





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_UpperCAmelCase				:       Union[str, Any]	   =				{
    """configuration_xlm_roberta_xl""": [
        """XLM_ROBERTA_XL_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """XLMRobertaXLConfig""",
        """XLMRobertaXLOnnxConfig""",
    ],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _UpperCAmelCase				:       Any	   =				[
        """XLM_ROBERTA_XL_PRETRAINED_MODEL_ARCHIVE_LIST""",
        """XLMRobertaXLForCausalLM""",
        """XLMRobertaXLForMaskedLM""",
        """XLMRobertaXLForMultipleChoice""",
        """XLMRobertaXLForQuestionAnswering""",
        """XLMRobertaXLForSequenceClassification""",
        """XLMRobertaXLForTokenClassification""",
        """XLMRobertaXLModel""",
        """XLMRobertaXLPreTrainedModel""",
    ]

if TYPE_CHECKING:
    from .configuration_xlm_roberta_xl import (
        XLM_ROBERTA_XL_PRETRAINED_CONFIG_ARCHIVE_MAP,
        XLMRobertaXLConfig,
        XLMRobertaXLOnnxConfig,
    )

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_xlm_roberta_xl import (
            XLM_ROBERTA_XL_PRETRAINED_MODEL_ARCHIVE_LIST,
            XLMRobertaXLForCausalLM,
            XLMRobertaXLForMaskedLM,
            XLMRobertaXLForMultipleChoice,
            XLMRobertaXLForQuestionAnswering,
            XLMRobertaXLForSequenceClassification,
            XLMRobertaXLForTokenClassification,
            XLMRobertaXLModel,
            XLMRobertaXLPreTrainedModel,
        )

else:
    import sys

    _UpperCAmelCase				:       Dict	   =				_LazyModule(__name__, globals()["""__file__"""], _import_structure)










def     a(      A       :    int       )		->       str:
					"""simple docstring"""





					if number > 0:
										raise ValueError("input must be a negative integer"       )
					a					     =   len(bin(A       )[3:]       )
					a					     =   bin(abs(A       ) - (1 << binary_number_length)       )[3:]
					a					     =   (
					    (
					        "1"
					        + "0" * (binary_number_length - len(A       ))
					        + twos_complement_number
					    )
					    if number < 0
					    else "0"
					)
					return "0b" + twos_complement_number


if __name__ == "__main__":
				import doctest

				doctest.testmod()
