"""simple docstring"""





from typing import TYPE_CHECKING

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


__A  =				{
    '''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  =				['''SpeechT5Tokenizer''']

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__A  =				[
				    '''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  =				_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
"""simple docstring"""





import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class  _snake_case     :
						snake_case__			  =			None
						snake_case__			  =			False
						snake_case__			  =			False
						snake_case__			  =			False
						snake_case__			  =			None
						snake_case__			  =			None
						snake_case__			  =			False
						snake_case__			  =			False
						snake_case__			  =			False
						snake_case__			  =			True
						snake_case__			  =			None
						snake_case__			  =			1
						snake_case__			  =			None
						snake_case__			  =			False
						snake_case__			  =			None
						snake_case__			  =			None






						def       lowerCamelCase__     (       self      :			Any    ):
													return self.__class__(**{k: copy.deepcopy(UpperCAmelCase    ) for k, v in self.__dict__.items()}    )