




import math





def        __UpperCAmelCase						(							lowerCamelCase_ :     int  )       ->  list:







			"""simple docstring"""





			SCREAMING_SNAKE_CASE_   : int					  =      [True] * n
			SCREAMING_SNAKE_CASE_   : Any					  =      False
			SCREAMING_SNAKE_CASE_   : List[Any]					  =      False
			SCREAMING_SNAKE_CASE_   : Optional[int]					  =      True

			for i in range(3  ,							int(n**0.5 + 1  )  ,							2  ):
						SCREAMING_SNAKE_CASE_   : Dict					  =      i * 2
						while index < n:
									SCREAMING_SNAKE_CASE_   : Any					  =      False
									SCREAMING_SNAKE_CASE_   : Any					  =      index + i

			SCREAMING_SNAKE_CASE_   : Union[str, Any]					  =      [2]

			for i in range(3  ,							lowerCamelCase_  ,							2  ):
						if is_prime[i]:
									primes.append(lowerCamelCase_  )

			return primes





def        __UpperCAmelCase						(							lowerCamelCase_ :     int = 99_99_66_66_33_33  )       ->  int:







			"""simple docstring"""





			SCREAMING_SNAKE_CASE_   : Union[str, Any]					  =      math.floor(math.sqrt(lowerCamelCase_  )  ) + 1_00
			SCREAMING_SNAKE_CASE_   : Tuple					  =      prime_sieve(lowerCamelCase_  )

			SCREAMING_SNAKE_CASE_   : int					  =      0
			SCREAMING_SNAKE_CASE_   : Union[str, Any]					  =      0
			SCREAMING_SNAKE_CASE_   : Dict					  =      primes[prime_index]

			while (last_prime**2) <= limit:
						SCREAMING_SNAKE_CASE_   : Optional[int]					  =      primes[prime_index + 1]

						SCREAMING_SNAKE_CASE_   : Union[str, Any]					  =      last_prime**2
						SCREAMING_SNAKE_CASE_   : Tuple					  =      next_prime**2

						# Get numbers divisible by lps(current)
						SCREAMING_SNAKE_CASE_   : List[str]					  =      lower_bound + last_prime
						while upper_bound > current <= limit:
									matches_sum += current
									current += last_prime

						# Reset the upper_bound
						while (upper_bound - next_prime) > limit:
									upper_bound -= next_prime

						# Add the numbers divisible by ups(current)
						SCREAMING_SNAKE_CASE_   : Optional[Any]					  =      upper_bound - next_prime
						while current > lower_bound:
									matches_sum += current
									current -= next_prime

						# Remove the numbers divisible by both ups and lps
						SCREAMING_SNAKE_CASE_   : Any					  =      0
						while upper_bound > current <= limit:
									if current <= lower_bound:
												# Increment the current number
												current += last_prime * next_prime
												continue

									if current > limit:
												break

									# Remove twice since it was added by both ups and lps
									matches_sum -= current * 2

									# Increment the current number
									current += last_prime * next_prime

						# Setup for next pair
						SCREAMING_SNAKE_CASE_   : Optional[Any]					  =      next_prime
						prime_index += 1

			return matches_sum


if __name__ == "__main__":
						print(solution())









from typing import Union

from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline


if is_vision_available():
						from PIL import Image

						from ..image_utils import load_image

if is_torch_available():
						from ..models.auto.modeling_auto import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING

UpperCamelCase__ :   List[str]						=							logging.get_logger(__name__)







@add_end_docstrings(lowerCamelCase_							)
class 				lowerCAmelCase_       (					lowerCamelCase_							):






				def __init__(			self      ,*snake_case__      ,**snake_case__ ):
							super().__init__(*snake_case__      ,**snake_case__ )
							self.check_model_type(snake_case__ )






				def 		snake_case	(			self      ,snake_case__=None      ,snake_case__=None      ,snake_case__=None      ,**snake_case__ ):
							SCREAMING_SNAKE_CASE_  ,    SCREAMING_SNAKE_CASE_   : Union[str, Any]					  =      {}, {}
							if padding is not None:
										SCREAMING_SNAKE_CASE_   : Any					  =      padding
							if truncation is not None:
										SCREAMING_SNAKE_CASE_   : Tuple					  =      truncation
							if top_k is not None:
										SCREAMING_SNAKE_CASE_   : int					  =      top_k
							return preprocess_params, {}, postprocess_params






				def __call__(			self      ,snake_case__      ,snake_case__ = None      ,**snake_case__ ):
							if isinstance(snake_case__      ,(Image.Image, str) ) and isinstance(snake_case__      ,snake_case__ ):
										SCREAMING_SNAKE_CASE_   : Optional[Any]					  =      {'image': image, 'question': question}
							else:
										SCREAMING_SNAKE_CASE_   : Optional[int]					  =      image
							SCREAMING_SNAKE_CASE_   : List[Any]					  =      super().__call__(snake_case__      ,**snake_case__ )
							return results






				def 		snake_case	(			self      ,snake_case__      ,snake_case__=False      ,snake_case__=False ):
							SCREAMING_SNAKE_CASE_   : List[str]					  =      load_image(inputs['image'] )
							SCREAMING_SNAKE_CASE_   : Dict					  =      self.tokenizer(
							    inputs['question']      ,return_tensors=self.framework      ,padding=snake_case__      ,truncation=snake_case__ )
							SCREAMING_SNAKE_CASE_   : Any					  =      self.image_processor(images=snake_case__      ,return_tensors=self.framework )
							model_inputs.update(snake_case__ )
							return model_inputs






				def 		snake_case	(			self      ,snake_case__ ):
							SCREAMING_SNAKE_CASE_   : Optional[int]					  =      self.model(**snake_case__ )
							return model_outputs






				def 		snake_case	(			self      ,snake_case__      ,snake_case__=5 ):
							if top_k > self.model.config.num_labels:
										SCREAMING_SNAKE_CASE_   : Union[str, Any]					  =      self.model.config.num_labels

							if self.framework == "pt":
										SCREAMING_SNAKE_CASE_   : Any					  =      model_outputs.logits.sigmoid()[0]
										SCREAMING_SNAKE_CASE_  ,    SCREAMING_SNAKE_CASE_   : Dict					  =      probs.topk(snake_case__ )
							else:
										raise ValueError(F'Unsupported framework: {self.framework}' )

							SCREAMING_SNAKE_CASE_   : Optional[int]					  =      scores.tolist()
							SCREAMING_SNAKE_CASE_   : Union[str, Any]					  =      ids.tolist()
							return [{"score": score, "answer": self.model.config.idalabel[_id]} for score, _id in zip(snake_case__      ,snake_case__ )]



