
from typing import TYPE_CHECKING

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


__SCREAMING_SNAKE_CASE			:   List[Any]         =     {
    'configuration_led': ['LED_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LEDConfig'],
    'tokenization_led': ['LEDTokenizer'],
}

try:
		if not is_tokenizers_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__SCREAMING_SNAKE_CASE			:   Union[str, Any]         =     ['LEDTokenizerFast']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__SCREAMING_SNAKE_CASE			:   Union[str, Any]         =     [
		    'LED_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'LEDForConditionalGeneration',
		    'LEDForQuestionAnswering',
		    'LEDForSequenceClassification',
		    'LEDModel',
		    'LEDPreTrainedModel',
		]


try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__SCREAMING_SNAKE_CASE			:   List[Any]         =     ['TFLEDForConditionalGeneration', 'TFLEDModel', 'TFLEDPreTrainedModel']


if TYPE_CHECKING:
		from .configuration_led import LED_PRETRAINED_CONFIG_ARCHIVE_MAP, LEDConfig
		from .tokenization_led import LEDTokenizer

		try:
				if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_led_fast import LEDTokenizerFast

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_led import (
				    LED_PRETRAINED_MODEL_ARCHIVE_LIST,
				    LEDForConditionalGeneration,
				    LEDForQuestionAnswering,
				    LEDForSequenceClassification,
				    LEDModel,
				    LEDPreTrainedModel,
				)

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_led import TFLEDForConditionalGeneration, TFLEDModel, TFLEDPreTrainedModel

else:
		import sys

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


from ..utils import requires_backends


__SCREAMING_SNAKE_CASE			:   Union[str, Any]         =     None


class 		__magic_name__   :





		def __init__(							self    :	Optional[int]						,  *lowerCamelCase__    :	List[str]						,  **lowerCamelCase__    :	Optional[Any]				):
							requires_backends(self						,  ['''detectron2''']				)





		@classmethod
		def       _A							(							cls    :	Dict						,  *lowerCamelCase__    :	List[str]						,  **lowerCamelCase__    :	Optional[Any]				):
							requires_backends(cls						,  ['''detectron2''']				)
