


import enum
import os
from hashlib import shaaaa
from typing import Optional

from .. import config
from .logging import get_logger


lowerCAmelCase__    :Tuple       =				get_logger(__name__)

class 						__a (							enum.Enum     ):
		_a      :    List[Any]           =      'all_checks'
		_a      :    List[str]           =      'basic_checks'
		_a      :    List[str]           =      'no_checks'



class 						__a (							UpperCAmelCase     ):
		pass



class 						__a (							UpperCAmelCase     ):
		pass



class 						__a (							UpperCAmelCase     ):
		pass



class 						__a (							UpperCAmelCase     ):
		pass



def 			lowerCAmelCase__					(     a__:						Optional[dict]     ,    a__:						dict     ,    a__:						Any=None			)    ->						List[str]:


							'''simple docstring'''





							if expected_checksums is None:
														logger.info('Unable to verify checksums.'			)
														return
							if len(set(a__			) - set(a__			)			) > 0:
														raise ExpectedMoreDownloadedFiles(str(set(a__			) - set(a__			)			)			)
							if len(set(a__			) - set(a__			)			) > 0:
														raise UnexpectedDownloadedFile(str(set(a__			) - set(a__			)			)			)
							_UpperCAmelCase											=     [url for url in expected_checksums if expected_checksums[url] != recorded_checksums[url]]
							_UpperCAmelCase											=     ' for ' + verification_name if verification_name is not None else ''
							if len(a__			) > 0:
														raise NonMatchingChecksumError(
														    F'''Checksums didn\'t match{for_verification_name}:\n'''
														    F'''{bad_urls}\n'''
														    'Set `verification_mode=\'no_checks\'` to skip checksums verification and ignore this error'			)
							logger.info('All the checksums matched successfully' + for_verification_name			)

class 						__a (							UpperCAmelCase     ):
		pass



class 						__a (							UpperCAmelCase     ):
		pass



class 						__a (							UpperCAmelCase     ):
		pass



class 						__a (							UpperCAmelCase     ):
		pass



def 			lowerCAmelCase__					(     a__:						Optional[dict]     ,    a__:						dict			)    ->						Optional[int]:


							'''simple docstring'''





							if expected_splits is None:
														logger.info('Unable to verify splits sizes.'			)
														return
							if len(set(a__			) - set(a__			)			) > 0:
														raise ExpectedMoreSplits(str(set(a__			) - set(a__			)			)			)
							if len(set(a__			) - set(a__			)			) > 0:
														raise UnexpectedSplits(str(set(a__			) - set(a__			)			)			)
							_UpperCAmelCase											=     [
							    {'expected': expected_splits[name], 'recorded': recorded_splits[name]}
							    for name in expected_splits
							    if expected_splits[name].num_examples != recorded_splits[name].num_examples
							]
							if len(a__			) > 0:
														raise NonMatchingSplitsSizesError(str(a__			)			)
							logger.info('All the splits matched successfully.'			)

def 			lowerCAmelCase__					(     a__:						str     ,    a__:						bool = True			)    ->						dict:


							'''simple docstring'''





							if record_checksum:
														_UpperCAmelCase											=     shaaaa()
														with open(a__     ,    'rb'			) as f:
																					for chunk in iter(lambda: f.read(1 << 2_0			)     ,    B''			):
																												m.update(a__			)
																					_UpperCAmelCase											=     m.hexdigest()
							else:
														_UpperCAmelCase											=     None
							return {"num_bytes": os.path.getsize(a__			), "checksum": checksum}







def 			lowerCAmelCase__					(     a__:						str			)    ->						Union[str, Any]:


							'''simple docstring'''





							if dataset_size and config.IN_MEMORY_MAX_SIZE:
														return dataset_size < config.IN_MEMORY_MAX_SIZE
							else:
														return False




from typing import TYPE_CHECKING

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


lowerCAmelCase__    :Tuple       =				{
    '''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__    :Dict       =				['''SpeechT5Tokenizer''']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCAmelCase__    :List[str]       =				[
		    '''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__    :str       =				_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
