
"""simple docstring"""







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__)






def        SCREAMING_SNAKE_CASE      (       _UpperCAmelCase						,	_UpperCAmelCase )			->     bool:
    lowerCamelCase__    :      List[str]					 =		len(_UpperCAmelCase )
    lowerCamelCase__    :      str					 =		[[False] * (required_sum + 1) for _ in range(arr_len + 1 )]

    # for each arr value, a sum of zero(0) can be formed by not taking any element
    # hence True/1
    for i in range(arr_len + 1 ):
        lowerCamelCase__    :      Tuple					 =		True

    # sum is not zero and set is empty then false
    for i in range(1						,	required_sum + 1 ):
        lowerCamelCase__    :      Dict					 =		False

    for i in range(1						,	arr_len + 1 ):
        for j in range(1						,	required_sum + 1 ):
            if arr[i - 1] > j:
                lowerCamelCase__    :      str					 =		subset[i - 1][j]
            if arr[i - 1] <= j:
                lowerCamelCase__    :      Dict					 =		subset[i - 1][j] or subset[i - 1][j - arr[i - 1]]

    return subset[arr_len][required_sum]


if __name__ == "__main__":
    import doctest

    doctest.testmod()





