





'''simple docstring'''






from typing import TYPE_CHECKING

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


A__				:   List[str]      ={
    '''configuration_tapas''': ['''TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TapasConfig'''],
    '''tokenization_tapas''': ['''TapasTokenizer'''],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      A__				:   Dict      =[
          '''TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST''',
          '''TapasForMaskedLM''',
          '''TapasForQuestionAnswering''',
          '''TapasForSequenceClassification''',
          '''TapasModel''',
          '''TapasPreTrainedModel''',
          '''load_tf_weights_in_tapas''',
      ]
try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      A__				:   Any      =[
          '''TF_TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST''',
          '''TFTapasForMaskedLM''',
          '''TFTapasForQuestionAnswering''',
          '''TFTapasForSequenceClassification''',
          '''TFTapasModel''',
          '''TFTapasPreTrainedModel''',
      ]


if TYPE_CHECKING:
      from .configuration_tapas import TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP, TapasConfig
      from .tokenization_tapas import TapasTokenizer

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tapas import (
                TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST,
                TapasForMaskedLM,
                TapasForQuestionAnswering,
                TapasForSequenceClassification,
                TapasModel,
                TapasPreTrainedModel,
                load_tf_weights_in_tapas,
            )

      try:
            if not is_tf_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_tapas import (
                TF_TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST,
                TFTapasForMaskedLM,
                TFTapasForQuestionAnswering,
                TFTapasForSequenceClassification,
                TFTapasModel,
                TFTapasPreTrainedModel,
            )


else:
      import sys

      A__				:   str      =_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)













'''simple docstring'''

from typing import List

from .keymap import KEYMAP, get_character





def lowerCamelCase						(     __lowerCamelCase :    str    )						->Optional[int]:

    def decorator(__lowerCamelCase :    int    ):
        _SCREAMING_SNAKE_CASE									=			getattr(__lowerCamelCase					,       """handle_key"""					,       []    )
        handle += [key]
        setattr(__lowerCamelCase					,       """handle_key"""					,       __lowerCamelCase    )
        return func

    return decorator





def lowerCamelCase						(     *__lowerCamelCase :    List[str]    )						->Dict:

    def decorator(__lowerCamelCase :    int    ):
        _SCREAMING_SNAKE_CASE									=			getattr(__lowerCamelCase					,       """handle_key"""					,       []    )
        handle += keys
        setattr(__lowerCamelCase					,       """handle_key"""					,       __lowerCamelCase    )
        return func

    return decorator


class 					a_     (				snake_case_       ):

    '''simple docstring'''


    def __new__(		cls ,		A ,		A ,		A       )		->   int:
        _SCREAMING_SNAKE_CASE									=			super().__new__(cls ,		A ,		A ,		A       )
        if not hasattr(A ,		"""key_handler"""       ):
            setattr(A ,		"""key_handler""" ,		{}       )
        setattr(A ,		"""handle_input""" ,		KeyHandler.handle_input       )

        for value in attrs.values():
            _SCREAMING_SNAKE_CASE									=			getattr(A ,		"""handle_key""" ,		[]       )
            for key in handled_keys:
                _SCREAMING_SNAKE_CASE									=			value
        return new_cls





    @staticmethod
    def 			snake_case_(		cls       )		->   str:
        _SCREAMING_SNAKE_CASE									=			get_character()
        if char != KEYMAP["undefined"]:
            _SCREAMING_SNAKE_CASE									=			ord(A       )
        _SCREAMING_SNAKE_CASE									=			cls.key_handler.get(A       )
        if handler:
            _SCREAMING_SNAKE_CASE									=			char
            return handler(cls       )
        else:
            return None





def lowerCamelCase						(     cls :    Any    )						->Dict:
    return KeyHandler(cls.__name__					,       cls.__bases__					,       cls.__dict__.copy()    )



