





'''simple docstring'''







def        lowerCamelCase_      (  SCREAMING_SNAKE_CASE__      :			str   ) ->	str:
						UpperCAmelCase_			:      Optional[Any]     						=  0

						# if input_string is "aba" than new_input_string become "a|b|a"
						UpperCAmelCase_			:      Tuple     						=  ''''''
						UpperCAmelCase_			:      Dict     						=  ''''''

						# append each character + "|" in new_string for range(0, length-1)
						for i in input_string[: len(SCREAMING_SNAKE_CASE__   ) - 1]:
												new_input_string += i + "|"
						# append last character
						new_input_string += input_string[-1]

						# we will store the starting and ending of previous furthest ending palindromic
						# substring
						UpperCAmelCase_						,       UpperCAmelCase_			:      Optional[int]     						=  0, 0

						# length[i] shows the length of palindromic substring with center i
						UpperCAmelCase_			:      List[Any]     						=  [1 for i in range(len(SCREAMING_SNAKE_CASE__   )   )]

						# for each character in new_string find corresponding palindromic string
						UpperCAmelCase_			:      str     						=  0
						for j in range(len(SCREAMING_SNAKE_CASE__   )   ):
												UpperCAmelCase_			:      Union[str, Any]     						=  1 if j > r else min(length[l + r - j] // 2,			r - j + 1   )
												while (
												    j - k >= 0
												    and j + k < len(SCREAMING_SNAKE_CASE__   )
												    and new_input_string[k + j] == new_input_string[j - k]
												):
																		k += 1

												UpperCAmelCase_			:      List[Any]     						=  2 * k - 1

												# does this string is ending after the previously explored end (that is r) ?
												# if yes the update the new r to the last index of this
												if j + k - 1 > r:
																		UpperCAmelCase_			:      Union[str, Any]     						=  j - k + 1  # noqa: E741
																		UpperCAmelCase_			:      Union[str, Any]     						=  j + k - 1

												# update max_length and start position
												if max_length < length[j]:
																		UpperCAmelCase_			:      Any     						=  length[j]
																		UpperCAmelCase_			:      List[str]     						=  j

    # create that string
						UpperCAmelCase_			:      Any     						=  new_input_string[start - max_length // 2 : start + max_length // 2 + 1]
						for i in s:
												if i != "|":
																		output_string += i

						return output_string


if __name__ == "__main__":
					import doctest

					doctest.testmod()












'''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 					__a      (lowerCamelCase     ):
							__a					:   int									=       "dandelin/vilt-b32-finetuned-vqa"
							__a					:   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."
							)
							__a					:   Any									=       "image_qa"
							__a					:   str									=       AutoProcessor
							__a					:   Any									=       AutoModelForVisualQuestionAnswering

							__a					:   List[Any]									=       ["image", "text"]
							__a					:   int									=       ["text"]

							def __init__(							self							:     Tuple       ,     *__magic_name__							:     Any       ,     **__magic_name__							:     Any   )					->       Tuple:







													"""simple docstring"""
													requires_backends(self       ,     ['''vision''']   )
													super().__init__(*__magic_name__       ,     **__magic_name__   )

							def     UpperCAmelCase__	(							self							:     Union[str, Any]       ,     __magic_name__							:     "Image"       ,     __magic_name__							:     str   )					->       Tuple:







													"""simple docstring"""
													return self.pre_processor(__magic_name__       ,     __magic_name__       ,     return_tensors='''pt'''   )

							def     UpperCAmelCase__	(							self							:     Any       ,     __magic_name__							:     List[str]   )					->       Optional[Any]:







													"""simple docstring"""
													with torch.no_grad():
																			return self.model(**__magic_name__   ).logits



							def     UpperCAmelCase__	(							self							:     int       ,     __magic_name__							:     int   )					->       Optional[int]:







													"""simple docstring"""
													UpperCAmelCase_			:      Dict     						=  outputs.argmax(-1   ).item()
													return self.model.config.idalabel[idx]





