





'''simple docstring'''



import fire

from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer




def    _lowerCAmelCase						(				lowerCamelCase_			:  Optional[Any]		,       lowerCamelCase_			:  List[str]		,       **lowerCamelCase_			:  List[str]				):
			__lowercase										=							AutoConfig.from_pretrained(lowerCamelCase_		,       **lowerCamelCase_				)
			__lowercase										=							AutoModelForSeqaSeqLM.from_config(lowerCamelCase_				)
			model.save_pretrained(lowerCamelCase_				)
			AutoTokenizer.from_pretrained(lowerCamelCase_				).save_pretrained(lowerCamelCase_				)
			return model


if __name__ == "__main__":
						fire.Fire(save_randomly_initialized_version)












'''simple docstring'''



from typing import TYPE_CHECKING

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


_SCREAMING_SNAKE_CASE					=    {'''configuration_van''': ['''VAN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''VanConfig''']}


try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_SCREAMING_SNAKE_CASE					=    [
	    '''VAN_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''VanForImageClassification''',
	    '''VanModel''',
	    '''VanPreTrainedModel''',
	]

if TYPE_CHECKING:
	from .configuration_van import VAN_PRETRAINED_CONFIG_ARCHIVE_MAP, VanConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_van import (
		    VAN_PRETRAINED_MODEL_ARCHIVE_LIST,
		    VanForImageClassification,
		    VanModel,
		    VanPreTrainedModel,
		)

else:
	import sys

	_SCREAMING_SNAKE_CASE					=    _LazyModule(__name__, globals()['''__file__'''], _import_structure)





