





'''simple docstring'''




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 					SCREAMING_SNAKE_CASE       (unittest.TestCase				):


     def 				SCREAMING_SNAKE_CASE    (		self):

          '''simple docstring'''






          __A		:					Dict						=			0


     def 				SCREAMING_SNAKE_CASE    (		self):

          '''simple docstring'''






          __A		:					Dict						=			AutoImageProcessor.from_pretrained('openai/clip-vit-base-patch32')
          self.assertIsInstance(_UpperCAmelCase		,      _UpperCAmelCase)


     def 				SCREAMING_SNAKE_CASE    (		self):

          '''simple docstring'''






          with tempfile.TemporaryDirectory() as tmpdirname:
               __A		:					Union[str, Any]						=			Path(_UpperCAmelCase) / 'preprocessor_config.json'
               __A		:					Dict						=			Path(_UpperCAmelCase) / 'config.json'
               json.dump(
                   {'image_processor_type': 'CLIPImageProcessor', 'processor_class': 'CLIPProcessor'}		,      open(_UpperCAmelCase		,      'w')		,      )
               json.dump({'model_type': 'clip'}		,      open(_UpperCAmelCase		,      'w'))

               __A		:					List[Any]						=			AutoImageProcessor.from_pretrained(_UpperCAmelCase)
               self.assertIsInstance(_UpperCAmelCase		,      _UpperCAmelCase)


     def 				SCREAMING_SNAKE_CASE    (		self):

          '''simple docstring'''






          with tempfile.TemporaryDirectory() as tmpdirname:
               __A		:					Tuple						=			Path(_UpperCAmelCase) / 'preprocessor_config.json'
               __A		:					Tuple						=			Path(_UpperCAmelCase) / 'config.json'
               json.dump(
                   {'feature_extractor_type': 'CLIPFeatureExtractor', 'processor_class': 'CLIPProcessor'}		,      open(_UpperCAmelCase		,      'w')		,      )
               json.dump({'model_type': 'clip'}		,      open(_UpperCAmelCase		,      'w'))

               __A		:					int						=			AutoImageProcessor.from_pretrained(_UpperCAmelCase)
               self.assertIsInstance(_UpperCAmelCase		,      _UpperCAmelCase)


     def 				SCREAMING_SNAKE_CASE    (		self):

          '''simple docstring'''






          with tempfile.TemporaryDirectory() as tmpdirname:
               __A		:					Optional[int]						=			CLIPConfig()

               # Create a dummy config file with image_proceesor_type
               __A		:					Union[str, Any]						=			Path(_UpperCAmelCase) / 'preprocessor_config.json'
               __A		:					List[Any]						=			Path(_UpperCAmelCase) / 'config.json'
               json.dump(
                   {'image_processor_type': 'CLIPImageProcessor', 'processor_class': 'CLIPProcessor'}		,      open(_UpperCAmelCase		,      'w')		,      )
               json.dump({'model_type': 'clip'}		,      open(_UpperCAmelCase		,      'w'))

               # remove image_processor_type to make sure config.json alone is enough to load image processor locally
               __A		:					int						=			AutoImageProcessor.from_pretrained(_UpperCAmelCase).to_dict()

               config_dict.pop('image_processor_type')
               __A		:					List[Any]						=			CLIPImageProcessor(**_UpperCAmelCase)

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

               __A		:					str						=			AutoImageProcessor.from_pretrained(_UpperCAmelCase)

               # make sure private variable is not incorrectly saved
               __A		:					List[str]						=			json.loads(config.to_json_string())
               self.assertTrue('_processor_class' not in dict_as_saved)

          self.assertIsInstance(_UpperCAmelCase		,      _UpperCAmelCase)


     def 				SCREAMING_SNAKE_CASE    (		self):

          '''simple docstring'''






          with tempfile.TemporaryDirectory() as tmpdirname:
               __A		:					Dict						=			Path(_UpperCAmelCase) / 'preprocessor_config.json'
               json.dump(
                   {'image_processor_type': 'CLIPImageProcessor', 'processor_class': 'CLIPProcessor'}		,      open(_UpperCAmelCase		,      'w')		,      )

               __A		:					int						=			AutoImageProcessor.from_pretrained(_UpperCAmelCase)
               self.assertIsInstance(_UpperCAmelCase		,      _UpperCAmelCase)


     def 				SCREAMING_SNAKE_CASE    (		self):

          '''simple docstring'''






          with self.assertRaisesRegex(
              _UpperCAmelCase		,      'clip-base is not a local folder and is not a valid model identifier'):
               __A		:					Optional[Any]						=			AutoImageProcessor.from_pretrained('clip-base')


     def 				SCREAMING_SNAKE_CASE    (		self):

          '''simple docstring'''






          with self.assertRaisesRegex(
              _UpperCAmelCase		,      R'aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'):
               __A		:					List[Any]						=			AutoImageProcessor.from_pretrained(_UpperCAmelCase		,      revision='aaaaaa')


     def 				SCREAMING_SNAKE_CASE    (		self):

          '''simple docstring'''






          with self.assertRaisesRegex(
              _UpperCAmelCase		,      'hf-internal-testing/config-no-model does not appear to have a file named preprocessor_config.json.'		,      ):
               __A		:					Dict						=			AutoImageProcessor.from_pretrained('hf-internal-testing/config-no-model')


     def 				SCREAMING_SNAKE_CASE    (		self):

          '''simple docstring'''






          with self.assertRaises(_UpperCAmelCase):
               __A		:					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(_UpperCAmelCase):
               __A		:					Dict						=			AutoImageProcessor.from_pretrained(
                   'hf-internal-testing/test_dynamic_image_processor'		,      trust_remote_code=_UpperCAmelCase)

          __A		:					Union[str, Any]						=			AutoImageProcessor.from_pretrained(
              'hf-internal-testing/test_dynamic_image_processor'		,      trust_remote_code=_UpperCAmelCase)
          self.assertEqual(image_processor.__class__.__name__		,      'NewImageProcessor')

          # Test image processor can be reloaded.
          with tempfile.TemporaryDirectory() as tmp_dir:
               image_processor.save_pretrained(_UpperCAmelCase)
               __A		:					List[Any]						=			AutoImageProcessor.from_pretrained(_UpperCAmelCase		,      trust_remote_code=_UpperCAmelCase)
          self.assertEqual(reloaded_image_processor.__class__.__name__		,      'NewImageProcessor')


     def 				SCREAMING_SNAKE_CASE    (		self):

          '''simple docstring'''






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

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

                    __A		:					Union[str, Any]						=			CustomImageProcessor.from_pretrained(_UpperCAmelCase)

               # 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(_UpperCAmelCase)
                    __A		:					List[str]						=			AutoImageProcessor.from_pretrained(_UpperCAmelCase)
                    self.assertIsInstance(_UpperCAmelCase		,      _UpperCAmelCase)

          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 				SCREAMING_SNAKE_CASE    (		self):

          '''simple docstring'''






          class 					SCREAMING_SNAKE_CASE       (a__				):
               lowerCAmelCase						     =			True

          try:
               AutoConfig.register('custom'		,      _UpperCAmelCase)
               AutoImageProcessor.register(_UpperCAmelCase		,      _UpperCAmelCase)
               # If remote code is not set, the default is to use local
               __A		:					Dict						=			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		:					Dict						=			AutoImageProcessor.from_pretrained(
                   'hf-internal-testing/test_dynamic_image_processor'		,      trust_remote_code=_UpperCAmelCase)
               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=_UpperCAmelCase)
               self.assertEqual(image_processor.__class__.__name__		,      'NewImageProcessor')
               self.assertTrue(not hasattr(_UpperCAmelCase		,      '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]






'''simple docstring'''




def 			_lowerCAmelCase     (    __snake_case    :					str					,				__snake_case    :					str     )	->	int:
     if len(__snake_case     ) != len(__snake_case     ):
          raise ValueError('String lengths must match!'     )

     __A		:					Optional[Any]						=			0

     for chara, chara in zip(__snake_case					,				__snake_case     ):
          if chara != chara:
               count += 1

     return count


if __name__ == "__main__":
  import doctest

  doctest.testmod()