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 __snake_case       (		_a	):
			lowerCAmelCase_														=							"""dandelin/vilt-b32-finetuned-vqa"""
			lowerCAmelCase_														=							(
			    """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_														=							"""image_qa"""
			lowerCAmelCase_														=							AutoProcessor
			lowerCAmelCase_														=							AutoModelForVisualQuestionAnswering

			lowerCAmelCase_														=							["""image""", """text"""]
			lowerCAmelCase_														=							["""text"""]




			def __init__(					self    :       Optional[Any] ,			*_lowercase    :       int ,			**_lowercase    :       Optional[int]   ):



					"""simple docstring"""






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




			def 			__a		(					self    :       Optional[Any] ,			_lowercase    :       int ,			_lowercase    :       int   ):



					"""simple docstring"""






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




			def 			__a		(					self    :       Dict ,			_lowercase    :       str   ):



					"""simple docstring"""






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




			def 			__a		(					self    :       Dict ,			_lowercase    :       Dict   ):



					"""simple docstring"""






					SCREAMING_SNAKE_CASE__    							=   outputs.argmax(-1   ).item()
					return self.model.config.idalabel[idx]

def 			__SCREAMING_SNAKE_CASE						(      __UpperCamelCase					: list				,  __UpperCamelCase					: list				,  __UpperCamelCase					: int				,  __UpperCamelCase					: int				,  __UpperCamelCase					: int			)							->      int:







  """simple docstring"""





  if index == number_of_items:
    return 0
  SCREAMING_SNAKE_CASE__    							=   0
  SCREAMING_SNAKE_CASE__    							=   0
  SCREAMING_SNAKE_CASE__    							=   knapsack(__UpperCamelCase				,  __UpperCamelCase				,  __UpperCamelCase				,  __UpperCamelCase				,  index + 1			)
  if weights[index] <= max_weight:
    SCREAMING_SNAKE_CASE__    							=   values[index] + knapsack(
        __UpperCamelCase				,  __UpperCamelCase				,  __UpperCamelCase				,  max_weight - weights[index]				,  index + 1			)
  return max(__UpperCamelCase				,  __UpperCamelCase			)


if __name__ == "__main__":
   import doctest

   doctest.testmod()
