


lowerCAmelCase__      		= [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
lowerCAmelCase__      		= [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
lowerCAmelCase__      		= {
    0: 'Sunday',
    1: 'Monday',
    2: 'Tuesday',
    3: 'Wednesday',
    4: 'Thursday',
    5: 'Friday',
    6: 'Saturday',
}
def 							_UpperCAmelCase				(UpperCamelCase__     :  int				,							UpperCamelCase__     :  int				,							UpperCamelCase__     :  int						):
       assert len(str(UpperCamelCase__						)						) > 2, "year should be in YYYY format"
       assert 1 <= month <= 12, "month should be between 1 to 12"
       assert 1 <= day <= 31, "day should be between 1 to 31"

       # Doomsday algorithm:
       _A      :       List[Any]				    = year // 100
       _A      :       List[str]				    = (5 * (century % 4) + 2) % 7
       _A      :       str				    = year % 100
       _A      :       List[Any]				    = centurian % 12
       _A      :       Tuple				    = (
           (centurian // 12) + centurian_m + (centurian_m // 4) + century_anchor
       ) % 7
       _A      :       Optional[Any]				    = (
           DOOMSDAY_NOT_LEAP[month - 1]
           if (year % 4 != 0) or (centurian == 0 and (year % 400) == 0)
           else DOOMSDAY_LEAP[month - 1]
       )
       _A      :       Tuple				    = (dooms_day + day - day_anchor) % 7
       return WEEK_DAY_NAMES[week_day]


if __name__ == "__main__":
    import doctest

    doctest.testmod()




from typing import TYPE_CHECKING

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


lowerCAmelCase__      		= {
    '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:
    lowerCAmelCase__      		= ['SpeechT5Tokenizer']

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

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