

def  UpperCamelCase_(							_snake_case     :						str			):




			"""simple docstring"""






			__a						   =str(_snake_case			).strip()
			if not oct_string:
						raise ValueError('Empty string was passed to the function'			)
			__a						   =oct_string[0] == '-'
			if is_negative:
						__a						   =oct_string[1:]
			if not oct_string.isdigit() or not all(0 <= int(_snake_case			) <= 7 for char in oct_string			):
						raise ValueError('Non-octal value was passed to the function'			)
			__a						   =0
			for char in oct_string:
						__a						   =8 * decimal_number + int(_snake_case			)
			if is_negative:
						__a						   =-decimal_number
			return decimal_number


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

						testmod()









from typing import TYPE_CHECKING

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


_lowerCAmelCase      :    Union[str, Any]						       =    {
    "configuration_ernie_m": ["ERNIE_M_PRETRAINED_CONFIG_ARCHIVE_MAP", "ErnieMConfig"],
}

try:
						if not is_sentencepiece_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_lowerCAmelCase      :    str						       =    ["ErnieMTokenizer"]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_lowerCAmelCase      :    Optional[Any]						       =    [
						    "ERNIE_M_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "ErnieMForMultipleChoice",
						    "ErnieMForQuestionAnswering",
						    "ErnieMForSequenceClassification",
						    "ErnieMForTokenClassification",
						    "ErnieMModel",
						    "ErnieMPreTrainedModel",
						    "ErnieMForInformationExtraction",
						]


if TYPE_CHECKING:
						from .configuration_ernie_m import ERNIE_M_PRETRAINED_CONFIG_ARCHIVE_MAP, ErnieMConfig

						try:
												if not is_sentencepiece_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_ernie_m import ErnieMTokenizer

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_ernie_m import (
												    ERNIE_M_PRETRAINED_MODEL_ARCHIVE_LIST,
												    ErnieMForInformationExtraction,
												    ErnieMForMultipleChoice,
												    ErnieMForQuestionAnswering,
												    ErnieMForSequenceClassification,
												    ErnieMForTokenClassification,
												    ErnieMModel,
												    ErnieMPreTrainedModel,
												)


else:
						import sys

						_lowerCAmelCase      :    Tuple						       =    _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)






