


from typing import TYPE_CHECKING

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


A				:       int      =  {
    '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				:       Dict      =  ['SpeechT5Tokenizer']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A				:       Optional[int]      =  [
	    '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				:       Any      =  _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)









def 						_lowerCAmelCase							(     _lowerCAmelCase			)    ->						int:


						'''simple docstring'''






						assert column_title.isupper()
						__snake_case				=		0
						__snake_case				=		len(_lowerCAmelCase			) - 1
						__snake_case				=		0

						while index >= 0:
												__snake_case				=		(ord(column_title[index]			) - 64) * pow(26   ,						_lowerCAmelCase			)
												answer += value
												power += 1
												index -= 1

						return answer


if __name__ == "__main__":
	from doctest import testmod

	testmod()





