from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def 							lowerCAmelCase(     ):
					__a		 =       HfArgumentParser(__lowerCamelCase						)
					__a		 =       parser.parse_args_into_dataclasses()[0]
					__a		 =       TensorFlowBenchmark(args=__lowerCamelCase						)
					try:
										__a		 =       parser.parse_args_into_dataclasses()[0]
					except ValueError as e:
										__a		 =       'Arg --no_{0} is no longer used, please use --no-{0} instead.'
										__a		 =       ' '.join(str(__lowerCamelCase						).split(' '						)[:-1]						)
										__a		 =       ''
										__a		 =       eval(str(__lowerCamelCase						).split(' '						)[-1]						)
										__a		 =       []
										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(__lowerCamelCase						)
										if len(__lowerCamelCase						) > 0:
															__a		 =       full_error_msg + begin_error_msg + str(__lowerCamelCase						)
										raise ValueError(__lowerCamelCase						)
					benchmark.run()


if __name__ == "__main__":
	main()





from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCamelCase_    :		Tuple							=	logging.get_logger(__name__)

lowerCamelCase_    :		List[Any]							=	{
    """google/fnet-base""": """https://huggingface.co/google/fnet-base/resolve/main/config.json""",
    """google/fnet-large""": """https://huggingface.co/google/fnet-large/resolve/main/config.json"""
    # See all FNet models at https://huggingface.co/models?filter=fnet
}


class 						a__							(       __snake_case		):
			A__    :       Dict        =      'fnet'



			def __init__(						self				,						UpperCAmelCase=3_2_0_0_0				,						UpperCAmelCase=7_6_8				,						UpperCAmelCase=1_2				,						UpperCAmelCase=3_0_7_2				,						UpperCAmelCase="gelu_new"				,						UpperCAmelCase=0.1				,						UpperCAmelCase=5_1_2				,						UpperCAmelCase=4				,						UpperCAmelCase=0.02				,						UpperCAmelCase=1e-12				,						UpperCAmelCase=False				,						UpperCAmelCase=5_1_2				,						UpperCAmelCase=3				,						UpperCAmelCase=1				,						UpperCAmelCase=2				,						**UpperCAmelCase				,						)			->   Dict:
								super().__init__(pad_token_id=UpperCAmelCase				,						bos_token_id=UpperCAmelCase				,						eos_token_id=UpperCAmelCase				,						**UpperCAmelCase   )

								__a		 =       vocab_size
								__a		 =       max_position_embeddings
								__a		 =       hidden_size
								__a		 =       num_hidden_layers
								__a		 =       intermediate_size
								__a		 =       hidden_act
								__a		 =       hidden_dropout_prob
								__a		 =       initializer_range
								__a		 =       type_vocab_size
								__a		 =       layer_norm_eps
								__a		 =       use_tpu_fourier_optimizations
								__a		 =       tpu_short_seq_length




