






'''simple docstring'''

def     __lowercase  (_lowercase     )   ->     str:


					"""simple docstring"""
					__lowerCamelCase						:       Dict				   =				0

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

					# append each character + "|" in new_string for range(0, length-1)
					for i in input_string[: len(_lowercase     ) - 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
					__lowerCamelCase						:       Dict				   =				0, 0

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

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

										__lowerCamelCase						:       int				   =				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:
															__lowerCamelCase						:       Tuple				   =				j - k + 1  # noqa: E741
															__lowerCamelCase						:       Tuple				   =				j + k - 1

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

    # create that string
					__lowerCamelCase						:       str				   =				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'''

import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import Audio, Features, Value
from .base import TaskTemplate







@dataclass(frozen=lowerCAmelCase_  )
class 	SCREAMING_SNAKE_CASE	(      lowerCAmelCase_  ):
       snake_case__    :     str   		=			field(default='automatic-speech-recognition'    ,   metadata={'include_in_asdict_even_if_is_default': True}  )
       snake_case__    :     ClassVar[Features]   		=			Features({'audio': Audio()}  )
       snake_case__    :     ClassVar[Features]   		=			Features({'transcription': Value('string'  )}  )
       snake_case__    :     str   		=			"audio"
       snake_case__    :     str   		=			"transcription"




       def 					a_					(					self      : Any	,    A__      : Any					):


            """simple docstring"""







            if self.audio_column not in features:
                 raise ValueError(f"Column {self.audio_column} is not present in features."					)
            if not isinstance(features[self.audio_column]	,    A__					):
                 raise ValueError(f"Column {self.audio_column} is not an Audio type."					)
            __lowerCamelCase						:       Dict				   =				copy.deepcopy(self					)
            __lowerCamelCase						:       List[Any]				   =				self.input_schema.copy()
            __lowerCamelCase						:       Optional[int]				   =				features[self.audio_column]
            __lowerCamelCase						:       Any				   =				input_schema
            return task_template




       @property
       def 					a_					(					self      : Any					):


            """simple docstring"""







            return {self.audio_column: "audio", self.transcription_column: "transcription"}



