


'''simple docstring'''







from typing import TYPE_CHECKING

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


_SCREAMING_SNAKE_CASE							: Any										=			{
    'configuration_ernie': ['ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ErnieConfig', 'ErnieOnnxConfig'],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_SCREAMING_SNAKE_CASE							: Tuple										=			[
		    'ERNIE_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'ErnieForCausalLM',
		    'ErnieForMaskedLM',
		    'ErnieForMultipleChoice',
		    'ErnieForNextSentencePrediction',
		    'ErnieForPreTraining',
		    'ErnieForQuestionAnswering',
		    'ErnieForSequenceClassification',
		    'ErnieForTokenClassification',
		    'ErnieModel',
		    'ErniePreTrainedModel',
		]

if TYPE_CHECKING:
		from .configuration_ernie import ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP, ErnieConfig, ErnieOnnxConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_ernie import (
				    ERNIE_PRETRAINED_MODEL_ARCHIVE_LIST,
				    ErnieForCausalLM,
				    ErnieForMaskedLM,
				    ErnieForMultipleChoice,
				    ErnieForNextSentencePrediction,
				    ErnieForPreTraining,
				    ErnieForQuestionAnswering,
				    ErnieForSequenceClassification,
				    ErnieForTokenClassification,
				    ErnieModel,
				    ErniePreTrainedModel,
				)

else:
		import sys

		_SCREAMING_SNAKE_CASE							: Dict										=			_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




"""simple docstring"""






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


__snake_case				:  int =       {'configuration_plbart': ['PLBART_PRETRAINED_CONFIG_ARCHIVE_MAP', 'PLBartConfig']}

try:
	if not is_sentencepiece_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__snake_case				:  Optional[Any] =       ['PLBartTokenizer']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__snake_case				:  List[str] =       [
	    'PLBART_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'PLBartForCausalLM',
	    'PLBartForConditionalGeneration',
	    'PLBartForSequenceClassification',
	    'PLBartModel',
	    'PLBartPreTrainedModel',
	]


if TYPE_CHECKING:
	from .configuration_plbart import PLBART_PRETRAINED_CONFIG_ARCHIVE_MAP, PLBartConfig

	try:
		if not is_sentencepiece_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_plbart import PLBartTokenizer

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_plbart import (
		    PLBART_PRETRAINED_MODEL_ARCHIVE_LIST,
		    PLBartForCausalLM,
		    PLBartForConditionalGeneration,
		    PLBartForSequenceClassification,
		    PLBartModel,
		    PLBartPreTrainedModel,
		)


else:
	import sys

	__snake_case				:  Any =       _LazyModule(__name__, globals()['__file__'], _import_structure)