


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 							lowercase  (						unittest.TestCase			):







     def 							lowercase__       (						self :						List[Any]      ):
           SCREAMING_SNAKE_CASE__       :  Tuple						     =		0







     def 							lowercase__       (						self :						List[str]      ):
           SCREAMING_SNAKE_CASE__       :  int						     =		AutoImageProcessor.from_pretrained('''openai/clip-vit-base-patch32'''      )
           self.assertIsInstance(_lowercase   ,   _lowercase      )







     def 							lowercase__       (						self :						Any      ):
           with tempfile.TemporaryDirectory() as tmpdirname:
                 SCREAMING_SNAKE_CASE__       :  Union[str, Any]						     =		Path(_lowercase      ) / '''preprocessor_config.json'''
                 SCREAMING_SNAKE_CASE__       :  List[Any]						     =		Path(_lowercase      ) / '''config.json'''
                 json.dump(
                     {'''image_processor_type''': '''CLIPImageProcessor''', '''processor_class''': '''CLIPProcessor'''}   ,   open(_lowercase   ,   '''w'''      )   ,   )
                 json.dump({'''model_type''': '''clip'''}   ,   open(_lowercase   ,   '''w'''      )      )

                 SCREAMING_SNAKE_CASE__       :  Tuple						     =		AutoImageProcessor.from_pretrained(_lowercase      )
                 self.assertIsInstance(_lowercase   ,   _lowercase      )







     def 							lowercase__       (						self :						Dict      ):
           # Ensure we can load the image processor from the feature extractor config
           with tempfile.TemporaryDirectory() as tmpdirname:
                 SCREAMING_SNAKE_CASE__       :  List[str]						     =		Path(_lowercase      ) / '''preprocessor_config.json'''
                 SCREAMING_SNAKE_CASE__       :  Optional[int]						     =		Path(_lowercase      ) / '''config.json'''
                 json.dump(
                     {'''feature_extractor_type''': '''CLIPFeatureExtractor''', '''processor_class''': '''CLIPProcessor'''}   ,   open(_lowercase   ,   '''w'''      )   ,   )
                 json.dump({'''model_type''': '''clip'''}   ,   open(_lowercase   ,   '''w'''      )      )

                 SCREAMING_SNAKE_CASE__       :  Any						     =		AutoImageProcessor.from_pretrained(_lowercase      )
                 self.assertIsInstance(_lowercase   ,   _lowercase      )







     def 							lowercase__       (						self :						List[str]      ):
           with tempfile.TemporaryDirectory() as tmpdirname:
                 SCREAMING_SNAKE_CASE__       :  int						     =		CLIPConfig()

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

                 # remove image_processor_type to make sure config.json alone is enough to load image processor locally
                 SCREAMING_SNAKE_CASE__       :  str						     =		AutoImageProcessor.from_pretrained(_lowercase      ).to_dict()

                 config_dict.pop('''image_processor_type'''      )
                 SCREAMING_SNAKE_CASE__       :  List[str]						     =		CLIPImageProcessor(**_lowercase      )

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

                 SCREAMING_SNAKE_CASE__       :  Union[str, Any]						     =		AutoImageProcessor.from_pretrained(_lowercase      )

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

           self.assertIsInstance(_lowercase   ,   _lowercase      )







     def 							lowercase__       (						self :						int      ):
           with tempfile.TemporaryDirectory() as tmpdirname:
                 SCREAMING_SNAKE_CASE__       :  List[str]						     =		Path(_lowercase      ) / '''preprocessor_config.json'''
                 json.dump(
                     {'''image_processor_type''': '''CLIPImageProcessor''', '''processor_class''': '''CLIPProcessor'''}   ,   open(_lowercase   ,   '''w'''      )   ,   )

                 SCREAMING_SNAKE_CASE__       :  Optional[int]						     =		AutoImageProcessor.from_pretrained(_lowercase      )
                 self.assertIsInstance(_lowercase   ,   _lowercase      )







     def 							lowercase__       (						self :						Union[str, Any]      ):
           with self.assertRaisesRegex(
               _lowercase   ,   '''clip-base is not a local folder and is not a valid model identifier'''      ):
                 SCREAMING_SNAKE_CASE__       :  List[Any]						     =		AutoImageProcessor.from_pretrained('''clip-base'''      )







     def 							lowercase__       (						self :						str      ):
           with self.assertRaisesRegex(
               _lowercase   ,   R'''aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'''      ):
                 SCREAMING_SNAKE_CASE__       :  Optional[Any]						     =		AutoImageProcessor.from_pretrained(_lowercase   ,   revision='''aaaaaa'''      )







     def 							lowercase__       (						self :						List[str]      ):
           with self.assertRaisesRegex(
               _lowercase   ,   '''hf-internal-testing/config-no-model does not appear to have a file named preprocessor_config.json.'''   ,   ):
                 SCREAMING_SNAKE_CASE__       :  Optional[Any]						     =		AutoImageProcessor.from_pretrained('''hf-internal-testing/config-no-model'''      )







     def 							lowercase__       (						self :						Any      ):
           # If remote code is not set, we will time out when asking whether to load the model.
           with self.assertRaises(_lowercase      ):
                 SCREAMING_SNAKE_CASE__       :  List[Any]						     =		AutoImageProcessor.from_pretrained('''hf-internal-testing/test_dynamic_image_processor'''      )
           # If remote code is disabled, we can't load this config.
           with self.assertRaises(_lowercase      ):
                 SCREAMING_SNAKE_CASE__       :  List[str]						     =		AutoImageProcessor.from_pretrained(
                     '''hf-internal-testing/test_dynamic_image_processor'''   ,   trust_remote_code=_lowercase      )

           SCREAMING_SNAKE_CASE__       :  Optional[Any]						     =		AutoImageProcessor.from_pretrained(
               '''hf-internal-testing/test_dynamic_image_processor'''   ,   trust_remote_code=_lowercase      )
           self.assertEqual(image_processor.__class__.__name__   ,   '''NewImageProcessor'''      )

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







     def 							lowercase__       (						self :						List[str]      ):
           try:
                 AutoConfig.register('''custom'''   ,   _lowercase      )
                 AutoImageProcessor.register(_lowercase   ,   _lowercase      )
                 # Trying to register something existing in the Transformers library will raise an error
                 with self.assertRaises(_lowercase      ):
                       AutoImageProcessor.register(_lowercase   ,   _lowercase      )

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

                       SCREAMING_SNAKE_CASE__       :  List[Any]						     =		CustomImageProcessor.from_pretrained(_lowercase      )

                 # 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(_lowercase      )
                       SCREAMING_SNAKE_CASE__       :  List[Any]						     =		AutoImageProcessor.from_pretrained(_lowercase      )
                       self.assertIsInstance(_lowercase   ,   _lowercase      )

           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 							lowercase__       (						self :						Optional[Any]      ):

           class 							lowercase  (						_UpperCAmelCase			):
                lowerCamelCase			:			Union[str, Any]      = True

           try:
                 AutoConfig.register('''custom'''   ,   _lowercase      )
                 AutoImageProcessor.register(_lowercase   ,   _lowercase      )
                 # If remote code is not set, the default is to use local
                 SCREAMING_SNAKE_CASE__       :  Optional[int]						     =		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__       :  List[Any]						     =		AutoImageProcessor.from_pretrained(
                     '''hf-internal-testing/test_dynamic_image_processor'''   ,   trust_remote_code=_lowercase      )
                 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__       :  Any						     =		AutoImageProcessor.from_pretrained(
                     '''hf-internal-testing/test_dynamic_image_processor'''   ,   trust_remote_code=_lowercase      )
                 self.assertEqual(image_processor.__class__.__name__   ,   '''NewImageProcessor'''      )
                 self.assertTrue(not hasattr(_lowercase   ,   '''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"""
from math import isqrt, loga

def 				_snake_case      (   __snake_case							:      int   ):




   """simple docstring"""







   _lowerCamelCase	:					List[str]   =		[True] * max_number
   for i in range(2						, isqrt(max_number - 1   ) + 1   ):
      if is_prime[i]:
         for j in range(i**2						, __snake_case						, __snake_case   ):
            _lowerCamelCase	:					Optional[int]   =		False

   return [i for i in range(2						, __snake_case   ) if is_prime[i]]

def 				_snake_case      (   __snake_case							:      int = 800800						, __snake_case							:      int = 800800   ):




   """simple docstring"""







   _lowerCamelCase	:					Union[str, Any]   =		degree * loga(__snake_case   )
   _lowerCamelCase	:					Union[str, Any]   =		int(__snake_case   )
   _lowerCamelCase	:					Dict   =		calculate_prime_numbers(__snake_case   )

   _lowerCamelCase	:					Optional[int]   =		0
   _lowerCamelCase	:					Any   =		0
   _lowerCamelCase	:					Any   =		len(__snake_case   ) - 1
   while left < right:
      while (
          prime_numbers[right] * loga(prime_numbers[left]   )
          + prime_numbers[left] * loga(prime_numbers[right]   )
          > upper_bound
      ):
         right -= 1
      hybrid_integers_count += right - left
      left += 1

   return hybrid_integers_count


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

