
'''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

import torch

from ..models.auto import AutoModelForVisualQuestionAnswering, AutoProcessor
from ..utils import requires_backends
from .base import PipelineTool


if TYPE_CHECKING:
      from PIL import Image





class 					A							(				__snake_case		):
     __magic_name__          =						'''dandelin/vilt-b32-finetuned-vqa'''
     __magic_name__          =						(
         '''This is a tool that answers a question about an image. It takes an input named `image` which should be the '''
         '''image containing the information, as well as a `question` which should be the question in English. It '''
         '''returns a text that is the answer to the question.'''
     )
     __magic_name__          =						'''image_qa'''
     __magic_name__          =						AutoProcessor
     __magic_name__          =						AutoModelForVisualQuestionAnswering

     __magic_name__          =						['''image''', '''text''']
     __magic_name__          =						['''text''']





     def __init__(				self		,     *SCREAMING_SNAKE_CASE		,     **SCREAMING_SNAKE_CASE      )					->							Dict:






         """simple docstring"""






         requires_backends(self		,     ['''vision''']      )
         super().__init__(*SCREAMING_SNAKE_CASE		,     **SCREAMING_SNAKE_CASE      )





     def 							__lowerCAmelCase				(				self		,     SCREAMING_SNAKE_CASE		,     SCREAMING_SNAKE_CASE      )					->							Optional[Any]:






         """simple docstring"""






         return self.pre_processor(SCREAMING_SNAKE_CASE		,     SCREAMING_SNAKE_CASE		,     return_tensors='''pt'''      )





     def 							__lowerCAmelCase				(				self		,     SCREAMING_SNAKE_CASE      )					->							Union[str, Any]:






         """simple docstring"""






         with torch.no_grad():
             return self.model(**SCREAMING_SNAKE_CASE      ).logits





     def 							__lowerCAmelCase				(				self		,     SCREAMING_SNAKE_CASE      )					->							List[Any]:






         """simple docstring"""






         A			:  Optional[int]   =		outputs.argmax(-1      ).item()
         return self.model.config.idalabel[idx]






'''simple docstring'''




import math
from collections.abc import Callable







def 						lowerCAmelCase_							(  snake_case__						,							snake_case__						,							snake_case__		):




    '''simple docstring'''



    A			:  float   =		xa
    A			:  float   =		xa
    while True:
        if x_n == x_na or function(snake_case__		) == function(snake_case__		):
            raise ZeroDivisionError('''float division by zero, could not find root'''		)
        A			:  float   =		x_na - (
            function(snake_case__		) / ((function(snake_case__		) - function(snake_case__		)) / (x_na - x_n))
        )
        if abs(x_na - x_na		) < 10**-5:
            return x_na
        A			:  Any   =		x_na
        A			:  Any   =		x_na







def 						lowerCAmelCase_							(  snake_case__		):




    '''simple docstring'''



    return math.pow(snake_case__						,							3		) - (2 * x) - 5


if __name__ == "__main__":
      print(intersection(f, 3, 3.5))




