# 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				(						lowerCamelCase_		):
   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			:				Tuple       ,	*_lowercase			:				Dict       ,	**_lowercase			:				Dict      ):



     """simple docstring"""






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




   def 	__a						(    self			:				Tuple       ,	_lowercase			:				"Image"       ,	_lowercase			:				str      ):



     """simple docstring"""






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




   def 	__a						(    self			:				List[Any]       ,	_lowercase			:				Any      ):



     """simple docstring"""






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




   def 	__a						(    self			:				List[Any]       ,	_lowercase			:				str      ):



     """simple docstring"""






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

from numpy import exp, pi, sqrt



def 	__SCREAMING_SNAKE_CASE  (					__UpperCamelCase    :       Any ,     __UpperCamelCase    :       float = 0.0 ,     __UpperCamelCase    :       float = 1.0	)							->					int:







  """simple docstring"""





  return 1 / sqrt(2 * pi * sigma**2	) * exp(-((x - mu) ** 2) / (2 * sigma**2)	)


if __name__ == "__main__":
   import doctest

   doctest.testmod()
