'''simple docstring'''


def   A_      (       SCREAMING_SNAKE_CASE_						)			->str:

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

  if num == 0:
    return "0b0"

  lowercase_     =       False

  if num < 0:
    lowercase_     =       True
    lowercase_     =       -num

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

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

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


if __name__ == "__main__":
       import doctest

       doctest.testmod()


'''simple docstring'''


from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__snake_case						  =		{"""configuration_focalnet""": ["""FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FocalNetConfig"""]}


try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __snake_case						  =		[
           """FOCALNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
           """FocalNetForImageClassification""",
           """FocalNetForMaskedImageModeling""",
           """FocalNetBackbone""",
           """FocalNetModel""",
           """FocalNetPreTrainedModel""",
       ]

if TYPE_CHECKING:
       from .configuration_focalnet import FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP, FocalNetConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_focalnet import (
                  FOCALNET_PRETRAINED_MODEL_ARCHIVE_LIST,
                  FocalNetBackbone,
                  FocalNetForImageClassification,
                  FocalNetForMaskedImageModeling,
                  FocalNetModel,
                  FocalNetPreTrainedModel,
              )

else:
       import sys

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

