


"""simple docstring"""


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


A  :     Any    					=    logging.get_logger(__name__)

A  :     str    					=    {
    "weiweishi/roc-bert-base-zh": "https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json",
}
class 						_UpperCamelCase						(     lowerCAmelCase__	):
							'''simple docstring'''







							__UpperCAmelCase		:					Dict          ="""roc_bert"""

							def __init__(  self					,     __a=3_05_22					,     __a=7_68					,     __a=12					,     __a=12					,     __a=30_72					,     __a="gelu"					,     __a=0.1					,     __a=0.1					,     __a=5_12					,     __a=2					,     __a=0.0_2					,     __a=1e-1_2					,     __a=True					,     __a=0					,     __a="absolute"					,     __a=None					,     __a=True					,     __a=True					,     __a=7_68					,     __a=9_10					,     __a=5_12					,     __a=2_48_58					,     __a=True					,     **__a					,     ):
										__lowerCAmelCase       					=    vocab_size
										__lowerCAmelCase       					=    max_position_embeddings
										__lowerCAmelCase       					=    hidden_size
										__lowerCAmelCase       					=    num_hidden_layers
										__lowerCAmelCase       					=    num_attention_heads
										__lowerCAmelCase       					=    intermediate_size
										__lowerCAmelCase       					=    hidden_act
										__lowerCAmelCase       					=    hidden_dropout_prob
										__lowerCAmelCase       					=    attention_probs_dropout_prob
										__lowerCAmelCase       					=    initializer_range
										__lowerCAmelCase       					=    type_vocab_size
										__lowerCAmelCase       					=    layer_norm_eps
										__lowerCAmelCase       					=    use_cache
										__lowerCAmelCase       					=    enable_pronunciation
										__lowerCAmelCase       					=    enable_shape
										__lowerCAmelCase       					=    pronunciation_embed_dim
										__lowerCAmelCase       					=    pronunciation_vocab_size
										__lowerCAmelCase       					=    shape_embed_dim
										__lowerCAmelCase       					=    shape_vocab_size
										__lowerCAmelCase       					=    concat_input
										__lowerCAmelCase       					=    position_embedding_type
										__lowerCAmelCase       					=    classifier_dropout
										super().__init__(pad_token_id=__a					,     **__a			)








"""simple docstring"""


import string


def _lowerCamelCase			(	_UpperCamelCase   ):

			'''simple docstring'''




			__lowerCAmelCase       					=    ""
			for i in sequence:
						__lowerCAmelCase       					=    ord(_UpperCamelCase   )
						if 65 <= extract <= 90:
									output += chr(155 - extract   )
						elif 97 <= extract <= 122:
									output += chr(219 - extract   )
						else:
									output += i
			return output


def _lowerCamelCase			(	_UpperCamelCase   ):

			'''simple docstring'''




			__lowerCAmelCase       					=    string.ascii_letters
			__lowerCAmelCase       					=    string.ascii_lowercase[::-1] + string.ascii_uppercase[::-1]
			return "".join(
			    letters_reversed[letters.index(_UpperCamelCase   )] if c in letters else c for c in sequence   )


def _lowerCamelCase			(	):

			'''simple docstring'''




			from timeit import timeit

			print("Running performance benchmarks..."   )
			__lowerCAmelCase       					=    "from string import printable ; from __main__ import atbash, atbash_slow"
			print(f"> atbash_slow(): {timeit('atbash_slow(printable)'					,				setup=_UpperCamelCase   )} seconds"   )
			print(f">      atbash(): {timeit('atbash(printable)'					,				setup=_UpperCamelCase   )} seconds"   )


if __name__ == "__main__":
	for example in ("ABCDEFGH", "123GGjj", "testStringtest", "with space"):
		print(f'''{example} encrypted in atbash: {atbash(example)}''')
	benchmark()




