




from argparse import ArgumentParser

from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test import TestCommand
from datasets.utils.logging import set_verbosity_info




def 		lowerCAmelCase_   (	lowerCamelCase   ):
				return {key.lstrip("""-"""   ): value for key, value in zip(unknown_args[::2]	,     unknown_args[1::2]   )}




def 		lowerCAmelCase_   (	):
				__magic_name__	:	str								=ArgumentParser(
				    """HuggingFace Datasets CLI tool"""	,     usage="""datasets-cli <command> [<args>]"""	,     allow_abbrev=lowerCamelCase   )
				__magic_name__	:	List[Any]								=parser.add_subparsers(help="""datasets-cli command helpers"""   )
				set_verbosity_info()

				# Register commands
				ConvertCommand.register_subcommand(lowerCamelCase   )
				EnvironmentCommand.register_subcommand(lowerCamelCase   )
				TestCommand.register_subcommand(lowerCamelCase   )
				RunBeamCommand.register_subcommand(lowerCamelCase   )
				DummyDataCommand.register_subcommand(lowerCamelCase   )

				# Parse args
				__magic_name__				, __magic_name__	:	Tuple								=parser.parse_known_args()
				if not hasattr(lowerCamelCase	,     """func"""   ):
								parser.print_help()
								exit(1   )
				__magic_name__	:	Dict								=parse_unknown_args(lowerCamelCase   )

				# Run
				__magic_name__	:	List[str]								=args.func(lowerCamelCase	,     **lowerCamelCase   )
				service.run()


if __name__ == "__main__":
							main()










from ... import PretrainedConfig


UpperCAmelCase_		:				List[str]									=     {
    "sijunhe/nezha-cn-base": "https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json",
}




class 		__A      (			UpperCamelCase__			):
						UpperCamelCase     						=					NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP
						UpperCamelCase     						=					"""nezha"""

						def __init__(		self   :List[Any]    , __snake_case   :Optional[int]=2_11_28    , __snake_case   :Dict=7_68    , __snake_case   :str=12    , __snake_case   :List[Any]=12    , __snake_case   :Optional[int]=30_72    , __snake_case   :Any="gelu"    , __snake_case   :List[str]=0.1    , __snake_case   :Optional[int]=0.1    , __snake_case   :Dict=5_12    , __snake_case   :Optional[int]=64    , __snake_case   :Any=2    , __snake_case   :List[Any]=0.02    , __snake_case   :List[str]=1E-12    , __snake_case   :Any=0.1    , __snake_case   :str=0    , __snake_case   :int=2    , __snake_case   :str=3    , __snake_case   :Any=True    , **__snake_case   :Any    , ):
										'''simple docstring'''

										super().__init__(pad_token_id=__snake_case    , bos_token_id=__snake_case    , eos_token_id=__snake_case    , **__snake_case )

										__magic_name__	:	Tuple								=vocab_size
										__magic_name__	:	str								=hidden_size
										__magic_name__	:	Dict								=num_hidden_layers
										__magic_name__	:	str								=num_attention_heads
										__magic_name__	:	int								=hidden_act
										__magic_name__	:	Optional[int]								=intermediate_size
										__magic_name__	:	Union[str, Any]								=hidden_dropout_prob
										__magic_name__	:	Any								=attention_probs_dropout_prob
										__magic_name__	:	Union[str, Any]								=max_position_embeddings
										__magic_name__	:	str								=max_relative_position
										__magic_name__	:	Tuple								=type_vocab_size
										__magic_name__	:	str								=initializer_range
										__magic_name__	:	Tuple								=layer_norm_eps
										__magic_name__	:	Optional[int]								=classifier_dropout
										__magic_name__	:	List[str]								=use_cache




