
'''simple docstring'''






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


A			      =      logging.get_logger(__name__)

A			      =      {
    'weiweishi/roc-bert-base-zh': 'https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json',
}




class     __snake_case		(   a__):
					_lowerCAmelCase			     =	'''roc_bert'''
					def __init__(     self,    A=3_0522,    A=768,    A=12,    A=12,    A=3072,    A="gelu",    A=0.1,    A=0.1,    A=512,    A=2,    A=0.02,    A=1e-12,    A=True,    A=0,    A="absolute",    A=None,    A=True,    A=True,    A=768,    A=910,    A=512,    A=2_4858,    A=True,    **A,    ):

									"""simple docstring"""


									lowerCamelCase					:			Any									= vocab_size
									lowerCamelCase					:			str									= max_position_embeddings
									lowerCamelCase					:			Union[str, Any]									= hidden_size
									lowerCamelCase					:			int									= num_hidden_layers
									lowerCamelCase					:			Tuple									= num_attention_heads
									lowerCamelCase					:			Optional[Any]									= intermediate_size
									lowerCamelCase					:			List[Any]									= hidden_act
									lowerCamelCase					:			List[Any]									= hidden_dropout_prob
									lowerCamelCase					:			Optional[int]									= attention_probs_dropout_prob
									lowerCamelCase					:			str									= initializer_range
									lowerCamelCase					:			Tuple									= type_vocab_size
									lowerCamelCase					:			int									= layer_norm_eps
									lowerCamelCase					:			Union[str, Any]									= use_cache
									lowerCamelCase					:			int									= enable_pronunciation
									lowerCamelCase					:			List[Any]									= enable_shape
									lowerCamelCase					:			Optional[Any]									= pronunciation_embed_dim
									lowerCamelCase					:			Tuple									= pronunciation_vocab_size
									lowerCamelCase					:			int									= shape_embed_dim
									lowerCamelCase					:			Optional[int]									= shape_vocab_size
									lowerCamelCase					:			Optional[int]									= concat_input
									lowerCamelCase					:			Dict									= position_embedding_type
									lowerCamelCase					:			str									= classifier_dropout
									super().__init__(pad_token_id=A,    **A      )


'''simple docstring'''






from __future__ import annotations





def    UpperCAmelCase							(  UpperCAmelCase__							:							int):
				lowerCamelCase					:			List[Any]									= str(UpperCAmelCase__)
				return len(UpperCAmelCase__) == 9 and set(UpperCAmelCase__) == set('123456789')





def    UpperCAmelCase							(  ):
				for base_num in range(99_99       ,							49_99       ,							-1):
								lowerCamelCase					:			Tuple									= 10_00_02 * base_num
								if is_9_pandigital(UpperCAmelCase__):
												return candidate

				for base_num in range(3_33       ,							99       ,							-1):
								lowerCamelCase					:			List[Any]									= 1_00_20_03 * base_num
								if is_9_pandigital(UpperCAmelCase__):
												return candidate

				return None


if __name__ == "__main__":
					print(f"""{solution() = }""")
