






'''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 UpperCAmelCase_					(    __A				):




      """simple docstring"""




      UpperCamelCase_								=			'''dandelin/vilt-b32-finetuned-vqa'''
      UpperCamelCase_								=			(
          '''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.'''
      )
      UpperCamelCase_								=			'''image_qa'''
      UpperCamelCase_								=			AutoProcessor
      UpperCamelCase_								=			AutoModelForVisualQuestionAnswering

      UpperCamelCase_								=			['''image''', '''text''']
      UpperCamelCase_								=			['''text''']






      def __init__( self			:		Optional[int]     ,      *UpperCAmelCase			:		Any     ,      **UpperCAmelCase			:		Dict		)  ->  Dict:


       '''simple docstring'''

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






      def 				A__      ( self			:		Tuple     ,      UpperCAmelCase			:		"Image"     ,      UpperCAmelCase			:		str		)  ->  Tuple:


       '''simple docstring'''

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






      def 				A__      ( self			:		Dict     ,      UpperCAmelCase			:		List[str]		)  ->  Optional[int]:


       '''simple docstring'''

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






      def 				A__      ( self			:		Dict     ,      UpperCAmelCase			:		Tuple		)  ->  List[str]:


       '''simple docstring'''

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











'''simple docstring'''



import importlib.metadata
from typing import Union

from packaging.version import Version, parse

from .constants import STR_OPERATION_TO_FUNC


SCREAMING_SNAKE_CASE						=	parse(importlib.metadata.version('torch'))


def 							lowercase_				(    __A :       Union[str, Version]					,      __A :       str					,      __A :       str			)       ->      Union[str, Any]:



 """simple docstring"""




 if operation not in STR_OPERATION_TO_FUNC.keys():
  raise ValueError(F'`operation` must be one of {list(STR_OPERATION_TO_FUNC.keys()			)}, received {operation}'			)
 lowercase					:   Any				  =STR_OPERATION_TO_FUNC[operation]
 if isinstance(__A					,      __A			):
  lowercase					:   List[Any]				  =parse(importlib.metadata.version(__A			)			)
 return operation(__A					,      parse(__A			)			)





def 							lowercase_				(    __A :       str					,      __A :       str			)       ->      Tuple:



 """simple docstring"""




 return compare_versions(__A					,      __A					,      __A			)



