
'''simple docstring'''



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_lowercase          =						{
    """configuration_megatron_bert""": ["""MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MegatronBertConfig"""],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_lowercase          =						[
						    """MEGATRON_BERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """MegatronBertForCausalLM""",
						    """MegatronBertForMaskedLM""",
						    """MegatronBertForMultipleChoice""",
						    """MegatronBertForNextSentencePrediction""",
						    """MegatronBertForPreTraining""",
						    """MegatronBertForQuestionAnswering""",
						    """MegatronBertForSequenceClassification""",
						    """MegatronBertForTokenClassification""",
						    """MegatronBertModel""",
						    """MegatronBertPreTrainedModel""",
						]

if TYPE_CHECKING:
						from .configuration_megatron_bert import MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, MegatronBertConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_megatron_bert import (
												    MEGATRON_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
												    MegatronBertForCausalLM,
												    MegatronBertForMaskedLM,
												    MegatronBertForMultipleChoice,
												    MegatronBertForNextSentencePrediction,
												    MegatronBertForPreTraining,
												    MegatronBertForQuestionAnswering,
												    MegatronBertForSequenceClassification,
												    MegatronBertForTokenClassification,
												    MegatronBertModel,
												    MegatronBertPreTrainedModel,
												)

else:
						import sys

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




from __future__ import annotations



def 							UpperCamelCase_( lowerCamelCase_					)       ->		float:
    if not nums:
        raise ValueError('List is empty'					)
    return sum(lowerCamelCase_					) / len(lowerCamelCase_					)


if __name__ == "__main__":
 import doctest

 doctest.testmod()


