


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  _a							(    unittest.TestCase):




 def 							UpperCAmelCase__( self						:		List[Any]		)->	str:
   lowerCAmelCase__       :      Dict   					= 0




 def 							UpperCAmelCase__( self						:		Union[str, Any]		)->	Dict:
   lowerCAmelCase__       :      Optional[Any]   					= AutoImageProcessor.from_pretrained('''openai/clip-vit-base-patch32'''		)
   self.assertIsInstance(lowerCamelCase_		, lowerCamelCase_		)




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

   with tempfile.TemporaryDirectory() as tmpdirname:
     lowerCAmelCase__       :      Optional[Any]   					= Path(lowerCamelCase_		) / '''preprocessor_config.json'''
     lowerCAmelCase__       :      Optional[Any]   					= Path(lowerCamelCase_		) / '''config.json'''
     json.dump(
         {'''image_processor_type''': '''CLIPImageProcessor''', '''processor_class''': '''CLIPProcessor'''}		, open(lowerCamelCase_		, '''w'''		)		, )
     json.dump({'''model_type''': '''clip'''}		, open(lowerCamelCase_		, '''w'''		)		)

     lowerCAmelCase__       :      Tuple   					= AutoImageProcessor.from_pretrained(lowerCamelCase_		)
     self.assertIsInstance(lowerCamelCase_		, lowerCamelCase_		)




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

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

     lowerCAmelCase__       :      List[str]   					= AutoImageProcessor.from_pretrained(lowerCamelCase_		)
     self.assertIsInstance(lowerCamelCase_		, lowerCamelCase_		)




 def 							UpperCAmelCase__( self						:		Tuple		)->	Optional[int]:

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

     # Create a dummy config file with image_proceesor_type
     lowerCAmelCase__       :      List[Any]   					= Path(lowerCamelCase_		) / '''preprocessor_config.json'''
     lowerCAmelCase__       :      Dict   					= 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
     lowerCAmelCase__       :      Union[str, Any]   					= AutoImageProcessor.from_pretrained(lowerCamelCase_		).to_dict()

     config_dict.pop('''image_processor_type'''		)
     lowerCAmelCase__       :      Optional[int]   					= CLIPImageProcessor(**lowerCamelCase_		)

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

     lowerCAmelCase__       :      Dict   					= AutoImageProcessor.from_pretrained(lowerCamelCase_		)

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

   self.assertIsInstance(lowerCamelCase_		, lowerCamelCase_		)




 def 							UpperCAmelCase__( self						:		Dict		)->	Dict:

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

     lowerCAmelCase__       :      str   					= AutoImageProcessor.from_pretrained(lowerCamelCase_		)
     self.assertIsInstance(lowerCamelCase_		, lowerCamelCase_		)




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

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




 def 							UpperCAmelCase__( self						:		Dict		)->	Optional[Any]:

   with self.assertRaisesRegex(
       lowerCamelCase_		, r'''aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'''		):
     lowerCAmelCase__       :      Tuple   					= AutoImageProcessor.from_pretrained(lowerCamelCase_		, revision='''aaaaaa'''		)




 def 							UpperCAmelCase__( self						:		Optional[int]		)->	int:

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




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

   with self.assertRaises(lowerCamelCase_		):
     lowerCAmelCase__       :      Dict   					= 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_		):
     lowerCAmelCase__       :      str   					= AutoImageProcessor.from_pretrained(
         '''hf-internal-testing/test_dynamic_image_processor'''		, trust_remote_code=lowerCamelCase_		)

   lowerCAmelCase__       :      Dict   					= 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_		)
     lowerCAmelCase__       :      int   					= AutoImageProcessor.from_pretrained(lowerCamelCase_		, trust_remote_code=lowerCamelCase_		)
   self.assertEqual(reloaded_image_processor.__class__.__name__		, '''NewImageProcessor'''		)




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

   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:
       lowerCAmelCase__       :      List[Any]   					= Path(lowerCamelCase_		) / '''preprocessor_config.json'''
       lowerCAmelCase__       :      List[str]   					= Path(lowerCamelCase_		) / '''config.json'''
       json.dump(
           {'''feature_extractor_type''': '''CLIPFeatureExtractor''', '''processor_class''': '''CLIPProcessor'''}		, open(lowerCamelCase_		, '''w'''		)		, )
       json.dump({'''model_type''': '''clip'''}		, open(lowerCamelCase_		, '''w'''		)		)

       lowerCAmelCase__       :      Any   					= 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_		)
       lowerCAmelCase__       :      Any   					= 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						:		List[Any]		)->	Dict:





   class  _a							(    _lowercase):
    _a  :  int				   =							True

   try:
     AutoConfig.register('''custom'''		, lowerCamelCase_		)
     AutoImageProcessor.register(lowerCamelCase_		, lowerCamelCase_		)
     # If remote code is not set, the default is to use local
     lowerCAmelCase__       :      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.
     lowerCAmelCase__       :      Tuple   					= 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
     lowerCAmelCase__       :      Union[str, Any]   					= 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]








from math import isqrt






def 					lowerCamelCase_   (	_a	):




		"""simple docstring"""






		lowerCAmelCase__       :      Dict   					= [True] * max_number
		for i in range(2     ,       isqrt(max_number - 1	) + 1	):
				if is_prime[i]:
						for j in range(i**2     ,       _a     ,       _a	):
								lowerCAmelCase__       :      int   					= False

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






def 					lowerCamelCase_   (	_a = 10**8	):




		"""simple docstring"""






		lowerCAmelCase__       :      Any   					= calculate_prime_numbers(max_number // 2	)

		lowerCAmelCase__       :      Tuple   					= 0
		lowerCAmelCase__       :      List[Any]   					= 0
		lowerCAmelCase__       :      Optional[int]   					= len(_a	) - 1
		while left <= right:
				while prime_numbers[left] * prime_numbers[right] >= max_number:
						right -= 1
				semiprimes_count += right - left + 1
				left += 1

		return semiprimes_count


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




