


# 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      lowerCAmelCase__       (				a):




     '''simple docstring'''
     __SCREAMING_SNAKE_CASE  			= "dandelin/vilt-b32-finetuned-vqa"
     __SCREAMING_SNAKE_CASE  			= (
         "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."
     )
     __SCREAMING_SNAKE_CASE  			= "image_qa"
     __SCREAMING_SNAKE_CASE  			= AutoProcessor
     __SCREAMING_SNAKE_CASE  			= AutoModelForVisualQuestionAnswering

     __SCREAMING_SNAKE_CASE  			= ["image", "text"]
     __SCREAMING_SNAKE_CASE  			= ["text"]


     def __init__(						self ,						*__lowerCamelCase ,						**__lowerCamelCase)			->				int:
            requires_backends(self ,						["vision"])
            super().__init__(*__lowerCamelCase ,						**__lowerCamelCase)


     def  _lowerCamelCase (						self ,						__lowerCamelCase ,						__lowerCamelCase)			->				Tuple:
            return self.pre_processor(__lowerCamelCase ,						__lowerCamelCase ,						return_tensors="pt")


     def  _lowerCamelCase (						self ,						__lowerCamelCase)			->				List[Any]:
            with torch.no_grad():
                   return self.model(**__lowerCamelCase).logits


     def  _lowerCamelCase (						self ,						__lowerCamelCase)			->				List[Any]:
            _A      :       str				    = outputs.argmax(-1).item()
            return self.model.config.idalabel[idx]




def 							_UpperCAmelCase				(UpperCamelCase__     :  Optional[Any]				,							UpperCamelCase__     :  Union[str, Any]						):
       # "extended trapezoidal rule"
       # int(f) = dx/2 * (f1 + 2f2 + ... + fn)
       _A      :       int				    = (boundary[1] - boundary[0]) / steps
       _A      :       Any				    = boundary[0]
       _A      :       List[Any]				    = boundary[1]
       _A      :       str				    = make_points(UpperCamelCase__				,							UpperCamelCase__				,							UpperCamelCase__						)
       _A      :       str				    = 0.0
       y += (h / 2.0) * f(UpperCamelCase__						)
       for i in x_i:
              # print(i)
              y += h * f(UpperCamelCase__						)
       y += (h / 2.0) * f(UpperCamelCase__						)
       return y
def 							_UpperCAmelCase				(UpperCamelCase__     :  List[str]				,							UpperCamelCase__     :  Optional[int]				,							UpperCamelCase__     :  Any						):
       _A      :       Optional[int]				    = a + h
       while x < (b - h):
              yield x
              _A      :       Dict				    = x + h
def 							_UpperCAmelCase				(UpperCamelCase__     :  Optional[int]						):  # enter your function here
       _A      :       Any				    = (x - 0) * (x - 0)
       return y
def 							_UpperCAmelCase				():
       _A      :       Optional[Any]				    = 0.0  # Lower bound of integration
       _A      :       Optional[int]				    = 1.0  # Upper bound of integration
       _A      :       List[Any]				    = 10.0  # define number of steps or resolution
       _A      :       Any				    = [a, b]  # define boundary of integration
       _A      :       Tuple				    = method_a(UpperCamelCase__				,							UpperCamelCase__						)
       print(f"y = {y}"						)


if __name__ == "__main__":
    main()
