



from typing import TYPE_CHECKING

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


UpperCAmelCase								=   {
    """configuration_led""": ["""LED_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LEDConfig"""],
    """tokenization_led""": ["""LEDTokenizer"""],
}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCAmelCase								=   ["""LEDTokenizerFast"""]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCAmelCase								=   [
	    """LED_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """LEDForConditionalGeneration""",
	    """LEDForQuestionAnswering""",
	    """LEDForSequenceClassification""",
	    """LEDModel""",
	    """LEDPreTrainedModel""",
	]


try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCAmelCase								=   ["""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

	UpperCAmelCase								=   _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






def      A_ (		__a       :			float						):

				"""simple docstring"""
				return int(__a						) if x - int(__a						) >= 0 else int(__a						) - 1


if __name__ == "__main__":
	import doctest

	doctest.testmod()

