




'''simple docstring'''

from typing import TYPE_CHECKING

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


a       :						List[Any]								=		{
    '''configuration_roc_bert''': ['''ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''RoCBertConfig'''],
    '''tokenization_roc_bert''': ['''RoCBertTokenizer'''],
}

try:
						if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						pass

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						a       :						List[Any]								=		[
						    '''ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''RoCBertForCausalLM''',
						    '''RoCBertForMaskedLM''',
						    '''RoCBertForMultipleChoice''',
						    '''RoCBertForPreTraining''',
						    '''RoCBertForQuestionAnswering''',
						    '''RoCBertForSequenceClassification''',
						    '''RoCBertForTokenClassification''',
						    '''RoCBertLayer''',
						    '''RoCBertModel''',
						    '''RoCBertPreTrainedModel''',
						    '''load_tf_weights_in_roc_bert''',
						]

if TYPE_CHECKING:
						from .configuration_roc_bert import ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, RoCBertConfig
						from .tokenization_roc_bert import RoCBertTokenizer

						try:
												if not is_tokenizers_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												raise OptionalDependencyNotAvailable()

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_roc_bert import (
												    ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
												    RoCBertForCausalLM,
												    RoCBertForMaskedLM,
												    RoCBertForMultipleChoice,
												    RoCBertForPreTraining,
												    RoCBertForQuestionAnswering,
												    RoCBertForSequenceClassification,
												    RoCBertForTokenClassification,
												    RoCBertLayer,
												    RoCBertModel,
												    RoCBertPreTrainedModel,
												    load_tf_weights_in_roc_bert,
												)


else:
						import sys

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












'''simple docstring'''




from abc import ABC, abstractmethod
from argparse import ArgumentParser






class 				__snake_case     (					__magic_name__							):





	@staticmethod
	@abstractmethod
	def   _snake_case   (		UpperCamelCase_		)      ->		Dict:
		raise NotImplementedError()





	@abstractmethod
	def   _snake_case   (		self		)      ->		List[Any]:
		raise NotImplementedError()



