


from typing import TYPE_CHECKING

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


A       :		Union[str, Any]    =   {
    """configuration_tapas""": ["""TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TapasConfig"""],
    """tokenization_tapas""": ["""TapasTokenizer"""],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A       :		Optional[Any]    =   [
	    """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       :		Union[str, 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       :		Any    =   _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)








def 		A_				(     _lowerCAmelCase     )						-> str:
 UpperCamelCase	:					Optional[int]       	=   int(_lowerCAmelCase     )
 if decimal in (0, 1):  # Exit cases for the recursion
  return str(_lowerCAmelCase     )
 UpperCamelCase	,    UpperCamelCase	:					Dict       	=   divmod(_lowerCAmelCase							,   2     )
 return binary_recursive(_lowerCAmelCase     ) + str(_lowerCAmelCase     )



def 		A_				(     _lowerCAmelCase     )						-> str:
 UpperCamelCase	:					Tuple       	=   str(_lowerCAmelCase     ).strip()
 if not number:
  raise ValueError("No input value was provided"     )
 UpperCamelCase	:					Optional[int]       	=   "-" if number.startswith("-"     ) else ""
 UpperCamelCase	:					Any       	=   number.lstrip("-"     )
 if not number.isnumeric():
  raise ValueError("Input value is not an integer"     )
 return F"""{negative}0b{binary_recursive(int(_lowerCAmelCase     )     )}"""


if __name__ == "__main__":
    from doctest import testmod

    testmod()
