






def     snake_case   (UpperCAmelCase__    )			->							str:

  if isinstance(UpperCAmelCase__      ,       UpperCAmelCase__    ):
    raise TypeError('\'float\' object cannot be interpreted as an integer'    )
  if isinstance(UpperCAmelCase__      ,       UpperCAmelCase__    ):
    raise TypeError('\'str\' object cannot be interpreted as an integer'    )

  if num == 0:
    return "0b0"

  UpperCamelCase_:   Optional[Any]        =							False

  if num < 0:
    UpperCamelCase_:   Tuple        =							True
    UpperCamelCase_:   int        =							-num

  UpperCamelCase_:   list[int]        =							[]
  while num > 0:
    binary.insert(0      ,       num % 2    )
    num >>= 1

  if negative:
    return "-0b" + "".join(str(UpperCAmelCase__    ) for e in binary    )

  return "0b" + "".join(str(UpperCAmelCase__    ) for e in binary    )


if __name__ == "__main__":
   import doctest

   doctest.testmod()





'''simple docstring'''



from typing import TYPE_CHECKING

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


UpperCAmelCase_							:	List[str]	     =		{
    '''configuration_gpt_bigcode''': ['''GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTBigCodeConfig'''],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCAmelCase_							:	int	     =		[
         '''GPT_BIGCODE_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''GPTBigCodeForSequenceClassification''',
         '''GPTBigCodeForTokenClassification''',
         '''GPTBigCodeForCausalLM''',
         '''GPTBigCodeModel''',
         '''GPTBigCodePreTrainedModel''',
     ]

if TYPE_CHECKING:
     from .configuration_gpt_bigcode import GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTBigCodeConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_gpt_bigcode import (
              GPT_BIGCODE_PRETRAINED_MODEL_ARCHIVE_LIST,
              GPTBigCodeForCausalLM,
              GPTBigCodeForSequenceClassification,
              GPTBigCodeForTokenClassification,
              GPTBigCodeModel,
              GPTBigCodePreTrainedModel,
          )


else:
     import sys

     UpperCAmelCase_							:	Any	     =		_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)






