





"""simple docstring"""




from math import isqrt







def 							_UpperCAmelCase		(       lowerCamelCase__     ):





		"""simple docstring"""




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

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







def 							_UpperCAmelCase		(       lowerCamelCase__ = 10**8     ):





		"""simple docstring"""




		lowerCAmelCase__        =   calculate_prime_numbers(max_number // 2     )

		lowerCAmelCase__        =   0
		lowerCAmelCase__        =   0
		lowerCAmelCase__        =   len(__lowerCAmelCase     ) - 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() = }")





"""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       a_      (     unittest.TestCase			):




					def 						_SCREAMING_SNAKE_CASE						(	self						:     Optional[int]     ):
							lowerCAmelCase__        =   0




					def 						_SCREAMING_SNAKE_CASE						(	self						:     List[Any]     ):
							lowerCAmelCase__        =   AutoImageProcessor.from_pretrained("""openai/clip-vit-base-patch32"""     )
							self.assertIsInstance(snake_case__  ,						snake_case__     )




					def 						_SCREAMING_SNAKE_CASE						(	self						:     Tuple     ):
							with tempfile.TemporaryDirectory() as tmpdirname:
									lowerCAmelCase__        =   Path(snake_case__     ) / """preprocessor_config.json"""
									lowerCAmelCase__        =   Path(snake_case__     ) / """config.json"""
									json.dump(
									    {"""image_processor_type""": """CLIPImageProcessor""", """processor_class""": """CLIPProcessor"""}  ,						open(snake_case__  ,						"""w"""     )  ,						)
									json.dump({"""model_type""": """clip"""}  ,						open(snake_case__  ,						"""w"""     )     )

									lowerCAmelCase__        =   AutoImageProcessor.from_pretrained(snake_case__     )
									self.assertIsInstance(snake_case__  ,						snake_case__     )




					def 						_SCREAMING_SNAKE_CASE						(	self						:     Union[str, Any]     ):
							# Ensure we can load the image processor from the feature extractor config
							with tempfile.TemporaryDirectory() as tmpdirname:
									lowerCAmelCase__        =   Path(snake_case__     ) / """preprocessor_config.json"""
									lowerCAmelCase__        =   Path(snake_case__     ) / """config.json"""
									json.dump(
									    {"""feature_extractor_type""": """CLIPFeatureExtractor""", """processor_class""": """CLIPProcessor"""}  ,						open(snake_case__  ,						"""w"""     )  ,						)
									json.dump({"""model_type""": """clip"""}  ,						open(snake_case__  ,						"""w"""     )     )

									lowerCAmelCase__        =   AutoImageProcessor.from_pretrained(snake_case__     )
									self.assertIsInstance(snake_case__  ,						snake_case__     )




					def 						_SCREAMING_SNAKE_CASE						(	self						:     Optional[int]     ):
							with tempfile.TemporaryDirectory() as tmpdirname:
									lowerCAmelCase__        =   CLIPConfig()

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

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

									config_dict.pop("""image_processor_type"""     )
									lowerCAmelCase__        =   CLIPImageProcessor(**snake_case__     )

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

									lowerCAmelCase__        =   AutoImageProcessor.from_pretrained(snake_case__     )

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

							self.assertIsInstance(snake_case__  ,						snake_case__     )




					def 						_SCREAMING_SNAKE_CASE						(	self						:     Dict     ):
							with tempfile.TemporaryDirectory() as tmpdirname:
									lowerCAmelCase__        =   Path(snake_case__     ) / """preprocessor_config.json"""
									json.dump(
									    {"""image_processor_type""": """CLIPImageProcessor""", """processor_class""": """CLIPProcessor"""}  ,						open(snake_case__  ,						"""w"""     )  ,						)

									lowerCAmelCase__        =   AutoImageProcessor.from_pretrained(snake_case__     )
									self.assertIsInstance(snake_case__  ,						snake_case__     )




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




					def 						_SCREAMING_SNAKE_CASE						(	self						:     Union[str, Any]     ):
							with self.assertRaisesRegex(
							    snake_case__  ,						R"""aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)"""     ):
									lowerCAmelCase__        =   AutoImageProcessor.from_pretrained(snake_case__  ,						revision="""aaaaaa"""     )




					def 						_SCREAMING_SNAKE_CASE						(	self						:     Optional[Any]     ):
							with self.assertRaisesRegex(
							    snake_case__  ,						"""hf-internal-testing/config-no-model does not appear to have a file named preprocessor_config.json."""  ,						):
									lowerCAmelCase__        =   AutoImageProcessor.from_pretrained("""hf-internal-testing/config-no-model"""     )




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

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

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




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

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

											lowerCAmelCase__        =   CustomImageProcessor.from_pretrained(snake_case__     )

									# 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(snake_case__     )
											lowerCAmelCase__        =   AutoImageProcessor.from_pretrained(snake_case__     )
											self.assertIsInstance(snake_case__  ,						snake_case__     )

							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						:     List[str]     ):

							class       a_      (     __UpperCamelCase			):
												UpperCamelCase_ :	Tuple			=    True

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

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




