		=  AutoImageProcessor.from_pretrained(snake_case      )
         self.assertIsInstance(snake_case					,			snake_case      )





   def 	_snake_case ( self      )				->  str:
      """simple docstring"""





      with tempfile.TemporaryDirectory() as tmpdirname:
         a__	:						int      		=  CLIPConfig()

         # Create a dummy config file with image_proceesor_type
         a__	:						str      		=  Path(snake_case      ) / "preprocessor_config.json"
         a__	:						Optional[int]      		=  Path(snake_case      ) / "config.json"
         json.dump(
             {"image_processor_type": "CLIPImageProcessor", "processor_class": "CLIPProcessor"}					,			open(snake_case					,			"w"      )					,			)
         json.dump({"model_type": "clip"}					,			open(snake_case					,			"w"      )      )

         # remove image_processor_type to make sure config.json alone is enough to load image processor locally
         a__	:						Dict      		=  AutoImageProcessor.from_pretrained(snake_case      ).to_dict()

         config_dict.pop("image_processor_type"      )
         a__	:						int      		=  CLIPImageProcessor(**snake_case      )

         # save in new folder
         model_config.save_pretrained(snake_case      )
         config.save_pretrained(snake_case      )

         a__	:						Optional[Any]      		=  AutoImageProcessor.from_pretrained(snake_case      )

         # make sure private variable is not incorrectly saved
         a__	:						str      		=  json.loads(config.to_json_string()      )
         self.assertTrue("_processor_class" not in dict_as_saved      )

      self.assertIsInstance(snake_case					,			snake_case      )





   def 	_snake_case ( self      )				->  Dict:
      """simple docstring"""





      with tempfile.TemporaryDirectory() as tmpdirname:
         a__	:						Optional[int]      		=  Path(snake_case      ) / "preprocessor_config.json"
         json.dump(
             {"image_processor_type": "CLIPImageProcessor", "processor_class": "CLIPProcessor"}					,			open(snake_case					,			"w"      )					,			)

         a__	:						Union[str, Any]      		=  AutoImageProcessor.from_pretrained(snake_case      )
         self.assertIsInstance(snake_case					,			snake_case      )





   def 	_snake_case ( self      )				->  Optional[Any]:
      """simple docstring"""





      with self.assertRaisesRegex(
          snake_case					,			"clip-base is not a local folder and is not a valid model identifier"      ):
         a__	:						List[str]      		=  AutoImageProcessor.from_pretrained("clip-base"      )





   def 	_snake_case ( self      )				->  Any:
      """simple docstring"""





      with self.assertRaisesRegex(
          snake_case					,			r"aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)"      ):
         a__	:						Union[str, Any]      		=  AutoImageProcessor.from_pretrained(snake_case					,			revision="aaaaaa"      )





   def 	_snake_case ( self      )				->  List[Any]:
      """simple docstring"""





      with self.assertRaisesRegex(
          snake_case					,			"hf-internal-testing/config-no-model does not appear to have a file named preprocessor_config.json."					,			):
         a__	:						Optional[Any]      		=  AutoImageProcessor.from_pretrained("hf-internal-testing/config-no-model"      )





   def 	_snake_case ( self      )				->  int:
      """simple docstring"""





      with self.assertRaises(snake_case      ):
         a__	:						Optional[int]      		=  AutoImageProcessor.from_pretrained("hf-internal-testing/test_dynamic_image_processor"      )
      # If remote code is disabled, we can't load this config.
      with self.assertRaises(snake_case      ):
         a__	:						Union[str, Any]      		=  AutoImageProcessor.from_pretrained(
             "hf-internal-testing/test_dynamic_image_processor"					,			trust_remote_code=snake_case      )

      a__	:						Dict      		=  AutoImageProcessor.from_pretrained(
          "hf-internal-testing/test_dynamic_image_processor"					,			trust_remote_code=snake_case      )
      self.assertEqual(image_processor.__class__.__name__					,			"NewImageProcessor"      )

      # Test image processor can be reloaded.
      with tempfile.TemporaryDirectory() as tmp_dir:
         image_processor.save_pretrained(snake_case      )
         a__	:						Dict      		=  AutoImageProcessor.from_pretrained(snake_case					,			trust_remote_code=snake_case      )
      self.assertEqual(reloaded_image_processor.__class__.__name__					,			"NewImageProcessor"      )





   def 	_snake_case ( self      )				->  Dict:
      """simple docstring"""





      try:
         AutoConfig.register("custom"					,			snake_case      )
         AutoImageProcessor.register(snake_case					,			snake_case      )
         # Trying to register something existing in the Transformers library will raise an error
         with self.assertRaises(snake_case      ):
            AutoImageProcessor.register(snake_case					,			snake_case      )

         with tempfile.TemporaryDirectory() as tmpdirname:
            a__	:						Optional[int]      		=  Path(snake_case      ) / "preprocessor_config.json"
            a__	:						List[Any]      		=  Path(snake_case      ) / "config.json"
            json.dump(
                {"feature_extractor_type": "CLIPFeatureExtractor", "processor_class": "CLIPProcessor"}					,			open(snake_case					,			"w"      )					,			)
            json.dump({"model_type": "clip"}					,			open(snake_case					,			"w"      )      )

            a__	:						Any      		=  CustomImageProcessor.from_pretrained(snake_case      )

         # Now that the config is registered, it can be used as any other config with the auto-API
         with tempfile.TemporaryDirectory() as tmp_dir:
            image_processor.save_pretrained(snake_case      )
            a__	:						Optional[Any]      		=  AutoImageProcessor.from_pretrained(snake_case      )
            self.assertIsInstance(snake_case					,			snake_case      )

      finally:
         if "custom" in CONFIG_MAPPING._extra_content:
            del CONFIG_MAPPING._extra_content["custom"]
         if CustomConfig in IMAGE_PROCESSOR_MAPPING._extra_content:
            del IMAGE_PROCESSOR_MAPPING._extra_content[CustomConfig]





   def 	_snake_case ( self      )				->  int:
      """simple docstring"""





      class   __lowerCAmelCase			(					_UpperCamelCase  ):
         _UpperCamelCase :						Optional[int]     		=				True

      try:
         AutoConfig.register("custom"					,			snake_case      )
         AutoImageProcessor.register(snake_case					,			snake_case      )
         # If remote code is not set, the default is to use local
         a__	:						List[Any]      		=  AutoImageProcessor.from_pretrained("hf-internal-testing/test_dynamic_image_processor"      )
         self.assertEqual(image_processor.__class__.__name__					,			"NewImageProcessor"      )
         self.assertTrue(image_processor.is_local      )

         # If remote code is disabled, we load the local one.
         a__	:						List[Any]      		=  AutoImageProcessor.from_pretrained(
             "hf-internal-testing/test_dynamic_image_processor"					,			trust_remote_code=snake_case      )
         self.assertEqual(image_processor.__class__.__name__					,			"NewImageProcessor"      )
         self.assertTrue(image_processor.is_local      )

         # If remote is enabled, we load from the Hub
         a__	:						Tuple      		=  AutoImageProcessor.from_pretrained(
             "hf-internal-testing/test_dynamic_image_processor"					,			trust_remote_code=snake_case      )
         self.assertEqual(image_processor.__class__.__name__					,			"NewImageProcessor"      )
         self.assertTrue(not hasattr(snake_case					,			"is_local"      )      )

      finally:
         if "custom" in CONFIG_MAPPING._extra_content:
            del CONFIG_MAPPING._extra_content["custom"]
         if CustomConfig in IMAGE_PROCESSOR_MAPPING._extra_content:
            del IMAGE_PROCESSOR_MAPPING._extra_content[CustomConfig]








from PIL import Image






def       _A  (      lowerCamelCase							, lowerCamelCase   ):

   def brightness(lowerCamelCase   ) -> float:
      return 128 + level + (c - 128)

   if not -255.0 <= level <= 255.0:
      raise ValueError("level must be between -255.0 (black) and 255.0 (white)"   )
   return img.point(lowerCamelCase   )


if __name__ == "__main__":
  # Load image
  with Image.open("""image_data/lena.jpg""") as img:
    # Change brightness to 100
    SCREAMING_SNAKE_CASE__       :			List[str]			      =						change_brightness(img, 1_0_0)
    brigt_img.save("""image_data/lena_brightness.png""", format="""png""")

