
import random


def     __lowerCAmelCase			(			a__  )       ->  bool:
				__a										=    num - 1
				__a										=    0

				while s % 2 == 0:
								__a										=    s // 2
								t += 1

				for _ in range(5  ):
								__a										=    random.randrange(2						,    num - 1  )
								__a										=    pow(a__						,    a__						,    a__  )
								if v != 1:
												__a										=    0
												while v != (num - 1):
																if i == t - 1:
																				return False
																else:
																				__a										=    i + 1
																				__a										=    (v**2) % num
				return True


def     __lowerCAmelCase			(			a__  )       ->  bool:
				if num < 2:
								return False

				__a										=    [
				    2,
				    3,
				    5,
				    7,
				    11,
				    13,
				    17,
				    19,
				    23,
				    29,
				    31,
				    37,
				    41,
				    43,
				    47,
				    53,
				    59,
				    61,
				    67,
				    71,
				    73,
				    79,
				    83,
				    89,
				    97,
				    101,
				    103,
				    107,
				    109,
				    113,
				    127,
				    131,
				    137,
				    139,
				    149,
				    151,
				    157,
				    163,
				    167,
				    173,
				    179,
				    181,
				    191,
				    193,
				    197,
				    199,
				    211,
				    223,
				    227,
				    229,
				    233,
				    239,
				    241,
				    251,
				    257,
				    263,
				    269,
				    271,
				    277,
				    281,
				    283,
				    293,
				    307,
				    311,
				    313,
				    317,
				    331,
				    337,
				    347,
				    349,
				    353,
				    359,
				    367,
				    373,
				    379,
				    383,
				    389,
				    397,
				    401,
				    409,
				    419,
				    421,
				    431,
				    433,
				    439,
				    443,
				    449,
				    457,
				    461,
				    463,
				    467,
				    479,
				    487,
				    491,
				    499,
				    503,
				    509,
				    521,
				    523,
				    541,
				    547,
				    557,
				    563,
				    569,
				    571,
				    577,
				    587,
				    593,
				    599,
				    601,
				    607,
				    613,
				    617,
				    619,
				    631,
				    641,
				    643,
				    647,
				    653,
				    659,
				    661,
				    673,
				    677,
				    683,
				    691,
				    701,
				    709,
				    719,
				    727,
				    733,
				    739,
				    743,
				    751,
				    757,
				    761,
				    769,
				    773,
				    787,
				    797,
				    809,
				    811,
				    821,
				    823,
				    827,
				    829,
				    839,
				    853,
				    857,
				    859,
				    863,
				    877,
				    881,
				    883,
				    887,
				    907,
				    911,
				    919,
				    929,
				    937,
				    941,
				    947,
				    953,
				    967,
				    971,
				    977,
				    983,
				    991,
				    997,
				]

				if num in low_primes:
								return True

				for prime in low_primes:
								if (num % prime) == 0:
												return False

				return rabin_miller(a__  )


def     __lowerCAmelCase			(			a__ = 1024  )       ->  int:
				while True:
								__a										=    random.randrange(2 ** (keysize - 1)						,    2 ** (keysize)  )
								if is_prime_low_num(a__  ):
												return num


if __name__ == "__main__":
					A     :	Any    = generate_large_prime()
					print(('Prime number:', num))
					print(('is_prime_low_num:', is_prime_low_num(num)))






import warnings
from contextlib import contextmanager

from ...processing_utils import ProcessorMixin






class 					__A    (    lowerCAmelCase ):

			'''simple docstring'''







			lowerCAmelCase_							     =						"""Speech2TextFeatureExtractor"""
			lowerCAmelCase_							     =						"""Speech2TextTokenizer"""





			def __init__(    self       ,  __lowerCAmelCase       ,  __lowerCAmelCase							):



				'''simple docstring'''







				super().__init__(__lowerCAmelCase       ,  __lowerCAmelCase							)
				lowerCamelCase__								=		self.feature_extractor
				lowerCamelCase__								=		False





			def __call__(    self       ,  *__lowerCAmelCase       ,  **__lowerCAmelCase							):



				'''simple docstring'''







				if self._in_target_context_manager:
					return self.current_processor(*__lowerCAmelCase       ,  **__lowerCAmelCase							)

				if "raw_speech" in kwargs:
					warnings.warn('''Using `raw_speech` as a keyword argument is deprecated. Use `audio` instead.'''							)
					lowerCamelCase__								=		kwargs.pop('''raw_speech'''							)
				else:
					lowerCamelCase__								=		kwargs.pop('''audio'''       ,  __lowerCAmelCase							)
				lowerCamelCase__								=		kwargs.pop('''sampling_rate'''       ,  __lowerCAmelCase							)
				lowerCamelCase__								=		kwargs.pop('''text'''       ,  __lowerCAmelCase							)
				if len(__lowerCAmelCase							) > 0:
					lowerCamelCase__								=		args[0]
					lowerCamelCase__								=		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:
					lowerCamelCase__								=		self.feature_extractor(__lowerCAmelCase       ,  *__lowerCAmelCase       ,  sampling_rate=__lowerCAmelCase       ,  **__lowerCAmelCase							)
				if text is not None:
					lowerCamelCase__								=		self.tokenizer(__lowerCAmelCase       ,  **__lowerCAmelCase							)

				if text is None:
					return inputs
				elif audio is None:
					return encodings
				else:
					lowerCamelCase__								=		encodings['''input_ids''']
					return inputs





			def 		__lowerCamelCase				(    self       ,  *__lowerCAmelCase       ,  **__lowerCAmelCase							):



				'''simple docstring'''







				return self.tokenizer.batch_decode(*__lowerCAmelCase       ,  **__lowerCAmelCase							)





			def 		__lowerCamelCase				(    self       ,  *__lowerCAmelCase       ,  **__lowerCAmelCase							):



				'''simple docstring'''







				return self.tokenizer.decode(*__lowerCAmelCase       ,  **__lowerCAmelCase							)





			@contextmanager
			def 		__lowerCamelCase				(    self							):



				'''simple docstring'''







				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.'''							)
				lowerCamelCase__								=		True
				lowerCamelCase__								=		self.tokenizer
				yield
				lowerCamelCase__								=		self.feature_extractor
				lowerCamelCase__								=		False



