



"""simple docstring"""





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


__lowerCAmelCase       :					Optional[Any]      					=					{
    '''configuration_roberta_prelayernorm''': [
        '''ROBERTA_PRELAYERNORM_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''RobertaPreLayerNormConfig''',
        '''RobertaPreLayerNormOnnxConfig''',
    ],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowerCAmelCase       :					Optional[int]      					=					[
						    '''ROBERTA_PRELAYERNORM_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''RobertaPreLayerNormForCausalLM''',
						    '''RobertaPreLayerNormForMaskedLM''',
						    '''RobertaPreLayerNormForMultipleChoice''',
						    '''RobertaPreLayerNormForQuestionAnswering''',
						    '''RobertaPreLayerNormForSequenceClassification''',
						    '''RobertaPreLayerNormForTokenClassification''',
						    '''RobertaPreLayerNormModel''',
						    '''RobertaPreLayerNormPreTrainedModel''',
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowerCAmelCase       :					Optional[int]      					=					[
						    '''TF_ROBERTA_PRELAYERNORM_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''TFRobertaPreLayerNormForCausalLM''',
						    '''TFRobertaPreLayerNormForMaskedLM''',
						    '''TFRobertaPreLayerNormForMultipleChoice''',
						    '''TFRobertaPreLayerNormForQuestionAnswering''',
						    '''TFRobertaPreLayerNormForSequenceClassification''',
						    '''TFRobertaPreLayerNormForTokenClassification''',
						    '''TFRobertaPreLayerNormMainLayer''',
						    '''TFRobertaPreLayerNormModel''',
						    '''TFRobertaPreLayerNormPreTrainedModel''',
						]

try:
						if not is_flax_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowerCAmelCase       :					str      					=					[
						    '''FlaxRobertaPreLayerNormForCausalLM''',
						    '''FlaxRobertaPreLayerNormForMaskedLM''',
						    '''FlaxRobertaPreLayerNormForMultipleChoice''',
						    '''FlaxRobertaPreLayerNormForQuestionAnswering''',
						    '''FlaxRobertaPreLayerNormForSequenceClassification''',
						    '''FlaxRobertaPreLayerNormForTokenClassification''',
						    '''FlaxRobertaPreLayerNormModel''',
						    '''FlaxRobertaPreLayerNormPreTrainedModel''',
						]


if TYPE_CHECKING:
						from .configuration_roberta_prelayernorm import (
						    ROBERTA_PRELAYERNORM_PRETRAINED_CONFIG_ARCHIVE_MAP,
						    RobertaPreLayerNormConfig,
						    RobertaPreLayerNormOnnxConfig,
						)

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_roberta_prelayernorm import (
												    ROBERTA_PRELAYERNORM_PRETRAINED_MODEL_ARCHIVE_LIST,
												    RobertaPreLayerNormForCausalLM,
												    RobertaPreLayerNormForMaskedLM,
												    RobertaPreLayerNormForMultipleChoice,
												    RobertaPreLayerNormForQuestionAnswering,
												    RobertaPreLayerNormForSequenceClassification,
												    RobertaPreLayerNormForTokenClassification,
												    RobertaPreLayerNormModel,
												    RobertaPreLayerNormPreTrainedModel,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_roberta_prelayernorm import (
												    TF_ROBERTA_PRELAYERNORM_PRETRAINED_MODEL_ARCHIVE_LIST,
												    TFRobertaPreLayerNormForCausalLM,
												    TFRobertaPreLayerNormForMaskedLM,
												    TFRobertaPreLayerNormForMultipleChoice,
												    TFRobertaPreLayerNormForQuestionAnswering,
												    TFRobertaPreLayerNormForSequenceClassification,
												    TFRobertaPreLayerNormForTokenClassification,
												    TFRobertaPreLayerNormMainLayer,
												    TFRobertaPreLayerNormModel,
												    TFRobertaPreLayerNormPreTrainedModel,
												)

						try:
												if not is_flax_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_flax_roberta_prelayernorm import (
												    FlaxRobertaPreLayerNormForCausalLM,
												    FlaxRobertaPreLayerNormForMaskedLM,
												    FlaxRobertaPreLayerNormForMultipleChoice,
												    FlaxRobertaPreLayerNormForQuestionAnswering,
												    FlaxRobertaPreLayerNormForSequenceClassification,
												    FlaxRobertaPreLayerNormForTokenClassification,
												    FlaxRobertaPreLayerNormModel,
												    FlaxRobertaPreLayerNormPreTrainedModel,
												)

else:
						import sys

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






"""simple docstring"""





def 	__lowerCAmelCase						(		__UpperCamelCase      :			str    ):


						'''simple docstring'''






						return " ".join(input_str.split()[::-1]    )


if __name__ == "__main__":
					import doctest

					doctest.testmod()

