

'''simple docstring'''





from typing import TYPE_CHECKING

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


UpperCamelCase_							=					{
    """configuration_squeezebert""": [
        """SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """SqueezeBertConfig""",
        """SqueezeBertOnnxConfig""",
    ],
    """tokenization_squeezebert""": ["""SqueezeBertTokenizer"""],
}

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

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCamelCase_							=					[
							    """SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """SqueezeBertForMaskedLM""",
							    """SqueezeBertForMultipleChoice""",
							    """SqueezeBertForQuestionAnswering""",
							    """SqueezeBertForSequenceClassification""",
							    """SqueezeBertForTokenClassification""",
							    """SqueezeBertModel""",
							    """SqueezeBertModule""",
							    """SqueezeBertPreTrainedModel""",
							]


if TYPE_CHECKING:
							from .configuration_squeezebert import (
							    SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    SqueezeBertConfig,
							    SqueezeBertOnnxConfig,
							)
							from .tokenization_squeezebert import SqueezeBertTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_squeezebert_fast import SqueezeBertTokenizerFast

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_squeezebert import (
														    SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    SqueezeBertForMaskedLM,
														    SqueezeBertForMultipleChoice,
														    SqueezeBertForQuestionAnswering,
														    SqueezeBertForSequenceClassification,
														    SqueezeBertForTokenClassification,
														    SqueezeBertModel,
														    SqueezeBertModule,
														    SqueezeBertPreTrainedModel,
														)

else:
							import sys

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








'''simple docstring'''





from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments






def 							_lowerCAmelCase (      )							->     List[Any]:
						lowercase   :       Tuple								=HfArgumentParser(__magic_name__	)
						lowercase   :       Union[str, Any]								=parser.parse_args_into_dataclasses()[0]
						lowercase   :       Any								=TensorFlowBenchmark(args=__magic_name__	)
						try:
												lowercase   :       List[Any]								=parser.parse_args_into_dataclasses()[0]
						except ValueError as e:
												lowercase   :       List[Any]								='''Arg --no_{0} is no longer used, please use --no-{0} instead.'''
												lowercase   :       Any								=''' '''.join(str(__magic_name__	).split(''' '''	)[:-1]	)
												lowercase   :       Optional[Any]								=''''''
												lowercase   :       List[str]								=eval(str(__magic_name__	).split(''' '''	)[-1]	)
												lowercase   :       Optional[Any]								=[]
												for arg in depreciated_args:
																		# arg[2:] removes '--'
																		if arg[2:] in TensorFlowBenchmark.deprecated_args:
																								# arg[5:] removes '--no_'
																								full_error_msg += arg_error_msg.format(arg[5:]	)
																		else:
																								wrong_args.append(__magic_name__	)
												if len(__magic_name__	) > 0:
																		lowercase   :       int								=full_error_msg + begin_error_msg + str(__magic_name__	)
												raise ValueError(__magic_name__	)
						benchmark.run()


if __name__ == "__main__":
							main()





