


"""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 				UpperCamelCase_			(				UpperCamelCase):

 """simple docstring"""





 snake_case__       :						int					      =    "dandelin/vilt-b32-finetuned-vqa"
 snake_case__       :						str					      =    (
     "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."
 )
 snake_case__       :						Dict					      =    "image_qa"
 snake_case__       :						Optional[int]					      =    AutoProcessor
 snake_case__       :						Union[str, Any]					      =    AutoModelForVisualQuestionAnswering

 snake_case__       :						Dict					      =    ["image", "text"]
 snake_case__       :						Union[str, Any]					      =    ["text"]




 def __init__(				self    :       Any    ,    *UpperCAmelCase__    :       Union[str, Any]    ,    **UpperCAmelCase__    :       Any     ) ->			int:
      requires_backends(self    ,    ["vision"]     )
      super().__init__(*UpperCAmelCase__    ,    **UpperCAmelCase__     )




 def 						UpperCAmelCase_   (				self    :       Union[str, Any]    ,    UpperCAmelCase__    :       "Image"    ,    UpperCAmelCase__    :       str     ) ->			Optional[Any]:
      return self.pre_processor(UpperCAmelCase__    ,    UpperCAmelCase__    ,    return_tensors="pt"     )




 def 						UpperCAmelCase_   (				self    :       str    ,    UpperCAmelCase__    :       Tuple     ) ->			Optional[Any]:
      with torch.no_grad():
           return self.model(**UpperCAmelCase__     ).logits




 def 						UpperCAmelCase_   (				self    :       int    ,    UpperCAmelCase__    :       Optional[Any]     ) ->			Any:
      __SCREAMING_SNAKE_CASE		     =       outputs.argmax(-1     ).item()
      return self.model.config.idalabel[idx]




"""simple docstring"""







from abc import ABC, abstractmethod
from argparse import ArgumentParser




class 				UpperCamelCase_			(				UpperCamelCase):

	"""simple docstring"""





	@staticmethod
	@abstractmethod
	def 						UpperCAmelCase_   (				UpperCAmelCase__    :       ArgumentParser     ) ->			Optional[Any]:
						raise NotImplementedError()




	@abstractmethod
	def 						UpperCAmelCase_   (				self    :       Optional[Any]     ) ->			List[str]:
						raise NotImplementedError()
