def lowerCamelCase						(     SCREAMING_SNAKE_CASE						,    SCREAMING_SNAKE_CASE			):
    '''simple docstring'''







    return x if y == 0 else greatest_common_divisor(SCREAMING_SNAKE_CASE						,    x % y			)



def lowerCamelCase						(     SCREAMING_SNAKE_CASE						,    SCREAMING_SNAKE_CASE			):
    '''simple docstring'''







    return (x * y) // greatest_common_divisor(SCREAMING_SNAKE_CASE						,    SCREAMING_SNAKE_CASE			)



def lowerCamelCase						(     SCREAMING_SNAKE_CASE = 20			):
    '''simple docstring'''







    __UpperCamelCase  :int    						=	1
    for i in range(1						,    n + 1			):
        __UpperCamelCase  :List[Any]    						=	lcm(SCREAMING_SNAKE_CASE						,    SCREAMING_SNAKE_CASE			)
    return g


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






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_speech_available, is_torch_available


__lowercase											=      {
    '''configuration_audio_spectrogram_transformer''': [
        '''AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''ASTConfig''',
    ]
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowercase											=      [
        '''AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''ASTForAudioClassification''',
        '''ASTModel''',
        '''ASTPreTrainedModel''',
    ]

try:
    if not is_speech_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowercase											=      ['''ASTFeatureExtractor''']

if TYPE_CHECKING:
    from .configuration_audio_spectrogram_transformer import (
        AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
        ASTConfig,
    )

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_audio_spectrogram_transformer import (
            AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
            ASTForAudioClassification,
            ASTModel,
            ASTPreTrainedModel,
        )

    try:
        if not is_speech_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .feature_extraction_audio_spectrogram_transformer import ASTFeatureExtractor


else:
    import sys

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





