from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_lowerCamelCase   :				Tuple     			=						{
    '''configuration_megatron_bert''': ['''MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MegatronBertConfig'''],
}

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

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





def 		__lowerCamelCase							(UpperCAmelCase__       :							str ,	UpperCAmelCase__       :							str = " "					):
					SCREAMING_SNAKE_CASE           =    []

					SCREAMING_SNAKE_CASE           =    0
					for index, char in enumerate(UpperCAmelCase__					):
										if char == separator:
															split_words.append(string[last_index:index]					)
															SCREAMING_SNAKE_CASE           =    index + 1
										elif index + 1 == len(UpperCAmelCase__					):
															split_words.append(string[last_index : index + 1]					)
					return split_words


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

							testmod()




