




from typing import TYPE_CHECKING

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


UpperCamelCase__    			=			{
    '''configuration_speecht5''': [
        '''SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''SPEECHT5_PRETRAINED_HIFIGAN_CONFIG_ARCHIVE_MAP''',
        '''SpeechT5Config''',
        '''SpeechT5HifiGanConfig''',
    ],
    '''feature_extraction_speecht5''': ['''SpeechT5FeatureExtractor'''],
    '''processing_speecht5''': ['''SpeechT5Processor'''],
}

try:
					if not is_sentencepiece_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase__    			=			['''SpeechT5Tokenizer''']

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase__    			=			[
					    '''SPEECHT5_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''SpeechT5ForSpeechToText''',
					    '''SpeechT5ForSpeechToSpeech''',
					    '''SpeechT5ForTextToSpeech''',
					    '''SpeechT5Model''',
					    '''SpeechT5PreTrainedModel''',
					    '''SpeechT5HifiGan''',
					]

if TYPE_CHECKING:
					from .configuration_speechta import (
					    SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP,
					    SPEECHT5_PRETRAINED_HIFIGAN_CONFIG_ARCHIVE_MAP,
					    SpeechTaConfig,
					    SpeechTaHifiGanConfig,
					)
					from .feature_extraction_speechta import SpeechTaFeatureExtractor
					from .processing_speechta import SpeechTaProcessor

					try:
										if not is_sentencepiece_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_speechta import SpeechTaTokenizer

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_speechta import (
										    SPEECHT5_PRETRAINED_MODEL_ARCHIVE_LIST,
										    SpeechTaForSpeechToSpeech,
										    SpeechTaForSpeechToText,
										    SpeechTaForTextToSpeech,
										    SpeechTaHifiGan,
										    SpeechTaModel,
										    SpeechTaPreTrainedModel,
										)

else:
					import sys

					UpperCamelCase__    			=			_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)








'''simple docstring'''







from math import isqrt


def 	SCREAMING_SNAKE_CASE_					(  _UpperCAmelCase	:	int  )  ->			bool:
       return all(number % divisor != 0 for divisor in range(2    ,isqrt(_UpperCAmelCase  ) + 1  )  )


def 	SCREAMING_SNAKE_CASE_					(  _UpperCAmelCase	:	int = 10**6  )  ->			int:
       _a    : List[Any]     					=0
       _a    : str     					=1
       _a    : Optional[Any]     					=7
       while prime_candidate < max_prime:
              primes_count += is_prime(_UpperCAmelCase  )

              cube_index += 1
              prime_candidate += 6 * cube_index

       return primes_count


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


