



"""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     UpperCAmelCase    (	unittest.TestCase  ):



   def    __UpperCAmelCase    (       self    :	int				):



     """simple docstring"""
     _snake_case   	=      0



   def    __UpperCAmelCase    (       self    :	Optional[Any]				):



     """simple docstring"""
     _snake_case   	=      AutoImageProcessor.from_pretrained('''openai/clip-vit-base-patch32'''				)
     self.assertIsInstance(__lowerCamelCase							,       __lowerCamelCase				)



   def    __UpperCAmelCase    (       self    :	Tuple				):



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

       _snake_case   	=      AutoImageProcessor.from_pretrained(__lowerCamelCase				)
       self.assertIsInstance(__lowerCamelCase							,       __lowerCamelCase				)



   def    __UpperCAmelCase    (       self    :	int				):



     """simple docstring"""
     # Ensure we can load the image processor from the feature extractor config
     with tempfile.TemporaryDirectory() as tmpdirname:
       _snake_case   	=      Path(__lowerCamelCase				) / '''preprocessor_config.json'''
       _snake_case   	=      Path(__lowerCamelCase				) / '''config.json'''
       json.dump(
           {'''feature_extractor_type''': '''CLIPFeatureExtractor''', '''processor_class''': '''CLIPProcessor'''}							,       open(__lowerCamelCase							,       '''w'''				)							,       )
       json.dump({'''model_type''': '''clip'''}							,       open(__lowerCamelCase							,       '''w'''				)				)

       _snake_case   	=      AutoImageProcessor.from_pretrained(__lowerCamelCase				)
       self.assertIsInstance(__lowerCamelCase							,       __lowerCamelCase				)



   def    __UpperCAmelCase    (       self    :	Optional[int]				):



     """simple docstring"""
     with tempfile.TemporaryDirectory() as tmpdirname:
       _snake_case   	=      CLIPConfig()

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

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

       config_dict.pop('''image_processor_type'''				)
       _snake_case   	=      CLIPImageProcessor(**__lowerCamelCase				)

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

       _snake_case   	=      AutoImageProcessor.from_pretrained(__lowerCamelCase				)

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

     self.assertIsInstance(__lowerCamelCase							,       __lowerCamelCase				)



   def    __UpperCAmelCase    (       self    :	Any				):



     """simple docstring"""
     with tempfile.TemporaryDirectory() as tmpdirname:
       _snake_case   	=      Path(__lowerCamelCase				) / '''preprocessor_config.json'''
       json.dump(
           {'''image_processor_type''': '''CLIPImageProcessor''', '''processor_class''': '''CLIPProcessor'''}							,       open(__lowerCamelCase							,       '''w'''				)							,       )

       _snake_case   	=      AutoImageProcessor.from_pretrained(__lowerCamelCase				)
       self.assertIsInstance(__lowerCamelCase							,       __lowerCamelCase				)



   def    __UpperCAmelCase    (       self    :	Tuple				):



     """simple docstring"""
     with self.assertRaisesRegex(
         __lowerCamelCase							,       '''clip-base is not a local folder and is not a valid model identifier'''				):
       _snake_case   	=      AutoImageProcessor.from_pretrained('''clip-base'''				)



   def    __UpperCAmelCase    (       self    :	Union[str, Any]				):



     """simple docstring"""
     with self.assertRaisesRegex(
         __lowerCamelCase							,       R'''aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'''				):
       _snake_case   	=      AutoImageProcessor.from_pretrained(__lowerCamelCase							,       revision='''aaaaaa'''				)



   def    __UpperCAmelCase    (       self    :	Any				):



     """simple docstring"""
     with self.assertRaisesRegex(
         __lowerCamelCase							,       '''hf-internal-testing/config-no-model does not appear to have a file named preprocessor_config.json.'''							,       ):
       _snake_case   	=      AutoImageProcessor.from_pretrained('''hf-internal-testing/config-no-model'''				)



   def    __UpperCAmelCase    (       self    :	List[Any]				):



     """simple docstring"""
     # If remote code is not set, we will time out when asking whether to load the model.
     with self.assertRaises(__lowerCamelCase				):
       _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(__lowerCamelCase				):
       _snake_case   	=      AutoImageProcessor.from_pretrained(
           '''hf-internal-testing/test_dynamic_image_processor'''							,       trust_remote_code=__lowerCamelCase				)

     _snake_case   	=      AutoImageProcessor.from_pretrained(
         '''hf-internal-testing/test_dynamic_image_processor'''							,       trust_remote_code=__lowerCamelCase				)
     self.assertEqual(image_processor.__class__.__name__							,       '''NewImageProcessor'''				)

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



   def    __UpperCAmelCase    (       self    :	Dict				):



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

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

         _snake_case   	=      CustomImageProcessor.from_pretrained(__lowerCamelCase				)

       # 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(__lowerCamelCase				)
         _snake_case   	=      AutoImageProcessor.from_pretrained(__lowerCamelCase				)
         self.assertIsInstance(__lowerCamelCase							,       __lowerCamelCase				)

     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[int]				):



     """simple docstring"""



     class     UpperCAmelCase    (	__SCREAMING_SNAKE_CASE  ):
        A__		:	int           =  True

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

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







import functools
from typing import Any



def 		UpperCamelCase     (       _UpperCAmelCase  :   str ,			_UpperCAmelCase  :   list[str]  )   ->			bool:






						'''simple docstring'''

						if not isinstance(_UpperCAmelCase ,			_UpperCAmelCase  ) or len(_UpperCAmelCase  ) == 0:
												raise ValueError("the string should be not empty string"  )

						if not isinstance(_UpperCAmelCase ,			_UpperCAmelCase  ) or not all(
						    isinstance(_UpperCAmelCase ,			_UpperCAmelCase  ) and len(_UpperCAmelCase  ) > 0 for item in words  ):
												raise ValueError("the words should be a list of non-empty strings"  )

						# Build trie
						_lowercase       :	dict[str, Any]           =   {}
						_lowercase       :	List[Any]           =   "WORD_KEEPER"

						for word in words:
												_lowercase       :	Optional[Any]           =   trie
												for c in word:
																		if c not in trie_node:
																								_lowercase       :	List[Any]           =   {}

																		_lowercase       :	Optional[int]           =   trie_node[c]

												_lowercase       :	str           =   True

						_lowercase       :	int           =   len(_UpperCAmelCase  )

						# Dynamic programming method
						@functools.cache
						def is_breakable(_UpperCAmelCase  :   int  ) -> bool:
												if index == len_string:
																		return True

												_lowercase       :	Union[str, Any]           =   trie
												for i in range(_UpperCAmelCase ,			_UpperCAmelCase  ):
																		_lowercase       :	List[str]           =   trie_node.get(string[i] ,			_UpperCAmelCase  )

																		if trie_node is None:
																								return False

																		if trie_node.get(_UpperCAmelCase ,			_UpperCAmelCase  ) and is_breakable(i + 1  ):
																								return True

												return False

						return is_breakable(0  )


if __name__ == "__main__":
							import doctest

							doctest.testmod()




