


"""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 		snake_case_(       a__			):
     __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_  :					Dict					,				**UpperCamelCase_  :					List[Any]				):
           requires_backends(self					,				['''vision''']				)
           super().__init__(*lowercase_					,				**lowercase_				)






     def      lowerCamelCase__     (	self  :					Tuple					,				UpperCamelCase_  :					"Image"					,				UpperCamelCase_  :					str				):
           return self.pre_processor(lowercase_					,				lowercase_					,				return_tensors='''pt'''				)






     def      lowerCamelCase__     (	self  :					List[Any]					,				UpperCamelCase_  :					int				):







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






     def      lowerCamelCase__     (	self  :					Any					,				UpperCamelCase_  :					Any				):
           lowerCAmelCase					:	List[Any]       =   outputs.argmax(-1				).item()
           return self.model.config.idalabel[idx]






"""simple docstring"""





def      _snake_case						(						_snake_case				:			int = 4000000			):
      lowerCAmelCase					:	int       =   [0, 1]
      lowerCAmelCase					:	List[str]       =   0
      while fib[i] <= n:
            fib.append(fib[i] + fib[i + 1]			)
            if fib[i + 2] > n:
                  break
            i += 1
      lowerCAmelCase					:	int       =   0
      for j in range(len(_snake_case			) - 1			):
            if fib[j] % 2 == 0:
                  total += fib[j]

      return total


if __name__ == "__main__":
 print(f"""{solution() = }""")


