


import warnings
from contextlib import contextmanager

from ...processing_utils import ProcessorMixin







class  snake_case_     (lowerCamelCase_   ):
					UpperCAmelCase__      :					str					   =    '''Speech2TextFeatureExtractor'''
					UpperCAmelCase__      :					Union[str, Any]					   =    '''Speech2TextTokenizer'''
					def __init__(   self     :str    ,__snake_case     :List[str]    ,__snake_case     :List[str]   )      ->					Union[str, Any]:
												super().__init__(__snake_case    ,__snake_case   )
												a__    =  self.feature_extractor
												a__    =  False
					def __call__(   self     :List[str]    ,*__snake_case     :Optional[Any]    ,**__snake_case     :str   )      ->					int:
												# For backward compatibility
												if self._in_target_context_manager:
																			return self.current_processor(*__snake_case    ,**__snake_case   )

												if "raw_speech" in kwargs:
																			warnings.warn('Using `raw_speech` as a keyword argument is deprecated. Use `audio` instead.'   )
																			a__    =  kwargs.pop('raw_speech'   )
												else:
																			a__    =  kwargs.pop('audio'    ,__snake_case   )
												a__    =  kwargs.pop('sampling_rate'    ,__snake_case   )
												a__    =  kwargs.pop('text'    ,__snake_case   )
												if len(__snake_case   ) > 0:
																			a__    =  args[0]
																			a__    =  args[1:]

												if audio is None and text is None:
																			raise ValueError('You need to specify either an `audio` or `text` input to process.'   )

												if audio is not None:
																			a__    =  self.feature_extractor(__snake_case    ,*__snake_case    ,sampling_rate=__snake_case    ,**__snake_case   )
												if text is not None:
																			a__    =  self.tokenizer(__snake_case    ,**__snake_case   )

												if text is None:
																			return inputs
												elif audio is None:
																			return encodings
												else:
																			a__    =  encodings['input_ids']
																			return inputs
					def 				lowerCamelCase__(   self     :str    ,*__snake_case     :Union[str, Any]    ,**__snake_case     :List[Any]   )      ->					Dict:
												return self.tokenizer.batch_decode(*__snake_case    ,**__snake_case   )
					def 				lowerCamelCase__(   self     :Tuple    ,*__snake_case     :Optional[Any]    ,**__snake_case     :int   )      ->					Union[str, Any]:
												return self.tokenizer.decode(*__snake_case    ,**__snake_case   )



					@contextmanager
					def 				lowerCamelCase__(   self     :Tuple   )      ->					Optional[int]:
												warnings.warn(
												    '`as_target_processor` is deprecated and will be removed in v5 of Transformers. You can process your '
												    'labels by using the argument `text` of the regular `__call__` method (either in the same call as '
												    'your audio inputs, or in a separate call.'   )
												a__    =  True
												a__    =  self.tokenizer
												yield
												a__    =  self.feature_extractor
												a__    =  False








from math import sqrt






def 							__lowercase     (				__lowerCAmelCase							:       int     ):

							if 1 < number < 4:
														# 2 and 3 are primes
														return True
							elif number < 2 or number % 2 == 0 or number % 3 == 0:
														# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
														return False

							# All primes number are in format of 6k +/- 1
							for i in range(5      ,					int(sqrt(__lowerCAmelCase     ) + 1     )      ,					6     ):
														if number % i == 0 or number % (i + 2) == 0:
																					return False
							return True






def 							__lowercase     (				__lowerCAmelCase							:       int = 1_0_0_0_1     ):
							a__    =  0
							a__    =  1
							while count != nth and number < 3:
														number += 1
														if is_prime(__lowerCAmelCase     ):
																					count += 1
							while count != nth:
														number += 2
														if is_prime(__lowerCAmelCase     ):
																					count += 1
							return number


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




