




from typing import TYPE_CHECKING

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


UpperCamelCase__		=						{
    'configuration_ernie_m': ['ERNIE_M_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ErnieMConfig'],
}

try:
							if not is_sentencepiece_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCamelCase__		=						['ErnieMTokenizer']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCamelCase__		=						[
							    '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

							UpperCamelCase__		=						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)






from typing import Callable






def  snake_case (							A      )							->							List[str]:




	'''simple docstring'''


	def wrapper(A      ):
		lowerCamelCase_							:		Dict							       =							function_with_docstring.__doc__
		return target_function

	return wrapper
