





from typing import TYPE_CHECKING

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


A   : Optional[Any]			=				{
    '''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:
					A   : Optional[Any]			=				['''SpeechT5Tokenizer''']

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					A   : Any			=				[
					    '''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

					A   : Optional[Any]			=				_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)










def        __lowerCamelCase (							__a       :int = 3   ,					__a       :int = 7   ,					__a       :int = 1_0_0_0_0_0_0   )		->    int:






		"""simple docstring"""

		A__  				=       0
		A__  				=       1

		for current_denominator in range(1   ,					limit + 1   ):
				A__  				=       current_denominator * numerator // denominator
				if current_denominator % denominator == 0:
						current_numerator -= 1
				if current_numerator * max_denominator > current_denominator * max_numerator:
						A__  				=       current_numerator
						A__  				=       current_denominator
		return max_numerator


if __name__ == "__main__":
					print(solution(numerator=3, denominator=7, limit=1_0_0_0_0_0_0))



