

"""simple docstring"""





from __future__ import annotations

import math

def     __SCREAMING_SNAKE_CASE    ( A_					):

	if num <= 0:
		lowerCAmelCase__      :		Any    							=      f'{num}: Invalid input, please enter a positive integer.'
		raise ValueError(A_					)

	lowerCAmelCase__      :		Any    							=      [True] * (num + 1)
	lowerCAmelCase__      :		Dict    							=      []
	lowerCAmelCase__      :		int    							=      2
	lowerCAmelCase__      :		List[str]    							=      int(math.sqrt(A_					)					)

	while start <= end:
		# If start is a prime
		if sieve[start] is True:
			prime.append(A_					)

			# Set multiples of start be False
			for i in range(start * start		,	num + 1		,	A_					):
				if sieve[i] is True:
					lowerCAmelCase__      :		Tuple    							=      False

		start += 1

	for j in range(end + 1		,	num + 1					):
		if sieve[j] is True:
			prime.append(A_					)

	return prime


if __name__ == "__main__":
							print(prime_sieve(int(input('''Enter a positive integer: ''').strip())))







"""simple docstring"""





# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

from ..models.auto import AutoModelForVisionaSeq
from ..utils import requires_backends
from .base import PipelineTool


if TYPE_CHECKING:
							from PIL import Image







class 							SCREAMING_SNAKE_CASE   (						a_			):






					"""simple docstring"""



					lowercase__												=			"Salesforce/blip-image-captioning-base"
					lowercase__												=			(
					    "This is a tool that generates a description of an image. It takes an input named `image` which should be the "
					    "image to caption, and returns a text that contains the description in English."
					)
					lowercase__												=			"image_captioner"
					lowercase__												=			AutoModelForVisionaSeq

					lowercase__												=			["image"]
					lowercase__												=			["text"]







					def __init__(			self     :							int  ,*lowercase_     :							int  ,**lowercase_     :							List[str]						):
						requires_backends(self  ,['''vision''']						)
						super().__init__(*lowercase_  ,**lowercase_						)







					def 			__lowerCAmelCase					(			self     :							List[str]  ,lowercase_     :							"Image"						):
						return self.pre_processor(images=lowercase_  ,return_tensors='''pt'''						)







					def 			__lowerCAmelCase					(			self     :							List[Any]  ,lowercase_     :							Any						):
						return self.model.generate(**lowercase_						)







					def 			__lowerCAmelCase					(			self     :							Dict  ,lowercase_     :							Union[str, Any]						):
						return self.pre_processor.batch_decode(lowercase_  ,skip_special_tokens=lowercase_						)[0].strip()




