




# 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       a					(       __lowerCamelCase      ):

     '''simple docstring'''





     lowerCAmelCase    :	Union[str, Any]       		=  'Salesforce/blip-image-captioning-base'
     lowerCAmelCase    :	Optional[Any]       		=  (
         '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.'
     )
     lowerCAmelCase    :	Optional[Any]       		=  'image_captioner'
     lowerCAmelCase    :	List[Any]       		=  AutoModelForVisionaSeq

     lowerCAmelCase    :	Optional[Any]       		=  ['image']
     lowerCAmelCase    :	int       		=  ['text']
     def __init__(     self       :      Union[str, Any] ,   *__snake_case       :      List[str] ,   **__snake_case       :      str    ):
         requires_backends(self ,   ['''vision''']    )
         super().__init__(*UpperCamelCase_ ,   **UpperCamelCase_    )
     def   lowerCamelCase_       (     self       :      Dict ,   __snake_case       :      "Image"    ):
         return self.pre_processor(images=UpperCamelCase_ ,   return_tensors='''pt'''    )
     def   lowerCamelCase_       (     self       :      int ,   __snake_case       :      Dict    ):
         return self.model.generate(**UpperCamelCase_    )




     def   lowerCamelCase_       (     self       :      Optional[int] ,   __snake_case       :      List[Any]    ):
         return self.pre_processor.batch_decode(UpperCamelCase_ ,   skip_special_tokens=UpperCamelCase_    )[0].strip()











from __future__ import annotations

from fractions import Fraction




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						int	,					__UpperCamelCase      :						int				)  ->							bool:
    return (
        num != den and num % 10 == den // 10 and (num // 10) / (den % 10) == num / den
    )




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						int				)  ->							list[str]:
    UpperCAmelCase_										=					[]
    UpperCAmelCase_										=					11
    UpperCAmelCase_										=					int('''1''' + '''0''' * digit_len				)
    for num in range(__UpperCamelCase	,					__UpperCamelCase				):
        while den <= 99:
            if (num != den) and (num % 10 == den // 10) and (den % 10 != 0):
                if is_digit_cancelling(__UpperCamelCase	,					__UpperCamelCase				):
                    solutions.append(f'{num}/{den}'				)
            den += 1
        num += 1
        UpperCAmelCase_										=					10
    return solutions




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						int = 2				)  ->							int:
    UpperCAmelCase_										=					1.0
    for fraction in fraction_list(__UpperCamelCase				):
        UpperCAmelCase_										=					Fraction(__UpperCamelCase				)
        result *= frac.denominator / frac.numerator
    return int(__UpperCamelCase				)


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





