

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


if __name__ == "__main__":
	import doctest

	doctest.testmod()






from typing import TYPE_CHECKING

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


A_       : List[str]         =			{
    'configuration_gpt_neox_japanese': ['GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GPTNeoXJapaneseConfig'],
    'tokenization_gpt_neox_japanese': ['GPTNeoXJapaneseTokenizer'],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A_       : Optional[int]         =			[
	    'GPT_NEOX_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'GPTNeoXJapaneseForCausalLM',
	    'GPTNeoXJapaneseLayer',
	    'GPTNeoXJapaneseModel',
	    'GPTNeoXJapanesePreTrainedModel',
	]


if TYPE_CHECKING:
	from .configuration_gpt_neox_japanese import GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoXJapaneseConfig
	from .tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_gpt_neox_japanese import (
		    GPT_NEOX_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST,
		    GPTNeoXJapaneseForCausalLM,
		    GPTNeoXJapaneseLayer,
		    GPTNeoXJapaneseModel,
		    GPTNeoXJapanesePreTrainedModel,
		)


else:
	import sys

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



