
from ..utils import DummyObject, requires_backends





class   __UpperCamelCase				(    metaclass=lowerCAmelCase__   ):






     """simple docstring"""







     lowerCAmelCase_     =	['''torch''', '''librosa''']



     def __init__(							self    :    Dict      ,		*_A    :    Any      ,		**_A    :    List[str]				):







       """simple docstring"""




       requires_backends(self      ,		['''torch''', '''librosa''']				)



     @classmethod
     def 				UpperCAmelCase__    (							cls    :    str      ,		*_A    :    Tuple      ,		**_A    :    Any				):







       """simple docstring"""




       requires_backends(cls      ,		['''torch''', '''librosa''']				)




     @classmethod
     def 				UpperCAmelCase__    (							cls    :    List[str]      ,		*_A    :    List[str]      ,		**_A    :    str				):







       """simple docstring"""




       requires_backends(cls      ,		['''torch''', '''librosa''']				)






class   __UpperCamelCase				(    metaclass=lowerCAmelCase__   ):






     """simple docstring"""







     lowerCAmelCase_     =	['''torch''', '''librosa''']



     def __init__(							self    :    str      ,		*_A    :    str      ,		**_A    :    List[Any]				):







       """simple docstring"""




       requires_backends(self      ,		['''torch''', '''librosa''']				)



     @classmethod
     def 				UpperCAmelCase__    (							cls    :    Optional[int]      ,		*_A    :    List[Any]      ,		**_A    :    List[Any]				):







       """simple docstring"""




       requires_backends(cls      ,		['''torch''', '''librosa''']				)




     @classmethod
     def 				UpperCAmelCase__    (							cls    :    int      ,		*_A    :    List[Any]      ,		**_A    :    Optional[int]				):







       """simple docstring"""




       requires_backends(cls      ,		['''torch''', '''librosa''']				)


from typing import TYPE_CHECKING

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


lowercase_											=	{
    """configuration_led""": ["""LED_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LEDConfig"""],
    """tokenization_led""": ["""LEDTokenizer"""],
}

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowercase_											=	["""LEDTokenizerFast"""]

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowercase_											=	[
       """LED_PRETRAINED_MODEL_ARCHIVE_LIST""",
       """LEDForConditionalGeneration""",
       """LEDForQuestionAnswering""",
       """LEDForSequenceClassification""",
       """LEDModel""",
       """LEDPreTrainedModel""",
   ]


try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowercase_											=	["""TFLEDForConditionalGeneration""", """TFLEDModel""", """TFLEDPreTrainedModel"""]


if TYPE_CHECKING:
   from .configuration_led import LED_PRETRAINED_CONFIG_ARCHIVE_MAP, LEDConfig
   from .tokenization_led import LEDTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_led_fast import LEDTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_led import (
          LED_PRETRAINED_MODEL_ARCHIVE_LIST,
          LEDForConditionalGeneration,
          LEDForQuestionAnswering,
          LEDForSequenceClassification,
          LEDModel,
          LEDPreTrainedModel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_led import TFLEDForConditionalGeneration, TFLEDModel, TFLEDPreTrainedModel

else:
   import sys

   lowercase_											=	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
