





import fire

from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer





def       _UpperCamelCase       (a__				:str				,     a__				:str				,     **a__				:List[str]    ):
							UpperCamelCase__			       =     AutoConfig.from_pretrained(a__				,     **a__    )
							UpperCamelCase__			       =     AutoModelForSeqaSeqLM.from_config(a__    )
							model.save_pretrained(a__    )
							AutoTokenizer.from_pretrained(a__    ).save_pretrained(a__    )
							return model


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











from typing import TYPE_CHECKING

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


UpperCamelCase__     =	{
    "configuration_swiftformer": [
        "SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "SwiftFormerConfig",
        "SwiftFormerOnnxConfig",
    ]
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase__     =	[
					    "SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
					    "SwiftFormerForImageClassification",
					    "SwiftFormerModel",
					    "SwiftFormerPreTrainedModel",
					]

if TYPE_CHECKING:
					from .configuration_swiftformer import (
					    SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
					    SwiftFormerConfig,
					    SwiftFormerOnnxConfig,
					)

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_swiftformer import (
										    SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
										    SwiftFormerForImageClassification,
										    SwiftFormerModel,
										    SwiftFormerPreTrainedModel,
										)

else:
					import sys

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




