


'''simple docstring'''


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__	(	__lowerCamelCase		):
			lowerCAmelCase       :		Any				      =   "dandelin/vilt-b32-finetuned-vqa"
			lowerCAmelCase       :		Optional[int]				      =   (
			    "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."
			)
			lowerCAmelCase       :		Tuple				      =   "image_qa"
			lowerCAmelCase       :		List[str]				      =   AutoProcessor
			lowerCAmelCase       :		List[Any]				      =   AutoModelForVisualQuestionAnswering

			lowerCAmelCase       :		Optional[Any]				      =   ["image", "text"]
			lowerCAmelCase       :		Optional[int]				      =   ["text"]




			def __init__(						self     :   List[str]		,     *lowerCamelCase__     :   str		,     **lowerCamelCase__     :   List[str]       )      ->List[str]:



					'''simple docstring'''







					requires_backends(self		,     ["vision"]       )
					super().__init__(*__A		,     **__A       )




			def 							lowerCAmelCase__			(						self     :   List[Any]		,     lowerCamelCase__     :   "Image"		,     lowerCamelCase__     :   str       )      ->str:



					'''simple docstring'''







					return self.pre_processor(__A		,     __A		,     return_tensors="pt"       )




			def 							lowerCAmelCase__			(						self     :   Any		,     lowerCamelCase__     :   Tuple       )      ->Optional[Any]:



					'''simple docstring'''







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






			def 							lowerCAmelCase__			(						self     :   Tuple		,     lowerCamelCase__     :   int       )      ->Any:



					'''simple docstring'''







					_UpperCAmelCase						:				Union[str, Any]	    =					outputs.argmax(-1       ).item()
					return self.model.config.idalabel[idx]










'''simple docstring'''
import random
def 				lowercase__   (   __lowercase						:  list				,  __lowercase						:  Optional[Any]     ) ->      tuple:



       """simple docstring"""






       __UpperCamelCase       ,						__UpperCamelCase       ,						__UpperCamelCase       =  [], [], []
       for element in data:
              if element < pivot:
                     less.append(__lowercase     )
              elif element > pivot:
                     greater.append(__lowercase     )
              else:
                     equal.append(__lowercase     )
       return less, equal, greater


def 				lowercase__   (   __lowercase						:  list				,  __lowercase						:  int     ) ->      Dict:



       """simple docstring"""






       if index >= len(__lowercase     ) or index < 0:
              return None

       __UpperCamelCase       =  items[random.randint(0				,  len(__lowercase     ) - 1     )]
       __UpperCamelCase       =  0
       __UpperCamelCase       ,						__UpperCamelCase       ,						__UpperCamelCase       =  _partition(__lowercase				,  __lowercase     )
       __UpperCamelCase       =  len(__lowercase     )
       __UpperCamelCase       =  len(__lowercase     )

       # index is the pivot
       if m <= index < m + count:
              return pivot
       # must be in smaller
       elif m > index:
              return quick_select(__lowercase				,  __lowercase     )
       # must be in larger
       else:
              return quick_select(__lowercase				,  index - (m + count)     )
