





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__)



from graphs.minimum_spanning_tree_kruskal import kruskal


def 							__lowerCAmelCase     (							)		->				Optional[Any]:
 '''simple docstring'''


 SCREAMING_SNAKE_CASE		    =      9
 SCREAMING_SNAKE_CASE		    =      [
     [0, 1, 4],
     [0, 7, 8],
     [1, 2, 8],
     [7, 8, 7],
     [7, 6, 1],
     [2, 8, 2],
     [8, 6, 6],
     [2, 3, 7],
     [2, 5, 4],
     [6, 5, 2],
     [3, 5, 14],
     [3, 4, 9],
     [5, 4, 10],
     [1, 7, 11],
 ]

 SCREAMING_SNAKE_CASE		    =      kruskal(_UpperCamelCase		,				_UpperCamelCase						)

 SCREAMING_SNAKE_CASE		    =      [
     [7, 6, 1],
     [2, 8, 2],
     [6, 5, 2],
     [0, 1, 4],
     [2, 5, 4],
     [2, 3, 7],
     [0, 7, 8],
     [3, 4, 9],
 ]

 assert sorted(_UpperCamelCase						) == sorted(_UpperCamelCase						)

