

'''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 		lowerCAmelCase__  ( unittest.TestCase   ):



 """simple docstring"""



 def  UpperCAmelCase__						(						self   :			List[str]     )    ->					Any:


      """simple docstring"""




      __SCREAMING_SNAKE_CASE      = 0
 def  UpperCAmelCase__						(						self   :			Tuple     )    ->					Dict:


      """simple docstring"""




      __SCREAMING_SNAKE_CASE      = AutoImageProcessor.from_pretrained("""openai/clip-vit-base-patch32"""     )
      self.assertIsInstance(_A   ,				_A     )
 def  UpperCAmelCase__						(						self   :			str     )    ->					Union[str, Any]:


      """simple docstring"""




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

           __SCREAMING_SNAKE_CASE      = AutoImageProcessor.from_pretrained(_A     )
           self.assertIsInstance(_A   ,				_A     )
 def  UpperCAmelCase__						(						self   :			Tuple     )    ->					Optional[Any]:


      """simple docstring"""




      with tempfile.TemporaryDirectory() as tmpdirname:
           __SCREAMING_SNAKE_CASE      = Path(_A     ) / """preprocessor_config.json"""
           __SCREAMING_SNAKE_CASE      = Path(_A     ) / """config.json"""
           json.dump(
               {"""feature_extractor_type""": """CLIPFeatureExtractor""", """processor_class""": """CLIPProcessor"""}   ,				open(_A   ,				"""w"""     )   ,				)
           json.dump({"""model_type""": """clip"""}   ,				open(_A   ,				"""w"""     )     )

           __SCREAMING_SNAKE_CASE      = AutoImageProcessor.from_pretrained(_A     )
           self.assertIsInstance(_A   ,				_A     )
 def  UpperCAmelCase__						(						self   :			List[str]     )    ->					List[Any]:


      """simple docstring"""




      with tempfile.TemporaryDirectory() as tmpdirname:
           __SCREAMING_SNAKE_CASE      = CLIPConfig()

           # Create a dummy config file with image_proceesor_type
           __SCREAMING_SNAKE_CASE      = Path(_A     ) / """preprocessor_config.json"""
           __SCREAMING_SNAKE_CASE      = Path(_A     ) / """config.json"""
           json.dump(
               {"""image_processor_type""": """CLIPImageProcessor""", """processor_class""": """CLIPProcessor"""}   ,				open(_A   ,				"""w"""     )   ,				)
           json.dump({"""model_type""": """clip"""}   ,				open(_A   ,				"""w"""     )     )

           # remove image_processor_type to make sure config.json alone is enough to load image processor locally
           __SCREAMING_SNAKE_CASE      = AutoImageProcessor.from_pretrained(_A     ).to_dict()

           config_dict.pop("""image_processor_type"""     )
           __SCREAMING_SNAKE_CASE      = CLIPImageProcessor(**_A     )

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

           __SCREAMING_SNAKE_CASE      = AutoImageProcessor.from_pretrained(_A     )

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

      self.assertIsInstance(_A   ,				_A     )
 def  UpperCAmelCase__						(						self   :			Union[str, Any]     )    ->					Any:


      """simple docstring"""




      with tempfile.TemporaryDirectory() as tmpdirname:
           __SCREAMING_SNAKE_CASE      = Path(_A     ) / """preprocessor_config.json"""
           json.dump(
               {"""image_processor_type""": """CLIPImageProcessor""", """processor_class""": """CLIPProcessor"""}   ,				open(_A   ,				"""w"""     )   ,				)

           __SCREAMING_SNAKE_CASE      = AutoImageProcessor.from_pretrained(_A     )
           self.assertIsInstance(_A   ,				_A     )
 def  UpperCAmelCase__						(						self   :			List[Any]     )    ->					Dict:


      """simple docstring"""




      with self.assertRaisesRegex(
          _A   ,				"""clip-base is not a local folder and is not a valid model identifier"""     ):
           __SCREAMING_SNAKE_CASE      = AutoImageProcessor.from_pretrained("""clip-base"""     )
 def  UpperCAmelCase__						(						self   :			Dict     )    ->					List[str]:


      """simple docstring"""




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


      """simple docstring"""




      with self.assertRaisesRegex(
          _A   ,				"""hf-internal-testing/config-no-model does not appear to have a file named preprocessor_config.json."""   ,				):
           __SCREAMING_SNAKE_CASE      = AutoImageProcessor.from_pretrained("""hf-internal-testing/config-no-model"""     )
 def  UpperCAmelCase__						(						self   :			List[Any]     )    ->					Tuple:


      """simple docstring"""




      with self.assertRaises(_A     ):
           __SCREAMING_SNAKE_CASE      = AutoImageProcessor.from_pretrained("""hf-internal-testing/test_dynamic_image_processor"""     )
      # If remote code is disabled, we can't load this config.
      with self.assertRaises(_A     ):
           __SCREAMING_SNAKE_CASE      = AutoImageProcessor.from_pretrained(
               """hf-internal-testing/test_dynamic_image_processor"""   ,				trust_remote_code=_A     )

      __SCREAMING_SNAKE_CASE      = AutoImageProcessor.from_pretrained(
          """hf-internal-testing/test_dynamic_image_processor"""   ,				trust_remote_code=_A     )
      self.assertEqual(image_processor.__class__.__name__   ,				"""NewImageProcessor"""     )

      # Test image processor can be reloaded.
      with tempfile.TemporaryDirectory() as tmp_dir:
           image_processor.save_pretrained(_A     )
           __SCREAMING_SNAKE_CASE      = AutoImageProcessor.from_pretrained(_A   ,				trust_remote_code=_A     )
      self.assertEqual(reloaded_image_processor.__class__.__name__   ,				"""NewImageProcessor"""     )
 def  UpperCAmelCase__						(						self   :			List[Any]     )    ->					Optional[int]:


      """simple docstring"""




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

           with tempfile.TemporaryDirectory() as tmpdirname:
                __SCREAMING_SNAKE_CASE      = Path(_A     ) / """preprocessor_config.json"""
                __SCREAMING_SNAKE_CASE      = Path(_A     ) / """config.json"""
                json.dump(
                    {"""feature_extractor_type""": """CLIPFeatureExtractor""", """processor_class""": """CLIPProcessor"""}   ,				open(_A   ,				"""w"""     )   ,				)
                json.dump({"""model_type""": """clip"""}   ,				open(_A   ,				"""w"""     )     )

                __SCREAMING_SNAKE_CASE      = CustomImageProcessor.from_pretrained(_A     )

           # 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(_A     )
                __SCREAMING_SNAKE_CASE      = AutoImageProcessor.from_pretrained(_A     )
                self.assertIsInstance(_A   ,				_A     )

      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  UpperCAmelCase__						(						self   :			Optional[Any]     )    ->					List[str]:


      """simple docstring"""




      class 		lowerCAmelCase__  ( __lowercase   ):



       """simple docstring"""



       lowerCAmelCase__       = True

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

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







def 					_snake_case	(  __snake_case = 100						):
					_UpperCamelCase			     =     (n * (n + 1) // 2) ** 2
					_UpperCamelCase			     =     n * (n + 1) * (2 * n + 1) // 6
					return sum_cubes - sum_squares


if __name__ == "__main__":
					print(f'{solution() = }')
