


'''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 		lowerCAmelCase__	(	UpperCAmelCase__		):
			lowerCAmelCase       :		str				      =   "dandelin/vilt-b32-finetuned-vqa"
			lowerCAmelCase       :		Optional[Any]				      =   (
			    "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       :		str				      =   "image_qa"
			lowerCAmelCase       :		Union[str, Any]				      =   AutoProcessor
			lowerCAmelCase       :		Optional[int]				      =   AutoModelForVisualQuestionAnswering

			lowerCAmelCase       :		List[Any]				      =   ["image", "text"]
			lowerCAmelCase       :		Any				      =   ["text"]




			def __init__(						self     :   Any		,     *lowerCamelCase__     :   List[str]		,     **lowerCamelCase__     :   Any       )      ->Dict:



					'''simple docstring'''







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




			def 							lowerCAmelCase__			(						self     :   List[Any]		,     lowerCamelCase__     :   "Image"		,     lowerCamelCase__     :   str       )      ->Optional[Any]:



					'''simple docstring'''







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




			def 							lowerCAmelCase__			(						self     :   str		,     lowerCamelCase__     :   List[str]       )      ->Union[str, Any]:



					'''simple docstring'''







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






			def 							lowerCAmelCase__			(						self     :   Any		,     lowerCamelCase__     :   Union[str, Any]       )      ->List[str]:



					'''simple docstring'''







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







'''simple docstring'''


import math






def        __lowerCAmelCase       (__lowerCAmelCase      ):
		return math.sqrt(__lowerCAmelCase      ) * math.sqrt(__lowerCAmelCase      ) == num






def        __lowerCAmelCase       (__lowerCAmelCase      ):
		_UpperCAmelCase						:				int	    =					0
		_UpperCAmelCase						:				Tuple	    =					n
		while left <= right:
				_UpperCAmelCase						:				int	    =					(left + right) // 2
				if mid**2 == n:
						return True
				elif mid**2 > n:
						_UpperCAmelCase						:				str	    =					mid - 1
				else:
						_UpperCAmelCase						:				List[str]	    =					mid + 1
		return False


if __name__ == "__main__":
						import doctest

						doctest.testmod()



