



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


a_								=       {
    """configuration_transfo_xl""": ["""TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TransfoXLConfig"""],
    """tokenization_transfo_xl""": ["""TransfoXLCorpus""", """TransfoXLTokenizer"""],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a_								=       [
      """TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """AdaptiveEmbedding""",
      """TransfoXLForSequenceClassification""",
      """TransfoXLLMHeadModel""",
      """TransfoXLModel""",
      """TransfoXLPreTrainedModel""",
      """load_tf_weights_in_transfo_xl""",
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a_								=       [
      """TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """TFAdaptiveEmbedding""",
      """TFTransfoXLForSequenceClassification""",
      """TFTransfoXLLMHeadModel""",
      """TFTransfoXLMainLayer""",
      """TFTransfoXLModel""",
      """TFTransfoXLPreTrainedModel""",
  ]


if TYPE_CHECKING:
  from .configuration_transfo_xl import TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP, TransfoXLConfig
  from .tokenization_transfo_xl import TransfoXLCorpus, TransfoXLTokenizer

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_transfo_xl import (
        TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST,
        AdaptiveEmbedding,
        TransfoXLForSequenceClassification,
        TransfoXLLMHeadModel,
        TransfoXLModel,
        TransfoXLPreTrainedModel,
        load_tf_weights_in_transfo_xl,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_transfo_xl import (
        TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST,
        TFAdaptiveEmbedding,
        TFTransfoXLForSequenceClassification,
        TFTransfoXLLMHeadModel,
        TFTransfoXLMainLayer,
        TFTransfoXLModel,
        TFTransfoXLPreTrainedModel,
    )

else:
  import sys

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














"""simple docstring"""





from typing import List

from .keymap import KEYMAP, get_character



def   a    (     __UpperCAmelCase      :    str  )    ->							Optional[int]:

						def decorator(__UpperCAmelCase      :    List[str]  ):
												__magic_name__:	Union[str, Any]							=       getattr(__UpperCAmelCase      ,   """handle_key"""      ,   []  )
												handle += [key]
												setattr(__UpperCAmelCase      ,   """handle_key"""      ,   __UpperCAmelCase  )
												return func

						return decorator



def   a    (     *__UpperCAmelCase      :    List[str]  )    ->							Union[str, Any]:

						def decorator(__UpperCAmelCase      :    Tuple  ):
												__magic_name__:	Union[str, Any]							=       getattr(__UpperCAmelCase      ,   """handle_key"""      ,   []  )
												handle += keys
												setattr(__UpperCAmelCase      ,   """handle_key"""      ,   __UpperCAmelCase  )
												return func

						return decorator



class       __A		(   SCREAMING_SNAKE_CASE_			):

					def __new__(			cls  :      Optional[Any]     ,		__snake_case  :      List[str]     ,		__snake_case  :      Optional[Any]     ,		__snake_case  :      Any					)			->							List[Any]:
											__magic_name__:	str							=       super().__new__(cls     ,		__snake_case     ,		__snake_case     ,		__snake_case					)
											if not hasattr(__snake_case     ,		"""key_handler"""					):
																	setattr(__snake_case     ,		"""key_handler"""     ,		{}					)
											setattr(__snake_case     ,		"""handle_input"""     ,		KeyHandler.handle_input					)

											for value in attrs.values():
																	__magic_name__:	List[str]							=       getattr(__snake_case     ,		"""handle_key"""     ,		[]					)
																	for key in handled_keys:
																							__magic_name__:	Any							=       value
											return new_cls






					@staticmethod
					def   lowerCamelCase__   (			cls  :      List[Any]					)			->							Optional[Any]:
											__magic_name__:	List[str]							=       get_character()
											if char != KEYMAP["undefined"]:
																	__magic_name__:	Union[str, Any]							=       ord(__snake_case					)
											__magic_name__:	Dict							=       cls.key_handler.get(__snake_case					)
											if handler:
																	__magic_name__:	List[str]							=       char
																	return handler(cls					)
											else:
																	return None



def   a    (     cls      :    List[Any]  )    ->							int:
						return KeyHandler(cls.__name__      ,   cls.__bases__      ,   cls.__dict__.copy()  )



