


from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import Features, Value
from .base import TaskTemplate





@dataclass(frozen=__UpperCamelCase      )
class   __a			(    __UpperCamelCase      ):
 __lowercase :							str        = field(default='language-modeling'       ,       metadata={'include_in_asdict_even_if_is_default': True}      )

 __lowercase :							ClassVar[Features]        = Features({'text': Value('string'      )}      )
 __lowercase :							ClassVar[Features]        = Features({}      )
 __lowercase :							str        = "text"
 @property
 def 		SCREAMING_SNAKE_CASE__   (   self )					->				Dict[str, str]:




        '''simple docstring'''
        return {self.text_column: "text"}






from typing import TYPE_CHECKING

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


__lowerCAmelCase		       =							{
    '''configuration_encodec''': [
        '''ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''EncodecConfig''',
    ],
    '''feature_extraction_encodec''': ['''EncodecFeatureExtractor'''],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __lowerCAmelCase		       =							[
     '''ENCODEC_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''EncodecModel''',
     '''EncodecPreTrainedModel''',
 ]

if TYPE_CHECKING:
 from .configuration_encodec import (
     ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP,
     EncodecConfig,
 )
 from .feature_extraction_encodec import EncodecFeatureExtractor

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_encodec import (
      ENCODEC_PRETRAINED_MODEL_ARCHIVE_LIST,
      EncodecModel,
      EncodecPreTrainedModel,
  )

else:
 import sys

 __lowerCAmelCase		       =							_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


