
from typing import TYPE_CHECKING

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


_lowerCamelCase       :				Tuple       =			{
    '''configuration_nezha''': ['''NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''NezhaConfig'''],
}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_lowerCamelCase       :				Union[str, Any]       =			[
			    '''NEZHA_PRETRAINED_MODEL_ARCHIVE_LIST''',
			    '''NezhaForNextSentencePrediction''',
			    '''NezhaForMaskedLM''',
			    '''NezhaForPreTraining''',
			    '''NezhaForMultipleChoice''',
			    '''NezhaForQuestionAnswering''',
			    '''NezhaForSequenceClassification''',
			    '''NezhaForTokenClassification''',
			    '''NezhaModel''',
			    '''NezhaPreTrainedModel''',
			]


if TYPE_CHECKING:
			from .configuration_nezha import NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP, NezhaConfig

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_nezha import (
						    NEZHA_PRETRAINED_MODEL_ARCHIVE_LIST,
						    NezhaForMaskedLM,
						    NezhaForMultipleChoice,
						    NezhaForNextSentencePrediction,
						    NezhaForPreTraining,
						    NezhaForQuestionAnswering,
						    NezhaForSequenceClassification,
						    NezhaForTokenClassification,
						    NezhaModel,
						    NezhaPreTrainedModel,
						)


else:
			import sys

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

import numpy as np






def        a_		(       __lowercase   :	np.array ) ->  np.array:
			return 1 / (1 + np.exp(-vector ))


if __name__ == "__main__":
			import doctest

			doctest.testmod()