def SCREAMING_SNAKE_CASE			(       lowercase_:		int			):
							_UpperCamelCase       :    Any					  =					[True for i in range(n + 1			)]
							_UpperCamelCase       :    Tuple					  =					[i - 1 for i in range(n + 1			)]
							_UpperCamelCase       :    List[Any]					  =					[]
							for i in range(2						,  n + 1			):
														if is_prime[i]:
																					primes.append(lowercase_			)
														for j in range(0						,  len(lowercase_			)			):
																					if i * primes[j] >= n:
																												break
																					_UpperCamelCase       :    List[Any]					  =					False

																					if i % primes[j] == 0:
																												_UpperCamelCase       :    Union[str, Any]					  =					totients[i] * primes[j]
																												break

																					_UpperCamelCase       :    Tuple					  =					totients[i] * (primes[j] - 1)

							return totients


if __name__ == "__main__":
	import doctest

	doctest.testmod()




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_speech_available,
    is_torch_available,
)


UpperCAmelCase     						=			{
    '''configuration_speech_to_text_2''': ['''SPEECH_TO_TEXT_2_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Speech2Text2Config'''],
    '''processing_speech_to_text_2''': ['''Speech2Text2Processor'''],
    '''tokenization_speech_to_text_2''': ['''Speech2Text2Tokenizer'''],
}


try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 UpperCAmelCase     						=			[
     '''SPEECH_TO_TEXT_2_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''Speech2Text2ForCausalLM''',
     '''Speech2Text2PreTrainedModel''',
 ]


if TYPE_CHECKING:
 from .configuration_speech_to_text_a import SPEECH_TO_TEXT_2_PRETRAINED_CONFIG_ARCHIVE_MAP, SpeechaTextaConfig
 from .processing_speech_to_text_a import SpeechaTextaProcessor
 from .tokenization_speech_to_text_a import SpeechaTextaTokenizer

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_speech_to_text_a import (
      SPEECH_TO_TEXT_2_PRETRAINED_MODEL_ARCHIVE_LIST,
      SpeechaTextaForCausalLM,
      SpeechaTextaPreTrainedModel,
  )

else:
 import sys

 UpperCAmelCase     						=			_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



